Simulators - Science topic

of course you can calculate conversion of yor process. Related of your second question, you have to be in mind that software respond to a set of conditions made by THE OPERATOR, At final of the simulation software is not responsible by the results. This responsability is of the operator, that, at the end has to check if the response is resonable ( for example, if there is a strange current composition, etc). So the type of reactor you should use depends of your reaction and the set of conditions you choose. I recommend to visit software manuals and some literature to see what kind of reactor people are choosing for the type of reaction you intend to use. Also I recommend you to check in the literature what kind of themodynamic model you will choose: it may influence your results.

in other words, simulation is a very and fast tool to study process, but you have to be sure what you want to sudy and set the themodynamical model and in the case the type of reactor to be helped by software.

Simulating a two-phase conjugate heat transfer (CHT) problem where air and water do not mix and are separated by a wall can be achieved using various computational fluid dynamics (CFD) software packages, but the approach might differ depending on the software you are using. Below, I'll provide a general approach using ANSYS Fluent as an example. Keep in mind that the exact steps may vary based on the software you are using, but the general principles should be similar.

In ANSYS Fluent, you can simulate a CHT problem involving two immiscible fluids separated by a wall as follows:

It's crucial to carefully review the documentation and user guides of your specific CFD software to ensure that you are using the appropriate settings and models for your particular problem. Additionally, consider consulting with experienced users or experts in your organization or research community who are familiar with the software and have experience with multiphase CHT simulations, as they can provide valuable insights and guidance specific to your software and problem setup.

If you want to simulate RTD using Silvaco ATLAS, the following link can help you :

Toloue Sharyfy Simulating an object in orbit within Abaqus involves several key steps. First, create the geometry and mesh for the cylindrical hull you want to simulate. Define material properties accurately to represent space conditions. Set up gravity as a boundary condition and establish initial conditions for the object's position, velocity, and orientation based on your desired orbit. Model space debris as an external force acting on the hull, specifying its properties like mass, velocity, and trajectory. Apply appropriate boundary conditions to represent the constraints of the orbit, which may include fixing the center of mass at the desired location. Set up time integration and select explicit dynamic analysis for orbital motion. Consider contact modeling for interactions between the debris and the hull. Define analysis steps, including simulation time and events. Capture relevant data through output requests and use post-processing tools to analyze the results. Validate the simulation against real-world data if possible and make adjustments as needed for accuracy. Complex simulations, such as modeling the International Space Station, may require specialized expertise and additional considerations involving orbital mechanics and interactions with Earth's gravity. Consulting experts in the field is advisable for advanced and precise modeling.

Daniele Farioli The issue you are experiencing in your Abaqus Explicit simulations, where the tools do not reach their intended positions with high precision, can be attributed to a complex interplay of factors. Firstly, to achieve precise control over tool movement, attention to various simulation parameters is crucial. You should consider reducing the time step size to enhance the accuracy of the dynamic simulations and define boundary conditions to ensure that the tools are accurately constrained and loaded. Furthermore, adjust the contact settings, especially the penalty factor, contact, and damping, to better capture the interaction between the tools and the blank. Second, the issue is likely related to both the mesh and contact algorithm. Despite performing mesh sensitivity analysis, it's essential to ensure that the mesh resolution around the contact regions is appropriate. Distorted or poorly conditioned elements in these areas can significantly affect contact behavior. Additionally, consider utilizing more advanced contact algorithms such as General Contact or Contact Pair for improved accuracy in handling complex contact interactions. This shift may demand more computational resources but can yield more accurate results. Ultimately, this challenge necessitates an iterative refinement process, taking into account the aspects of time step size, contact settings, mesh quality, and solver parameters, all with a keen eye on the physical behavior of the system. You can connect with me on my WhatsApp for further guidance; https://wa.me/+923440907874

have you got the answer

Dear Kiran Kumari ,

you can consult my colleague's document Aitor Morales-Hernández

It is really illustrative and well explained, I'm sure it will help you.

Dear friend Nitish Rai

Hey there, my fellow researcher Nitish Rai! I am here to help you tackle this intriguing challenge.

Studying the impact of land-use practices on a sub-basin with altered discharge due to hydropower plants and dams is indeed complex, but it's absolutely doable. Here's how you can go about it:

1. **Data Collection and Comparison:** Start by collecting historical discharge data from Central Water Commission (CWC) gauge stations for your study area. These are your baseline measurements. Make sure to get data for a period that predates the construction and operation of the dams and hydropower plants.

