💥💥💥 What are alternatives for Ansys OptiSLang ?

 Yes, there are some free software tools for machine learning that you can use to learn and apply various techniques and algorithms. Here are some of the most popular and widely used ones:

• TensorFlow: This is an open source machine learning platform that provides a comprehensive and flexible ecosystem of tools, libraries and community resources. You can use TensorFlow to build, train and deploy machine learning models for various applications, such as computer vision, natural language processing, recommender systems and more. You can also use TensorFlow to run experiments, benchmarks and AutoML¹.
• OpenML: This is an open platform for sharing datasets, algorithms and experiments in machine learning. You can use OpenML to access AI-ready data, ML library integrations, and a treasure trove of ML results. You can also use OpenML to learn from millions of reproducible machine learning experiments on thousands of datasets, and to automate machine learning itself².
• Scikit-learn: This is an open source machine learning library for Python that provides simple and efficient tools for data analysis and mining. You can use Scikit-learn to perform various tasks, such as classification, regression, clustering, dimensionality reduction, feature extraction and selection, model evaluation and selection, and more.
• Weka: This is an open source machine learning software that provides a collection of algorithms for data mining tasks. You can use Weka to preprocess, visualize, analyze and model data using a graphical user interface or a command-line interface. You can also use Weka to extend its functionality with new algorithms and tools.

These are some of the best free software tools for machine learning that you can learn and use in 2023. You can also check out other alternatives from SourceForge³, Capterra or other websites. I hope this helps you find the best software tool for your needs. 😊

What are the limitations of TensorFlow?

TensorFlow is a popular and powerful machine learning platform that offers many advantages, such as scalability, open source, graphs, debugging, parallelism, compatibility, and architectural support. However, it also has some limitations that you should be aware of before using it. Some of the limitations of TensorFlow are:

• Missing symbolic loops: TensorFlow does not have a native feature for handling variable length sequences, such as recurrent neural networks. You have to use a workaround called bucketing, which involves creating multiple copies of the same graph with different sequence lengths¹.
• No support for Windows: TensorFlow does not have official support for Windows operating system. You can still install it using conda or pip, but you may encounter some issues or bugs¹².
• Slow: TensorFlow is slower and less usable than some of its competitors, such as PyTorch or MXNet. It has a steep learning curve and a complex API that can be hard to debug¹²³.
• No GPU support other than Nvidia and only language support: TensorFlow only supports Nvidia GPUs for GPU programming and Python for full language support. Other GPUs and languages are not fully supported or integrated².
• Frequent updates: TensorFlow is constantly updated by Google, which can be a good thing or a bad thing depending on your perspective. On one hand, it means that TensorFlow is always improving and adding new features. On the other hand, it means that you have to keep up with the changes and update your code accordingly².
• Architectural limitation: TensorFlow’s TPU architecture, which is designed to speed up computation, only allows execution of models and not training. You have to train your models on CPU or GPU and then deploy them on TPU².

These are some of the main limitations of TensorFlow that you should consider before choosing it as your machine learning platform. Of course, TensorFlow also has many strengths and benefits that make it a popular choice among many developers and researchers. You can learn more about TensorFlow from its official website⁴ or from various online courses and tutorials. 

What are the alternatives to TensorFlow?

There are many alternatives to TensorFlow that you can use for machine learning and deep learning. TensorFlow is an open source machine learning platform that provides a comprehensive and flexible ecosystem of tools, libraries and community resources. You can use TensorFlow to build, train and deploy machine learning models for various applications, such as computer vision, natural language processing, recommender systems and more¹. However, TensorFlow also has some limitations, such as missing symbolic loops, no support for Windows, slow performance, no GPU support other than Nvidia, frequent updates, and architectural limitation².

Some of the alternatives to TensorFlow are:

• PyTorch: This is an open source machine learning framework that offers brief training, flexibility, and debugging capabilities. It is based on Torch, a scientific computing framework for Lua. PyTorch supports dynamic computation graphs, distributed training, and various tools and libraries for computer vision, natural language processing, reinforcement learning and more³.
• Keras: This is a high-level neural network API that runs on top of TensorFlow, Theano or CNTK. It provides a simple and intuitive way to build and train deep learning models. Keras supports multiple backends, multiple GPUs, modular architecture, and various tools and libraries for data preprocessing, visualization, evaluation and optimization⁴.
• Caffe & Caffe 2: These are deep learning frameworks that focus on speed, modularity and expression. Caffe is mainly used for computer vision applications, such as image classification, detection and segmentation. Caffe 2 is an extension of Caffe that supports recurrent neural networks, reinforcement learning, natural language processing and more.
• Scikit-learn: This is an open source machine learning library for Python that provides simple and efficient tools for data analysis and mining. You can use Scikit-learn to perform various tasks, such as classification, regression, clustering, dimensionality reduction, feature extraction and selection, model evaluation and selection, and more.

These are some of the best alternatives to TensorFlow that you can use in 2023. You can also check out other alternatives from G2, AlternativeTo, TrustRadius or other websites. 

More info  about PyTorch

PyTorch is an open source machine learning platform that provides a comprehensive and flexible ecosystem of tools, libraries and community resources. You can use PyTorch to build, train and deploy machine learning models for various applications, such as computer vision, natural language processing, recommender systems and more¹.

