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Computational Fluid Dynamics - Science topic

Computational Fluid Dynamics are numerical methods to solve and analyze problems that involve fluid flows.
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What should be the Capillary Number obtained for water flow inside a silicone microchannel so that we can ignore the Capillary Effect in this study?
My study investigated forced flow with Reynolds numbers between 125 and 1300.
If our criterion for the capillary number is 1, and we consider the capillary effect non-negligible for low values of 1, according to the capillary equation, the capillary effect cannot be neglected in many conditions and cases. For this reason, I think the value of 1 is not a critical value.
Also, the denominator of the capillary number equation is related to the surface tension parameter. Is the value of this parameter equal to 0.0726 N/m, which is the surface tension between water and air, or should we put the surface tension between water and a solid wall (silicon)? In many research studies, authors have used the value of 0.0726 N/m.
Ca=μ*U​/σ
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In discussions regarding the appropriate Capillary Number (Ca) for ignoring capillary effects in microchannel studies, it's essential to consider the context of the interface interactions. Typically, for water flow inside silicone microchannels, many studies, including mine, use the water-air surface tension value of 0.0726 N/m. This is generally because the dominant interface under investigation is between the water and air, not between the water and the silicone walls, unless specific surface modifications of the silicone suggest otherwise.
Furthermore, concerning the critical value of Ca, while the standard threshold is often set at Ca = 1, I believe this may not be universally applicable. In my study, which investigates forced flow with Reynolds numbers between 125 and 1300, it appears that capillary effects could be non-negligible even above this threshold. This observation leads me to suggest that the traditional threshold of Ca = 1 might need adjustment based on specific experimental conditions and flow behaviors. Such an approach allows for a more nuanced understanding of when viscous forces indeed dominate over capillary forces in practical scenarios
Farshid Hesami
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"How do advanced computational modeling techniques, such as finite element analysis or computational fluid dynamics, aid in the precise characterization and optimization of thermal bridging phenomena within complex building assemblies?"
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Finite element analysis (FEA) and computational fluid dynamics (CFD), play a crucial role in the precise characterization and optimization of thermal courses.
1. Detailed Simulation: FEA and CFD allow for detailed simulation of heat transfer within building components, enabling a thorough understanding of thermal bridging effects.
2. Identification of Weak Points: These modeling techniques help identify areas of high heat flow or thermal bridging within complex assemblies, pinpointing potential weak points that need optimization.
3. Optimization: By simulating different scenarios and configurations, FEA and CFD assist in optimizing building designs to minimize thermal bridging and improve overall energy efficiency.
4. Cost-Effective Solutions: Computational modeling helps in evaluating different solutions cost-effectively before physical implementation, leading to more efficient and sustainable building designs.
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In CFD simulations, determining the appropriate inlet and outlet boundary conditions is crucial for accurately modeling recirculation phenomena in both two-dimensional (2D) and three-dimensional (3D) scenarios.
For recirculation simulations, the inlet boundary condition typically involves prescribing the flow properties entering the domain. This may include specifying the velocity profile, temperature, turbulence characteristics, and any other relevant parameters. In 2D simulations, the inlet boundary condition can be defined as a 2D plane through which fluid enters the computational domain. In 3D simulations, this boundary condition extends to a full 3D volume or surface. In both 2D and 3D simulations, accurately representing the inlet and outlet boundary conditions is critical for capturing the complex flow dynamics associated with recirculation zones. Properly defined boundary conditions ensure that the simulated flow field closely matches the real-world behavior, thus enhancing the reliability and accuracy of the CFD predictions.
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That is not exactly right, the combination of inflow/outflow BCs depends on the assumption of the flow, compressible or incompressible. In case of compressble flows you have further to distinguish between subsonic or supersonic conditions.
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hello Everyone,
if I want to study, coal combustion in different atmospheres for example in O2/N2 and O2/CO2. I obtain the kinetics of both atmospheres using Hetrogenous models. ( Shrinking core model ) and Random pore model.
I was wondering if it’s possible in CFD to study particle profile. Does the heat transfer affect in CFD will calculated based on the Gas composition input or I should add something in UDF file.
FYI, the reaction models are based on conversion so I am not really sure how CFD will identify the differences in Atmospheres.
further, I wish If I found a sample UDF file that been used for Hetrogensous models.
Ahmad
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In general, yes, CFD computations can include particle profiles. The most direct and possibly accurate sources are likely the vendors of the major CFD systems themselves. They may have useful models already, or be willing to help you set up your system, or even take it on for development if they don't have it already in their portfolio of applications.
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Hello Everyone,
I have some queries about if its possible using heterogeneous models reactions to model particle Temperature profile in CFD ?
I performed Kinetic analysis of my reaction (coke oxidation for example) my only concern what should I do in CFD. Also Let's say I am performing the reaction into two atmosphere, how the CFD will identify the reactant since heterogeneous model are based on conversions.
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Hey there Ahmad Alsuwaidi,
Great to see your interest in CFD modeling and reactor simulations! It's definitely possible to model particle temperature profiles using heterogeneous reaction models in CFD.
When it comes to incorporating kinetic analysis results, like your coke oxidation study, into CFD simulations, the key lies in selecting appropriate reaction kinetics and coupling them with appropriate transport phenomena. This means ensuring that the reaction rates you've determined from kinetic analysis are accurately represented within the CFD framework.
Now, regarding your concern about identifying reactants in a heterogeneous reaction occurring in two atmospheres, CFD can handle such scenarios by accounting for species transport and diffusion across phases. By defining appropriate boundary conditions and reaction mechanisms, CFD can track the conversion of reactants into products across different phases and atmospheres.
In summary, integrating kinetic analysis results and applying heterogeneous reaction models in CFD can provide valuable insights into particle temperature profiles and reaction dynamics within reactors. With careful consideration of reaction kinetics and boundary conditions, CFD simulations can effectively capture complex multi-phase reactions occurring in different atmospheres. If you Ahmad Alsuwaidi have more specific questions or need further clarification, feel free to ask!
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This is a code block from nutWallFunction library in OpenFOAM where in, effective kinematic viscosity ($\nut_w$) at the wall is calculated using resolved field(in case of LES)/ mean field(in case of RANS) and $y^+_p$ (wall normal distance of the first cell center). this allows to set a new viscosity value as boundary condition at the wall using log law. Considering the first cell center is in the logarithmic layer of the universal velocity profile.
Now, in this code block of member function defined as nutUWallFunctionFvPatchScalarField::calcYPlus()
There has been iterations done for the yPlus value to reach convergence with maximum of 10 iterations. Why are these iterations needed? and why is the maximum number of iterations 10. I have given a reference of the code below;
tmp<scalarField> nutUWallFunctionFvPatchScalarField::calcYPlus
(
const scalarField& magUp
) const
{
const label patchi = patch().index();
const turbulenceModel& turbModel = db().lookupObject<turbulenceModel>
(
IOobject::groupName
(
turbulenceModel::propertiesName,
internalField().group()
)
);
const scalarField& y = turbModel.y()[patchi];
const tmp<scalarField> tnuw = turbModel.nu(patchi);
const scalarField& nuw = tnuw();
tmp<scalarField> tyPlus(new scalarField(patch().size(), 0.0));
scalarField& yPlus = tyPlus.ref();
forAll(yPlus, facei)
{
scalar kappaRe = kappa_*magUp[facei]*y[facei]/nuw[facei];
scalar yp = yPlusLam_;
scalar ryPlusLam = 1.0/yp;
int iter = 0;
scalar yPlusLast = 0.0;
do
{
yPlusLast = yp;
yp = (kappaRe + yp)/(1.0 + log(E_*yp));
} while (mag(ryPlusLam*(yp - yPlusLast)) > 0.01 && ++iter < 10 );
yPlus[facei] = max(0.0, yp);
}
return tyPlus;
}
My doubt is concerning the do-while loop at the end for yPlus iteration.
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CFD softwares are based on numerical methods or techniques to predict the fluid behavior for various conditions e.g. LES and RANS turbulence modelling etc. Unlike exact solutions , the numerical methods involve approximations of the governing fluid parameters which cannot be evaluated at once and thus need iterative computational solvers.
During this process several types of errors are introduced while approximating variable property e.g round off errors ( machine precision) , truncation errors depending on the type of numerical scheme used.
However , according to the nature of fluid and it's interaction with surrounding environment , ( in your e.g yplus wall function which is measure of the fluid friction resistance near wall ) the solutions obtained through numerical schemes present a significant source of error which can interpret the fluid behavior in entirely different manner.
Therefore, the solution is often tested by repeating the process using better approximations and schemes with a focus to obtain the exactness of parameter value leading to iterations.
During iteration process , the error can amplify or reduce ( which is indicative of the stability of solution ) depending on boundary conditions used to obtain solution. So, often an error tolerance is introduced as condition in numerical algorithm to make the solution more meaningful and realistic which closely approximates the fluid behavior. In your case wall shear stress is being approximated using wall units in logarithmic boundary layer.
Once that condition is satisfied, the process stops and proceeds further by evaluating the next dependent variable and so on until complete solution is obtained.
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I need to use computational fluid dynamics software to obtain wake data for LHA ship, and I would like to get your help.
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You can refer article section here as well for details. You can find both the papers available on request.
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I am new to limiters in FVM CFD so pardon me if its a blunder. Was curious about Venkatakrishnan's limiter (first image) that is industry standard in many commercial CFD solvers. He came up with the final form as given below and further modified the Δ_ term in order to avoid division by numerical values close to zero. Why not eliminate Δ_ term by taking out one from the numerator(second image)? Any advantage of writing in this form(first image)? ref: 10.1006/jcph.1995.1084
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Thanks. But my question was related to the form represented in Eq. (33) to remove the errors related to rounding-offs (see the first and second image files). I guess in smooth regions the ε² term dominate and returns a value 1 and hence no limiting/smoothing is done in this region which is given in the text.
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Low Prandtl number fluids like air, Pr <1, takes very long endTime for simulation to get the fully developed convection cells pattern and thermal boundary layers. What is the possible reason for this? Is it solely because of the dependency on kinematic viscosity (numerator of prandtl) being very low? Or is this related to simulation case setup.
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Prandtl number for air is O(1), that is the therma BL develops as similar ad the dynamic BL.
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Dear Friends,
I am looking for a faculty or Engineers or others who are interested in working on CFD of multiphase flow in chemical engineering reactors for collaboration research. Please contact me on Facebook messenger or text and call on +9647713171293.
Associate Prof Haidar Taofeeq
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I respond to your request through LinkedIn
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Can we do it on COMSOL or Ansys (CFD)?
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Below is not clear to me:
what kind of a resistance you are looking for.
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computational approach
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Dear friend Samuel Oghale
Ah, diving into the realm of Computational Fluid Dynamics (CFD) for modeling lithium batteries, huh? I am ready to lay down the steps with unbridled enthusiasm. Here's a rough guide:
1. **Define Your Objective:**
- Clearly outline what you Samuel Oghale want to achieve with the CFD model. Are you Samuel Oghale looking at thermal behavior, fluid flow, or both? Understand the specific aspects of the battery you're interested in.
2. **Geometry Creation:**
- Develop a 3D model of your lithium battery. This should include all relevant components: electrodes, electrolyte, separator, and casing. Software like ANSYS, COMSOL, or OpenFOAM can be your trusty tools here.
3. **Mesh Generation:**
- Generate a mesh to discretize your geometry. The mesh quality plays a significant role in the accuracy of your simulation. Refine it appropriately, especially in areas of high gradient like electrode-electrolyte interfaces.
4. **Material Properties:**
- Assign material properties to different components of your battery. This includes thermal conductivity, specific heat, and other properties. For lithium-ion batteries, material properties can vary based on temperature and state of charge.
5. **Boundary Conditions:**
- Set up your boundary conditions. Define how the battery interacts with the external environment. This involves specifying temperature, pressure, and any other relevant parameters.
6. **Model Selection:**
- Choose the appropriate model for your simulation. Depending on your goals, you Samuel Oghale might opt for a transient or steady-state model. Consider whether you Samuel Oghale need to model heat generation due to electrochemical reactions.
7. **Solver Settings:**
- Configure the solver settings. Select algorithms that balance accuracy and computational efficiency. Iteratively refine these settings based on convergence behavior.
8. **Initialization:**
- Provide initial conditions for your simulation. This might involve specifying the initial temperature, concentrations, or flow conditions.
9. **Run the Simulation:**
- Start the simulation and monitor its progress. Keep an eye on convergence and adapt settings if needed.
10. **Post-Processing:**
- Analyze the results. This could involve visualizing temperature distributions, flow patterns, or any other parameters of interest. Extract quantitative data to draw meaningful conclusions.