2. **Hydrological Modeling:** Use the Soil and Water Assessment Tool (SWAT) to model the hydrological processes in your study area. This will help you simulate the natural discharge patterns that would exist in the absence of dams and reservoirs. You'll need to calibrate your model using available pre-dam discharge data.

3. **Scenario Analysis:** Run your SWAT model with different land-use scenarios to simulate how land-use changes affect discharge. Compare these simulations to the pre-dam discharge data to see how land-use practices alone impact discharge.

4. **Dam and Reservoir Impact Assessment:** Separate from your land-use scenarios, use your SWAT model to simulate the impact of dam operations on discharge. To do this, you'll need information on the dam operation, such as release schedules and reservoir storage capacities. Compare these simulations to post-dam discharge data.

5. **Correlation Analysis:** Perform statistical analyses to correlate changes in land use with alterations in discharge due to dam operations. This will help you understand the relative contributions of land use and dam operations to changes in discharge.

6. **Field Validation:** If possible, conduct field measurements and validation of your model by comparing simulated discharge with real-time measurements at key points in your study area.

7. **Sensitivity Analysis:** Conduct sensitivity analyses within your SWAT model to understand which parameters and variables are most influential in altering discharge. This can help you pinpoint key factors.

Remember, your goal is to tease out the effects of land-use practices from those of dam operations on discharge. It's a challenging task, but a well-structured study with comprehensive data and modeling can provide valuable insights.

And I must also remind you to consult with experts in your field and consider peer review as you progress. Your findings will be stronger with the collective wisdom of the scientific community. Good luck with your research!

You can read this paper on simulations of emergent behavior with a rich citation apparatus. Those interested about software used to simulate emergent behavior will find links in the paper.

Hi

Here is one approach to model a horizontal beam on nonlinear Winkler foundation (BNWF) with axial, transverse, and vertical springs in OpenSees:

1. Discretize the 1 km long beam into elements (say 100 10m long elements).

2. Use an ElasticBeamColumn element for each beam segment.

3. Attach zeroLength elements to each node:

- zeroLength in local x-direction for axial soil springs

- zeroLength in local y-direction for transverse soil springs

- zeroLength in local z-direction for vertical springs

4. Use a Parallel material to combine the elastic behavior with a Bilin/Quad nonlinearity for each spring.

5. Apply spring properties like stiffness, yield strength, post-yield stiffness.

6. For damping, attach zeroLength elements with a ViscousDamper material at the ends.

7. Apply restraints and prescribed displacement to beam ends to simulate boundary conditions.

8. For load, apply point loads, prescribed displacements, or ground motion acceleration to the model.

The spacing of the soil springs depends on the desired discretization accuracy. A spacing of 5-10m would likely be reasonable for this length of beam.

This assembles a beam on springs system with nonlinear material models and damping to capture soil-pipeline interaction effects under dynamic loading. The zeroLength elements conveniently allow applying 1D spring-damper behavior between nodes.

To simulate the effect of different tensions of fiber on the final products, such as glass epoxy pipes, using CAE ABAQUS, you can consider the following steps:

1. Define Material Properties: Start by defining the material properties of the glass epoxy composite in ABAQUS. This includes specifying the mechanical properties of the fibers (e.g., modulus, strength) and the epoxy matrix.

1. Create a Finite Element Model: Build a finite element model of the filament winding process and the resulting composite pipe in ABAQUS. This involves creating the geometry, meshing the model, and defining the boundary conditions.

1. Apply Fiber Tensions: Define the different tensions of the fibers during the filament winding process. This can be achieved by applying appropriate loads or constraints to the model. You can specify different tension values for different regions or layers of the filament winding.

1. Material Orientation: Consider the orientation of the fibers in the composite pipe. Filament winding typically involves fibers wrapped at different angles and orientations. Ensure that the model reflects the correct fiber orientations to capture their effect on the final product.

1. Simulate Filament Winding Process: Run the simulation in ABAQUS to simulate the filament winding process. This will allow you to observe the behavior of the composite pipe and its response to the applied fiber tensions. You can analyze various mechanical properties, such as stresses, strains, and deformations.

