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I am doing my thesis on pull-out test and my problem is in the compressive damage . Please guide me with an article and an example to solve my problem.
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Amin Borhan, Not exactly same but you can watch if it is helpful: https://www.youtube.com/watch?v=YE2QFLRL_vU
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I am having trouble with penetration between my corrugated core and rigid platen. My model is simulating a quasi-static compression. the top platen compresses and the bottom is fixed. As shown in the images I have penetration at the bottom and top of the corrugated core and analytical rigid platen. I use a node to surface interaction with the master being the platen and the secondary is the nodes along the top and bottom core. I can't use a line as a surface so I have to use the nodes. Is there any way to remove penetration?
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Chase Mortensen, the surface to surface interaction with smaller slave surface mesh density will solve the problem. For more, let's connect on WhatsApp to discuss; https://wa.me/+923440907874
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Hello everyone
I'm modeling a steel-reinforced coupling beam in DIANA which is embedded to an adjacent shear wall. I want to model rods in the embedment region, which only transfer axial loads in compression. For further explanation, these rods are fully attached (welded let's say) to some steel plates, where the steel section of the beam is ONLY placed on these steel plates (there is no connection such as weld or bolts). Therefore, these rods only work if they are in compression. Since all these rods, steel plates, and steel beam are surrounded by concrete, therefore I think these rods can only experience axial deformations.
I'm wondering if there is an specific type of an element in DIANA which only resist compression forces and axial deformations, or I should apply these features by defining some interfaces.
I appreciate every one's time and attention in advance.
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To define an axial element in DIANA software that only transfers compression, you can use the following methods:
Method 1: Using a linear spring with zero stiffness in tension
  1. Create a new material with a Young's modulus of zero and a Poisson's ratio of 0.5.
  2. Create a new element type using the linear spring element template and select the new material.
  3. Draw the element in your model and assign it to the new element type.
Method 2: Using a nonlinear spring with a bilinear stiffness curve
  1. Create a new material with a nonlinear stress-strain curve that has a bilinear shape. The first branch of the curve should have a finite stiffness in compression, and the second branch should have a stiffness of zero.
  2. Create a new element type using the nonlinear spring element template and select the new material.
  3. Draw the element in your model and assign it to the new element type.
Method 3: Using the enhanced truss element
  1. Draw the element in your model and assign it to the enhanced truss element type.
  2. Edit the element properties and set the "Tension stiffness" parameter to zero.
All of these methods will create an axial element that can only transfer compression loads.
Based on the image you provided, I recommend using the enhanced truss element type with zero tension stiffness. This will model the behavior of the rods in the embedment region accurately.
To create the enhanced truss element, follow these steps:
  1. In the DIANA menu, go to Elements > Create Element Type.
  2. In the Create Element Type dialog box, select the Enhanced Truss element type and click OK.
  3. In the Enhanced Truss Element Type dialog box, set the following parameters:Material: Select the material that you want to use for the element. Cross-section: Select the cross-section that you want to use for the element. Tension stiffness: Set the tension stiffness to zero.
  4. Click OK to create the new element type.
Once you have created the enhanced truss element type, you can draw it in your model and assign it to the rods in the embedment region.
Please note that it is important to make sure that the nodes of the enhanced truss elements are properly connected to the nodes of the surrounding concrete elements. This can be done using the Connect Nodes command in the DIANA menu.
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I want to model a cold formed steel tube in abaqus. Major longitudinal tensile residual stresses exist on the outside surfaces of the section, and equivalent longitudinal compressive stresses exist on the inside surfaces of the section.
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To model a cold-formed steel tube with major longitudinal tensile residual stresses on the outside surfaces and equivalent longitudinal compressive stresses on the inside surfaces in Abaqus, you can follow these steps:
Geometry Creation:
Create the geometry of the cold-formed steel tube using the appropriate CAD software or Abaqus built-in modeling capabilities.
Material Definition:
Define the material properties for the cold-formed steel tube in Abaqus. This should include the Young's modulus, Poisson's ratio, and yield stress of the material.
To incorporate the residual stresses, you can define them using the "Initial stresses" option. Specify the appropriate tensile residual stress value for the outside surfaces and the equivalent compressive residual stress value for the inside surfaces.
Meshing:
Generate a suitable mesh for the cold-formed steel tube geometry using Abaqus meshing capabilities. Ensure that the mesh is fine enough to capture the desired details and deformations accurately.
Boundary Conditions:
Apply appropriate boundary conditions to simulate the loading and constraints in your model. These conditions may include fixed displacements or prescribed loads depending on your specific analysis requirements.
Loading:
Apply the actual loading conditions that you want to simulate on the cold-formed steel tube. This could include tensile, compressive, or bending loads, depending on your analysis objectives.
Analysis Setup:
Define the analysis settings such as time steps, convergence criteria, and element types.
Specify the appropriate analysis type, such as static or dynamic analysis, depending on the nature of your problem.
Solve and Post-Processing:
Run the analysis and monitor the convergence. After the analysis is complete, examine the results to obtain the desired information, including stress distributions, deformations, and any other quantities of interest.
Remember that modeling residual stresses accurately can be challenging, and the specific approach may vary depending on the complexity of the manufacturing process used for cold forming the steel tube. It is recommended to consult relevant literature, research papers, or experts in the field for more specific guidance on modeling residual stresses in cold-formed steel tubes within Abaqus.
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I did compression test on Instron 8801 UTM machine. I like to validate my obtained compression stress, Compression strength value in simulation software. My crosshead displacement speed is 2mm/min.
In this case, which module I need to select? ( Static structural or dynamic or quasi static or non linear simulation).
I am using Fusion 360 for simulation. How to correlate the compression stress with the simulated results.
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Yes, it is possible to validate Universal Testing Machine (UTM) compression test results using simulation software. Simulation software can be used to model and analyze the behavior of materials under different loading conditions, such as compression tests. This allows you to compare the simulation results with experimental data obtained from UTM compression tests, aiding in validation and improving the understanding of material behavior.
Here's a general process for validating UTM compression test results using simulation software:
1. **Material Characterization:** First, you need to accurately characterize the material properties that will be used in the simulation. This includes parameters like Young's modulus, Poisson's ratio, yield strength, etc.
2. **Geometry and Boundary Conditions:** Create a simulation model that replicates the geometry and boundary conditions of your actual UTM compression test setup. This might involve creating a virtual sample of the material and defining how it is clamped or constrained.
3. **Apply Loads:** Apply the same or similar loading conditions as used in the UTM test. This could involve applying a compressive force or displacement to the virtual sample.
4. **Simulation:** Run the simulation using appropriate numerical methods, such as finite element analysis (FEA) or finite difference analysis. The software will calculate how the material responds to the applied loads.
5. **Compare Results:** Once the simulation is complete, compare the results obtained from the simulation with the experimental results from the UTM compression test. Compare quantities like stress-strain curves, deformation patterns, and failure points.
6. **Adjust Parameters:** If there are discrepancies between the simulation and experimental results, you might need to adjust material properties, boundary conditions, or other simulation parameters to improve the match.
7. **Iterative Process:** Simulation and validation can be an iterative process. You might need to make several adjustments to the simulation setup to achieve a close match with the experimental results.
8. **Validation Criteria:** Define specific validation criteria that the simulation results should meet, such as peak load, deformation at failure, stress-strain curve shape, etc.
It's important to note that the accuracy of the simulation depends on the accuracy of the material properties, boundary conditions, and the fidelity of the simulation software itself. Additionally, the simulation is a model of the real-world behavior and might not capture all intricacies of the actual test. Therefore, careful calibration, validation, and consideration of the limitations are essential.