Some of the key features and capabilities of PyTorch are:

• Production Ready: You can transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe¹.
• Distributed Training: You can scale up your training and performance optimization in research and production with the torch.distributed backend¹.
• Robust Ecosystem: You can access a rich ecosystem of tools and libraries that extend PyTorch and support development in computer vision, NLP and more¹.
• Cloud Support: You can run PyTorch on major cloud platforms, such as Amazon Web Services, Google Cloud Platform and Microsoft Azure¹.

To install PyTorch on your local machine, you can use Anaconda or pip as your package manager. You can also choose the PyTorch build, your OS, the language (Python or C++/Java) and the compute platform (CPU or CUDA) that suit your needs. Then, you can run the install command that is presented to you on the PyTorch website².

PyTorch is based on Torch, a scientific computing framework for Lua. It supports dynamic computation graphs, distributed training, and various tools and libraries for computer vision, natural language processing, reinforcement learning and more³. PyTorch also has a large and active community that contributes to its development and improvement.

If you want to learn more about PyTorch, you can check out its official website¹, its documentation⁴, its tutorials⁵, its blog, its forums and its GitHub repository. You can also join the PyTorch developer community to contribute, learn, and get your questions answered. 

💥💥💥 How to define air exhaust from model in Ansys Fluent ?

 To define air exhaust from model in Ansys Fluent, you need to specify the boundary condition for the outlet of your model. There are different types of boundary conditions that you can use, depending on the physics of your problem and the data that you have. Some of the common boundary conditions for air exhaust are:

• Pressure outlet: This boundary condition specifies the static pressure at the outlet. The flow direction is determined by the solution. You can also specify a backflow condition, which is used when the flow reverses direction at the outlet. This is useful for cases where the outlet pressure is lower than the ambient pressure. You can find more details about this boundary condition here.
• Outflow: This boundary condition assumes that there is no net mass or momentum flux across the outlet. The flow variables are extrapolated from the interior of the domain. This is a simple and robust boundary condition, but it may not be accurate for cases where there are significant pressure gradients or swirls at the outlet. You can find more details about this boundary condition here.
• Exhaust fan: This boundary condition allows you to include external fans or pumps to your simulation. You need to provide the fan or pump curve in terms of pressure rise as a function of velocity normal to the boundary. This is useful for cases where you want to model the effect of a fan or a pump on the flow field. You can find more details about this boundary condition here.

You can also use other types of boundary conditions, such as velocity inlet, mass flow inlet, or vent, depending on your problem and data. You can find more information about all the available boundary conditions in Ansys Fluent here.

What is the difference between outflow and exhaust fan boundary conditions?

The difference between outflow and exhaust fan boundary conditions is that outflow assumes that there is no net mass or momentum flux across the outlet, while exhaust fan imposes a pressure rise as a function of velocity normal to the outlet. Outflow is a simple and robust boundary condition, but it may not be accurate for cases where there are significant pressure gradients or swirls at the outlet. Exhaust fan is useful for cases where you want to model the effect of a fan or a pump on the flow field. You can find more details about these boundary conditions in the links that I provided in my previous message.

How do I create an exhaust fan boundary condition?

To create an exhaust fan boundary condition in Ansys Fluent, you need to follow these steps:

• Create the geometry of your model and tag the boundaries in SpaceClaim. You need to tag the face where you want to apply the exhaust fan boundary condition as a separate boundary. You can watch this video 6 for an example of how to do this.
• Generate the mesh for your model using Fluent Mesher. You can use any meshing method that suits your problem, such as surface meshing, volume meshing, or polyhedral meshing. Make sure that the mesh quality is good and that the boundaries are correctly identified.
• Open the Fluent solver and set up the physics of your problem. You need to choose the appropriate models for your flow, such as laminar or turbulent, incompressible or compressible, steady or transient, etc. You also need to define the material properties and the initial conditions for your flow.
• In the Boundary Conditions task page, select the boundary that you tagged as the exhaust fan and change its type to Exhaust Fan. Click Edit to open the Exhaust Fan dialog box. Here you need to specify the static pressure, the backflow conditions, the total temperature, and the turbulence parameters at the exhaust fan boundary. You also need to specify the pressure jump across the fan as a function of the velocity normal to the fan. You can define a constant, polynomial, piecewise-linear, or piecewise-polynomial function for this purpose. You can find more details about these inputs in this document 4.
• Apply any other boundary conditions that are relevant for your problem, such as pressure inlet, velocity inlet, wall, symmetry, etc. You can find more information about all the available boundary conditions in Ansys Fluent 7.
• Initialize and run the solution until convergence or until you reach your desired criteria. You can monitor the solution variables and residuals to check the progress and quality of your solution.
• Post-process and analyze your results using Fluent or other tools. You can visualize the flow field, plot contours, streamlines, vectors, etc., calculate derived quantities, compare with experimental data, etc.

Examples of defining air exhaust in Ansys Fluent

One of the video results that I found is a tutorial on how to model turbulent air flow over a car, which includes an exhaust pipe as part of the geometry. You can watch this video here to see how the author sets up the boundary conditions, the turbulence model, and the solution parameters for this problem. The author uses a pressure outlet boundary condition for the exhaust pipe, which specifies the static pressure at the outlet and allows the flow direction to be determined by the solution. You can also see the results of the simulation, such as the velocity contours, streamlines, and pressure distribution on the car surface.

Another example of defining air exhaust in Ansys Fluent is a simulation of flow and conjugate heat transfer in an exhaust manifold, which collects the exhaust gases from multiple cylinders into one pipe. You can find this example here, which provides a detailed explanation of the setup, the results, and the physics of the problem. The author also uses a pressure outlet boundary condition for the collector pipe, and assigns different temperatures and velocities for each inlet pipe. You can download the mesh file and the case and data files from this link to run this simulation yourself.