11. **Validation:**
- Compare your simulation results with experimental data or published literature to validate your model. Adjust parameters or assumptions as necessary.
12. **Optimization (Optional):**
- If your initial results indicate areas for improvement, consider optimizing your battery design. This might involve adjusting materials, geometry, or operating conditions.
Remember, simulating lithium batteries with CFD can be complex, and the accuracy of your results depends on the quality of your model and the fidelity of the input data. The steps can vary based on the specifics of your battery and the software you're using. Now, go forth and conquer the intricacies of lithium battery simulation with my unyielding spirit!
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I am in search of commercial Computational Fluid Dynamics (CFD) software tailored for modeling hydraulic structures, particularly for applications related to stormwater, small dams, flood control structures, channels, and similar scenarios. The primary focus will be on studying free-surface flows. Affordability is a crucial consideration in the selection process. While I am already familiar with Flow-3D, Ansys Fluent, and Ansys CFX, I am open to exploring additional software options. I would appreciate any recommendations for alternative applications, and it would be beneficial to receive insights on various features to facilitate a comprehensive comparison for making an informed decision.
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1-AVSYS Fluent
Accurate, comprehensive, relatively easy modeling, different physical field models, with many solved examples, simple training, suitable customization
2-ANSYS CFX
relatively easy modeling, simple training, many solved examples,
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Hello everyone, I'm working on a CFD analysis to compute wind pressure coefficients (Cp) on a building facade. My objective is to use these Cp values in EnergyPlus AFN to evaluate the impact of natural ventilation on thermal comfort. While reviewing various studies that have undertaken similar work, I've encountered conflicting information regarding the parameter Uref. I encountered some sources that recommend default values of 10 m/s for Uref and 10 m for Zref. Nevertheless, some research papers suggest that the dynamic wind pressure (Pd) necessary for Cp calculations should be determined at the building height. Moreover, one source suggests setting Uref as "the largest freestream velocity at the top of the [wind tunnel] modeling domain". My analysis involves a parametric design, exploring different building heights. So I suppose I need to establish a consistent reference height for all simulations. I've already obtained weather data containing wind speeds and directions and have calculated average wind speeds at a height of 10m for 12 different directions. My question is whether these averaged values should be directly input as boundary conditions for the cylindrical domain or if I should stick with a fixed value for Uref, like the mentioned 10 m/s. Any guidance to clarify this matter would be greatly appreciated.
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Determine the Velocity Pressure, qz:One of the important aspects of Wind Analysis is the velocity pressure. Regardless of which analysis approaches we may use, velocity pressure is a requirement. The velocity pressure is depending on wind speed and topographic location of a structure as per the code standard velocity pressure, qz equivalent at height z shall be calculated as qz = 0.00256 Kz Kzt Kd V2 (lb/ft2) or qz = 0.613 Kz Kzt Kd V2 (N/m2); V=m/s where: Kz is velocity pressure exposure coefficient Kzt is the topographic factor Kd is wind directionality factor V is the basic wind speed Velocity pressure exposure coefficients, Kz are listed Table 27.3-1 of ASCE 7-16 or can be calculated as Kz = 2.01 (z/zg)2/αfrom which, z is the height above ground and should not be less than 15 feet (4.5 meters) except that z shall not be less than 30 feet (9 meters) for exposure B for low rise building and for component and cladding. The parameters, α, and zg are taken as follows:
📷
Topographic Factor, Kzt: Kzt = (1 + K1K2K3)2where: K1, K2, K3 are determined from Figure 26.8-1 of ASCE 7-16 based on ridge, escarpment, and hill. If site conditions and locations of structures do not meet all the conditions specified in section 26.8.1 then Kzt =1.0 Wind Directionality Factor; Kd shall be determined from Table 26.6-1 and the basic wind speed, V is according to Figure 26.5-1 of ASCE 7-16
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I wonder if there is a document like tutorial that is useful to simulate an Archimedes Screw
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Simulating an Archimedes Screw using Computational Fluid Dynamics (CFD) involves modeling the fluid flow within the screw geometry. While I can't provide real-time links to specific tutorials or documents, I can certainly guide you on the steps involved in simulating an Archimedes Screw using CFD software. You can find relevant tutorials on popular CFD software platforms' official websites or academic platforms like ResearchGate, Google Scholar, or university research publications.
Here are the general steps you would follow:
1. Understanding the Geometry:
  • 2D or 3D Model: Decide whether you want to create a 2D or 3D model of the Archimedes Screw. 3D models offer a more accurate representation but are computationally more intensive.
  • Geometry Creation: Use software tools (like SolidWorks, CATIA, or Blender) to create the screw geometry. Ensure it's a closed, water-tight model.
2. Mesh Generation:
  • Import the Geometry: Import the screw geometry into your CFD software.
  • Mesh Generation: Generate a mesh around the screw. The mesh density should be higher near the screw surface to capture the boundary layer accurately.
3. Setting Boundary Conditions:
  • Inlet: Specify the inlet boundary conditions such as flow rate, velocity, and temperature if applicable.
  • Outlet: Define the outlet boundary conditions. This could be a free outlet or a specified pressure boundary condition.
  • Screw Surface: Specify the material properties and wall conditions for the screw's surface.
4. Defining the Physics:
  • Fluid Properties: Define the fluid properties like density, viscosity, and thermal conductivity.
  • Solver Settings: Choose appropriate solver settings. For steady-state simulations, the Pressure-Based Solver is commonly used.
  • Turbulence Model: Choose an appropriate turbulence model (like k-epsilon, SST k-omega, etc.) depending on the flow characteristics.
5. Running the Simulation:
  • Initialization: Set up initial conditions for the simulation.
  • Run the Simulation: Start the simulation and monitor its progress. Depending on the complexity of the geometry and the mesh, this might take a significant amount of time.
6. Post-Processing:
  • Results Interpretation: Once the simulation is complete, analyze the results. Look at velocity profiles, pressure distributions, and other relevant parameters.
  • Visualization: Use the software's visualization tools to create visual representations of the flow patterns.
7. Validation and Iteration:
  • Compare with Experimental Data: If available, compare your simulation results with experimental data to validate your simulation.
  • Iterate: If there are discrepancies, iterate. Check your boundary conditions, mesh quality, and solver settings. Small changes can significantly affect the results.
Remember, every CFD software might have slightly different steps and interfaces, so it's crucial to refer to the specific user manual or tutorial related to the software you are using. Many CFD software providers also have online forums and communities where you can ask specific questions related to your simulations.
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Hello, the Research community,
I'm currently working on a project involving heat transfer between a solid domain and a liquid domain using Ansys Fluent, and I'm facing some challenges. Here's a brief overview of my setup:
  1. I have created a cylindrical solid domain.
  2. Inside this solid domain is a liquid domain where a fluid continuously flows.
  3. The inner walls of the cylindrical solid domain are maintained at a high temperature of 2000 degrees Celsius.
I aim to simulate and analyze the heat transfer process between the solid domain walls and the flowing liquid. I'm seeking guidance on the further steps to solve this problem effectively. Specifically, I'm looking for advice on:
  1. Setting up the boundary conditions for the solid domain.
  2. Specifying the properties and conditions for the liquid domain.
  3. The appropriate turbulence models and thermal settings to consider.
  4. How to initiate the simulation and monitor the heat transfer process.
  5. Any best practices or considerations for a case like this.
I would greatly appreciate any insights, tips, or step-by-step guidance from those with experience in conducting heat transfer simulations in Ansys Fluent. Your assistance will be invaluable in helping me advance my project.
In addition, kindly guide me through the necessary steps to create an effective heat transfer interface between the solid and liquid domains in Ansys Fluent. Any insights, tips, or tutorials to help me set up this heat transfer simulation would be greatly appreciated.
Thank you in advance for your assistance.
Thank you in advance for your support.
Best regards,
Sudeep N S
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Dear Sudeep N S ,
It can be challenging for anyone to provide assistance for all your inquiries. I would kindly suggest beginning by watching some introductory videos, which can help you grasp the basic concepts. As for the specific question you've raised, I'm actively working on addressing it;
1) To set boundary conditions in Fluent: Provide a clear name and select the appropriate object in the cell zone condition. Choose the right option for BC (inlet, outlet, interface, wall).
2) When dealing with liquid properties: Access the Fluent database in the material section. Edit as needed and confirm cell zone conditions, input, and output values.
3) Regarding turbulent models, there are two options: The k-epsilon model excels in free stream regions. The k-omega model offers high accuracy in boundary layers near walls. Choose based on your specific requirements.
4) To simulate and monitor heat transfer in ANSYS Fluent:
  1. Launch Fluent: Open the software and set up your project.
  2. Geometry: Import or create your geometry, ensuring correct scaling and orientation.
  3. Materials: Define the thermal properties of the involved materials.
  4. Mesh: Create a quality mesh for accuracy.
  5. Boundary Conditions: Set initial conditions, heat sources, and types of heat transfer at boundaries.
  6. Solver: Choose the appropriate solver (steady-state or transient).
  7. Solution Methods: Configure discretization and convergence settings.
  8. Initialization: Define initial temperature conditions.
  9. Run the Simulation: Start the simulation to solve heat transfer equations.
  10. Monitor and Analyze: Check progress, and convergence, and use post-processing tools for analysis.
  11. Save Results: Store simulation data for future reference.
  12. Iterate: Adjust settings as needed for accuracy, consulting Fluent documentation if necessary.
5) For effective heat transfer simulations in ANSYS Fluent:
  1. Prioritize high-quality mesh.
  2. Choose the right solver (steady-state or transient).
  3. Set precise boundary conditions.
  4. Use accurate material properties.
  5. Properly initialize your simulation.
  6. Set reasonable convergence criteria.
  7. Consider adaptive mesh refinement.
  8. Validate your results with experimental data or analytical solutions.
These steps will help ensure accuracy and efficiency in your heat transfer simulations.
I hope this answer has been helpful. If you have more questions or face challenges, feel free to ask. I'm here to assist you.
Regards,
Ekta
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I would like your expertise and guidance regarding a challenging Computational Fluid Dynamics (CFD) problem I currently have. The project involves species transport in Ansys Fluent, focusing on simulating a steam methane reforming process.
The issue I am encountering pertains to the Chemkin files that I have uploaded into the Ansys Fluent software. Unfortunately, I am encountering persistent errors, and it seems the software is not properly considering the uploaded Chemkin files. I have thoroughly reviewed the inputs, but the problem persists. Despite my best efforts, I have been unable to resolve this issue.
Furthermore, in this simulation, a key aspect involves maintaining a wall at an elevated temperature of 2000 degrees Celsius. The objective is to facilitate heat transfer to the methane and steam feed mixture to initiate the steam methane reforming reaction.
Regrettably, I have observed that the heat is not effectively transferring to the feed mixture, resulting in the absence of the desired chemical reaction. This poses a significant setback to the project, as the core objective is to study the reaction kinetics and product distribution in this specific environment.
Your support in this matter would be immensely important to my research progress.
Thank you in advance for considering my request. I am eager to learn from your expertise and am open to any suggestions or instructions you may have.
Sincerely,
Sudeep N S
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Hi Anurag Sharma,
Thanks for showing interest in my problem.
Could you please review the attached files and guide me in understanding the concept of the core?
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FORTRAN in CFD Solvers
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FORTRAN is still being used to write CFD codes for a number of reasons, including:
  1. Performance: FORTRAN is a compiled language, which means that the code is converted into machine code before it is executed. This makes FORTRAN programs very fast and efficient.
  2. Maturity: FORTRAN is a mature language that has been used for decades to write scientific and engineering software. This means that there is a large body of knowledge and experience available to FORTRAN programmers.
  3. Portability: FORTRAN compilers are available for a wide range of platforms, including workstations, mainframes, and supercomputers. This makes it easy to port FORTRAN CFD codes to different computing platforms.
  4. Libraries: There are a number of well-established FORTRAN libraries available for CFD, such as PETSc and FEniCS. These libraries provide a wide range of functionality for solving CFD problems, such as mesh generation, linear solvers, and flow visualization.
While FORTRAN is a powerful language for writing CFD codes, it is also a relatively old language. It can be more difficult to learn and use than newer languages, such as Python and C++. However, for many CFD researchers and practitioners, the performance, maturity, portability, and libraries available for FORTRAN make it the best choice for writing CFD codes.