Popular simulation software used for these purposes includes Abaqus, ANSYS, COMSOL, and others. The specific software you choose will depend on your familiarity, the features it offers, and the level of detail you require in your simulation.
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What is the most common compression algorithm and which machine learning algorithm is best for image processing?
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The most common compression algorithm for images is the JPEG (Joint Photographic Experts Group) algorithm. JPEG is a widely used lossy compression method that reduces the file size of images while maintaining a reasonable level of visual quality. It achieves compression by analyzing and quantizing the color and spatial information in the image.
As for machine learning algorithms in image processing, there isn't a single "best" algorithm, as the choice depends on the specific task and data at hand. However, certain algorithms are commonly used in various image processing applications:
  1. Convolutional Neural Networks (CNNs): CNNs are the go-to choice for a wide range of image processing tasks, including image classification, object detection, segmentation, and more. They are designed to automatically learn hierarchical features from images, making them highly effective for handling complex visual data.
  2. Generative Adversarial Networks (GANs): GANs are used for tasks like image generation, style transfer, and data augmentation. They consist of a generator and a discriminator that work together to generate high-quality synthetic images.
  3. Recurrent Neural Networks (RNNs): While mainly used for sequential data, RNNs can also be used in image processing tasks where temporal information is important, such as video analysis or captioning images.
  4. Support Vector Machines (SVMs): SVMs can be used for image classification and segmentation. They work well when there's a clear boundary between classes.
  5. Random Forests and Decision Trees: These are used for tasks like image segmentation and feature extraction. They can work well when dealing with structured or tabular image data.
  6. K-Nearest Neighbors (KNN): KNN can be used for tasks like image recognition and classification, especially in scenarios with relatively small datasets.
  7. Deep Learning Architectures for Specific Tasks: Some tasks have specialized architectures, such as U-Net for biomedical image segmentation, Mask R-CNN for instance segmentation, and YOLO (You Only Look Once) for real-time object detection.
The "best" algorithm depends on factors like the nature of the image processing task, the amount of available data, computational resources, and the desired level of accuracy. In many modern applications, deep learning approaches like CNNs often outperform traditional machine learning algorithms due to their ability to capture intricate patterns and features in images.
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What is the algorithm that reduces file size and difference between encoding and compression?
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Compression algorithms are normally used to reduce the size of a file without removing information. This can increase their entropy and make the files appear more random because all of the possible bytes become more common.Here, an algorithm scans image files and reduces their size by discarding information considered less important or undetectable to the human eye. Using lossy methods therefore requires you to make a balanced judgment between: storage/delivery requirements. It depends on user's need, with compression ratio being only one factor of the equation. ZPAQ and ARC are the best compressors, but 7Z and RAR formats has a clear advantage in terms of decompression speed, faster than for any other tested format. MPEG algorithms compress video data to reduce number of bytes that can be easily transmitted and then decompressed. MPEG stands for The Moving Picture Experts Group (MPEG). It was established in 1988 by the initiative of Hiroshi Yasuda and Leonardo Chiariglione. You can compress a large video file by opening it in a video editing or playback software and exporting it as a smaller file type. Can you compress a video on your phone? Yes, but you will need to upload the video file to an online converter or use a video editing app. There are many different ways to reduce video file size without losing quality. By using a video compressor, trimming the video length, adjusting the bitrate, or converting to a web-friendly format, you can significantly reduce the file size of your video. Although video compression shrinks files, it may also impact video quality. Video encoding, however, compresses your video files without compromising quality. With encoded videos, the gigabytes of data become mere megabytes. And your content becomes compatible with many devices and platforms. Video encoding is the process of compressing and potentially changing the format of video content, sometimes even changing an analog source to a digital one. In regards to compression, the goal is so that it consumes less space. This is because it's a lossy process that throws away information related to the video. Encoding converts data into a standard format and increases performance because there is less disk I/O during query execution. It also passes encoded values to other operations, saving memory bandwidth.
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Homogeneous Charge Compression Ignition (HCCI) and Gasoline Direct Injection (GDI) are advanced engine technologies that aim to improve engine efficiency and reduce emissions in modern automotive engines. Each technology offers unique advantages that contribute to overall performance enhancements. Here's how HCCI and GDI achieve these objectives:
  1. Homogeneous Charge Compression Ignition (HCCI): HCCI is a combustion technology that combines features of traditional spark ignition (SI) engines and compression ignition (CI) engines. In HCCI engines, a homogeneous mixture of air and fuel is compressed to a high temperature and pressure, causing spontaneous ignition without the need for a spark plug. This combustion process allows for more complete and efficient burning of the fuel-air mixture, leading to several benefits:
a. Improved Efficiency: HCCI engines operate at higher compression ratios, similar to diesel engines, resulting in higher thermodynamic efficiency. The higher compression ratios contribute to better fuel economy compared to conventional SI engines.
b. Reduced CO2 Emissions: HCCI's improved combustion efficiency leads to lower fuel consumption, resulting in reduced carbon dioxide (CO2) emissions, a significant greenhouse gas.
c. Lower NOx Emissions: The absence of a flame front in HCCI combustion reduces peak temperatures and, consequently, nitrogen oxide (NOx) emissions, a major contributor to air pollution.
  1. Gasoline Direct Injection (GDI): GDI is a fuel injection technology that precisely injects fuel directly into the combustion chamber of each cylinder in a spark-ignited gasoline engine. Unlike traditional port fuel injection (PFI), where fuel is injected into the intake manifold, GDI offers several advantages:
a. Better Combustion Control: GDI allows for more precise control of the air-fuel mixture, enabling stratified charge combustion. The stratified mixture creates leaner conditions during low-load operation, leading to improved efficiency.
b. Higher Compression Ratios: GDI's ability to control the air-fuel mixture facilitates higher compression ratios, leading to improved thermal efficiency and fuel economy.
c. Reduced Particulate Matter (PM) Emissions: GDI can help reduce particulate matter emissions compared to PFI, as the fuel is directly injected into the combustion chamber, leading to better fuel-air mixing and more complete combustion.
d. Enhanced Knock Resistance: GDI can inject small amounts of fuel during the compression stroke to create a charge cooling effect, which improves the engine's knock resistance, allowing for higher compression ratios and more advanced ignition timing for improved efficiency.
By leveraging HCCI and GDI technologies, automotive engineers can achieve higher engine efficiency, reduced fuel consumption, and lower emissions. These advancements play a crucial role in meeting stringent emissions regulations and achieving sustainable mobility goals in modern automotive engines. However, it's important to note that implementing these technologies requires careful engine calibration and control strategies to ensure proper combustion and avoid potential challenges such as uncontrolled combustion, engine knock, and particulate matter formation.
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HCCI and GDI are two technologies that aim to improve the efficiency and reduce the emissions of gasoline engines. HCCI stands for homogeneous charge compression ignition, and GDI stands for gasoline direct injection.
HCCI is a combustion mode that uses a homogeneous mixture of air and fuel that is compressed and ignited by the high temperature and pressure in the cylinder, without the need for a spark plug. This allows for a higher compression ratio, lower fuel consumption, and lower emissions of nitrogen oxides (NOx) and particulate matter (PM) compared to conventional spark ignition engines. However, HCCI also has some challenges, such as controlling the combustion timing, preventing engine knock, and extending the operating range¹.