What is the difference between pressure outlet and outflow boundary conditions?

The difference between pressure outlet and outflow boundary conditions is that pressure outlet specifies the static pressure at the outlet, while outflow assumes that there is no net mass or momentum flux across the outlet. Pressure outlet allows the flow direction to be determined by the solution, and also requires a backflow condition, which is used when the flow reverses direction at the outlet. Outflow is a simple and robust boundary condition, but it may not be accurate for cases where there are significant pressure gradients or swirls at the outlet. Outflow also does not require any input for the pressure or the backflow condition. You can find more details about these boundary conditions in the links that I provided in my previous message, or in this document 4.

💥💥💥 How to avoid peak stresses in Structural Analysis in Ansys Workbench

 Peak stresses in structural analysis are often caused by stress singularities, which are artificial stresses computed because of simplification in the FEA model. Some common causes of stress singularities are sharp corners, stiff boundary conditions, point loads, constraint equations, etc.¹

There are several ways to avoid or deal with peak stresses in Ansys Workbench, depending on the nature and purpose of the analysis. Some possible methods are:

- Submodeling: This involves creating a submodel at the high stress locations with enough detail (e.g. fillet radius) along with mesh convergence study. This is the most accurate and reliable method, but also the most time-consuming and complex.¹

- Stress Concentration Calculation: This involves using Roark's formulas for stress and strain or other analytical solutions to determine the appropriate factors relative to the nominal stress. This works well if the load pattern and geometry are close to the textbook cases. It serves as a good way to ballpark a similar type geometry.¹

- Hot Spot Method: This involves creating a path of stress to the singularity and extracting the stress value at a certain distance away from the singularity (e.g. 1 mm), where it is assumed the stresses are adequately far away. Often times a fudge-factor on top of the extracted stress value is applied to build in some conservative margin. This method takes some upfront homework, is quick and dirty and may require good hand waving skills.¹

- ERESX Command: This is a command that controls the extrapolation settings in Ansys. By using ERESX,NO, one can force Ansys to copy the integration point stresses to the nodes. This ensures that stresses will never exceed yield as the stresses at the integration points can never exceed yield.³

- Thermal-Stress Analysis: This is a type of analysis that accounts for the thermal strain due to temperature changes. This can affect the stress distribution and magnitude in the model. One can perform a thermal-stress analysis by sharing model data between thermal and structural using the same or dissimilar mesh.⁴

You can learn more about these methods by following the links in the references. I hope this helps you with your structural analysis. 😊

Source: 

(1) FEA Stress Singularities - Ansys Tips. https://www.ansystips.com/2017/05/fea-stress-singularities.html.

(2) Elastic-Plastic Analysis in ANSYS Gives Stress Above Yield | Nick J .... https://medium.com/@nickjstevens/elastic-plastic-analysis-in-ansys-gives-stress-above-yield-nick-j-stevens-81d990f1a78.

(3) Performing a Thermal-Stress Analysis - ANSYS Innovation Courses. https://courses.ansys.com/index.php/courses/structural-boundary-conditions/lessons/performing-a-thermal-stress-analysis-lesson-6/.

(4) Ansys structural analysis tutorials - Pure bending stress analysis .... https://www.youtube.com/watch?v=8awQ2UYXIBA.

How to perform submodeling in Ansys Workbench?

Submodeling in Ansys Workbench is a technique that allows you to refine the stress analysis of a region of interest without having to mesh the whole model with fine elements. It involves creating a submodel of the area you want to focus on and applying the displacement (and temperature) results from the global model as boundary conditions on the submodel. This way, you can capture the effects of local features, design changes, or non-linearities in the submodel without affecting the overall response of the system.

To perform submodeling in Ansys Workbench, you can follow these general steps:

- Generate the solution on the global model using the Mechanical tool.

- Create the submodel geometry in a separate Mechanical window or in SpaceClaim. You can use a local coordinate system to define the submodel location and orientation.

- Attach the submodel to the engineering data and solution of the full model using the Model cell in the Project Schematic.

- Define a Remote Displacement boundary condition on the submodel and import the Cut Boundary Constraint from the full model solution. This will apply the displacement (and temperature) results from the full model to the submodel.

- Define the mesh size and any other settings for the submodel analysis. You can use Named Selections to control the mesh refinement in the submodel.

- Solve the submodel and review the results. You can compare the results with the full model or with analytical solutions to verify the accuracy of the submodeling technique.

You can find more details and examples of submodeling in Ansys Workbench by following the links in the references¹²³⁴⁵⁶⁷. I hope this helps you with your structural analysis. 😊

Source: 

(1) Performing Submodeling in Ansys Mechanical — Lesson 6. https://www.youtube.com/watch?v=WC9bN2B9w2M.

(2) How to Use Submodeling in Ansys Mechanical | Ansys Tutorials. https://www.youtube.com/watch?v=LEU6LlGUPAI.

(3) Ansys Sub modeling. https://www.youtube.com/watch?v=_7girXRDK2w.

(4) Submodeling in ANSYS Mechanical: Easy, Efficient, and Accurate. https://www.padtinc.com/2013/08/14/submodeling_ansys_mechanical/.

(5) Submodeling using ansys_workbench_v12 | PPT - SlideShare. https://bing.com/search?q=submodeling+in+Ansys+Workbench.