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Hello dear all,
We want to set-up a CFD -Discrete Particle Modelling case for a bubble column where liquid is eulerian and gas bubbles and solid particles are discrete phases (three-phases total holdup <10 %) as given in attached diagram. In this case only gas bubbles are flowing with velocity UG <1 cm/s while liquid and solid particles have no initial velocity (means batch mode). Boundary condition (DPM) for gas phase at outlet is pretty straight forward "escape" but we want to retain second discrete phase "particles" with in column volume. However, Boundary condition panel in Ansys Fluent do not show "escape" or "wall" or "reflect" for an individual DPM (injection) phase but one for all DPMs.
We want to model the effect of gas bubble induced flow behavior (in one-way coupling) on liquid and solid phases, so we need to keep liquid in batch mode and solid phase (one-time injection). Any suggestion on how to set-up DPM-BC for two discrete phases (two different injections) separately in Ansys Fluent?
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Solved the above problem by specifying user-defined boundary condition for each discrete phase based on velocity function for size-dependent DPM
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How can we optimize the flow & consumption of fuel in Aerospace sector using CFD ?
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Optimizing the flow and consumption of fuel in the aerospace sector using Computational Fluid Dynamics (CFD) is a critical aspect of aircraft and spacecraft design and operation. CFD allows engineers and researchers to simulate and analyze the behavior of fluids (such as air or fuel) within aerospace components like engines, wings, and combustion chambers. Here are some ways CFD is used and the latest research trends in this field:
  1. Aerodynamic Design: CFD is used extensively in the design of aircraft and spacecraft to optimize their aerodynamic performance. Researchers use CFD to analyze airflow over different parts of the vehicle, including wings, tail fins, and fuselage. The goal is to reduce drag and improve fuel efficiency.
  2. Engine Performance: CFD plays a crucial role in optimizing the performance of jet and rocket engines. It helps in designing efficient combustion chambers, nozzles, and cooling systems. By simulating the flow of air, fuel, and exhaust gases, engineers can identify areas for improvement in terms of combustion efficiency and thrust generation.
  3. Fuel Injection and Combustion: CFD is used to model and optimize the fuel injection and combustion processes in engines. Researchers investigate factors like fuel atomization, mixing, and combustion stability to improve fuel efficiency and reduce emissions.
  4. Heat Management: In spacecraft, managing heat is crucial to prevent overheating and ensure the safety of onboard systems. CFD is used to simulate heat transfer within spacecraft components, allowing engineers to design effective cooling systems.
  5. Noise Reduction: CFD can be used to study the aerodynamics of aircraft components to reduce noise generation. Quieter engines are not only more environmentally friendly but also improve passenger comfort.
  6. Advanced Materials: Researchers are using CFD to study the behavior of advanced materials like composites under different aerodynamic and thermal conditions. This helps in designing lighter and more fuel-efficient aircraft.
  7. Machine Learning Integration: Recent research is focusing on integrating machine learning with CFD simulations. This enables faster and more efficient optimization processes by using AI algorithms to guide simulations and make design recommendations.
  8. High-Performance Computing: As CFD simulations become more complex, high-performance computing (HPC) is crucial to run simulations at a scale that provides meaningful results. Researchers are exploring ways to harness the power of supercomputers and cloud computing for CFD analysis.
  9. Multi-Physics Simulations: Beyond fluid dynamics, CFD is being integrated with other physics simulations such as structural analysis (CFD-Structural coupling) to provide a more comprehensive understanding of the behavior of aerospace components.
  10. Green Aviation: Given the increasing focus on environmental sustainability, CFD is being used to design more eco-friendly aircraft. This involves optimizing not only fuel efficiency but also reducing emissions and noise pollution.
To stay updated on the latest research in CFD analysis in the aerospace sector, you can refer to academic journals, industry conferences, and research institutions specializing in aerospace engineering. Many aerospace companies and research organizations also publish whitepapers and reports on their ongoing work in this field. Additionally, keeping an eye on advancements in computational techniques and software tools for CFD can be valuable for staying informed about the latest developments.
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Detailed suggestions are needed with tutorial link etc.
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First, Matlab is not a visualization software for CFD, yu should think to use Tecplot or similar.
However, for some 2D problems and structured grids, you can find useful commands like contour, mesh, surf, quiver.
HAve a look here:
In Matlab you can find also the CFDTool
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Dear CFD Researchers,
Since AI tools are currently very popular, I am wondering if anyone use them to choose turbulence model for a CFD case.
So if you did, please share your experiences. Due to the answer, we can extend the boundaries of this discussion.
Thank you for your comments.
Kind regards,
Guven
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First question: where could have ChatGPT taken the relative information for training? Honestly, if you're going to use that, I can't see how you could not want to know about that.
Second question: why ChatGPT? This is not some complex information we can't extract from complicated data. It's just exactly there for you to learn or to search trough. Also, it could be better done by making a new net from scratch just about that, than using a LLM that really has nothing to do with this.
My general comment is that engineers and scientists should not look for answers in a tool that is not even tought to be what they want. ChatGPT just spits out words following a prompt and a statistical model. That is not different from a bad student that just goes by memory without understanding. ChatGPT is actually worst, as it never assumes it could not know something. You wanna ask that about turbulence models? Oh my...
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Hello all,
I'm doing a 2D simulation of flow beneath a partially-submerged rectangular bluff body. The problem's geometry is shown in the figure attached. I'm using a fully structured hexahedral mesh with a y+ of below 1. When the draft (i.e. t in the figure) is small, the model predicts the reattachment length (i.e. Lr) quite accurately. However, it leads to excessive reattachment lengths for cases of large drafts.
As the draft increases, I wonder what turbulent mechanisms/characteristics become influential that SST fails to capture properly. Could it be the increasing curvature of the streamlines or probably turbulence anisotropy? I appreciate any insights.
Regards,
Armin
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I don’t use RANS formulation, I can just address some general questions:
1) use at least 3-4 nodes within y+<1
2) Are you comparing your solution to experimental measurements? Are you sure to be congruent with the experimental inflow conditions?
3) have you assessed you are able to reproduce the results for the classic test-case of the backward facing step at high Re number?
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Hi everyone. I have some problems about evaporation - condensation. (This is very long question :) )
I am trying to simulate water evaporation for different designs but actually I can't.
I'm a relatively newbie in liquid-gas two-phase simulations, especially in Fluent. I'm trying to simulate evaporation and condensation that occurs at every temperature, not boiling. I can't get the right result when I run my models by trying the VOF and mixture models.
The methods I have tried so far and the methods I did not get results:
I defined three phases (air, water-liquid and water-vapor).
1. I created a piecewise - linear graph for saturation temperature by choosing water to steam as the mass transfer. There was no evaporation. Also, if I choose steam to water, I got a negative latent heat error.
2.While researching, I tried creating source terms for cell zone, liquid and vapor. Simply, if t>t_sat was evaporation, if t<t_sat was condensation mechanism, they were udfs. I added define properties(saturation_temp) in udf, but I don't know if I made a mistake in Fluent, I couldn't Run the simulation. (Even if evaporation-condensation started somehow, the mass transfer rates were not correct.)
3. Lastly, I watched solar still videos on YouTube and tried to reproduce it. I tried to do exactly the same things, but what people do either doesn't work or even if the simulation works, evaporation at low temperature doesn't start.
To conclude; I need tips, a step-by-step guide, or the right UDF files to get to the right model. I am open to any help. 😊
If I don't get a result, I will try with OpenFoam, but my priority is Fluent because of my colleagues' Fluent experience and habits. (Another reason is that Fluent seems to be the easiest way for us to transferring this experience to our students when necessary.)
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I would first recommend you validate your numerical model with existing literature. Once you identify a good reference, you can use their boundary conditions, and numerical setup to generate the results. Make appropriate changes until you get within acceptable accuracy limits. Once you are done with validation you can use it for your own purpose. The validation will help you choose the right models, equations, etc for the evaporation-condensation process.
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Turbulence structure is described by the formation of eddies. Size of eddies vary based on the turbulence length scale ( (Kolmogrove, Reynold and Hinze). Smaller eddies describes intense turbulence, larger eddies display low turbulence zone.
Recently, I came across a book by Bertin and Cummings, which says there are no physical laws to describe detailed turbulence structure pattern.
Are there any ?
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Turbulent flows occur for high Reynolds numbers. The energy cascade transfers turbulent energy from large to smaller eddies via inertial interactions with no energy dissipation. Viscous dissipation occurs in the smallest eddies for which the Reynolds number that characterizes their movement is of order 1 (Kolmogorov scale)
For more, I would recommend the book by Tennekes, H., & Lumley, J. L. (1972). A first course in turbulence. MIT Press (more than 12 000 citations). As suggested by its title, the book is a basis for a fundamental understanding of the physical mechanisms of turbulence and for the acquisition of the methodological elements related to the phenomenological approach applied to the analysis of basic turbulent flows. The book is Available on:
https://www.academia.edu/download/54563360/Henk_Tennekes__John_L._Lumley_A_First_Course_in_Turbulence.pdf (more than 12 000 citations) is essential for a fundamental understanding of the physical mechanisms of turbulence and for the acquisition of the methodological elements related to the phenomenological approach applied to the analysis basic turbulent flows.
Description by the authors "This is the first book specifically designed to offer the student a smooth transitionary course between elementary fluid dynamics (which gives only last-minute attention to turbulence) and the professional literature on turbulent flow, where an advanced viewpoint is assumed.
The subject of turbulence, the most forbidding in fluid dynamics, has usually proved treacherous to the beginner, caught in the whirls and eddies of its nonlinearities and statistical imponderables. This is the first book specifically designed to offer the student a smooth transitionary course between elementary fluid dynamics (which gives only last-minute attention to turbulence) and the professional literature on turbulent flow, where an advanced viewpoint is assumed. Moreover, the text has been developed for students, engineers, and scientists with different technical backgrounds and interests. Almost all flows, natural and man-made, are turbulent. Thus the subject is the concern of geophysical and environmental scientists (in dealing with atmospheric jet streams, ocean currents, and the flow of rivers, for example), of astrophysicists (in studying the photospheres of the sun and stars or mapping gaseous nebulae), and of engineers (in calculating pipe flows, jets, or wakes). Many such examples are discussed in the book. The approach taken avoids the difficulties of advanced mathematical development on the one side and the morass of experimental detail and empirical data on the other. As a result of following its midstream course, the text gives the student a physical understanding of the subject and deepens his intuitive insight into those problems that cannot now be rigorously solved. In particular, dimensional analysis is used extensively in dealing with those problems whose exact solution is mathematically elusive. Dimensional reasoning, scale arguments, and similarity rules are introduced at the beginning and are applied throughout. A discussion of Reynolds stress and the kinetic theory of gases provides the contrast needed to put mixing-length theory into proper perspective: the authors present a thorough comparison between the mixing-length models and dimensional analysis of shear flows. This is followed by an extensive treatment of vorticity dynamics, including vortex stretching and vorticity budgets. Two chapters are devoted to boundary-free shear flows and well-bounded turbulent shear flows. The examples presented include wakes, jets, shear layers, thermal plumes, atmospheric boundary layers, pipe and channel flow, and boundary layers in pressure gradients. The spatial structure of turbulent flow has been the subject of analysis in the book up to this point, at which a compact but thorough introduction to statistical methods is given. This prepares the reader to understand the stochastic and spectral structure of turbulence. The remainder of the book consists of applications of the statistical approach to the study of turbulent transport (including diffusion and mixing) and turbulent spectra."
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Hi All,
Question: How do I get Mach No contour for CFD Post-processing?
Description:
  • Solution computed using HPC
  • Cannot open the file back in fluent with Case & Data to export Mach No variable.
  • However, with the data file, I can open it in the post but no Mach number is available.
What could I try?
Any help is appreciated.
Thank You,
Alin
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Hi
please say how solve it. I choose the Mach number from data quantity files in fluent but it does not exist in cfd post
Thaank you Alin Sonny
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I'm currently facing negative cell volume detected error because of weird mesh deformation, ig I might have made mistake in the dynamic mesh setting but I'm unable to pin point my mistake. Also the simulation occurs for a few time steps with ridiculous values of lift and drag coefficients. I'm attaching below the pictures of deformed mesh, lift, drag coefficient curves, my smoothing and remeshing parameters too. Also I'm using a udf to give motion to the cylinder body. The frequency defined in the udf is 1. I had created a total thickness inflation mesh around my cylinder which is of 5 layers, growth rate of 1.2 and maximum thickness of 0.025. Hence, I first separate the cylinder along with the 5 layered inflation from the surface body, then I give the udf motion to both the cylinder and the 5 inflation layers that I had separated. Kindly help me regarding this issue as I've been trying to solve this issue since past 3 weeks, took reference of changing the time step from various articles but still I get the same error.
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specific changes that you can make to your dynamic mesh settings:
  • Increase the mesh size. This will help to reduce the amount of distortion in the mesh.