GDI is a fuel injection system that injects gasoline directly into the cylinder, instead of into the intake manifold. This allows for a better control of the air-fuel ratio, a higher power output, and a lower fuel consumption compared to port fuel injection engines. GDI also enables the use of stratified charge combustion, where a rich mixture of fuel and air is injected near the spark plug, while a lean mixture is present in the rest of the cylinder. This reduces the heat losses and increases the thermal efficiency².
By combining HCCI and GDI, it is possible to achieve a more flexible and efficient combustion system that can switch between different modes depending on the engine load and speed. For example, HCCI can be used at low to medium loads, where it offers high efficiency and low emissions, while GDI can be used at high loads, where it provides high power and torque³. Some research studies have investigated the effects of injection timing and air swirl on the fuel stratification, combustion, and emissions formation of GDI-HCCI engines²³. The results show that these parameters can influence the combustion stability, efficiency, and emissions of NOx, CO, HC, and PM in different ways.
In summary, HCCI and GDI are two technologies that enhance engine efficiency and reduce emissions in modern automotive engines by using different combustion modes and fuel injection systems. They can also be combined to create a more flexible and adaptable combustion system that can optimize the performance under different operating conditions.
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Hi everyone,
I recently ran some compression tests for hydrogels and received data in form of force (N) and displacement (mm). I am new to this area so would really appreciate your help here. For starters, I know that I need to convert it into Stress (pascal) vs Strain data (mm/mm). However I am really confused how I need to represent my strain. I have converted the force into stress by dividing with area of upper plate but with strain I am lost between engineering strain ((Io-I)/I) and true strain (Ln(I/Io)). Would be obliged if you can kindly shed some light into it.
Thanks in advance
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Analyzing compressive test data from a rheometer for Young's modulus involves several steps:
Data Preparation: Ensure you have collected accurate and consistent data from the rheometer. The data should include stress and strain measurements obtained during the compressive test.
Stress-Strain Curve: Plot the stress (force applied) against strain (deformation) to create a stress-strain curve. This curve provides insights into the material's behavior under compression.
Linear Elastic Region Identification: In the stress-strain curve, identify the linear elastic region where the material behaves elastically. This is typically the initial part of the curve, before any significant plastic deformation occurs.
Young's Modulus Calculation: Young's modulus (E) represents the stiffness of a material and is calculated using the formula:
E = Stress / Strain
In the linear elastic region, stress is directly proportional to strain. Calculate the slope of the linear portion of the stress-strain curve to determine Young's modulus. The slope can be calculated as:
Slope = ΔStress / ΔStrain
Young's modulus is then the reciprocal of the slope.
Data Fitting: You can also use data fitting techniques to extract Young's modulus. Fit the linear portion of the stress-strain curve to a linear equation (y = mx + b), where 'm' is the slope (Young's modulus).
Units: Ensure that the units of stress and strain are consistent (e.g., stress in Pascals and strain as a dimensionless ratio or percentage) to obtain the correct unit for Young's modulus (Pascals or N/m²).
Report: Present the calculated Young's modulus along with the method used for analysis, any assumptions made, and the range of strains over which the calculation was performed.
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Hello everyone,
Attached you will find these pictures where i realized the job (compression only surface displacement) in Ansys Software. Everything is going well but in Abaqus CAE model, i can't find it.
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I didn't have more knowledge in mechanical.but iam having knowledge in xontrol syatem and also in electrical
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Good day to everyone,
I have constructed scaffolding. For this purpose, I attempted to perform a compression simulation based on experimental compression data, as we are required to input certain properties into a simulation physics.
My question is how can I determine the simulated young modulus and compare it to the experimentally obtained young modulus, even though I am providing the experimental data as input?
Also, I wish to determine the anisotropy properties of the designed scaffold as well.
Thank you in advance.
---------------------------------
Regards
Rajkumar
IIT Kanpur, India
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Thank you Dr. Kristaq Hazizi for your insightful suggestions. You have cleared my doubt regarding the same. But still I have one confusion from point no. 2 (from upper most paragraph). While extracting the simulated young modulus from stress strain curve during the simulation, would it be same as the experimental one have ?
It is because, we are giving the experimental initial yield point as the input into the model, so curve will start to turned from that point only and will gave the same linear elastic region that the experimental one have. So I think young modulus will come same, then how can we compare them ?
Regarding the anisotropy, I fully understand it.
Thank you once again for giving your valuable time.
---------------------------------
Regards
Rajkumar
IIT Kanpur, India
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How to do quasi static compression test (2mm/min) in ansys Workbench? Please help me
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5. To set the displacement of the loading step to 2mm/min, click on the "Displacement" tab and enter "2" in the "Value" field.
Hello Sir
Rana Hamza Shakil
As you have mentioned displacement 2 that means total displacement is two, here, i am unable to figure out how the rate of displacement has been defined in your solution. please let me know.
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Hi,
I made some alginate discs and calculated their rheological properties, however, after much searching I found this equation which is below and lets me calculate the Young Modulus. However, I wanted to make sure their are not any other ways of calculating it from frequency sweeps gained from a rheometer. Is there a better way.
G = E / [2(1 + ν)]
where: E — Modulus of elasticity in tension or compression, also known as Young's modulus; ν — Poisson's ratio, another material constant; and. G — shear modulus (also known as modulus of rigidity).
Any help you could give would appreciated.
Best wishes,
Abdullah
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Check out the full lame constant table. An example is below but there are many sources
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I was trying to create a FEM model of an LVI and CAI experiment. For the CAI simulation, the load displacement curve I obtained is way too stiff compared to the experimental result. The maximum compression load is already quite similar with the experiment. Is there parameters that I can change to reduce the compressive stiffness ?
The simulation model was created in the ABAQUS Explicit solver. The composite plate is divided into 16 layers of laminate and 15 layers of interfaces. Each layer of laminate and interface have thickness of 0.215 mm and 0.025 mm respectively. The laminate was meshed with SC8R and use the Hashin damage model. The interface layer is modelles using COH3D8 elements and the QUADS damage criterion and energy based Benzeggah damage evolution.
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To address your specific concern regarding the compressive stiffness in your FEM model of the LVI (Low-Velocity Impact) and CAI (Compression After Impact) experiment, here are some potential factors you can consider:
  1. Material modeling: Ensure that the material properties of your composite plate accurately represent the behavior of the actual material used in the experiment. The laminate layers and interface layers should be modeled with appropriate constitutive models that capture the material response under compression. It's crucial to validate the material properties by conducting material tests and comparing the results with the experimental data.
  2. Damage models: Evaluate the damage models used for the laminate layers and interface layers. The Hashin damage model for the laminate layers and the COH3D8 elements with the QUADS damage criterion and energy-based Benzeggah damage evolution for the interface layers are a good starting point. However, you may need to adjust the damage parameters to better match the experimental results. Calibrating the damage initiation and evolution parameters based on experimental data can help improve the accuracy of the simulation.
  3. Interface modeling: Pay attention to the modeling of the interfaces between the laminate layers. The interface properties, such as strength, friction, and bonding, can significantly influence the compressive stiffness. Make sure to consider the interface behavior under compression and adjust the interface properties accordingly.
  4. Mesh density and refinement: Check the mesh density and refinement in your model. In regions where compressive deformations are expected, ensure that the mesh is fine enough to capture the localized responses accurately. Adequate mesh refinement can help improve the accuracy of the simulation results.
  5. Boundary conditions: Confirm that the boundary conditions in your simulation are consistent with the experimental setup. The applied loads, constraints, and displacement conditions should match those used in the LVI and CAI experiments. Small variations in boundary conditions can lead to significant differences in the results.