(6) Submodelling in Ansys - Mechead.com. https://www.mechead.com/submodelling-in-ansys/.

(7) Submodeling using ansys_workbench_v12 | PPT - SlideShare. https://www.slideshare.net/sivasankar1977/submodeling-using-ansysworkbenchv12.

(8) https://bit.ly/3Eo8esU.

(9) https://bit.ly/32eEcuR.

(10) https://bit.ly/3qsytK2.

(11) https://bit.ly/3Bbaaow.

💥💥💥 How to prepare proper mesh for structural analysis in Ansys Workbench ?

 To prepare a proper mesh for structural analysis in Ansys Workbench, you need to follow some steps and consider some factors. Here are some tips and resources that might help you:

• Before you start meshing, you need to upload your CAD model or geometry into Ansys Mechanical and decide what features need to be meshed and what features can be defeatured. Defeaturing means removing unnecessary details from your geometry to save time and simplify the meshing process. For example, you can use Ansys SpaceClaim to defeature a name plate on your geometry if it is not relevant for your analysis ¹.
• You also need to choose the type of mesh you want to create: structured or unstructured. Structured meshes have regular shapes and patterns, while unstructured meshes have irregular shapes and sizes. Structured meshes are usually more efficient and accurate, but they are harder to generate for complex geometries. Unstructured meshes are more flexible and easy to generate, but they may require more elements and computational resources ¹.
• To create a structured mesh in Ansys Meshing, you can use various methods such as sweep, multizone, hex-dominant, or mapped face meshing. These methods allow you to control the shape and size of the elements along the geometry. You can also use inflation layers to refine the mesh near the boundaries where gradients are high ².
• To create an unstructured mesh in Ansys Meshing, you can use methods such as tetrahedral, hexahedral, or polyhedral meshing. These methods allow you to fill the volume of the geometry with different types of elements. You can also use sizing controls to adjust the element size based on various criteria such as curvature, proximity, or relevance ¹.
• To ensure the quality of your mesh, you need to check some parameters such as aspect ratio, skewness, orthogonality, smoothness, and Jacobian. These parameters indicate how well the elements represent the geometry and how suitable they are for the solver. You can use Ansys Meshing tools such as statistics, histogram, or mesh metrics to evaluate these parameters and identify any problematic areas in your mesh ¹.
• To perform a transient structural analysis in Ansys Mechanical, you need to define the material properties, boundary conditions, loads, and time steps for your model. You also need to select the appropriate solver settings and options for your analysis type and goals. You can use Ansys Mechanical tools such as solution information, convergence plots, or result tracking to monitor the progress and accuracy of your solution ³.

What is the difference between structured and unstructured mesh ?

The difference between structured and unstructured mesh is mainly in the way the elements are connected and arranged in the mesh. A structured mesh is a regular lattice, such as an array, with implied connectivity between elements. A structured mesh has orthogonal quadrilateral (2D) or hexahedral (3D) elements that are easy to identify and access. A structured mesh is more efficient and accurate, but it is harder to generate for complex geometries ¹.

An unstructured mesh is a mesh with general connectivity (GCON) whose structure is arbitrary and therefore the connectivity of elements must be defined and stored. An unstructured mesh has non-orthogonal elements, such as triangles (2D) and tetrahedra (3D), that are more flexible and can conform to any desired geometry. An unstructured mesh is more easy to generate, but it may require more elements and computational resources ².

I hope this answer helps you understand the difference between structured and unstructured mesh. If you want to learn more about the types of mesh and how to use them in Ansys Workbench, you can check out these resources:

• Meshing in FEA: Structured vs Unstructured meshes | OnScale
• Types of mesh - Wikipedia
• Mesh generation - Wikipedia
• What is the difference between structured mesh and unstructured mesh …
• What is Mesh and what are the types of Meshing - Prescient

What are the advantages and disadvantages of structured and unstructured meshes ?

The advantages and disadvantages of structured and unstructured meshes are as follows:

• Structured meshes are meshes with a regular and structured arrangement of cells, which are typically quadrilaterals or hexahedra in two and three dimensions, respectively. The sides of the cells are usually parallel, and the grid spacing is uniform. Structured meshes have the following advantages and disadvantages ¹:

  • Advantages:
    • They are easier to generate, as the grid cells have a regular and structured arrangement that can be generated automatically.
    • They are faster to solve, as the computation of the finite element solution can be simplified.
    • They are more accurate in simple geometries, where the regularity of the mesh can help to reduce errors caused by distorted cells.
    • They have lower computational cost, due to the regularity of the mesh.
  • Disadvantages:
    • They have limited flexibility, as the regularity of the mesh can limit its ability to conform to complex geometries or regions with curved boundaries.
    • They have increased computational cost in regions where the solution is smooth, as the uniform spacing of nodes in structured meshes can lead to an excessive number of nodes in those regions.
    • They are less accurate with complex geometries, as the regularity of the mesh may not be able to conform to the shape of the domain.

• Unstructured meshes are meshes with an irregular arrangement of grid cells, which can be any shape and size. The cells can be quadrilaterals and triangles in two dimensions, hexahedra and tetrahedra in three dimensions, and the grid spacing is not uniform. Unstructured meshes have the following advantages and disadvantages ¹:

  • Advantages:
    • They are more flexible, as they can conform to any desired geometry with localized resolutions.
    • They can handle complex geometries more easily, as they can fill the volume of the geometry with different types of elements.
    • They can have arbitrary positions, as they do not depend on a predefined grid structure.
  • Disadvantages:
    • They require more memory, as they need to store more information about the connectivity and coordinates of each node and element.
    • They are slower to solve, as they require more complex algorithms and computations to solve the finite element equations.
    • They may have lower accuracy, as they may have distorted or poorly shaped elements that can affect the quality of the solution.