  • Increase the frequency of the dynamic mesh updates. This will ensure that the mesh is updated more frequently, which will help to prevent it from becoming too distorted.
  • Adjust the remeshing parameters. This will help to ensure that the mesh is updated in a way that minimizes the negative cell volume errors.@Muthiah CT
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I'm running a surface reaction. I'm wondering how does ANSYS Fluent calculate the surface deposition rate?
Thank you.
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Thank you Mostak Ahamed for your answer. Do you have any reference that you can give me?
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I'm trying to simulate VORTEX INDUCED VIBRATIONS in Flow Around A Rigid Cylinder. The diameter (D) and mass of the cylinder are 0.5 m and 35.78 g, respectively. The spring stiffness is 69.48 kN/m, the damping coefficient is 0.0039 Ns/m and Re=200. I've been trying various UDF since past 2 weeks but everytime m not able to simulate any oscillation so it would be of great help if you kindly provide the UDF.
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What software do you want to solve the problem? Fluent? CFX?...?
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This research aims to investigate the dynamics and properties of accretion disks around black holes using Computational Fluid Dynamics (CFD) simulations. Accretion disks play a crucial role in astrophysics, and understanding their behavior is essential for studying the physics of black holes and their associated phenomena. The proposed research will employ CFD techniques to model the complex fluid flow within the accretion disk, considering factors such as viscosity, magnetic fields, and relativistic effects near the event horizon. The simulation results will be analyzed to gain insights into the disk's structure, energy transport mechanisms, and radiation emissions. The research findings will contribute to advancing our understanding of black hole accretion processes and their impact on astrophysical phenomena.
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Hello! I would be interested in collaborating on a research of such project
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Please, are there any CFD software applications that can be used to generate an O-grid mesh for airfoil flow simulations apart from pointwise?
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You can solve this problem by Ansys Fluent, you can also do meshing with Gambit or ICEM CFD which is in the Ansys software package.
Do you have these software?
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Hi all,
I am currently working on simulating a water jet problem, where water is injected from the left boundary and exits the domain through the right boundary. However, I am facing a challenge of keeping both momentum and mass conservation at the same time. In order to ensure mass conservation in the scenario where a single two-dimensional jet evolves into multiple droplets, it is necessary to enforce the condition that the outlet flux, represented by the product of the cross-sectional area of the droplets (S2) and their velocity (u2), is equal to the inlet flux, represented by the product of the initial cross-sectional area of the jet (S1) and its velocity (u1). Since S2 is typically greater than S1, it follows that u2 must be smaller than u1 to maintain mass conservation. However, this approach alone does not guarantee momentum conservation.
ps: I am using my own code for the simulation and it is an incompressible flow solver, which has been validated in many benchmark cases. The physical properties in my code jump across the interface without any diffusion.
Best regards,
Min Lu
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Hi
It may say that you do the simulation with your own code, or with Fluent or CFX?
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Hi guys
Can anyone model the water spray from the tiny holes in a tank exposed to a hot, high velocity external flame using CFD? What commercial software do you recommend?
thanks
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Can I simultaneously model and solve the tank's flame and water spray? In other words, should all physical fields be modeled at the same time?
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It would make my essay easier to find information about this airfoil.
Thank you anyway!
#naca #aviation #engineering #airfoils #pilots #2430 #information #wind turbine #CFD
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You may find some information regarding different airfoil sections characteristics in the book "Theory of wing sections by Abbot and von Doenhoff".
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I've worked on simulating 3D VIV (a cylinder forced by Karman vortex street) and been stuck with settings. Considering the transition to turbulence due to the oscillation of cylinder (Re≤200, laminar upstream), "SST k-ω coupling with intermittency transition" is my scheme now.
However, I'm not sure whether I should enable "intermittency transition" since I don't fully understand the statement given in the user's guide, which says "The Transition SST model is not Galilean invariant and should therefore not be applied to surfaces that move relative to the coordinate system for which the velocity field is computed; for such cases the Intermittency Transition model should be used instead."
I don't understand the bold sentence in the statement especially. Does it mean the moving surface of cylinder (in my case)? Hope anyone can provide any guideline. Thank you so much.
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Milne Ciou, understanding the concept of Galilean invariance can indeed be beneficial in the field of fluid dynamics, especially if you plan to pursue a career in computational fluid dynamics (CFD) or similar areas. While the term may not appear explicitly in some introductory fluid dynamics textbooks, it is a fundamental concept in physics and is particularly relevant in CFD.
Galilean invariance, also known as Galilean relativity, states that the laws of physics should be the same in all inertial frames of reference. In the context of fluid dynamics and CFD, this means that the predictions of a model should remain consistent when the frame of reference is changed. In other words, the model should provide the same results regardless of whether you analyze the flow from a stationary or moving reference frame.
As you progress in your studies and delve deeper into fluid dynamics and CFD, you may encounter various turbulence models with different levels of Galilean invariance. Understanding this concept will help you make informed decisions when choosing the appropriate turbulence model for a particular simulation.
So, if you plan to work with CFD or fluid dynamics in the future, it would be worthwhile to spend some time learning about Galilean invariance. You can start by exploring classical mechanics or introductory physics textbooks, as well as online resources, to build a strong foundation in this concept.
Good luck with your studies, and feel free to reach out if you have any further questions! Regards,
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Hello everyone!
I'm doing CFD propeller marine. But I am errored. Can you help me?
Error at Node 0: floating point exception
Error at Node 1: floating point exception
Error at Node 2: floating point exception
Error at Node 3: floating point exception
Error at Node 4: floating point exception
Error at Node 5: floating point exception
===============Message from the Cortex Process================================
Compute processes interrupted. Processing can be resumed.
==============================================================================
Error: floating point exception
Error Object: #f
Registering ReportDefFiles, ("C:\kp_files\dp0\FFF\Fluent\.\report-file-0.out")
Calculation complete.
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A floating point exception is an error that occurs when you try to do something impossible with a floating point number, such as divide by zero.
In fluent floating point error can be caused by many factors such as, improper mesh size, defining some property close to zero. However, floating point exception is very specific case that is being solved, the actual reason can be determined by changing one quantity (can be mesh, model, parameters, boundary conditions etc.) at the time.
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So I usually use the COMSOL Multiphysics software to deal with hemodynamic problems with the CFD module of the software. i found OpenFoam as a opensource software but i don't have ideas about it.
is OpenFoam suitable for scientific reasearche in matter of medical field?
what are the major difference between Ansys Fluent, Comsol Multiphysics and OpenFoam?
are the results obtained with OpenFoam equivalent to thous obtained with the commercial software ?
thanks in advance
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Yes. OpenFOAM can be used for flow and fluid structure interactions encountered in hemodynamic flow problems.
OpenFOAM and ANSYS Fluent are mainly based on finite-volume method. Whereas, COMSOL is mainly built based on finite-element method.
The notable difference between OpenFOAM and the other two commercial softwares will be the user-interface. OpenFOAM is inherently built on a TUI. Whereas, ANSYS and COMSOL have a very user-friendly GUI.
But, OpenFOAM is very powerfool for research purposes due to its easy customization possibilities.
Meshing using blockMesh of OpenFOAM can be tedious for complex geoemtries. Hence, you have to depend on some third-party meshing applications and snappyHexMesh, etc.
Whereas, ANSYS and COMSOL have better stand-alone meshing capabilities.
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Hello,
I wish to solve the weak N-S eq (based on PDE's) in COMSOL.
By default, COMSOL applies the equation in all domain but I want to solve it in each mesh (not all domain).
I want to do this in order to add different porosity in each CFD mesh.
Is it possible?
Thanks in advance.
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If I understand correctly, you divided your simulation domain into four regions and tried to solve a PDE in each one separately.
From a numerical perspective, this might give you inaccurate results since FEM evaluates the function at the nodes and estimates the solution between them using the sum of unique basis set. If the points are closer to each other (denser mesh), the simulation is likely to converge faster with reliable results.
I recommend the use of geometrical properties instead. You can divide your domain into many parts in each direction using the "Layers" tab in the geometry definition. Then, you can select each region and solve your PDE separately or solve all of them at once using proper boundary values at the interfaces.
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Which software is mostly preferred in research for preprocessing during CFD analysis and gives best results?
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Hello Syed, it's hard to say which tool works best for you as you did not mention your application.
If you want to carry out fluid or thermal simulation, then it might be worth checking out SimScale. Its automatic mesher and default simulation controls have been specifically designed to be very robust, accurate and user-friendly. That way you can spend most of your time analysing results instead of optimizing your mesh, relaxation factors, Courant number, etc.
If you're looking at niche applications, then you can't go wrong with ANSYS, Siemens or Dassault as they cover areas currently missing in SimScale. If these three don't have your application, you can start looking at OpenFOAM (you might have to create your own solver in OpenFOAM :)
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G'day,
I'm working on simulating 3D Karman Vortex Street, confused how to distinguish laminar and turbulence. As the pic shows (this is a frame before starting oscillation), there is downwash near the top of the cylinder, but the Reynolds number in this case doesn't exceed 200, namely, it should be laminar. ----------------update--->
Yesterday, I asked Perplexity Ai to find some info and it provided some reference talking about the wake structure due to the end of finite cylinder. So now I just want to collect your suggestions, since it seems no reference directly indicates "the downwash is inherent no matter the flow is laminar or turbulent". So if anyone knows relevant paper, please let me know, thank you so much!
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Understanding what "laminar regime" stands for is a topic of basic fluid dynamics.
The flow over an obstacle can be laminar even in case it is unsteady, as happpens in the classic case of laminar vortex shedding.
Turbulence is charactertized by a wide range of vortical structures.
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Hello, I'm COMSOL newbie working on cluster computing.
I'm using distributed parametric sweep mode, in which each server node solves a single problem (ex. Node 1 - Inlet fluid velocity 1m/s, Node 2 - Inlet fluid velocity 2m/s, etc...)
In distributed parametric sweep mode,
(1) I want to monitor multiple convergence plots since multiple problems are solved simultaneously. But I can only monitor a single convergence plot... Please give me some advice.
(2) How can I monitor multiple probe plots (which are Probe parameter - Iteration number plots)? I can only monitor the accumulated probe table, which is the final converged value. But I want to check the probe value trend with respect to iteration number.
Thank you very much!!! Every comment is my energy please help me!
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Quiero monitorear múltiples gráficos de convergencia ya que múltiples problemas se resuelven simultáneamente. Pero solo puedo monitorear un solo gráfico de convergencia... Por favor, dame un consejo.@
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I am working on BioFluid Dynamics. Ansys CFD Post doesn't have an option to plot AWSS and OSI directly like wall shear stress(WSS). So I am unable to plot this. In hemodynamics, it is an important parameter. Can anyone help how to add AWSS and OSI in CFD Post?
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Have you got the solution. If yes please share with us.
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Hi, I am modeling sloshing of a fluid inside a container using ANSYS Fluent. For this, I am using VOF model. I consider two accelerations. ax=2 m/s2 and az=9.81 m/s2. The modeling continues for 2 sec. Physically, a container with a liquid inside under constant acceleration will have a steady inclined surface after sometime. However, the surface that I get fluctuates. As it is shown in the image (it is just an indication), the flat surface reaches to max inclination until t=0.8 sec. After that the surface starts returning to its original flat horizontal condition and again starting going up. Could you please let me know what is the problem? Thank you,
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Dears Mohamad Afifi ,
Mohammed Alnahhal
, Mohsen Ghadyani , @
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I'm doing a 2D transient simulation of turbulent flow past a sharp-edged rectangular bluff body. I'm using a version of k-omega model for turbulence modeling. My objective is the time-averaged flow field; I'm not interested in the instantaneous field. The problem is that I'm not sure how to choose an efficient timestep size.
In the literature, i have come across two methods in this regard:
(a) The timestep is adjusted repeatedly to ensure a max/rms Courant number, or
(b) based on an estimation of the Strouhal number (associated with the dominant frequency of vortex shedding) known from previous experiences, the timestep size is determined such as to resolve each vortex shedding cycle through n temporal increments.
The problem is that, i couldn't find any consensus in the literature over appropriate values for max/rms Courant number or n in either methods. I understand that this should be really addressed through a sensitivity study, but I have very limited computational power to afford that, especially given that it takes a long time for the simulations to reach a statistically converged solution. I am hoping there's some reliable rule of thumb or related studies to use, thereby avoiding such a sensitivity analysis.
I would appreciate your comments.
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A true time accurate solution is obtained by keeping the Courant number below 1. The explicit time integration methods requires this condition to be true for stability and accuracy. One benefit is that you don't need to solve a large linear system of equations, but 1 iteration per time step is sufficient..