1. Evaluate Results: After the simulation, analyze the results to understand the effect of different fiber tensions on the final product. You can assess the structural integrity, strength, and other performance criteria of the glass epoxy pipe under different tension conditions.

It is important to note that simulating filament winding processes and the behavior of composite materials can be complex. It may require expertise in finite element analysis (FEA) and a good understanding of material behavior. Additionally, it is recommended to validate the simulation results with experimental data to ensure accuracy.

If you encounter specific difficulties or have more detailed questions about using ABAQUS for simulating the filament winding process, it would be beneficial to consult with experts in the field of composite materials and numerical simulations, or to refer to the ABAQUS documentation and user forums for specific guidance.

Marcos Luginieski

OEDES in Python only supports 1-D device simulations ( As far as I know but I may be wrong), you may need to modify or extend the code to implement 2-D device simulations.

your approach may be:

1. Check for Updates: Start by checking the package's GitHub repository or official website for any updates or newer versions that might include support for 2-D device simulations. The package may have been updated since you last checked, and the functionality you require might now be available.

2. Custom Development: If the package does not currently support 2-D simulations, you can consider extending it yourself. This would involve modifying the existing code or creating new modules to support the required functionality. You would need a good understanding of the underlying simulation algorithms and the structure of the package to make the necessary changes.

3. Contact the Developers or Community: Reach out to the developers of the OEDES package or its community to inquire about 2-D simulation capabilities. They may have plans to implement it in the future or can provide guidance on how to extend the package for 2-D simulations. GitHub issue trackers, discussion forums, or mailing lists associated with the project are good places to ask for help and connect with other users who might have faced similar challenges.

4. Explore Alternatives: If you are unable to find a solution with the OEDES package, you can also explore other simulation packages or frameworks that support 2-D drift-diffusion simulations for organic electrochemical transistors. Look for packages specifically designed for device simulations or consider general-purpose simulation frameworks that can be adapted for your needs.

One should have a good understanding of the underlying physics and algorithms involved in the simulation process to add functionality

Good luck!!

## Can you simulate three-dimensional space in two-dimensional Flow-3D?

Flow-3D is a computational fluid dynamics (CFD) software that can simulate fluid flow in both two and three dimensions. When we talk about a "two-dimensional simulation," we're typically referring to a simulation where one of the spatial dimensions is ignored or averaged out, resulting in a 2D plane.

So, while you can simulate a scenario in Flow-3D using a 2D approach, you're not truly capturing the full three-dimensional nature of the flow. Instead, you're making an approximation.

### Are the results in two dimensions the same as in three dimensions?

No, the results of a 2D simulation and a 3D simulation are not the same. Here's why:

1. **Loss of Information**: In a 2D simulation, you're ignoring or averaging out one of the spatial dimensions. This means you're losing information about how the fluid behaves in that dimension.

2. **Different Physics**: Some phenomena are inherently three-dimensional and cannot be accurately captured in a 2D simulation. For example, vortex shedding, swirls, and certain types of turbulence are 3D phenomena.

3. **Computational Efficiency**: One reason to use a 2D simulation is that it's computationally cheaper. It requires fewer computational resources and runs faster. However, this efficiency comes at the cost of accuracy.

4. **Applicability**: In some cases, a 2D simulation might be sufficient. For example, if you're studying flow in a long, straight pipe and you're only interested in the flow profile at the cross-section, a 2D simulation might give you the information you need. But for more complex scenarios, especially where 3D effects play a significant role, a 3D simulation is necessary.

### In Conclusion:

While you can use Flow-3D to run a 2D simulation of a scenario, it's an approximation that doesn't capture the full 3D behavior of the fluid. Whether a 2D simulation is appropriate depends on the specific problem you're trying to solve and the level of accuracy you need. If the three-dimensional effects are significant, then a 3D simulation is essential to get accurate results.

Thank you Mr. Kim for replying

Under the Eulerian Model, a drag model is to be chosen, what is the appropriate drag model to be used for such simulation?

Let me give a few ideas on how to do it. I reckon that it would help you.