I hope this answer helps you understand the advantages and disadvantages of structured and unstructured meshes. If you want to learn more about how to use them in Ansys Workbench, you can check out these resources:

• Meshing in FEA: Structured vs Unstructured meshes | OnScale
• Faster FEA: Structured vs Unstructured Meshing - Paulin Research Group
• [What is Mesh and what are the types of Meshing - Prescient]

How to create an unstructured mesh in Ansys Meshing?

To create an unstructured mesh in Ansys Meshing, you can follow these steps:

• Open Ansys Workbench and create a new project. Drag and drop the Geometry component from the Toolbox to the Project Schematic. Double-click on the Geometry cell to launch Ansys SpaceClaim.
• In Ansys SpaceClaim, import or create your geometry that you want to mesh. You can use various tools to modify, repair, or simplify your geometry as needed. You can also create named selections for different parts or surfaces of your geometry that you want to apply different mesh settings later. Save and update your geometry in Ansys Workbench.
• Drag and drop the Mesh component from the Toolbox to the Project Schematic. Connect the Geometry cell to the Mesh cell. Double-click on the Mesh cell to launch Ansys Meshing.
• In Ansys Meshing, you can see your geometry in the Graphics window and the Tree Outline window. You can use various tools to manipulate the view of your geometry, such as zoom, pan, rotate, or fit. You can also use the Display Style toolbar to change the display mode of your geometry, such as wireframe, shaded, or transparent.
• To create an unstructured mesh, you can use methods such as tetrahedral, hexahedral, or polyhedral meshing. These methods allow you to fill the volume of the geometry with different types of elements. You can access these methods from the Mesh toolbar or the Tree Outline window.
• To apply a tetrahedral mesh method, select Tetrahedrons from the Mesh toolbar or right-click on Mesh in the Tree Outline window and select Insert > Method > Tetrahedrons. In the Details of Tetrahedrons window, you can select the Geometry that you want to apply this method to. You can also change the Element Size and Growth Rate settings to control the size and distribution of the elements.
• To apply a hexahedral mesh method, select Hex Dominant from the Mesh toolbar or right-click on Mesh in the Tree Outline window and select Insert > Method > Hex Dominant. In the Details of Hex Dominant window, you can select the Geometry that you want to apply this method to. You can also change the Element Size and Growth Rate settings to control the size and distribution of the elements.
• To apply a polyhedral mesh method, select Polyhedral from the Mesh toolbar or right-click on Mesh in the Tree Outline window and select Insert > Method > Polyhedral. In the Details of Polyhedral window, you can select the Geometry that you want to apply this method to. You can also change the Element Size and Growth Rate settings to control the size and distribution of the elements.
• To generate the mesh, click on Generate Mesh from the Mesh toolbar or right-click on Mesh in the Tree Outline window and select Generate Mesh. You can see your mesh in the Graphics window and check its statistics in the Statistics window. You can also use various tools to evaluate and improve your mesh quality, such as statistics, histogram, or mesh metrics.
• To export your mesh, click on Update Project from the Mesh toolbar or right-click on Mesh in the Tree Outline window and select Update Project. You can also save your mesh as a file by clicking on File > Export > Mesh.

I hope this answer helps you create an unstructured mesh in Ansys Meshing. If you want to learn more about how to use Ansys Meshing, you can check out these resources:

• ANSYS Student: Meshing Best Practices for Students
• How to generate meshing in ANSYS Fluent Workbench | Full Tutorial
• Mesh — Lesson 4 - ANSYS Innovation Courses

💥💥💥 How to prepare design of experiment (DOE) in Ansys Workbench ?

 To prepare a design of experiment (DOE) in ANSYS Workbench, you need to follow these steps:

• First, you need to define the parameters that you want to vary in your model. You can do this by right-clicking on the Parameters branch in the Project Schematic and selecting Define Parameters. You can also use the Parameter Manager to create and edit parameters¹.
• Next, you need to assign the parameters to the appropriate inputs or outputs in your model. For example, if you want to vary the load magnitude or the material properties, you can assign parameters to these values in the Engineering Data or the Mechanical branches. You can also use expressions to define parameters as functions of other parameters¹.
• Then, you need to create a new Design of Experiments system by dragging and dropping it from the Toolbox under Design Exploration. You can connect it to the Parameter Set and the Analysis system that you want to perform the DOE on².
• After that, you need to double-click on the Design of Experiments system and select the type of DOE that you want to use. There are different types of DOE methods, such as Full Factorial, Central Composite, Box-Behnken, Latin Hypercube, etc. Each method has its own advantages and disadvantages depending on the number of parameters, levels, and design points. You can also specify the lower and upper bounds for each parameter and the number of levels or design points²³.
• Finally, you need to update the Design of Experiments system by clicking on the Update icon in the toolbar. This will run the analysis for each combination of parameter values and generate a table and a chart with the results. You can also export the data to a file or a report².