  6. Calibration and validation: It's essential to calibrate and validate your FEM model against experimental data. Compare the load-displacement curves obtained from the simulation with the experimental results at different stages of the LVI and CAI experiments. This iterative process can help identify discrepancies and guide adjustments in the model parameters and setup.
Remember that accurately simulating LVI and CAI experiments can be challenging due to the complexity of the material behavior and the dynamic nature of the impact and compression. It may require multiple iterations and adjustments to achieve a closer match between the simulation and experimental results.
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Imagining you have 1 m3 cubed container made out of steel and inside the container is 5 bar. What will the force be felt on the container if the pressure inside suddenly drops to 1 bar? Temperature can be omitted if needed.
Trying to design a yield limit for pressure-drop resistant materials through tensile/compressive measurements.
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The force acting on the walls of the container due to the pressure inside can be calculated using the formula:
F = P * A
where:
  • F is the force,
  • P is the pressure, and
  • A is the area.
Given a cubical container with an edge length of 1 m, one side's surface area (A) is 1 m^2. Since a cube has six faces, the total surface area is 6 m^2.
When the pressure inside the container drops from 5 bar to 1 bar, the pressure change (ΔP) is -4 bar. Converting this to pascals (since 1 bar equals 100,000 Pa), the pressure change is -400,000 Pa or -400,000 N/m^2.
So, the total force change experienced by the walls of the container is:
ΔF = ΔP * A ΔF = -400,000 N/m^2 * 6 m^2 ΔF = -2,400,000 N
The negative sign indicates that the force has decreased due to the pressure drop.
The stress on the walls of the container is the force divided by the area over which the force is distributed. In this case, the change in stress on the walls is equal to the change in pressure because the area cancels out:
Δσ = ΔF / A Δσ = -400,000 N/m^2
This means the stress on the walls of the container decreases by 400,000 N/m^2 due to the pressure drop. This stress is what your material must be able to withstand. The yield limit of your material, obtained through tensile or compressive tests, should be higher than this value to prevent deformation.
Please note that this calculation assumes that the stress is evenly distributed over the walls of the container, and ignores other potential factors such as strain hardening, material defects, or localized stresses due to design features (like welds, or changes in thickness). A more detailed analysis using mechanical engineering and material science principles would be needed for a thorough safety assessment.
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Please let me know.
Regards,
Saiyad
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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:
  1. Homogeneity and Isotropy: Most conventional material models in ABAQUS assume that the material is homogeneous (properties are the same at all points) and isotropic (properties are the same in all directions). If your 3D-printed part does not meet these assumptions, you might need to consider a more advanced material model or modify the material properties based on the expected loading conditions.
  2. Experimental Data: Ideally, the material properties should be based on experimental data from tests conducted on samples produced under the same conditions as the final part. If you use data from the literature or the material supplier, you should ensure that it applies to your specific 3D printing conditions.
  3. Tensile vs Compression Properties: Some materials, especially composites and certain metals, can exhibit different properties under tension and compression. If your part is expected to experience both types of loading, you might need to include both data sets in your material model.
  4. Strain Rate Effects: The material properties can be rate-dependent if the loading conditions involve high strain rates (e.g., impact or blast loading). In this case, you must use a material model that includes strain rate effects.
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.
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Myself Nekin Joshua R. I like to do Fatigue compression test on 3D printed Polymer based Structure.
What is the ASTM Standard for Fatigue Compression test on 3D printed Polymer based Honeycomb structure?
What is the Specimen Size?
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you would be best using ASTM D638-22for this test
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Binary sequences 1100100101
Symbolized by binary P(0)=1/2 P(1)=1/2 H(x)=-0.5*log2(0.5)-0.5*log2(0.5)=-1
Symbolized by quaternions
P(11)=1/5 P(00)=1/5 P(10)=1/5 P(01)=2/5 H(x)=-1/5*log2(1/5)*3-2/5*log2(2/5)=-1.9219
...
Is there a problem with my understanding?
If not ,which result is information entropy?
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Firstly, the calculated entropy in both cases is positive (entropy is always non-negative).
Secondly, the probability of each bit/symbol is calculated over a large number of occurrences.
Thirdly, entropy = 1 for 'Symbolized by binary' case means the entropy is maximum because each bit is equi-probable. On the other hand, for the 'symbolized by quaternions' case, the entropy < 2 because the calculations considers that all states are not equi-probable.
I hope it helps.
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i want to cite this article on research gate.
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Hello,
you can get to the journal's webpage via the doi of the article easily. You can find 'cite article' right below the title and authors. If you click this, you'll get a suggestion of how to cite this article (Andena L, Caimmi F, Leonardi L, Nacucchi M, De Pascalis F. Compression of polystyrene and polypropylene foams for energy absorption applications: A combined mechanical and microstructural study. Journal of Cellular Plastics. 2019;55(1):49-72. doi:10.1177/0021955X18806794).
However, different journals have different ways to cite. Thus you might adapt the citation accordingly to the journal's guidelines.
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The cell cycle of my MCF10a cells sometimes looks "compressed" with no clearly distinct phases. Other times I get a cell cycle that looks perfectly fine with clear phases and I can´t find a reason why I get such different results. I use DAPI to stain the cells, but I already checked the stain and the protocol and they are alright. So i think it might not be an issue with the staining itself but propably with the cells or the culture conditions or something else?
Has anyone had similar problems or has an idea what the problem could be?
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Thanks for your suggestions.
Yes I always use the same flowcytometer with the same settings.
I also tried out staining with PI but the cell cycle looked the same (bad) as with DAPI.
It´s a good point, I´ll attach two histograms with one "good" and one "bad" example. Maype that will clarify what my problem is.
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I am currently working on my thesis in Retrofitting of soft story. At first step i am trying to validate a experimental test. There i need to model a bracing with gap in it. The bracing should act only in compression after the gap is closed and free in tension. For creating simplified model i tried to create compression only element with uniaxial non linear elasticity model available for steel in Diana where i gave input to stress-strain diagram with very small value in tension and in compression, i gave nearly 0 value upto strain when gap closes and after that normal stress strain value of steel. I got the hysterisis result where there is increases in lateral resistance as compared to test result. how an i fix this? Is there any approach to model gap element? i tried contact analysis too but could not make it out.I have attached hysteresis result of Experiment and Diana Modeling. The bracing should start working after 1% drift.
Thank you.
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Add an interface element with your manual stiffness properties almost 0 till a certain displacement and then increase the stiffness when the gap is closed.
drop me an email if you need more info.
a.vandenbos_NLyseConsultants.com
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I have a word file and want to sent via an email but I am unable to compress it without changing the format. I need it to be in word as it has track changes responses.
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Compess it wice.
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Hello everyone,
I am developing a FE model with cohesive elements in ABAQUS 6.13-1 . As mentioned in the "Linear elastic traction-separation behavior" paragraph of the Abaqus Documentation:
a compression factor can be set for cohesive elements with uncoupled traction-separation behavior, so that their compressive stiffness is equal to the specified factor times the tensile stiffness. The only way to define the compression factor is to comprise the following command in the input file of the model:
*ELASTIC, TYPE=TRACTION, COMPRESSION FACTOR=f
and replace f with the desired value. (It cannot be specified in Abaqus/CAE)
However, when I submit the job input file, the Analysis Input File Processor aborts the job with the error shown in the attached image.
Has anybody encountered the same problem?
Should I type this command in another way to make it acceptable?
Maybe it could be attributed to my version of ABAQUS and a more recent version is required to recognise this command?
P.S. The analysis runs and the results are exportable without any problem when the compression factor definition is not included in the input file. Also, the names of the job and the input file have knowingly been removed from the attached image.