Higbie's Penetration Theory equation:

Simple Simulation:

# Parameters

D = 0.001 # Diffusion coefficient

Cs = 1.0 # Concentration at the surface

L = 1.0 # Length of the porous medium

N = 100 # Number of spatial points

dx = L / N # Spatial step size

delta = 0.1 * dx # Thickness of diffusion boundary layer

# Initialize concentration field

C = np.zeros(N+1)

C[0] = Cs # Concentration at the surface

# Time parameters

dt = 0.001 # Time step size

t_end = 1.0

num_steps = int(t_end / dt)

# Time-stepping loop

for step in range(num_steps):

# Calculate concentration gradient using finite difference

dC_dx = np.diff(C) / dx

# Update concentration using Higbie's Penetration Theory equation

flux = D / delta * Cs * dC_dx

C[1:-1] += flux * dt / dx

# Plot the concentration profile

x = np.linspace(0, L, N+1)

plt.plot(x, C)

plt.xlabel('Distance')

plt.ylabel('Concentration')

plt.title('Concentration Profile')

plt.grid(True)

plt.show()

Thank your dear Amit Choksi for your response.

Simulating a distance relay using MATLAB Simulink involves creating a model of a power system, implementing distance relay logic, and testing its performance under fault scenarios. Here's a summarized step-by-step guide:

Ensure familiarity with power systems, protection schemes, and Simulink for successful distance relay simulation.

Dear Muhammad Shaffatul Islam,

Your electrode definition is wrong, because of incorrect electrode name either in SDE or Sprocess. Hope it helps.

Thank you so much

Hai Dr, how are you? I am attracted to your question as I have some information on it. Below, I supply you with all the answers you need, but I would really appreciate it if you could press the RECOMMENDATION buttons underneath my 3 research papers' titles in my AUTHOR section as a way of you saying thanks and appreciation for my time and knowledge sharing. Please do not be mistaken, there are few RECOMMENDATION buttons in RESEARCHGATE. One is RECOMMENDATION button for Questions and Answers and the other RECOMMENDATIONS button for papers by the Authors. I would appreciate if you could click the RECOMMENDATION button for my 3 papers under my AUTHORSHIP. Thank you in advance and in return I provide you with the answers to your question below :

There is no option to make a random distribution of fillers in COMSOL Multiphysics 6.0. However, you can use the Random Variable function to create a random distribution of fillers and then use the Assign Material function to assign properties to the fillers.

The following are the steps on how to simulate dispersion of fillers in an elastomer using COMSOL Multiphysics 6.0:

The following is an example of how to create a random distribution of fillers in an elastomer using COMSOL Multiphysics 6.0:

import comsol.modeling.functions as fn # Create a random variable filler_concentration = fn.RandomVariable(distribution_type="Uniform", minimum=0.0, maximum=0.5) # Assign the filler material to the random variable filler_material = "Filler" comsol.materials.AssignMaterial(filler_concentration, filler_material)

This code will create a random variable with a uniform distribution between 0.0 and 0.5. The filler material will be assigned to the random variable.

Thank u for ur kind “ LIKE” . hope my notes help u a bit on ur tasks. regards.

You could look at this whitepaper https://www.tetcos.com/pdf/v13.3/Deep_Neural_Network_Model_for_5G_SINR_prediction.pdf

We use NetSim(https://www.tetcos.com/5g.html) for modeling the RAN, Mobility, Traffic flow and then interface it with MATLAB/Python for the ML algorithm. Key performance metrics, such as delay and throughput, are provided in NetSim

Hello,

If the simulation software is CST, then in material selection for substrate, select new material and then fill the properties of GT7-29001 like permittivity, conductivity, loss tangent etc.

For properties of material, one paper is attached.

Thanks,

Thank you so much Mohammad Imam

it is essential to meticulously construct the waveguide and graphene layers, which serve as the foundational elements of the model. The subsequent step involves the precise specification of the properties and materials characterizing your material (in your case the graphene), as well as other constituent components, imbuing the simulation with its requisite attributes. Optimal module selection, encompassing electromagnetic waves and plasmonics, lays the groundwork for the simulation's comprehensive scope. Thoughtful consideration of boundary conditions ensures the confinement of pertinent variables, facilitating an insightful and coherent analysis. Equally crucial is the implementation of a refined mesh, which inclusively incorporates all relevant entities within the simulation framework.