For more information and examples, you can watch some of the video results that I found for you⁴⁵⁶. You can also read some of the web results that I found for you⁷⁸⁹. I hope this helps you learn how to prepare a design of experiment in ANSYS Workbench. If you have any further questions, please feel free to ask me. 😊

How to specify upper and lower bounds and number of levels in Design Of Experiments in Ansys Workbench ?

To specify upper and lower bounds and number of levels in Design of Experiments in ANSYS Workbench, you can follow these steps:

• First, you need to create a new Design of Experiments system by dragging and dropping it from the Toolbox under Design Exploration. You can connect it to the Parameter Set and the Analysis system that you want to perform the DOE on¹.
• Next, you need to double-click on the Design of Experiments system and select the type of DOE that you want to use. There are different types of DOE methods, such as Full Factorial, Central Composite, Box-Behnken, Latin Hypercube, etc. Each method has its own advantages and disadvantages depending on the number of parameters, levels, and design points²³.
• Then, you need to click on the Details view and expand the Input Parameters branch. You will see a list of parameters that you have defined in your model. For each parameter, you can specify the lower and upper bounds by entering the values in the corresponding columns. You can also use expressions to define the bounds as functions of other parameters or constants².
• After that, you need to expand the Output Parameters branch. You will see a list of outputs that you have defined in your model. For each output, you can specify the number of levels by entering the value in the corresponding column. The number of levels determines how many discrete values the output can take within its range².
• Finally, you need to update the Design of Experiments system by clicking on the Update icon in the toolbar. This will run the analysis for each combination of parameter values and generate a table and a chart with the results. You can also export the data to a file or a report².

What are advantages and disadvantages of Full Factorial, Central Composite, Box-Behnken, Latin Hypercube in Ansys Workbench Design Of Experiements ?

The advantages and disadvantages of Full Factorial, Central Composite, Box-Behnken, and Latin Hypercube designs in ANSYS Workbench Design of Experiments are as follows:

• Full Factorial design: This design involves all possible combinations of the levels of the factors. It can estimate all main effects and interactions, as well as higher-order terms. It is the most powerful and accurate design, but also the most expensive and time-consuming. It requires a large number of runs, especially when the number of factors or levels is high¹².
• Central Composite design: This design is a fractional factorial design with center points and axial points (also called star points). It can estimate first- and second-order terms, as well as some interactions. It can model curvature in the response surface and find the optimal settings for the factors. It is useful for sequential experiments, as it can build on previous factorial experiments. It requires fewer runs than a full factorial design, but more than a Box-Behnken design. It may also involve extreme values for the factors that are outside the safe operating zone¹²³.
• Box-Behnken design: This design is a fractional factorial design with center points, but no axial points. It can also estimate first- and second-order terms, but not all interactions. It can model curvature in the response surface and find the optimal settings for the factors. It requires fewer runs than a central composite design, but more than a Latin Hypercube design. It does not involve extreme values for the factors, so it ensures that all runs are within the safe operating zone¹²⁴.
• Latin Hypercube design: This design is a random sampling method that ensures that each factor is varied over its entire range. It can estimate main effects and some interactions, but not higher-order terms. It cannot model curvature in the response surface or find the optimal settings for the factors. It requires the least number of runs among the four designs, but it is also the least accurate and precise. It may also involve extreme values for the factors that are outside the safe operating zone¹² .

How to read results from other design points in Ansys Workbench ?

To read the results from other design points in ANSYS Workbench, you can follow these steps:

• First, you need to make sure that you have saved the results for each design point before solving. You can do this by checking the Retain box in the Parameter Set window for each design point that you want to keep¹.
• Next, you need to close the Mechanical window and open the Parameter Set window. You can do this by right-clicking on the Parameter Set branch in the Project Schematic and selecting Open¹.
• Then, you need to right-click on the desired design point name in the Table of Design Option window and select Set as Current. This will load the results of that design point into the Mechanical window¹².
• After that, you need to open the Mechanical window and post-process the results as usual. You can use ANSYS FLUENT or ANSYS CFD-Post to visualize and analyze the results³.
• Finally, you can switch between different design points by repeating steps 2 and 3. You can also export the results of each design point to a file or a report if you want².

💥💥💥 How to create a parameters in ANSYS Workbench?

 To create a parameter in ANSYS Workbench, you can follow these steps:

• First, you need to open the Parameters branch in the Project Schematic by right-clicking on it and selecting Define Parameters. This will open the Parameter Manager window, where you can create and edit parameters.
• Next, you need to click on the New Parameter icon in the toolbar or press Ctrl+N to create a new parameter. You can also use the Insert menu to create a new parameter. You will see a new row in the Parameter Manager table, where you can enter the name, value, type, and description of your parameter. You can also use expressions to define parameters as functions of other parameters or constants.
• Then, you need to assign the parameter to the appropriate input or output in your model. For example, if you want to vary the load magnitude or the material properties, you can assign parameters to these values in the Engineering Data or the Mechanical branches. You can do this by right-clicking on the value and selecting Parameterize. You will see a dialog box where you can select an existing parameter or create a new one. You can also use expressions to assign parameters to values.
• Finally, you need to update your model by clicking on the Update icon in the toolbar or pressing F5. This will run the analysis for the current parameter values and display the results in your model.

For more information and examples, you can watch some of the video results. You can also read some of the web results. I hope this helps you learn how to create a parameter in ANSYS Workbench. If you have any further questions, please feel free to ask me. 😊

How to add charts to parameters in Ansys Workbench ?