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Hello,
I want to consider compressive behavior for cohesive interaction, did you solve your problem?
How do I add a compressive behavior for cohesive contact?
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To generate a spectrum from compressed audio file, one need to decompress the audio file, perform STFT to get a spectrogram then optionally enhance it to become a mel-spectrogram, MFCC etc. Any variant seem to work as the performance don't differ much. Then the spectrogram used as inputs to a convolutional neural network.
IIRC the Ogg Vorbis file format saves the filter bank coefficient as MDCT.
Can we skip the decompression and STFT part and just use the MDCT coefficient somehow?
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Maybe the question was not clear. I specifically mentioned Ogg Vorbis files or similar where psychoacoustic, critical bands and filter banks were applied during compression.
I read that the trick won't work with MP3.
Lossless algorithm e.g. FLAC likely don't perform any filtering before compression so that's out too.
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The article has submited IEEE-TIT. Preprint manuscript is Post Shannon Information Theory.You can find it on this website. Please give a fair review.Thank you.
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Anyone can evaluate it.English is not my native language, so I hope there is no ambiguity.
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Hi all,
I prepared a batch of 40-mm cubic UHPC samples for the compressive test. However, I got a strange failure pattern after the 28-day compressive test. As you can see from my attached photo, instead of the typical failure pattern, the sample broke into three triangular pieces. Could you tell me what are the possible reasons for such failure pattern?
Thank you very much!
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Brittle materials in compression fail by shear, which may be explained by the Mohr-Coulomb failure theory. The angle of the fracture plane vs load direction gives the friction coefficient on that plane. Zero friction gives the fracture angle 45 degrees, while higher angles, as in your case, corresponds to non-zero friction. If you get three pieces (two equally inclined fracture planes) or two (one failure plane) is entirely random.
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Good day,
I'm trying to numerically simulate the compression of a polyurethane foam shock absorber for car.
I use ABACUS/Explicit
The constants for the equation of state were obtained from experimental data for compression, at a "characteristic" (small) compression rate using the MCalibration program.
While resolving, an error message was received:
The ratio of deformation speed to wave speed exceeds 1.0000 in at least one element.
One of the possible causes of the error is the incorrect calculation of the constants for the polyurethane foam equation of state.
*** using the "standard" equation of foam, which is in ABAQUS
I am ready to send the model and experimental data to anyone who has the desire and opportunity to devote time to this task.
Previously, I tried to simulate this task with ABAQUS/Standart and with ANSYS Workbench
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Good evening,
I was able to solve these problems with the help of the program, LS-DYNA.
I calculate and calibrate the constants for the used equations of state using the MСalibration program.
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I am trying to use EEG data from GigadB repository. The data is archived and compressed in tar.gz file. The data is in .mat format: memory size of compressed file is around 226 GB. I used a download manager to download the file and extracted using 7zip application. When the extracted.mat files are opened in matlab, I get error message as, " file corrupted" sometimes else cannot read the first line. Is the error due to the multiple connection in download manager. The link to the data is:https://ftp.cngb.org/pub/gigadb/pub/10.5524/100001_101000/100788/EEG_ConvertedData.tar.gz
I wish to know how to successfully download and extract it
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To download and extract a tar.gz file, you can follow these steps:
  1. Open the terminal on your computer.
  2. Navigate to the directory where you want to download and extract the file.
  3. Use the wget command to download the tar.gz file. For example, if the file URL is "http://example.com/file.tar.gz", you would run: wget http://example.com/file.tar.gz
  4. Once the download is complete, use the tar command to extract the file. For example, if the file name is "file.tar.gz", you would run: tar -xzf file.tar.gz
  5. This will extract the contents of the tar.gz file into a new directory in the current directory.
Note: The x flag is used to extract the files, z is used to decompress the gzipped file, and f is used to specify the filename.
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I have Compressive load, Compressive extension, Compressive strain, Compressive stress values. How to calculate Energy absorption of compression test.
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Energy is normally calculated from stress and strain curve and the area under the curves gives us the energy absorbed.
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LAND SUBSIDENCE
1.  Feasible to apply the same concept of ‘consolidation’ (associated with the drainage of a clay layer) - used in soil mechanics - for assessing the compaction - associated with a petroleum reservoir?
If yes, then, would it remain feasible to ensure that the ‘reservoir fluid compressibility’ would remain much smaller than the ‘reservoir rock compressibility’ associated with the reservoir?
Also, how to deduce the ‘fluid density’ associated with the estimation of ‘coefficient of consolidation’ for an oil-water system?  
2.  Whether the ‘centers of subsidence’ really coincide with the ‘centers of production wells’ associated with an oil field?
3.  Despite the depositional environments @ various subsidence sites in the vicinity of a wellbore at the surface level remains varied, could we still expect a thick sequence of either an unconsolidated or poorly-consolidated sediments (which essentially forms an interbedded permeable-semipermeable system) within the reservoir thickness of a petroleum reservoir during hydrocarbon production?
What will happen if a relatively large fraction of the reservoir thickness (or width) consists of highly-compressible clay in the context of land subsidence?
Even otherwise, focusing on reservoir seals, if the seal consists of significant clay with swelling properties, then, won’t the ‘total potential compaction of reservoir seal’ remain to be greater than the ‘compaction of the reservoir’ (assuming the compressibility of clay to remain a couple of orders of magnitude greater than the compressibility of the sand)?
If (a) the intrinsic permeability of clay remains to be several orders of magnitude less than the reservoir permeability; and also, if (b) the compaction in reservoir results from the drainage of both the brine and hydrocarbons, while the compaction from seal remains associated only with the brine drainage; then, how do we take into the simultaneous compaction of both seal and the reservoir?
4.  Can we distinguish ‘seal compaction’ resulting from ‘seal compressibility’ and its associated ‘changes in effective stress in seal’ – from that of ‘reservoir compaction’?
5.  To what extent, ‘water flooding’ would be able to arrest ‘land subsidence’ by means of ‘enhancing the potentiometric heads in the reservoirs’ causing ‘an expansion of reservoir’?
6.  Feasible to learn the essence of ‘mitigating the rate of subsidence’ from ‘Wilmington Oil Field’ (located in Long Beach, California) case study?
7.  Feasible to correlate ‘hydrologic model’ (potentiometric-surfaces/drawdowns at the basin scale) with the ‘subsidence model’ associated with a petroleum reservoir?
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Not necessarily - compaction and induced subsidence will in principle be controlled by the combination of pressure depletion, reservoir thickness and reservoir consolidation. These parameters do not necessarily coincide with the centre of surface production. This es especially the case if field development is with deviated or horizontal wells.
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I am trying to build an x-ray in-situ compression device and would like to use an x-ray transparent metal so that in-situ imaging would be possible.
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the the x-ray attenuation goes down with the atomic number Z;
in case of the photo-electric part of the attenuation by Z3 *).
So, from your knowledge,
a) please select some candidates with high yield strength, which might fit your mechanical needs and
b) choose the one with the lowest atomic number.
To my opinion, Ti (Z = 22) is such a candidate.
Best regards
G.M.
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I have a image set and all images has similar background except the object in the image if any. Is there any techniques in computer vision to compress all images by using the similarity feature?
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Compression-based similarity measures employ in an unusual way general off-the-shelf compressors, by exploiting them to estimate the amount of information shared by any two objects. Such techniques, of which the most well-known is the Normalized Compression Distance (NCD).
Regards,
Shafagat
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I have a Eminence N151M 8 ohm compression driver with me and eminence alpha 2 8 ohm speaker. I wanted to use these both components together to deliver a high frequency loud sound. So how can I coonect these driver and speaker with each other? Please let me know the solution. And if anyone having user mannual for both the products please do share it.