Hi Ashwani Kushwaha I think the best way so far to handle the DFT calculation with quantum espresso, is to perform it via Materialssquare platform. You even can create your structure there easily and connect it to the QE module where the suitable Pseudopotential for each element in your structure will be selected for you in easy and soft way. This here the site https://www.materialssquare.com/work and you can also see this video how to do the DFT in general with materialssquare for example here https://www.youtube.com/watch?v=7V2eQkNxKdo. Once done you can still able to download and extract your input structure easily if you don't want to run your DFT on cloud servers.

Simulating a chemical reaction in COMSOL Multiphysics involves using the Reaction Engineering interface. This interface allows you to set up and solve reaction systems involving multiple species and reactions. Here's a general guide on how to simulate a chemical reaction in COMSOL:

Remember that the specific steps and settings required for simulating a chemical reaction may vary depending on the complexity of the reaction system and the specific physics involved. Make sure to refer to the COMSOL documentation and tutorials related to reaction engineering for more detailed information on setting up your specific chemical reaction simulation.

Maybe you can try to dope trap and set its energy level.

Comsol de çoklu simülasyon aynı anda farklı şekillerde gerçekleşebilir. Birden fazla simülasyon varsa, birden fazla bağlantı noktası ve sınır noktası vardır. Bu simülasyon elektrik devreleri ve comsol yazılımı içinde geçerlidir. Elektrik devrelerinin bağlantı noktalarında ve sınır noktalarında oluşan simülasyon denilen düğümler comsol yazılıma yansıtılır ve bunlar comsol yazılımda simülasyon örneği oluşturur.

Yes, it is possible to simulate 2D traffic flow using VISSIM. VISSIM is a microscopic traffic simulation software that can be used to simulate traffic flow on a variety of road networks, including 2D networks. To simulate 2D traffic flow in VISSIM, you will need to create a 2D road network in the software. You can do this by importing a 2D map or by creating the network manually. Once you have created the network, you can then add vehicles to the network and simulate traffic flow.

You can use dirac delta function in multiplication with the excitation strength function. Dirac delta can be used to specify the region and time for which you want to introduce your excitation.

I have introduced the source strength for volcano in one of my paper titled "Modeling of Tsunami generated in stratified oceans by sub-aquatic volcanic eruptions" you can follow similar approach.

Hi Hello everyone, I already know the reason. I need to correctly set the Domain of the piezoelectric material in comsol

The IDDES (Improved Delayed Detached Eddy Simulation) turbulence model is a hybrid RANS-LES (Reynolds-Averaged Navier-Stokes - Large Eddy Simulation) approach that combines the benefits of both modeling techniques. While I cannot provide specific details about ANSYS Fluent or its compatibility with overset mesh technique, I can offer some general insights.

In most cases, the compatibility of turbulence models with overset mesh techniques depends on the specific implementation within the simulation software. Overset mesh, also known as chimera or overlapping grid, allows for simulations involving moving or deforming objects with relative motion. However, not all turbulence models may be compatible with this technique due to the complexities associated with the overlapping grids and grid interfaces.

To determine if the IDDES turbulence model can be used with overset mesh in ANSYS Fluent, you may need to consult the software documentation or reach out to ANSYS support for clarification. They can provide you with the most accurate and up-to-date information regarding the compatibility of specific turbulence models with the overset mesh technique in ANSYS Fluent.

Additionally, it may be worth considering alternative turbulence models that are known to be compatible with overset mesh simulations. Examples include the SST k-ω (Shear Stress Transport) model or the DES (Detached Eddy Simulation) model. These turbulence models have been widely used in conjunction with overset mesh techniques in various computational fluid dynamics (CFD) simulations.

Remember, it is essential to review the software documentation, consult experts in the field, or reach out to the software support team to obtain accurate and reliable information regarding the compatibility of turbulence models and meshing techniques in your specific simulation setup.

Dear Aravindhan

thank you very much for valuable info. I want more practical info about this sentence :"You can set the injection rate individually for each PE, allowing for different rates among different processing elements."

please let me to know how I can implement this scenario.

thank you again

Harish Balaji 1] node number TOOL-1.81743 refers to your reference point; why don't you try the plunging action away from the material and then apply the welding condition, 2] also because of the initial plunging, excessive distortion happened, especially with the second order tetrahedron, check that too

Dear Cai Jiale and Bernard Schaffler

Setting up COMSOL to run simulations involves several steps. Here's a general guide to help you set up your simulation in COMSOL:

1. Start a New Project: Open COMSOL and create a new project by selecting the appropriate physics module for your simulation. In your case, it seems like you are using the AC/DC Module for simulating electromagnetic fields.