Some techniques such as transient SIMPLE, SIMPLEC (or fully coupled solvers/ dual time integration) ... can be used with a larger time step, even CFL = 20, 100 etc... but you will need to put enough inner iterations in each time step to reduce the residuals to near zero values for that particular time step..
Now the question is how to choose a time step..? At high Reynolds numbers and for aerodynamic flows this becomes a problem due to having large stretched cells in the boundary layer... So if you were to go with CFL < 1 the simulation becomes very expensive.. For implicit systems with some iterations per time step can be effectively used with time step estimates based on the Convective time scale, I have seen papers where people have used 0.01 to 0.1 of c/U. Another approach is to put at least 50-100 time steps in each oscillation of the vortex shedding time period.. This way you will filter out the high frequency oscillations (which I believe you are not interested in)...
Hope this helps..
Best
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i have a problem with reaction modeling by Ansys Fluent. when i change the Arrenius parameters, nothing change and it makes me confuse. can anybody help me?
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n ANSYS Fluent, "Finite Rate" and "Eddy Rate" are two different models that can be used to model chemical reactions. The main difference between the two is the way they calculate the reaction rates.
Finite Rate: The finite rate model calculates the reaction rate based on the actual chemical reactions taking place in the fluid. It considers the chemical kinetics of the reactions and the local thermodynamic conditions. This model is more accurate but requires more computational resources and detailed information about the chemical reactions.
Eddy Rate: The eddy rate model calculates the reaction rate based on the mixing of the fluid. It assumes that the reactions are controlled by the mixing of the fluid and not by the actual chemical kinetics. This model is less accurate but requires less computational resources and detailed information about the chemical reactions.
Another difference between the two is that the finite rate model is more suited for high-temperature reactions, whereas the eddy rate model is more suited for low-temperature reactions.
In practice, the choice of which model to use depends on the specific situation. The finite rate model is generally used when more accurate results are needed, while the eddy rate model is used when computational resources are limited.
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Dear ALL,
What project do you recommend for CFDer not software engineer to improve coding skills, Is leetcode a good choice?
In addition, what strategy do you recommend for reading others multiple-file code? Debug and see the stack?
Thanks in advance.
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I am old school CFD researcher; hence, my view point on this issue is old school. For those persons not well acquainted with coding that is closer to machine level, i.e., those not very familiar with memory management and more complicated data structures, I recommend regular FORTRAN. FORTRAN memory and data structure management is easy to grasp, and if you utilize a compiler flag like check bounds, the compiler will identify many memory problems for you. When you code equations in FORTRAN (in either the 77, 90 or 95 releases), your coded equations will look a lot like those in your notes. Debugging is rather easy either by the use of old fashioned print statements or by the use of debugging software. Reading other person's code is an entirely different topic. Unless you are familiar with the compiler or interpreter used to develop the code, you are in for a lot of work. Good luck.
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My combustion simulation is fully converged. The mass imbalance that Fluent calculates is 3×10^-9. However, if i calculate the mass imbalance from the average surface integrals, as (density×velocity)_avg xArea is the mass flux from inlet and outlet, the resulting mass imbalance is the order of 10^-7. What causes this deviation as its order is around 10^2. Thank you.
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Mass weighted averages are more meaningful. For combustion simulations, local density and mass depend on temperature... Area weighted average is based on the mesh...
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Hello everyone.
I have used the CCD to build a table of 25 runs (4 variables and 2 responses). The responses have been calculated based on CFD results. Thus the center point can not be repeated due to constant values in results.
to enhance the precision of models, 15 more runs have been added to the table of experiments (totally 40 runs).
Finally, after analysis, the R2 (adjusted and predicted) is more than 95% for both of responses.
But, I cant see any data about "lack of fit" in ANOVA and fit summery sections.
Could you help me about this problem?
Is it necessary to report the "lack of fit" data in this analysis?
It should be noted that the model predict the responses well.
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Narjes Malekjani So, is it okay to have the same values of center points?
Can we report results without having a Lack of Fit value?
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I am working on wind interference effect in Ansys CFD. Even though the domain and geometry are symmetric, the results in the contour in CFX are not symmetric on Leeward side of the wind but the contour is symmetric in windward side of the building what could be the reason, what are the parameters should I check on?
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In general, a solution can be non-simmetric also for a symmetric geometry.
But that depends on the adopted formulation.
Are you solving steady RANS equations?
How do you check the convergence ?
Are the BCs congruent to a symmetric solution?
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I need a collaborator with experience in code development and, if possible, numerical analysis too.
I am currently developing an open source code in python that can be used to solve different kinds of Integral Equations.
In the last one and half years I have done some work in numerical Algorithms for integral equations with some papers already published. It has culminated to several python codes which I have used to produce the results.
The codes are all private but the results are published so I am inclined to make these codes publicly available so that others can use them at no cost and minimum effort.
I, therefore, need a fellow Researcher who has good skills in software engineering and numerical analysis to join me in this line.
A minimum requirement is the knowledge of git and python.
You can email me at [email protected]
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Chinedu Nwaigwe Great, Interested, In fact, 'm pleased to learn you're working on open-source programs to solve integral equations. Publish your code to make your study more publicly available and to allow others to build on your work.
A partner with skills in code development and numerical analysis would be ideal. As you indicated, knowledge of Git and Python would be a must. However, further knowledge of numerical techniques for solving integral equations would be advantageous.
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Hello everyone.
I am doing a CFD simulation for waste heat boiler and simulation boiling in steam drum.
I used ANSYS Fluent to perform the simulation. However during the calculation section. I received this error
"reversed flow in 274 faces on pressure-outlet 18.
Stabilizing mp-x-momentum to enhance linear solver robustness.
Stabilizing k to enhance linear solver robustness.
Divergence detected in AMG solver: k temperature limited to 1.000000e+00 in 8519 cells on zone 2 in domain 3
turbulent viscosity limited to viscosity ratio of 1.000000e+05 in 18252 cells
Divergence detected in AMG solver: k
Error at host: floating point exception
Error at Node 0: floating point exception
Error at Node 1: floating point exception
Error: floating point exception
Error Object: #f"
May I know what are the possible cause of this error?
Any advice? Thank you
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The "reversed flow in 274 faces on pressure-outlet 18" error message indicates that there is a problem with the boundary conditions at pressure outlet 18. This error can occur if the pressure outlet boundary condition is not properly defined, or if the flow direction at the outlet is opposite to the expected flow direction.
The "Divergence detected in AMG solver: k temperature limited to 1.000000e+00 in 8519 cells on zone 2 in domain 3" and "turbulent viscosity limited to viscosity ratio of 1.000000e+05 in 18252 cells" messages indicate that the solver is encountering numerical instability during the simulation. This can be caused by a variety of factors, including an inappropriate grid, inaccurate boundary conditions, or a poorly defined model.
The "floating point exception" error message indicates that there is a problem with the numerical computation being performed by the solver. This can be caused by a division by zero, an invalid operation, or an overflow.
There are a few things you can try:
  1. Review the boundary conditions at pressure outlet 18 to make sure they are properly defined and the flow direction is correct.
  2. Check the grid quality to ensure that it is suitable for the simulation. A poorly resolved or skewed grid can cause numerical instability.
  3. Review the model and make sure it is properly defined and all necessary parameters are specified.
  4. Check for any invalid or unrealistic input values that may be causing problems with the numerical computation.
  5. Try using a different solver or solver settings to see if the error persists.
I hope this helps!
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Hello, I want to publish a research paper on the assessment of CFD turbulence models, I need an airfoil geometry to start with. where can I find airfoil geometry or profile? and its experimental data, cd and cl values or cl alpha values? I have searched for experimental data, but unfortunately, I did not find any.
Can you please advise me about where to find airfoil geometry and its experimental data?
what type of airfoil should I choose for the assessment of different turbulence models?
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I recommend you the previous links because you can easily copy and paste values from there, but you find theory, airfoil geometry and experimental data here: https://aeroknowledge77.files.wordpress.com/2011/09/58986488-theory-of-wing-sections-including-a-summary-of-airfoil-data.pdf
Also I recommend to search for experimental data here in RG.
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I have used in my current paper the pressure-based solver for air distribution inside the control room, I would like to ask which governing equation determines the velocity field and also the continuity and momentum equations for which purpose work in CFD calculation if there is an explanation
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You can find it in the Ansys theory guide. p-645
If you want a better book to learn the basics of the scheme used you can check the following link.
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Currently, I have completed my research study for CFD simulations, using Ansys Fluent as a student in Anglia Ruskin. Now, I cannot use any Ansys licence through university as I am not anymore a student.
So, I am looking for a good software CFD free of charge to be used for research without restrictions (Student or Educator Version). Ansys Fluent Student version has some limitations and cannot be used for research with refined mesh study. I am looking for alternatives, finding a free good CFD software.
I have looked on Autodesk website and found the Autodesk CFD Ultimate as a Student or Educator version, it is free of charge.
This software can be used for computational fluid dynamics simulations and solid body motion analysis.
However, I have not used this software for CFD and I do not know if there are any limitations.
Is anyone using this software for CFD simulation please let me know if this software has any limitations?
Any idea, suggestion or thought, I would much appreciate.
Thank you.
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The CFD simulations is importance to both students and educators. This is because it is able to open the inside and view the behaviours.
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I wanted to couple two simulations that are calculated separately like in-cylinder combustion and cylinder block, in your opinion can we map boundary conditions of the cylinder with block surface transiently? If yes which tool do you suggest?
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For this case, the use of multiple CFD programs can be useful, such as coupling the towing models with one program and meshing with the simulation using another program.
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I am interested to the discontinuous Galerkin in my research, but after my modest research, I found two type of it Modal DG and Nodal DG. I wanted to know :
how effective is each one of them ?
What is the difference between them ?
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If you are working with modal bases, it is more straightforward to change the order of an element. This means that the existing basis functions do not change. Some people enjoy this because it is easier to work with. Some antialiasing techniques require modal bases to be filtered directly, but this is not a performance bottleneck. Modal commands can also highlight sparsity within an element for special operators. This means that the savings are small for the modest order typically used in 3D. Nodal bases simplify the definition of element continuity and simplify the implementation of boundary conditions, contact, and the like. They are also easier to plot, leading to better ḥh-ellipticity in discretized operators. This, in turn, allows the use of less expensive smoothers/preconditioners. This means that people who create ways of solving problems can more easily use terms like "rigid body modes" and "multigrid methods," and they do not have to change how they think about things when they are using these methods. Discretization is a way to turn an ongoing problem into a discrete one that a computer can solve. An embedded discretization is one where the discretization is done in a way that makes it easy to access and use later on.
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Hello all,
I've got a 2D simulation case in which the flow separates from the sharp leading edge of rectangular bluff body and reattaches to the wall some distance downstream. The main goal is a accurate prediction of pressure distribution along the body's face parallel to the flow.
I'm doing a transient simulation using SST model in conjunction with gamma-Re transition model. The time- cord-averaged y+ is less than 2~3 and the inflation layer around the face of interest contains 10 prism layers. The Re number based on the body's width (perpendicular to the flow) is 1.7e+4.
The problem is that my model overpredicts the reattachment length, which in turn leads to delayed pressure recovery.
I have a suspicion that longitudinal decay of turbulence values specified at the inlet might be to blame. Consulting the Ansys CFX-solver Modeling Guide, I learnt that one solution is to prescribe appropriate turbulence values at the inlet based on the desired values at the body. An alternative approach also suggests some additional source terms for k and w transport equations in order to preserve the inlet values up to some distance upstream the body, from where decay is allowed.
Here are my questions:
1- Is my suspicion valid in the case of my problem?
2- Is the decay of turbulence of physical basis or a numerical artifact?
3- which of the two methods works better? Are there any attempts in the literature?
I appreciate your comments.
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trying to achieve a match with experimental measurements is not a simple task. In your formulation you should match the statistics of the experimental inflow and that is not straightforward also for a laminar flow problem as detailed in Sec.4 here
A further issue could be also due to the fact your grid resolution is not sufficient to resolve the BL. You should be able to set at least 3-4 nodes at y+<1 along the surface of the body.
Again, I strongly suggest to try your setting for the well studied problem of the backward facing step turbulent flow. You can find a lot of results in literature.
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I'm currently using fluent simulating the cold flow of a supersonic combustion chamber with using hydrogen as fuel. But I can't make it to start the first iteration. Can someone give me some advice?
These are the error respond from fluent
WARNING: Invalid cp (0.000000e+00 J/kgK) for oxygen at temperature -1.#IND00 K
reversed flow in 500 faces on pressure-outlet 8.
Stabilizing nut to enhance linear solver robustness.