Thank you....
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Each material is more resistant to a certain force. Concrete and above all prestressed concrete withstands compressive stress. In tensile bending torsion and shear it has a problem. Reinforcing steel has super tensile strength. And we make these two materials work together so that the concrete receives the compression and the steel receives the tension. Great combination. Is it so or not? No, its not like that. Ideally, the steel and concrete would have exhausted their compressive and tensile strengths before they failed. But this does not happen. Both concrete and steel fail before they exhaust their strength. This is because during the bending of the body of the load-bearing elements, in addition to the compressive and tensile forces, another force, the shear force, appears on the interface where the concrete and steel are in contact. The concrete covering the steel having no resistance to the shear force breaks along the steel and their cooperation stops. Thus before the steel and concrete exhaust their tensile and compressive strengths, shearing cancels their strengths. This problem grows even more when the critical area of failure occurs at the ends of the load-bearing elements, because apart from the mentioned problem we also have the potential difference in adhesion. Another problem is that the cover concrete does not withstand bending and breaks leaving the steel reinforcement exposed so the bond is cancelled. The ideal would be if we could eliminate the bending of the beam and the shearing that occurs at the concrete-steel interface when the steel begins to stretch. Then only concrete and steel would exhaust 100% of their ultimate compressive and tensile strengths before failing. There is a solution? Yes there is a solution but it is rarely used. It's called, prestressing. Prestressing uses the steel to compress the concrete with the help of hydraulic pullers, and compaction systems at their ends. The compression in the concrete makes it capable of receiving the developing tensile forces. It reduces the bending of the trunk, thus also the deformation of the load-bearing element. It increases the effective cross-section because the compressive force is distributed throughout the cross-section, effectively eliminating the inert concrete cover. The main one is that prestressing has strong ductility and is considered elastic since it restores the structure (compression ratio) to its original position by tilting the developing cracks after a strong inelastic displacement of the structure. Now why they don't do this to the walls that are the cause of the distortion in the whole structure I don't know. If prestressing is applied at the ends of the longitudinal rigid walls and is combined with compaction in the foundation soil then the overturning moment and the bending moment and the shear failure of the cover concrete will be stopped and the response of the cross section will increase with respect to the other intersecting that of basis. Consider that a Φ/50mm cross-section steel lifts a two-story building into the air and we place 8000 kg of steel on the two-story building and have an earthquake problem due to shear failure.
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Interesting topic ........ Thanks dear Dr Ioannis Lymperis for sharing !!!
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Deformation waves not associated with earthquakes continuously pass over the surface of the Earth. These are waves with periods of 12, 24 hours and 14 days. Long waves are imperceptible to people, although they have an amplitude 10 times greater than seismic waves. In areas with a thin earth's crust, they usually do not provoke earthquakes (I do not consider mantle earthquakes). If the earth's crust is not subject to geodeformations, then they destroy it. After an earthquake, waves of geodeformation can provoke the collapse of buildings (before the earthquake, these territories were not deformed).
Video from INTERNET
Let's start the discussion.
I will quote information from my other discussion.
The earthquake in Turkey occurred on the date of the tide syzygy in the solid body of the Earth on February 6, 2023. On the dates of syzygy, the amplitude of geodeformations increases by no less than 20%. The first destructive earthquake occurred at 01:17 (M=7.8), the second at 10:24 (M=6.7). At this time, at the earthquake epicenter, the amplitude of the diurnal and semidiurnal tides in the solid body of the Earth reached positive extremes. In addition, due to the 14-day zonal tide in the solid body of the Earth, the conditions of stretching and compression of the Earth's crust were formed on the surface of the planet. The zonal tide in the solid body of the Earth is associated with the extrema of the angular velocity of the Earth's rotation. The data is available only for February 3. Attached the chart https://hpiers.obspm.fr/ . Stretch conditions on February 3 and February 10, 2023. On February 3, in accordance, rapid changes in the Earth's gravitational field on a planetary scale were recorded. Changes in the gravitational field recorded by our method, see satellite images https://meteologix.com/. Between the expansion phases, the compression phase is fixed. The compression occurred on February 6, 2023 and triggered an earthquake https://zn.ua/img/forall/u/14/8/photo_2023-02-06_15.16_.16_.jpeg . These are the facts of the formation of compression deformations on March 6. The scale is planetary.
Planetary-scale deformations (amplitude 30 cm) were blocked on February 6 in the epicentral zone of the future earthquake. The blocking of tidal waves in the solid body of the Earth is associated with the release of heat. In the atmosphere, the release of heat leads to a decrease in atmospheric pressure. Warm air weighs less. Look at the color map of atmospheric pressure and low pressure above the epicenter at the moment of maximum compression (map from Twitter https://twitter.com/BookofCrusty/status/1622643773900464128?t=Yy-KLEZn-FDuHvyIHh1y5w&s=09 ). The relapse occurred on February 20, 2023 after 14 days during the next cycle of the positive extremum of the angular velocity of the Earth's rotation associated with the repetition of the phase of the zonal tide in the solid body of the Earth.
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Thanks for your reply. Thank you for the data!
From it, it is clear that you have something to work with. This shows something else you write about, and you know exactly what I mean.
'These are waves with periods of 12, 24 hours and 14 days. '
'06 UTC min (-13 cm), 10 UTC max (0 cm), 16 UTC min (-14 cm), 22 max ( 22 cm).'[this should have been extended either the day before or the day after]
You have another value of max around pm.10 05.02.2023. or 07.02.2023 which does not correspond to 24 (12) hours, as the period is about 2-5% different.. This 2-5 % is not a negligible factor.
Regards,
Laszlo
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Good day to everyone,
I have designed a scaffold which is made up of a plastic material. I wanted to do a compression simulation for the same. I would like to know which model should I consider in my physics for this plastic-based scaffold.
Many thanks.
Regards
Rajkumar
IIT Kanpur, India
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I am running crystal plasticity simulation in Damask. I am carrying compression deformation on a 3d geometry having 300 number of grains. My final aim of deformation upto a final compression of 0.9 . I have achieved up to total compression of 0.3 without any convergence error.but beyond this deformation I am facing the problem of convergence in Damask. Solving this Issue previously Damask developer shared a paper about adaptive re-meshing. The paper is very informative and increased my knowledge about solving convergence issue in Damask. Basically they are using two methods for solving convergence issue in damask "The mesh replacement method and the mesh distortion control method" although i have understood the procedure which they follow for establishing the above two methods.Now i am trying to follow one of the above methods to solve my convergence issue But due to my limited information, I need guidance about how to re-mesh my deform geometry in order to get undistorted mesh. 1). is there any method available in damask to achieve this re-mesh geometry? 2). how can we re-mesh our deform geometry? 3).Can we achieve mesh distortion control method by only changing the input loading file, if it is then how? any help regarding this will be appreciated
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Dear jiazhen he
I was facing the problem of large plastic deformation and according to damask developer that they will implement remeshing technique in the upcoming new version of damask but still it has not been launched ,may be it take a little bit longer time for launching. My problem has not solved yet I have done compression upto 60 percent using phenomenological crystal plasticity but further compression does not achieved. It means I have not found out proper solution till now.
Thank you
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Which formulae are best used for calculating q, w, ∆U and ∆H for a nitrogen gas with a mass of 1.12 g that has been compressed adiabatically in the temperature range of 100 to 400 K from 400 torr and 1000 cm3 to final volume of 250 cm3 with Cp,m = 29.1 J/K/mol?