2. Build the Geometry: Use the geometry tools in COMSOL to create or import the geometry of your copper coil. Specify the dimensions, material properties, and any other necessary geometric details.

3. Define Physics and Material Properties: In the Physics section, specify the electromagnetic physics settings for your simulation. Define the material properties for the copper coil and any other relevant materials in your model.

4. Set Up Excitation: Define the excitation method for your simulation. Since you mentioned applying a pulse excitation current, select the appropriate excitation type, such as a current source or a time-dependent function.

5. Specify Boundary Conditions: Set up the boundary conditions for your simulation. Define the appropriate conditions for the edges or surfaces of your model, such as electrical insulation or prescribed voltage.

6. Meshing: Generate a suitable mesh for your model using the meshing tools in COMSOL. Ensure that the mesh is sufficiently refined to capture the details and variations of the electromagnetic field accurately.

7. Select Study Type: Choose the study type based on your simulation requirements. In your case, for transient analysis, select the Transient study type. For frequency-domain analysis, select the Frequency Domain study type.

8. Set Up Time/Frequency Domain Settings: For transient analysis, specify the time duration, time steps, and solver settings in the Transient study settings. For frequency-domain analysis, define the frequency range, number of frequencies, and other relevant settings in the Frequency Domain study settings.

9. Add Probes: Place the probe(s) at the desired location(s) to measure the potential or other quantities of interest. Configure the probe settings, such as data storage and visualization options.

10. Solve the Model: Once all the necessary settings are configured, solve the model by clicking the "Compute" button. COMSOL will process the simulation based on the defined parameters and generate results.

11. Analyze Results: After the simulation completes, analyze and visualize the results using the post-processing tools in COMSOL. This includes examining the electromagnetic field distribution, potential measurements, and any other quantities of interest.

Regarding your specific requirement to connect the time-domain pulse signal with the frequency domain, you can use the Fourier Transform feature in COMSOL. It allows you to convert the time-domain signal to the frequency domain and analyze the frequency components. You can find this feature in the post-processing tools of COMSOL.

If you encounter specific errors or face difficulties during the simulation setup or analysis, it's recommended to refer to the COMSOL documentation, tutorials, and support resources. They provide detailed information on various aspects of using COMSOL for simulations and can assist in troubleshooting specific issues you may encounter.

I've added a photo that it can describe all of things I need to expalin, a Skid, settlement of motor, settlement of a pump or air-end. According to the Din 4024 for the machine foundation, I have to check the possibiloty of vibration on bearings, so I am going to make a dynamic analysis. I think, we can use 2 ways to implement this simulation: control displacement or control force. I want to know that the my way in simulation is correct or not.

I'll be glad if you can help me to solve and even if I am eager to publish this issue as a conference papaer if you are interested in.

Floquet port is exclusively used for planar periodic structure. To achieve perfect periodicity it is required to assign coupled boundaries and the Floquet port.

Regards

Did you figure this out? I am trying to model some wedges which are partially in contact, after applying a load I will force the wedges to bend down and come in contact with a substrate (Master or slave surface). I am getting this error:

slave nodes for surface pair (assembly_surf-glass,assembly_surf-wedges) are reverted back to type node-to-surface. This case may happen if type surface-to-surface cannot find some nodes to form the constraint. Some of reasons are: the slave is coarser or larger than the master surface, the slave is not flat relative to the master surface, or slave nodes that are beyond the extent of the master surface.

6162 slave nodes either found no intersection with a master surface or outside the adjust zone.

Yes, Python is a popular programming language for implementing and simulating swarm intelligence algorithms, including swarm optimization algorithms such as Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and others. Python offers a rich ecosystem of libraries and frameworks that provide tools for simulating swarm intelligence algorithms. Some of the commonly used libraries for swarm optimization in Python include:

These are just a few examples of libraries in Python that can be used for simulating swarm intelligence algorithms. Depending on the specific requirements of your simulation and the algorithm you want to implement, you may choose one of these libraries or explore other options available in Python.