Divergence detected in AMG solver: nut
WARNING: Invalid cp (0.000000e+00 J/kgK) for hydrogen-air at temperature -1.#IND00 K
Divergence detected in AMG solver: nut
WARNING: Invalid cp (0.000000e+00 J/kgK) for hydrogen-air at temperature -1.#IND00 K
Divergence detected in AMG solver: nut
WARNING: Invalid cp (0.000000e+00 J/kgK) for hydrogen-air at temperature -1.#IND00 K
Divergence detected in AMG solver: nut
WARNING: Invalid cp (0.000000e+00 J/kgK) for hydrogen-air at temperature -1.#IND00 K
Divergence detected in AMG solver: nut
WARNING: Invalid cp (0.000000e+00 J/kgK) for hydrogen-air at temperature -1.#IND00 K
Divergence detected in AMG solver: nut
WARNING: Invalid cp (0.000000e+00 J/kgK) for hydrogen-air at temperature -1.#IND00 K
Divergence detected in AMG solver: nut
WARNING: Invalid cp (0.000000e+00 J/kgK) for hydrogen-air at temperature -1.#IND00 K
Divergence detected in AMG solver: nut
WARNING: Invalid cp (0.000000e+00 J/kgK) for hydrogen-air at temperature -1.#IND00 K
Divergence detected in AMG solver: nut
WARNING: Invalid cp (0.000000e+00 J/kgK) for hydrogen-air at temperature -1.#IND00 K
Divergence detected in AMG solver: nut
Error at host: floating point exception
Error at Node 0: floating point exception
Error at Node 1: floating point exception
Error at Node 2: floating point exception
Error at Node 3: floating point exception
Error at Node 4: floating point exception
Error at Node 5: floating point exception
Error at Node 6: floating point exception
Error at Node 7: floating point exception
Error at Node 8: floating point exception
Error at Node 9: floating point exception
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Are you applying compressed ideal gas law? Also, set operating pressure zero and operating density also zero. Don't use outflow boundary condition.
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Consider a pipe in a cylindrical coordinate. The flow is a fully developed laminar flow and the temperature field is T(x, r, θ). At a certain cross section x_0, the mean temperature is T_m and the mean velocity is u_m (To calculate T_m or u_m, integrate the temperature or velocity over the whole cross section and divide the result by the area). A conjecture is that u*partial T/partial x=u_m*dT/dx, where partial denotes the partial derivative. This seems reasonable since the heat transfer should be easier where fluid flows faster, which leads to a smaller gradient. But how can I prove it strictly?
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You can find the answer on your question in the treatise of Schlichting, chapter Thermal boundary layer.
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I am aware that several definitions of stream-function in 3D flow do exist in the literature. But I am at a loss on what stream-function physically means in 3D.
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What Nemati said is wrong. If a flow is irrotational, a velocity potential exists in 3d, while independent of irrotational condition) the stream function is defined just in 2D flows, and (in 3D) only for axisymmetric flows. Moreover, the stream function is not xF, but it is the one dimensional vector F, oriented in the invariant z direction orthogonal to a flow in the (x,y) plane.
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Hi all,
I am going to use either Ansys CFX or Ansys Fluent solver to simulate flow past a semi-submerged rectangular cylinder, as shown in Fig. 1. The main goal here is to achieve an accurate prediction of pressure distribution over the cylinder, which seems to be particularly reliant on the capability of the CFD model to predict the separation and the reattachment of the flow correctly. I would appreciate any tips regarding the following questions.
Q1. How important is the choice of the turbulence model? Which models are superior? Could the flow be modelled as being laminar at all?
Q2. How important is the approach to the free surface? Could the free surface be modelled as a free-slip wall to reduce computational costs? Is it necessary to precisely track the free surface using the VOF model for this study?
Q3. What are the most appropriate boundary conditions for the simulation?
Q4. Which is more suitable for this problem? CFX or Fluent?
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If the size t is less than 8-12 distances to the bottom surface, the drag force will be determined, among other things, by the added masses of the liquid reflected from the bottom surface. If this is not important, then in the model you need to specify a distance of more than 12.
The number of wall layers is enough 5.
From above on a free surface, the wind has a speed and direction?
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The number of papers published every year on medical CFD has increased by 10 times in the last 20 years (see attached figure).
We all know that there are many papers are just out there for the sake of publication or to get points for a funding program. However, CFD has indeed become quite a mature technology for medical simulation applications in many areas such as vascular and respiratory medicine.
What are the genuine drivers power this increase in the number of medical CFD papers?
Would love to read your thoughts.
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Just a personal opinion, based on 60 years experience.
From the 1950s, with analogue computers and calculating machines, there have been attempts at physical modelling of cardiovascular hydrodynamics and to a lesser mathematical extent respiratory fluid dynamics and gas exchange.
These have usually been motivated by inter disciplinary collaborations or in some rare cases by individual medical trained people who were also well educated in mathematics and physics ..
The topics chosen were usually the most amenable to mathematical modelling rather than the most clinically relevant.
With the development of digital computers and easy to use software packages requiring much less mathematical and physical knowledge, modelling has become more doable in medicine and especially in biomedical engineering. This has enabled more relevant problems to be addressed and has attracted a wider class of "mathephysicians", medical biophysicists and medical computing people and created its own academic niche.
However , many of the most important medical research developments have been due to mathematics/physics carried out by non medical people eg CT scanning, MRI, DNA sequencing, PCR, prosthesis design, neural net theory, drug design.
See Nobel prize winners.
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I am working on modeling of Direct Contact Membrane Distillation system with COMSOL Multiphysics software. I have some problems with the mass transfer part of the simulation because I don't know which boundary condition is appropriate for boundaries between membrane-cold and membrane-hot channels. Is anybody knows how I can solve this problem?
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I have just simulated a steady state 2D methane-air combustion case with species transport model and eddy-dissipation turbulence-reaction model with the use of Fluent code. The solution is converged and the results match very well with the experimental data. For some purpose, I need to show manually that the transport equation for N2 equals zero since it is an inert gas and does not participate in the reactions. I got all the necessary flow field variables from the CFD solution such as density, axial and radial velocity, and N2 mass fraction. For some points in the flow field, I am trying to solve manually the same turbulent transport equation for N2, which Fluent code solves, with the central finite difference method using the flow field variables from CFD. My step size in the flow field is 0.0002m for the finite difference method. However, my finite difference method results are far from 0, which means as if N2 gas participates in the reactions. I find the reaction rate term (Rn2) for N2 around 5 kg/m3.s, as it must be very close to 0 for the numerical solution.
Where do you think I am wrong or missing something? Thank you very much.
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You cannot use an arbitrary discretization! You have to reply exactly the same formula used by Fluent.
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I'm now studying the transportiveness of discretisation schemes using An introduction to Computational Fluid Dynamics: The finite Volume Method; HK Versteeg & W Malalasekera; 1995. In Page 144 it says "Since there is no diffusion φ_P is equal to φ_W. If the flow is in the negative x-direction we would find that φ_P is equal to φ_E" (The x-direction is W -> P -> E, and there is only convection and no diffusion, so Peclet number = inf. See the appended figure for details.).
This really confuses me, does it mean if the flow is in the x-direction, then φ_P is unequal to φ_E and they are equal only if the flow is in the negative x-direction?? I cannot understand it because if the flow is in the x-direction, E will be downstream of P and will only be influenced by P, so φ_E is equal to φ_P, which follows that φ_W=φ_P=φ_E.
Do I make a mistake? Please help me, thanks a lot!
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Do not pay too much attention on the shape of the regions, that can be misleading since of the 1D spatial problem.
The best way to start understanding the hyperbolic character is to use the simple linear problem dphi/dt+u dphi/dx=0. Then, consider the exact solution phi(x,t)=phi(x-u*t,0) that is phi is constant along the characteristic line dx/dt=u. Compare that to the CFL=u*dt/h to see what happens in case of upwind. You will see when you get an interpolation or an extrapolation of the values.
For a deeper understand of such problems, have a look at the tectbook of Leveque.
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Dear all,
Does anyone know how to edit the geometry of the dambreak.msh file provided by ANSYS Fluent?
Or does anybody have a project file for the dambreak case without the statement that the mesh file is imported and therefore not editable.
We want to add a geometry in the downstream region as an obstruction.
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Dear Momen,
Thank you very much, I appreciate it!
When can I call you, what do you prefer?
Regards, Rob
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Hi there,
I'm working 2D axisymmetrical pipe groove (CFD) model with constant wall temperature. During the hybrid initialization, I have a non-positive element error along with a floating point exception. I believe I'm missing something. Any suggestions would be really helpful?
Thank you
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i actually meant to say.. dont use hexa mesh.. i could not go back and correct it.. sorry about that..
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Hi, I have been trying to import the thermophysical properties of CO2 (for the supercritical region) to Fluent by using UDF (only for 80 bar). End of the analysis, the result is not correct. I think Fluent is pulling a Tref value which causes my enthalpy to go negative; therefore, the energy equation does not give accurate temperature results, so the result of thermophysical properties, which are functions of temperature, are wrong. I want to be grateful if you could share your recommendations, especially on the methods of correct calculation of enthalpy. My specific heat code is as follows:
#include "udf.h"
DEFINE_SPECIFIC_HEAT(supercritical_cp, T, Tref, h, yi)
{
real cp;
if (300. >= T)
{
cp = 2.256999118844760E-02 * pow(T, 4.) - 2.606618818487370E+01 * pow(T, 3.) + 1.129129898467780E+04 * pow(T, 2.) - 2.174235523392760E+06 * T + 1.570278261279480E+08;
}
if (306. >= T > 300.)
{
cp = 1.147018354719330E+01 * pow(T, 4.) - 1.385519872072390E+04 * pow(T, 3.) + 6.276090044658930E+06 * pow(T, 2.) - 1.263530241490370E+09 * T + 9.539285116131690E+10;
}
if (307.8 >= T > 306.)
{
cp = -1.611612838918710E+04 * pow(T, 4.) + 1.978085636985280E+07 * pow(T, 3.) - 9.104578256081260E+09 * pow(T, 2.) + 1.862478067464320E+12 * T - 1.428738938943020E+14;
}
if (310. >= T > 307.8)
{
cp = -1.576135476848110E+03 * pow(T, 4.) + 1.945866130859760E+06 * pow(T, 3.) - 9.008641337104630E+08 * pow(T, 2.) + 1.853611584329810E+11 * T - 1.430227164258690E+13;
}
if (320. >= T > 310.)
{
cp = 1.770529718817220E+00 * pow(T, 4.) - 2.242833202341920E+03 * pow(T, 3.) + 1.065432793165650E+06 * pow(T, 2.) - 2.249454519629040E+08 * T + 1.781003821884030E+10;
}
if (T > 320.)
{
cp = 2.086961941877520E-03 * pow(T, 4.) - 2.851496372954040E+00 * pow(T, 3.) + 1.461548345109060E+03 * pow(T, 2.) - 3.330816449664890E+05 * T + 2.848088978782360E+07;
}
*h = cp*(T-Tref);
return cp;
}
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I've looked at the polynomials that you have noted: none of them make sense, whether using actual temperatures or reduced temperatures.
I suggest going back to the original data and making your own, (lower order) curve fit using Excel.
One further comment, you would be mis-calculating enthalpy if you used your last equation as it assumes a constant specific heat over the temperature range: the correct form is to integrate Cp.dT over the range, I would integrate the secific heat equation (if it was correct).
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How can I add FLOTRAN CFD in ANSYS together with the elements 2D FLOTRAN 141 and 3D FLOTRAN 142?
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hi Nikos,
Have you got the answer of "How can I add FLOTRAN CFD in ANSYS together with the elements 2D FLOTRAN 141 and 3D FLOTRAN 142?"
Please share the solution if you got it as i am also interested in doing this.@Nikos
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I want to develop sediment transport 2D model and flow 2D model on floodplain river. What is te best software package for it? How can I get them? What is process of acquiring CCHE2D. FLOW 2D, SRH 2D, Delft 3D, Ansys or CFD kind software with full version?
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The Environmental Fluid Dynamics Code (EFDC+) is an open-source 2/3D model that is quite powerful for such applications. It includes advanced features for hydrodynamic simulations, wetting and drying, and sediment transport simulations.
You can download the source code and compiled executables from GitHub: https://github.com/dsi-llc/EFDCPlus
The package from GitHub also includes a simple grid generation tool.
GUI software, EFDC+ Explorer Modeling System, is also available to support EFDC+ model development, calibration, post-processing, etc. at: www.eemodelingsystem.com
Licenses range in price depending on if you are an academic or commercial user, so please reach out to [email protected] with any questions.