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Use the formulas provided in our Student Dictionary
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Many failure theories belong to different materials, however, is there a specific failure criterion for lattice or cellular structures under compression or tension?
Is it enough to select this failure criteria based on the class of material? or design of the structure is also an important factor to consider?
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Selection of failure criteria doesn't depend only on the class of material, design of the structure needs to be considered too. For example, Euler buckling is particularly relevant for slender structures with a high aspect ratio, while Tsai-Hill is more appropriate for composite structures with complex laminate configurations. You should also check Von Mises yield, Puck, Hashin criterions. :)
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Given a multi-layer (say 10-12) neural network, are there standard techniques to compress it to a single layer or 2 layer NN ?
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I'm working in a 2D model where a circle is compressed inside a groove that is pushed (see picture below). There needs to be 2 contacts declared: one between the groove and the circle; and the other one between the circle and the rectangle that is the one compressing it.
I have tried declaring a General Contact as the rectangle and the groove are the same material, but I get the following two warnings in the .msg file:
***WARNING: THERE ARE 2 UNCONNECTED REGIONS IN THE MODEL.
***WARNING: SOLVER PROBLEM. NUMERICAL SINGULARITY WHEN PROCESSING NODE C4.348 D.O.F. 2 RATIO = 250.029E+12 .
If I declare 2 surface-to-surface contacts for each one I get the same two warnings. The thing is, I don't know which contact is not detecting. Can someone help me?
Thanks :)
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Hi Julia,
Did you check the job diagnostics section?
results- tools-job diagnostics
click on the error and it shows the location of it.
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Two equal and opposite forces balance This is known. So if we apply corresponding compressive forces to the tensile forces, they will balance. This is the prestressing mechanism that static civil engineers use to achieve large bridge spans, so large that this would be impossible to achieve with simple linear reinforcement and the cooperation mechanism of concrete and steel, that of relevance that they use in construction. I will try to explain to you the reason.
As a span increases, the bending loads increase, so the tension and compression in the cross-section also increase. To receive the compression, we increase the concrete, that is, we increase the cross-section height. When I increase the dimensions of the cross-section, the loads also increase. To receive the loads we also increase the steel reinforcement. Steel has superior tensile strength, but to receive the tension it needs the help of concrete. That is, the concrete must have the ability to hold the steel inside it when it pulls from the right and left so that the steel does not slip through the concrete and their cooperation is broken. This pulling force applied at the interface of the two materials of steel and concrete is called shear.
The concrete not being able to withstand the shear caused by the pull of the steel breaks, their cooperation is lost and the bridge falls. As the span of the bridge increases, so we increase its mass and its loads, but without having the possibility to increase above a limit the strength of the concrete coating in terms of shearing. This is why we cannot construct large spans of 50 meters in bridges with the simple linear reinforcement that we construct in buildings. Concrete with the simple reinforcement method of this relevance has a problem because it cannot withstand the shear caused by the high tensile strength of the steel. Concrete, however, has superior strength in receiving the torsional force. So what do we do? We apply large compressive forces to the cross-section to neutralize the tensile forces and balance the forces and this means that along with the tensile forces we have also neutralized the shear forces at the interface of the concrete and the steel, since we have neutralized the tension that causes them.
In large earthquakes the seismic loads are three times the static loads. The shear failure of the concrete is given by the tripling of the stresses In order for this not to happen, the static civil engineers must apply prestressing to the walls and not only place reinforcement of the relevance With only two prestressing tendons on the slopes of the walls, they would replace 80% of the linear steel reinforcement, reduce the concrete cross-sections and increase the earthquake resistance of the structure. The other crazy thing that the statics do is that they try to stop the large moment of the overturning of the walls, which comes from the inertia of the vertical slabs, with the cross-sections of the slabs, without drawing external balance forces from the ground. If the prestressing tendon we just mentioned were anchored to the ground and not to the base, then all the forces of the overturning moments would be diverted into the ground and the cross-sections of the slabs would not break.
The shear base cuts the cross-sections of the walls near the base, and its force is equal to the magnitude of the acceleration, multiplied by the mass of the structure. This is also the power of inertia of construction. The cross-section of the wall increases its strength in relation to the shear base by 40% when we apply compression to the cross-section of 70% of the breaking point of the concrete. Basic and well-known engineering data which, for some unknown reason, do not apply to the statics of earthquake-resistant structures. Still compacting with the ground ensures a strong foundation.
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Thank you dear Dr Ioannis Lymperis for sharing this interesting question !!!!
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3D printers use various polymer materials and metals. PLA, ABS, TPU, PETG, Peek, Ultem, nylon, Polyamide12, SS316, Ti-6Al-4V, Alsi10mg are some of the 3D printing materials. I need to know the Energy Absorption, Specific energy absorption, Strength, Stiffness of those materials.
Please help me to find the same.
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Below is a table (generated by chatGPT) showing the Specific Energy Absorption, Strength, and Stiffness for each of the materials you listed.
Note: The specific energy absorption, strength, and stiffness values given above are typical values and may vary slightly depending on the manufacturing process, dimensions, and specific type of material.
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Hi,
I'm conducting compressive mechanical tests on jello material on a rheometer HR20 by TA Instruments. The cross hatched top plate is 8mm in diameter and circular in shape.
I'm testing hockey puck shaped jello samples ( 8mm in diameter, 2mm in height) and calculated the area under the curve given by the software.
1. I'm getting results as Pa %. Don't the numbers seem too high for a small soft sample? (I triple checked my input dimensions and down speed).
2. I generated another graph from the same data with um on the x axis instead of %. The numbers make more sense this way but I need help equating between this value and the one from the first graph(as they should be the same when manipulating units).
3 To my understanding, area under the curve is toughness which should be provided in units as J/mm3. Does anyone know how to convert the values from the previous 2 questions to J/mm3?
Please help if you understand this problem, it is greatly appreciated!
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Regarding the 3rd question, the area under curve represents toughness (amount of work done /unit volume) of material specimen, In you case it is 96.1kPa %. The tensile strength is however, ~580.1 kPa = ~ 0.6 MPa. and the Youngs (elastic) modulus is ~ (580.1 /95.5)*(100/1000) = 0.61MPa
However, i am not sure if there are direct conversion units from Pa% to J/mm^3 .
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I need to know about the ASTM standard Dimension for Quasi Static Compression testing and tensile testing. And what are all the other standards available to test our fabricated specimen.
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  1. ASTM D695: Standard Test Method for Compressive Properties of Rigid Plastics. This standard covers the determination of compressive properties of rigid plastics using a uniaxial compressive test.
  2. ASTM D638: Standard Test Method for Tensile Properties of Plastics. This standard covers the determination of tensile properties of plastics using a uniaxial tensile test.
  3. ASTM D7012: Standard Test Method for Compressive Properties of Polymer Matrix Composite Materials with Unsupported Gage Section by Shear Loading. This standard covers the determination of compressive properties of polymer matrix composite materials using a shear loading test.
  4. ASTM D7249: Standard Test Method for Compressive Properties of Polymer Matrix Composite Materials with Unsupported Gage Section by Flexure (Load in Tension)
  5. ASTM D3039: Standard Test Method for Tensile Properties of Polymer Matrix Composite Materials. This standard covers the determination of tensile properties of polymer matrix composite materials using a uniaxial tensile test.
  6. ASTM D3410: Standard Test Method for Compressive Properties of Unreinforced and Reinforced Plastics and Electrical Insulating Materials.
  7. ASTM D3518: Standard Test Method for In-Plane Shear Response of Polymer Matrix Composite Materials by Tensile Test of a ±45° Laminate.