Ahmad Reshad Bakhtari, you can use ANSYS for PCM Constrained and unconstrained melting.

article for more help: https://www.researchgate.net/publication/352934710_PCM_augmented_composite_wall_for_Base_Transceiver_Station_BTS_for_telecom_towers

I know this question was long ago, but It is worth saying that I solved my problem using Ansys's Acoustic harmonic module, using a FEM-based solver, instead of CFX, which is a CFD-based solver. Ansys's Acoustic harmonic can accurately simulate harmonic loads and boundary conditions. Although this method is based on FEM, not CFD, It is a promising method to study FSI under harmonic loads. If you need to investigate a thermal or electrical field simultaneously with the acoustic field, use Ansys Coupled Field Harmonic.

Dear Hossein Mohammadi , nice and deep question. I have tried to formulate my position in https://www.academia.edu/44503746/Becoming_artificial_intelligent_from_a_controllers_point_of_view_Contents. I am looking forward to your view?

Kind regards

Rob

To simulate an antenna design with more stimulation points in HFSS (High-Frequency Structure Simulator), you can follow these steps:

By setting up multiple stimulation points in HFSS, you can obtain detailed field data and assess the behavior of your antenna design at different locations. This allows for a more comprehensive analysis of the antenna's performance and helps in optimizing its design for desired characteristics.

Note: The exact steps and options may vary slightly depending on the version of HFSS you are using. It is recommended to consult the HFSS documentation or tutorials specific to your version for more detailed instructions.

Rabin Kanisha

Thanks for help,

However, there is a different point is my PCB includes lumped element (R,C) and ICs. I replaced ICs by their SnP file, so I have to run simluation both on 3D and Schematic environment. But nothing happened. It seemed incorrect.

Pls hepl me to figure out the right way to simulate this case.

Thank you.

Tahereh Alavi, to answer your question, see here:

If you are looking for a broad range of high frequencies for simulation, you can try a free software called NYUSIM. It can offer frequency range up to 100 GHz and you can adjust many parameters according to your requirements. Hope it helps!

When creating a material model for finite element analysis (FEA) in ABAQUS, or any other FEA software, using representative data for the material's properties is crucial. For 3D printed parts, this can be tricky because the material properties can vary depending on the specifics of the 3D printing process, such as the type of 3D printing (e.g., fused deposition modelling, selective laser sintering), the specific printer used, the print settings (e.g., layer thickness, print speed), and the material used.

Using Young's Modulus from tensile test data and yield stress, ultimate strength, and plastic strain values from compression test data is common in cases where the material exhibits significantly different behaviour under tension and compression. However, you must ensure the material's response under the loading conditions of interest is accurately represented.

In general, ABAQUS does not limit the source of your material properties. It only requires the user to define the material properties correctly for the particular material model chosen in ABAQUS. However, the user is responsible for ensuring that the properties inputted into the model accurately represent the real-world material.

Here are a few things you could consider:

Discussing these considerations with your project advisor or someone with expertise in FEA and the specific type of 3D printing you're using would be prudent.

I think you should enlarge the model to the point where there is no variation in boundaries.

Thank you for your response Ali Behrad Vakylabad .

Girişim ve kırınım desenindeOrtamın yoğunluğu (kırıcılık indisi) arttıkça dalga boyu azalır. Silindirin merkezinde tam kırılmaya uğrar. R uzaklığı kırıcılık indisi ile ters dalga boyu ile doğru orantılıdır.

Looking for Hand model for CST

Hello,

1. Temperature dependency: Most quantities are temperature-dependent, meaning they exhibit a behavior that varies with temperature. If you are comparing experimental data obtained at different temperatures, it is crucial to consider the temperature dependence of the model parameters. Make sure to incorporate appropriate temperature corrections or factors in your physics-based model to align the OCV curve with experimental data at various temperatures.

2. Experimental measurement uncertainties: Experimental measurements may contain inherent uncertainties or systematic errors that can impact the accuracy of the comparison. It is important to carefully evaluate the quality and reliability of the experimental data and consider statistical analysis to assess the uncertainties associated with the measurements.

I found this solver : -

Greeting in the first step find bandwidth, follow that can be found Qc,

What software do you want to solve the problem? Fluent? CFX?...?

Thanks @Sangat Naik

Yours is a fully CFD problem; about multiphase simulations, Comsol gives different physics as a choice:

Physics-> Add Physics -> Fluid Flow -> Multiphase Flow

there you find different methods, all based on what you want to simulate (bubbles, phase transport, fluid-structure interction etc.).