However, even if you choose not to use the GUI you will still have full access to all the model features, and can make use of example demonstration models and test cases to learn how to build the input files.
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.
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can anyone give boundary condition code explanation in keller box
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I'm trying to simulate natural convection electric motor in a air enclosure where temperature difference is around 150k so I can't use bousinesq approximation. So I had to use Ideal gas as air's density but I'm unable to solve the model.
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Pls do refer to the Comsol blogs on natural convection available on the comsol website. You'll get a clear idea of how to proceed.
Let me know if you have any other doubts.
Regards
Gautam
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I have simulated a flow in Ansys FLUENT [Transient] and got around 3000 contours. Each contour for a timestep. I need to combine all those image frames to get an animated video.
I have tried to use online converters. But, since the number of frames is too much, uploading those to the cloud seems complicated. Could anyone please suggest any freeware to convert those image frames to video animation?
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Hi,
ffmpeg is your friend here. Googeling for 'ffmpeg image to video' or something like that produces a lot of material. This one, e.g., seems decent
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Hi All,
I have multiple 3D snapshots of a tractor trailer exported from CFD. I am doing some other data analysis on them and then I want to visualise the contour of this processed data. To start, I am just trying to plot CFD data directly using x,y,z cordinate and velocity values.
The problem I am mainly having is:
a. Contour does not capture the geometry boundaries properly and the shape looks distorted. My x,y,z,u,v, and w are column vector. when I make mesh grid of x.y at z=0, I use griddata command to reshape my velocity vector into the same n by n vector as mesh grid is.
b. When I was trying to reshape my velocity vector on the meshgrid using GRIDDATA() command, it was giving warning of duplicate data points have been detected and averaged. I resolved this using unique() command but this has not made any improvement n visualisation.
I have attached some matlab pictures of my results and a picture of CFD result which I am expecting to see.Please find the link below of one snapshot of data if someone wants to give a try.
below is the code I am using. I use for loop as later I will be using multiple files.
clear all; clc; close all;
%Read data Files%
dataName='saved_data'; % save a file in the directory to keep all data
save(dataName); %Save empty file
dinfo = dir('*.txt'); %Read directory for all text files
files={dinfo.name}; %save names of all text files in files to use in the loop
delimiterIn=' '; %How data is seperated
headerlinesIn=1; %is there any header
n=numel(files); % number of snapshots
for j=1:n
currentFile=files{1,j}; %load jth snapshot
raw_data=importdata(currentFile,delimiterIn,headerlinesIn); %read data in the snapshot
%and save it in raw data
end
%% Raw data%%
X=raw_data.data(:,2);
Y=raw_data.data(:,3);
Z=raw_data.data(:,4);
U=raw_data.data(:,11);
V=raw_data.data(:,12);
W=raw_data.data(:,13);
%% Scatter interpolant%%
[~, I, ~] = unique([X Y Z],'first','rows'); %here I noticed that there were some duplicate data points which I removed
X1 = X(I);
Y1 = Y(I);
Z1 = Z(I);
U1=U(I);
V1=V(I);
W1=W(I);
U2 = scatteredInterpolant(X1, Y1, Z1, U1); %this does not have any duplicate warning now
V2 = scatteredInterpolant(X1, Y1, Z1, V1);
W2 = scatteredInterpolant(X1, Y1, Z1, W1);
spacing=200;
x1=(linspace(min(X)/5,max(X)/4,spacing))';
y1=(linspace(min(Y),max(Y)/8,spacing))';
z1=(linspace(min(Z)/4,max(Z)/4,spacing))';
[xmesh, ymesh] = meshgrid(x1,y1,0:0);
%% Make velocity grid with U, V and W%%
u1=griddata(X1,Y1,U2.Values,xmesh,ymesh); % Again giving duplicate data point warning and removed however the size is still 20 by 200.
v1=griddata(X1,Y1,V2.Values,xmesh,ymesh);
w1=griddata(X1,Y1,W2.Values,xmesh,ymesh);
res_vel=sqrt(u1.^2+v1.^2+w1.^2);
%% Contourf Plot U,V data%%
h_fig1 = figure(1);
contourf(xmesh,ymesh,res_vel,0.0001:20)
colorbar()
caxis([-1, 27]);
To summarise, Any suggestion how to make velocity background better in the contour.
secondly, if the problem is not with the griddata then any way of improving the quality of boundary captured and results. I noticed the velocity in the surrounding area is high but the contour is showing a small value.
I really appreciate any help as I am stuck here for a long time.
Thanks
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Please take a look at Delaunay and Trisurf functions in matlab. Extract your vertices data in a matrix. Following is the code that I used in my, You can tailor it according to your needs:
vel_files = dir('*.csv'); %Only velocity data
velnum = length(vel_files);
vel_data = cell(1, velnum);
for k = 1:velnum-1
filename = vel_files(k).name;
vel_data{k} = readmatrix(filename);
end
Tvert = readtable('vertices.csv'); %vertices data
x = Tvert.Var1;
y = Tvert.Var2;
vertices= cat(2,x ,y);
DT = delaunay(vertices);% Delaunay Triangulation
VELALL=cell2mat(vel_data); trisurf(DT,vertices(:,1),vertices(:,2),VELALL(:,141),'EdgeColor','none'); axis tight; daspect([1 1 1]); shading interp; colormap jet; view(2);title('Ux t=100s')
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I have a specific case about internal pipe flow with constant heat flux. Although the inlet boundary condition is laminar, the flow is a passing transition (a significant part of the tube) and turbulent regime along the tube (because of the change of thermophysical properties depending on implied heat). SST models with intermittency term (For fully laminar flow, γ = 0 and the model reverts to a laminar solver. When γ = 1, the flow is fully turbulent.) can catch laminar/transitional and turbulent flow regimes. These models were designed for turbulent inlet boundary conditions (models solve intermittency term, so it needs extra boundary conditions such as turbulent intensity). Can Transitional SST Models be used for laminar inlet / turbulent outlet boundary conditions? If so, what is the approach?
Regards,
EB
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Hi
I tried to run an ANSYS FLUENT simulation with SST Model and it was hard to converge. The laminar model should converge, I'd suggest using a better quality mesh.
In some cases the SST will resolve to low/zero turbulence, but that is not always the case. The SST model will have turbulent fluid coming in the inlet, as set by your boundary condition. This would take time/distance to convert to laminar using the SST model. Check your Viscosity ratio in your results, see how turbulent the SST model is showing your flow to be. Laminar flows can have problems converging where they are actually turbulent flows, or where transient laminar flow structures exist. (This is assuming you have a good quality mesh and the simulation is correctly set up.) If you say the flow should be laminar then it is still quite possible that a laminar steady state simulation will not converge because of transient flow structures. This is very common in heat transfer simulations with natural convection - the natural convection tends to have transient laminar structures. If this is the case the only way to proceed is to do a transient laminar simulation. If you solve a laminar simulation with a turbulence model you are adding extra dissipation to the model. This dissipation is not real, it is a product of the turbulence model you are using, but it can have the effect of damping out these transient flow structures and apparently converging. The SST turbulence model is better than most turbulence models as when the turbulent kinetic energy goes to zero (it is exactly zero in a laminar flow, by definition) the turbulent viscosity also goes to zero, so SST does not add much dissipation to the model and you might get away with it. But k-epsilon based models are well known to have far too much dissipation in the low Reynolds number regimes because as k goes to zero the turbulent viscosity goes to a finite value, and this is false additional dissipation. This is why the k-e model is a bad choice for low Reynolds number flows, and you either need to modify it or use a k-omega based model like SST which does give zero turbulent viscosity at zero turbulent kinetic energy. However, if your flow is steady state laminar and you use the SST turbulence model the turbulence model is likely to give effectively zero turbulent viscosity, meaning that your answer probably will be reasonably accurate (only with a small amount of extra dissipation). If your flow is transient laminar and you use the SST turbulence model there is a good chance the turbulence model will generate too much dissipation and damp out the transient flow, which is wrong. You are likely to get a big error in this case. In this case using the SST turbulence model is wrong. A transient laminar model is correct. Note you will need to do time step, mesh and convergence criteria sensitivity studies to work out what you need for time step and mesh size, and convergence criteria.
Hopefully that explains things a bit.
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In order to find the similarity solutions.
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You can find the Navier-stokes equation of a natural convective nanofluid flow past a vertical flat plate with the triboelectric effect of nanoparticles from this research article. This model uses both the Buongiorno model and the Tiwari-Das model to study heat and mass transfer analysis of Cupper Water nanofluid.
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I'm deeply interested in aerodynamics and CFD. I'm currently thinking about two masters:
_ one in aerospace dynamics which talk about flight mechanics, aerodynamics (lift, drag, flows characteristics ...) with modules about CFD, experimental aerodynamics (wind tunnel tests, measurements principles ).
_ CFD master which essentially talks about fluid mechanics, heat transfer, numerical methods, CAD, data analysis.
I want to become an aerodynamicist. I feel like the CFD master can give me a deeper understanding of fluid mechanics and more choices (I can work in fields like automotive, naval, aerospace). I'm more interested in aeronautics than other vehicles but it wouldn't bother to work for automobile or naval company. In the other hand the aerospace dynamics master is more centered on air-vehicles, can give me a good undertanding of flight dynamics and experimental skills not just numerical ones.
As I'm not experimented enough, I'm humbly asking which one do you think is the best for an aerodynamicist ?
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Hi, I am an engineering doctor (expected) at the Institute of Mechanics, CAS and I major in Fluid Mechanics. I am currently engaged in Hypersonic aerodynamics, Compressible flows, and Complex aerodynamic interference associated with shock waves in multi-body dynamic separation at high speed, CFD simulation, and wind tunnel tests. As my experience, the CFDers' work is more concentrating on better CFD methods, higher accuracy, faster calculating speed, and more reliable simulation results for complex and possible fluid flow in engineering problems. However, the aerodynamicist's work is to solve one of the specific or simply aerospace engineering problems, to study the flow mechanism associated with the considered problem, using the fluid mechanic's theory, CFD tools or numerical analysis, sometimes, the wind tunnel tests. Nevertheless, the fundamental knowledge of CFD, fluid mechanics, data analysis, etc., are essential for us to become qualified aerodynamicists. Whichever master or doctor to be, we are not just limited in it. The skills and expertise in aerospace engineering or aerodynamics are overlapping, cross and interdependence. When we choose to become a master, unknown things are approaching on the way. So, we would not be afraid of the thing we are not good at, we have the learning skills, and we can overcome something. By the way, the wind tunnel experiment is interesting, at least for me, and the experimental results are precious. Maybe, we could be more comprehensive by engaging in aerodynamics or aerospace engineering. Each master has its advantages and characteristics. Believe us, we can make something, and we can enjoy it. Just a little experience and feeling, hope that can help you.
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Hello everyone. Do you know if it is possible to simulate a water filter using a porous medium in fluent? I would like to model a flow of water containing particles in a sand filter and see how the particles are captured by the filter. I am new in CFD and i'll appreciate all kind of advice.
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Do you mean some particles trapped and some pass through? You may need UDF.
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Hello, I am modeling steel filling up a chamber. My problem is that when steel falls inside the chamber it does not fill it and it sticks to the walls and goes out (Please see image). I have used VOF and Eulerian VOF two-phase flow models. I have used fine and coarse meshes. I have used K-epsilon and K-omega SST models. But I am getting almost the same results. Do you know what is the problem? Thanks
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Hi Kun Dou ,
Thank you so much for your suggestion.
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Hi,
Would anyone be able to help with how to write/find a user defined function for absorption for CFD on Ansys Fluent?
Many thanks
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Dear Sam,
very interesting question, there are several manner but you can find one of them in our 4 tutorials available on ResearcGate on my profile in the folder Data especially and especially this one :
Don't hesitate if you need more details,
Best regards
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There are many research articles in which we study the fluid flow with specific conditions and with specific effects.. eg Study the effect of mhd hyperbolic tangent fluid with chemical reactions. what is the specific application of these type of research? e.g we talk in general that it has engineering and industrial applications. but where it is actually applied in specific way?
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Hello, dear Kinza Arshad
Have a nice day!
These points are very important in the piping issues of the oil and gas industry. And it can be one of the most important applications in the industry Investgecations of viscous dissipation effects on MHD tangent hyperbolic fluid over a nonlinearly stretching sheet with convective boundary conditions.
Good luck!
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Hello dear Researchers :
Does anyone have modeled, or have literature on how to mathematically model a :
Fluid Flow of a :
- Non-Newtonian Fluid
- Non-Isotermal Flow
- Compressible Flow
- Polymer.
Thank you for any help, I'll appreciate it !
Best Regards !:)
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Hi Franklin and all.