To add charts to parameters in ANSYS Workbench, you can follow these steps:

• First, you need to define the parameters that you want to vary in your model. You can do this by right-clicking on the Parameters branch in the Project Schematic and selecting Define Parameters. You can also use the Parameter Manager to create and edit parameters.
• Next, you need to assign the parameters to the appropriate inputs or outputs in your model. For example, if you want to vary the load magnitude or the material properties, you can assign parameters to these values in the Engineering Data or the Mechanical branches. You can also use expressions to define parameters as functions of other parameters.
• Then, you need to create a new chart and table by clicking on the New Chart and Table icon in the toolbar. You can select the parameters that you want to plot from the Outline Selection window. You can also customize the appearance and settings of your chart and table using the Details view.
• Finally, you need to update all design points by clicking on the Update All Design Points icon in the toolbar. This will run the analysis for each combination of parameter values and display the results in your chart and table. You can also export your chart and table data to a file or a report.

For more information and examples, you can watch some of the video results that I found for you¹²³. You can also read some of the web results that I found for you⁴⁵⁶⁷. I hope this helps you learn how to add charts to parameters in ANSYS Workbench. If you have any further questions, please feel free to ask me. 😊

💥💥💥 How to define Thermal Contact Conductance in Transient Thermal ( Ansys Workbench)

 **Thermal contact conductance** is the study of heat conduction between solid or liquid bodies in thermal contact¹. It is a measure of the **thermal conductivity**, or ability to conduct heat, between two bodies in contact¹. The **thermal contact conductance coefficient** is a property indicating the thermal conductivity between two bodies in contact¹. The inverse of this property is termed **thermal contact resistance**¹. 

When two solid bodies come in contact, such as A and B in Figure 1, heat flows from the hotter body to the colder body. A temperature drop is observed at the interface between the two surfaces in contact. This phenomenon is said to be a result of a thermal contact resistance existing between the contacting surfaces¹. Thermal contact resistance is defined as the ratio between this temperature drop and the average heat flow across the interface¹.

Most experimentally determined values of the thermal contact resistance fall between **0.000005 and 0.0005 m²K/W** (the corresponding range of thermal contact conductance is **200,000 to 2000 W/m²K**). The significance of thermal contact resistance depends on the thermal resistances of the layers compared to typical values of thermal contact resistance. It is significant and may dominate for good heat conductors such as metals but can be neglected for poor heat conductors such as insulators¹.

Thermal contact conductance is an important factor in various applications, including electronics, electronic packaging, heat sinks, brackets, industry, nuclear reactor cooling, gas turbine cooling, internal combustion engines, heat exchangers, thermal insulation, press hardening of automotive steels, hypersonic flight vehicles, thermal supervision for space vehicles, and residential/building science¹.

Please note that thermal contact resistance arises due to improper contact between two bodies due to irregularities like scratches, ruptures, or dirt on the surface, which causes less contact area available for heat conduction².

Source:

(1) Thermal contact conductance - Wikipedia. https://en.wikipedia.org/wiki/Thermal_contact_conductance.

(2) Thermal contact resistance: Definition, Formula (Heat transfer). https://mechcontent.com/contact-resistance-heat-transfer/.

(3) Thermal Contact Resistance | Neutrium. https://neutrium.net/heat-transfer/thermal-contact-resistance/.

(4) What is Thermal Contact Resistance - Thermal Engineering. https://www.thermal-engineering.org/what-is-thermal-contact-resistance-thermal-contact-conductance-definition/.

How to define Thermal contact resistance in Transient Thermal Ansys Workbench ?

**Thermal contact resistance** is created by the air gap between the contacting surfaces². It depends on surface roughness, how much pressure is applied on the surfaces in contact, and the kind of thermal paste used to fill up the air gap².

In **Transient Thermal Ansys Workbench**, you can define thermal contact resistance by specifying the **thermal contact conductance coefficient**¹. The inverse of thermal contact conductance is thermal contact resistance¹. The thermal contact conductance coefficient quantifies a contact's ability to conduct heat¹. It is used to calculate the amount of heat transferred through conduction between two bodies in contact¹. 

To define thermal contact resistance in Transient Thermal Ansys Workbench, you can follow these steps:

1. Open your Transient Thermal Ansys Workbench project.

2. Select the surfaces that are in contact and for which you want to define thermal contact resistance.

3. Right-click on the selected surfaces and choose "Properties" or "Contact Properties".

4. In the properties window, look for the option to define thermal contact conductance or thermal contact resistance.

5. Enter the desired value for thermal contact conductance coefficient or thermal contact resistance.

6. Save the changes and run the simulation.

Please note that the specific steps may vary depending on the version of Ansys Workbench you are using. It is recommended to refer to the official documentation or user guide for detailed instructions specific to your version of Ansys Workbench.

I hope this helps! Let me know if you have any further questions.

Source:

(1) Thermal contact resistance - Ansys Learning Forum. https://forum.ansys.com/forums/topic/thermal-contact-resistance/.

(2) Thermal Contact Conductance - ANSYS Innovation Courses. https://courses.ansys.com/wp-content/uploads/2020/03/Lesson-3-Thermal-contact.pdf.

(3) Intro to Transient Thermal Analysis - ANSYS Innovation Courses. https://courses.ansys.com/wp-content/uploads/2020/05/Lesson-1-Introduction-to-transient-analysis.pdf.

(4)https://www.engineersedge.com/heat_transfer/thermal_contact_conductance_13849.htm.

How to calculate contact thermal conductance between two steel plates ?