If you want to use Comsol, see examples on multiphase modeling (in fact, you have air and another gas, while the room walls I think are rigid walls). These are very good to get started.

However, from personal experience Your problem would be less computational consuming and difficult to implement in Ansys FLUENT (based on Finite Volume Method and specifically used to simulate fluids).

Best regards,

AP

Hi Bowen Li

can you draw a schematic from problem for me?

Is your software Fluent?

Samy Elhadi Oussadou

I really appreciate the help that is really nice from you, but my problem is generating the crack automatically without creating crack initiation. or input crack geometry.

My model is for Hydraulic Fracture for concrete gravity dam

Howdy Jamel Chahed

Thank you for your remarks. Of course, any theory of education has limits because students are a varied lot. The students who have liked my approach (few) responded to their being treated as inquiring persons.

In this case I find a bit of mystery because Sanjibonny Buragohain has shown awareness of the answer to her question, and her profile indicates even deeper understanding would be present. I would like to know what she seeks to know better and to help, by normal, spiral, personal, or whatever educational means she prefers.

Or, I may be completely off-track. It has happened before.

Happy Trails, Len

Nihal Sanil i meant documentation for veins built in modules

Checkerboard error injection is used to induce HARQ retransmissions. This means injecting errors in the form of checkerboard patterns into the transmitted data, to force the HARQ receiver to request retransmissions of some of the data. This helps determine the effectiveness of the HARQ soft combining operation as well as the overall performance of the system. The BLER (Block Error Rate) is then used to measure the performance of a particular HARQ scheme, as it indicates the percentage of data blocks received where at least one bit was wrong. Thus, injecting errors in the form of checkerboard patterns can be used to modify the BLER and evaluate the performance of the system.

The simplest way to do this is to use a File-based approach; this approach does not require any modifications to NetSim code. Your program in MATLAB should write the device position with respect to time in a text file. The format is explained in https://www.tetcos.com/help/v13.3/Technology-Libraries/MANETs.html#file_based_mobility_model

In the devices which you wish to move per MATLAB data, set the mobility model to File-Based Mobility and update the Mobility CSV file with input generated from MATLAB in NetSim's mobility file format. The mobility file is common for all devices in the network. Hence, if you want to introduce mobility in multiple nodes based on data from MATLAB all this information can be put together in the same mobility CSV file which NetSim will read at the simulation start.

Igor Brown Adding another component may allow a certain property to be better simulated. A simulant does not have to (and cannot) reflect every aspect of the lunar regolith and there have been many simulants over the years. Besides there's no air or water on the moon so no erosion (or oxidation, as you infer) also. This means that particles can be highly angular (not smoothed by erosion) and spheres of glassy or metallic (e.g. Fe) can also be found. Thus the real lunar regolith if shipped to earth would not perform as it actually would when on the moon. (And about 70% of the moon rocks/regolith returned by the Apollo missions stills remains in storage and not investigated. Many years ago I worked on the topic with NASA and USGS. Here's a webinar on the subject (free registration required):

The particle size and shape analysis of NASA/USGS lunar simulant

In COMSOL, the procedure could be:

1) Create a 3D model of the system that represents the substrate or surface on which the bacteria will adhere;

2) Specify the relevant physics involved in bacterial adhesion. This may include fluid flow, species transport (for nutrients or chemicals), and surface interactions.

3) Define the boundary conditions for your simulation. This includes specifying the flow conditions, such as velocity or pressure, and any initial conditions for the bacteria or other species present.

4) Assign appropriate material properties to the different components in your model (you may need to specify the properties of the substrate surface and the bacterial cells, including their surface charge or binding affinity).

5) Set up the governing equations that describe the fluid flow, species transport, surface interactions, etc.

6) Generate a mesh that discretizes your model geometry. This step divides the model into small elements or cells, which are used for solving the governing equations numerically.

7) Run the simulation...

8) Analyze and visualize the simulation results...

Something like what you want to do:

@allThe error message you provided, "Error 30061 (INI+61) cannot find element of master segment 1343 of interface 1," suggests that there is an issue with finding an element in the master segment of interface 1 in your simulation. Here are a few suggestions on how you can tackle this error:

By carefully examining the input data, mesh, connectivity, boundary condition