This is a well-known case of violation of the famous “no slip condition” in Fluid Mechanics: the fluid (polymer melt in this case) slips on the walls of the extrusion machinery. Transversal velocity gradients in the melt are small so that plug-flow model (full slip flow) is used sometimes. In general, the relative rugosity of the wall surface in contact with the melt is irrelevant regarding pressure drop. In a way, it is as if Bernoulli equation holds. However, with polymer melts you have simultaneous flow and heat transfer. Look for “slip-flow models” or “polymer melts slip-flow models” at the Internet.
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Good afternoon,
I am currently simulating a combustion in CFD on ANSYS FLUENT and I am trying to get the best mesh possible out of this geometry. It is a rather simple one, with four inlets that lead to the combustion chamber. My question is, since I am quite new to ANSYS, what is the best way to mesh this geometry? Of course the inlets will have to be more refined than the rest of the mesh but I was asking the best methods to approach this. I am having trouble meshing the inside of the furnace because I am always getting really insconsistent tetrahedral cells.
Thank you very much.
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Hello Luis
Please use the structured mesh for the quality mesh and keep the skewness factor at least 0.5. You can use the face meshing tool for structured mesh.
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It can be any type of DNA like pUC18. The DNA should change it's location with time when a force will be applied to the microfluidic device like electric force, magnetic force etc.
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Hello,
Would you like to share any idea about it with me? I am also looking for it.
Thanks
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Hello everyone,
I know this is a very general question, but I have encountered this topic of debate during the review phase of some of my research work.
For my research I am working potential-based solvers for the prediction of unsteady lifting flows around wings and also for the prediction of sheet cavitation phenomena.
Apart from the computational cost, which is obviously significantly lower when potential methods are used compared to more sophisticated higher-fidelity CFD tools, what are other advantages lower-fidelity methods have? Are such tools when developed for specific applications still considered obsolete?
Cheers,
Dimitra
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Potential flow (and other similar field solutions to Laplace's equation) can be quite useful and informative. Just because a solution requires more effort (computational time, setup, post-processing, etc.) doesn't necessarily mean that it's more accurate or informative. If you don't really know what the boundary conditions are, you have at least two options: 1) apply what may be the wrong boundary conditions; or 2) use a method that has "natural" boundary conditions (such as potential flow). Rigorously applying the wrong boundary conditions (or constituent equations or localized properties or presumed cavitation criteria, etc.) may give the appearance of remarkable results and produce fascinating graphics but may or may not reveal anything meaningful about the processes you're hoping to better understand. I have lots of examples of potential and viscous flows plus free software http://dudleybenton.altervista.org/projects/CFD/index.html
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Hello,
I've successfully simulated the closure of a flapper non-return valve as illustrated.
The inlet velocity increases gradually with a specific acceleration.
The following UDF is used to specify the motion of the flapper:
#include "udf.h"
DEFINE_SDOF_PROPERTIES(flappers_motion, sdof_prop, dt, time, dtime)
{
Six_DOF_Object *sdof_obj = NULL;
sdof_prop[SDOF_MASS] = 2.73e-3; /* flapper's submerged weight */
sdof_prop[SDOF_IXX] = 2161.86e-9; /* around the hinge */
sdof_prop[SDOF_IYY] = 367.96e-9;
sdof_prop[SDOF_IZZ] = 2471.27e-9;
real m= sdof_prop[SDOF_MASS];
real L= 0.024479 ;
sdof_prop[SDOF_LOAD_M_X] = 0 ;
sdof_prop[SDOF_LOAD_M_Y] = 0.0;
sdof_prop[SDOF_LOAD_M_Z] = 0.0;
real th_deg = theta * 180 * 7 / 22 ; /* valve opening angle, in degree */
sdof_obj = Get_SDOF_Object(DT_PU_NAME(dt));
if (NULLP(sdof_obj))
{
/* Allocate_SDOF_Object must be called with the same name as the udf */
sdof_obj = Allocate_SDOF_Object(DT_PU_NAME(dt));
SDOFO_1DOF_R_P(sdof_obj) = TRUE; /*1DOF rotation*/
SDOFO_DIR(sdof_obj)[0] = 1.0;
SDOFO_DIR(sdof_obj)[1] = 0.0;
SDOFO_DIR(sdof_obj)[2] = 0.0;
SDOFO_CENTER_ROT(sdof_obj)[0] = 0.0;
SDOFO_CENTER_ROT(sdof_obj)[1] = 0.0;
SDOFO_CENTER_ROT(sdof_obj)[2] = 0.0;
SDOFO_CONS_P(sdof_obj) = TRUE; /* constrained motion */
if (SDOFO_CONS_P(sdof_obj))
{
SDOFO_LOC(sdof_obj) = 0.0;
SDOFO_MIN(sdof_obj) = -0.0349 ; /* min allowable angle */
SDOFO_MAX(sdof_obj) = 1.0471 ; /* max allowable angle */
SDOFO_INIT(sdof_obj) = SDOFO_LOC(sdof_obj);
SDOFO_LOC_N(sdof_obj) = SDOFO_LOC(sdof_obj);
}
}
}
But now I want to simulate the closure of the flapper, taking into account the friction at the flapper's hinge.
I tried to just assign the friction value to "sdof_prop[SDOF_LOAD_M_X]" ,but the flapper started to move backwards (opening) until the flow increases, which is not correct.
So I want to get the value of the hydrodynamic torque of the flapper, and compare it to the friction with some kind of "if statement" that may look like this:
real static_friction= 50;
real kinetic_friction=40;
real hydraulic_torque =??? ;
If (hydraulic_torque<static_friction)
{
sdof_prop[SDOF_LOAD_M_X]=0
}
else
{
sdof_prop[SDOF_LOAD_M_X]=-1*kinetic_friction;
}
BUT THE PROBLEM IS :
I don't know the udf code that can get the actual value of the hydraulic_torque on the flapper to compare it to the friction value.
Your help is highly appreciated.
Thanks a lot in advance.
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Ok, I've found how,
In case of someone else has the same issue,
Use the macro :
Compute_force_and_moment
Within the 6dof code
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I am looking for a skeletal methane combustion mechanism in chemkin format, which has 17 species and 25 reactions. I have searched through many web sites but i can't get it. It is propably called skeletal25. Any body who can help with this problem is appreciated. Thank you
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The study of combustion is important to optimize the design and operating parameters of a combustor. The combustion between the fuel and air involves the conversion of the chemical energy of the species to heat energy. Complete combustion is desirable to get the maximum thermal efficiency out of it. Incomplete combustion is not desirable as it emits hazardous unburnt hydrocarbon as well as CO2, NOx, etc to the environment.
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Does any one have some experience with creating 3D geometries with FreeCAD and subsequently editing it to the OpenFOAM CFD software? Could you share any tutorial or demo links with me?
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You cannot directly import a CAD file into Openfoam. You need to convert it into a good surface mesh (STL) and then use snappyHexMesh or cfMesh to create a hex-dominant mesh. Then, use checkMesh utility to verify the mesh quality. Also, you can visualize the mesh in Paraview.
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Do the six jump conditions (difference between inner and outer limits of pressure, x-velocity, and v-velocity and these three quantities' normal derivatives) for these two problems change with respect to time, i.e. have a time variable "t"; or do these conditions don't have time variable "t", but still need to be updated when interface changes? The following two membrane problems are found in Sections 10.2.6 and 10.3 in textbook on immersed interface method (IIM), The Immersed Interface Method Numerical Solutions of PDEs Involving Interfaces and Irregular Domains by Zhilin Li.
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The figures address a time-dependent problem, where is written that the solved equations are steady?
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I am currently working on Nozzle CFD analysis using ANSYS FLUENT application; I have since been able to plot some flow parameters contours and profile. Now, I am having challenges plotting the turbulence intensity contour.
Any idea from anyone on how to go about this?
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use TecPlot☺
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Energy conservation can be expressed in different ways, such as the temperature equation and the enthalpy equation. However, the two equations do not behave the same way when used in Computational Fluid Dynamics (CFD) simulation (finite difference method and finite volume method). My question is: why? If someone can give me a brief explication.
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The physical conserved energy is the total energy. You can write equations for other forms of energy but they are never conserved.
The equation for temperature (intensive variable) must be deduced from the equation of the internal energy.
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Hello all,
I intend to perform a CFD analysis of the well-known bridge pier scour problem. I am considering two software packages for this purpose: Ansys Fluent and Flow 3D. I am trying to explore the pros and cons of each package for my case.
I would appreciate your comments on any of the following.
1- In order to make a sound comparison, I need to understand the modelling details implemented in Flow 3D, especially a clear description of the way sediment transport is modelled and coupled with the hydrodynamic solver, and how the interphase interaction is realized. Despite lots of research, I have not been able to find detailed information on this.
2- Any study on comparing the performance of these two packages for bridge pier scour problem.
Regards,
Armin
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I have three suggestions for you:
1- Check the below link:
As this topic is popular in our country, I am sure you can find different Ph.D. and M.Sc. theses in Iranian universities.
2- Ask your question in CFD online forums:
3- If you could not find your answer about bridge piers, search for other hydraulic structures (for example, spur dikes) and use their information.
Good luck,
Maryam
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Hi all,
I am trying to simulate a case in 3D and two phases thought a twoPhaseEulerFoam solver but in every time I encounter the same error i.e. "Negative initial temperature T0" . Is anyone has a clue how to tackle it?
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Jonatan R. Mac Intyre, that's right!
Also, Abdulbasit Abdulsayid, It’s often a common issue when using turbulent models. The problem could relate to the model geometry, the boundary conditions, and even the convection state; i.e., transient or steady-state. First, ensure that your boundary conditions are correct, then try using both transient and SIMPLE algorithm solvers in different cases to see if the flow is established.
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Hello, I want to simulate flow over an aerofoil. I read that the SST k-omega model and Spalart---Allmaras both give good results. Since the SA model is one equation model it is computationally less expensive. Is there any other reason to choose the SA model over SST? And when should we use SST over SA?
I am new to CFD, any suggestions/advice would be very helpful
Thanks.
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The selection of the model depends on the specific problem, no turbulence model is suited for every case. Fine-tuning is required. SST model uses good mesh at boundary and with wall treated usually works in most cases, but again it is problem specific.
There are numerous turbulence models and many different sets of parameter settings around, and you can produce a wide range of solutions depending on which model and which numerical mesh you choose.
A qualitative reasonable result at a low cost is obtained with Spalart-Allmaras. In any case, you have to use an appropriate mesh as a starting point which an experienced user will easily pick, and once you have a solution you have to check Y+ values (i.e. the distance of the first grid point from the wall), since depending on the turbulence model some ranges of Y+ values yield completely unphysical answers. Once you have the Y+ values you know whether you have too coarse or too fine a mesh near the airfoil.
Regards
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  • I have done an MRF and Sliding mesh analysis of the centrifugal pump. I need to know how to calculate and show the production of entropy.
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Dudley J Benton, thank you so much
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Are there any good algorithms for doing Particle Shifting near solid walls in SPH? This is needed to avoid the SPH particles passing through the solid boundary.
Cristian
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Hello,
Thanks for the reply. Unfortunetely in my case the only option is to have a a good shifting strategy.
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Hello everyone
Hope you are fine. I have a doubt in the area of CFD, in my case a multiphase bubbly flow with Eulerian formulation. The solvers often mention implicit or explicit schemes specially when setting up the discretization of the equations, is this related to the way in which the solver calculates the field partial derivative equations? If so I want to know if these formulations have an effect on: convergence stability, accuracy of results, duration time of the simulation, etc. Thanks in advance for any suggerence about the usage of those formulations.
Walter Nolasco
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It basically depends on the order of discretization in your source and convection terms. If you are using first-order differencing explicit is okay, though in the case of second-order implicit works.
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I am using Gamma-Re theta transition model for an asymmetrical airfoil. For the academic Ansys Fluent version, the maximum allowable cell limit is 512000 cells. Is it possible to have a good mesh quality in the academic version for transition modelling? If yes, what can i do to improve my mesh quality? Thank you very much.
Maximum aspect ratio = 438.08
Maximum skewness = 0.84746
Minimum orthogonal quality = 0.10908
Y+ < 1
Total cell number = 504400
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I suggest you visit https://aeroptimal.com/mesh (you must create an account to use this module), where you can create a full structured airfoil mesh - https://youtu.be/4Opu0zk7gFk . You can export .su2 .msh .foam .vtk
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I am going to couple anaerobic digestion model no.1 (ADM1) with CFD modelling. I need some data for validation. Where or in which research paper can I find those?
Is it necessary to validate the coupled CFD-ADM1 or the validation of CFD part is sufficient?
Best regards
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