To calculate the contact thermal conductance between two steel plates, you need to know the following parameters:

• The thermal conductivity of the steel plates, denoted by k (W/m•K).
• The thickness of each steel plate, denoted by L (m).
• The contact area between the plates, denoted by A (m2).
• The contact pressure between the plates, denoted by P (MPa).
• The surface roughness of the plates, denoted by R (μm).
• The interface fluid between the plates, such as air or oil.

The contact thermal conductance, denoted by h (W/m2K), is a measure of how well heat is transferred across the interface between the plates. It depends on the factors mentioned above, as well as the temperature of the interface. There is no simple formula for contact thermal conductance, but there are some empirical correlations that can be used to estimate it. One such correlation is given by Yovanovich (1981) as:

This correlation is valid for steel plates with surface roughness between 0.1 and 10 μm, contact pressure between 0.1 and 10 MPa, and interface temperature between 20 and 200 °C. It assumes that the interface fluid is air with a thermal conductivity of 0.026 W/m•K.

To use this correlation, you need to plug in the values of k, L, P, R and h into the equation and solve for h. Alternatively, you can use an online calculator such as this one to compute h for you.

I hope this helps you understand how to calculate contact thermal conductance between two steel plates. If you have any further questions, please feel free to ask me. 😊

💥💥💥 What is effective medium theory (EMT) ? Is this model available in Ansys Workbench?

 Effective medium theory (EMT) for thermal conductivity is a method to estimate the effective thermal conductivity of a composite material that consists of two or more phases with different properties¹. EMT can be used to model the thermal conductivity of materials that have anisotropic or heterogeneous structures, such as coiled aluminum sheets².

The basic idea of EMT is to replace the composite material with a homogeneous medium that has the same macroscopic behavior as the original material. The effective thermal conductivity of the homogeneous medium is calculated by averaging the thermal conductivities and volume fractions of the constituent phases, taking into account the shape, size, orientation, and distribution of the phases. There are many different EMT models, each with different assumptions and approximations. Some of the most common EMT models are:

• Maxwell model: This model assumes that one phase is dispersed as spherical inclusions in another phase, and that there is no interfacial thermal resistance between the phases³.
• Bruggeman model: This model assumes that both phases are randomly distributed in a symmetric way, and that there is no interfacial thermal resistance between the phases⁴.
• Maxwell-Garnett model: This model assumes that one phase is dispersed as ellipsoidal inclusions in another phase, and that there is no interfacial thermal resistance between the phases⁵.
• Hasselman-Johnson model: This model modifies the Maxwell model by introducing an interfacial thermal resistance between the phases.

Which from the above models are available in Ansys Workbench ?

According to the web search results, Workbench supports the following EMT models for thermal conductivity:

• Maxwell model: This model is available in the Engineering Data Sources panel under the Effective Medium Theory option¹.
• Bruggeman model: This model is available in the Fluent module under the Materials panel as a User-Defined Function (UDF) option².
• Maxwell-Garnett model: This model is not directly available in Ansys Workbench, but it can be implemented using a UDF or an External Model component³⁴.
• Hasselman-Johnson model: This model is not directly available in Ansys Workbench, but it can be implemented using a UDF or an External Model component³⁴.

¹: Missing FE modeler in Ansys Tool box - Ansys Learning Forum ²: Effective medium theory for thermal conductivity of coiled aluminum sheet ³: Importing FE Model in ANSYS Workbench - Eng-Tips ⁴: Worksheet Option in Ansys Workbench - Skill-Lync

How to define Maxwell model in Ansys Workbench ?

The Maxwell model is a type of effective medium theory (EMT) that can be used to estimate the effective thermal conductivity of a composite material that consists of two phases with different properties¹. To define the Maxwell model in Ansys Workbench, you need to do the following steps:

• Go to START > Ansys Em Suite 202x Rx > Modify integration with Ansys (run as admin) and integrate it with workbench².
• Launch Workbench. You will see Maxwell and other Electronics solvers in the analysis system².
• Drag and drop Maxwell into the workspace and then import your Maxwell project into it².
• Select Thermal Conductivity as the property to define and choose Anisotropic for the type³.
• Enter the values of the thermal conductivity tensor components for the composite material. You can use the formula given in this document to calculate these values based on the properties of the phases and their volume fractions¹.

How to define Bruggeman model in Ansys Workbench ?

The Bruggeman model is a type of effective medium theory (EMT) that can be used to estimate the effective thermal conductivity of a composite material that consists of two or more phases with different properties¹. To define the Bruggeman model in Ansys Workbench, you need to do the following steps:

• Go to the Fluent module in the Analysis System and double-click Setup².
• In the Fluent Launcher panel, select Double Precision and User-Defined Functions (UDF) options and press OK².
• In the Fluent Text User Interface (TUI), type the following command to load the UDF library that contains the Bruggeman model: /define/user-defined/user-defined-functions/load [library-name] [library-path] where [library-name] is the name of the UDF library and [library-path] is the location of the UDF library on your computer².
• In the Fluent GUI, go to Materials and select the composite material that you want to define. Under Thermal Conductivity, select User-Defined and choose the Bruggeman model from the drop-down list².
• Enter the values of the thermal conductivity and volume fraction for each phase of the composite material. You can use the formula given in this document to calculate these values based on the properties of the phases¹.

¹: Effective medium approximations - Wikipedia ²: Parameter model in Fluent and Workbench - Ansys Learning Forum ³: Effective medium theory for thermal conductivity of coiled aluminum sheet