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I need a dataset of uncompressed videos for a forensic task if any member has the dataset of uncompressed videos or Dataset of compressed videos with known frame sequence kindly share with me.
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Sahib Khan There are a number of publicly available video datasets that may be relevant for your forensic work. Among the most popular datasets are:
The Video DNA collection contains uncompressed and compressed movies with known frame sequences. It may be used for video content identification as well as video forensics.
The VGG Face dataset contains a huge number of face videos, some of which have been compressed. Uncompressed and compressed movies with known frame sequences are included in the collection.
The Youtube-8M dataset contains millions of video URLs as well as annotations for each video. This collection includes both compressed and uncompressed videos.
The UCF101 dataset contains a wide range of behaviors captured in films, such as daily activities and sports. This collection includes both compressed and uncompressed videos.
These are just a few examples; there are many additional datasets available on the internet depending on the task and the source from which it was acquired.
You should also look for datasets that are specialized to your field of study or application, since there may be domain-specific datasets that are more relevant to your goal.
You might also look for datasets on famous data-sharing sites like Kaggle, which has a big amount of datasets linked to many study disciplines including computer vision and video analysis.
Remember that certain datasets may have legal or copyright restrictions on their usage, so read and understand any terms and conditions before utilizing the dataset in your work.
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I'm trying to simulate nonlinear compressive buckling of a material. However, it's not buckling as I would (theoretically) expect for lengths crossing the buckling threshold. It would just compress and fail at the failure strength/strain as specified in MAT024 - Piecewise Linear Plasticity. For further reference, I am using solid elements and it's a pin-pin configuration.
Theoretically, I'm thinking that a small lateral load/perturbation is needed to trigger the buckling and/or build the meshing with an out-of-straightness. I'm not an expert in FEA/LSDYNA, so any help with choosing the right keywords to get my specimen to buckle is appreciated.
I've already got the specimen to buckle elastically (eigenvalue), but struggling with nonlinear buckling.
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It is possible that your simulation is not experiencing buckling because the material is behaving plastically before reaching the buckling threshold. In order to achieve buckling, you may need to increase the stiffness of the material or decrease the load applied to the specimen.
If you want to introduce a lateral load or perturbation to trigger buckling, you can do so by applying an initial geometric imperfection to the specimen. This can be done in LSDYNA by using the *INITIAL_IMPERFECTION keyword and specifying the magnitude and distribution of the imperfection.
You may also want to consider using an element type that is more suitable for simulating buckling behavior, such as a shell element or a reduced integration element.
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I want to perform compression and tensile test for a hydrogel sample for biomedical application. What should be the dimensions of the sample? Can anyone provide ASTM protocol for compression testing?
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The dimensions of the sample depend on the size of your testing machine and the type of test you want to perform. In general, the sample should be large enough to fit securely in the testing machine and allow for accurate measurement of deformations, but small enough to be representative of the material as a whole. Some guidelines for sample size are provided in ASTM D638, Standard Test Method for Tensile Properties of Plastics, and ASTM D695, Standard Test Method for Compressive Properties of Rigid Plastics.
For compression testing of a hydrogel sample, you can use the protocol outlined in ASTM D695. This standard covers the determination of compressive properties of rigid plastics using a compression testing machine. It includes provisions for testing specimens of various sizes, including Type I specimens with a 50 mm diameter and a thickness between 2.5 mm and 10 mm, and Type II specimens with a thickness between 10 mm and 50 mm.
The test procedure involves preparing the specimen, aligning it in the testing machine, and applying a compressive force at a specified rate until the specimen fractures or reaches a specified deflection. The compressive strength, modulus of elasticity, and strain at yield or at maximum load can be determined from the results of the test.
I hope this helps. Let me know if you have any additional questions.
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I'm doing a compression test on four self-reinforced composites
fibre/ matrix
1- PET / PET
2- PLA / PLA
3- CARBON / PET
4- GLASS / PET
fabric style 2x2 twill weave woven
I need the required properties to add them in Ansys library for analysing
thanks all
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To add a new composite material property that is not in the ANSYS library, you can follow the steps outlined below:
  1. Open ANSYS and create a new model.
  2. Go to the "Material Properties" tab in the model tree.
  3. Right-click on "Materials" and select "Add Material" from the menu.
  4. In the "Add Material" dialog box, select "Composite" as the material type.
  5. Enter a name for the composite material and click "OK".
  6. In the "Composite Material Properties" dialog box, select the type of composite material you want to define (e.g. fiber-reinforced composite, matrix-dominated composite, etc.).
  7. Enter the material properties for the fibers and matrix material, as well as any interactions or interfaces between these components. You can also specify the volume fraction and orientation of the fibers within the matrix.
  8. Click "Apply" to save the composite material properties and close the dialog box.
By following these steps, you should be able to add a new composite material property to the ANSYS library and use it in your model. It may be helpful to review the ANSYS documentation and examples to gain a deeper understanding of the specific tools and settings that are available for defining composite materials.
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Need a turbulence generator for generating the initial velocity field for direct numerical simulation of decaying compressible isotropic turbulence.
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I have data obtained from compression test. how to calculate young modulus from a compression test (stress-strain curve) with nonlinear elastic region?
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Young's modulus of elasticity is a material constant for a linear elastic material. I can find no references in my office library to Young's modulus for a nonlinear elastic material.
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In the 1st law of thermodynamics, the work is taken negative under the compression of gaseous atoms. If we take ‘+g’ of body falling from the height then why not we take positive work of gaseous atoms when leaving the original state to meet with compression in a container at ground surface. The work is negative when the compressed gaseous atoms perform chemical activity to restore the original state. (Thus, the work in solid atoms should be taken negative when converting into re-crystallization/liquid state.)
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Please check the Final copy of article DOI: 10.26434/chemrxiv-2022-m6qhd-v10
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Should I use openfoam for direct numerical simulation of compressible turbulence (decaying compressible isotropic turbulence)?
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Samuel Oyefusi Thanks for your suggestion.
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I am doing a comparative study of different pulse stretching and compressing techniques which are used in the Chirped Pulse Amplification Systems. On what all basis can we do a comaparison of different techniques? Which is the best method to the comparative study?
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The stretchers and compressors should introduce dispersion but little other distortions to laser pulses.
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I need to consider the deformation of the previous model and the stress-strain distribution, so I exported the deformed parts of the previous model, as well as the stress strain, but after setting the initial state, the next compression cannot be performed, and it shows that it cannot converge, but it can run successfully without setting the initial state.
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Dear Nils Wagner,
Thank you for your response!
The first file below is a simple stamping, and the second file is the file I imported the deformed plate after stamping for compression. At present, due to the initial state setup problems, I just set up a stress field, which can run successfully.
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I am trying to establish contact between two newly generated surface after failure in Implicit. For example, i have applied enough tensile force to break the part into two pieces and then compressed two piece to examine is there any contact between the newly generated surfaces. As you can see surfaces simply penetrate into each other without any resistance even though i have defined a general contact with All*self contact domain. Is there any way to be able to define contact in this condition? Your help is highly appreciated.
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To select all the internal elements of the slave surface; choose the surface type as 'Node Region' then select the geometry set instead of a surface which will select all the nodes in the whole body. See the vedio tutorial: https://youtu.be/uC6stySfCPI
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Since timber material exhibits different behaviour in tension and compression, it fails in a ductile manner when the compression load is applied and it behaves as a brittle material when subjected to a tensile load. Most existing models for anisotropic materials are derived based on Hill’s criterion, which does not distinguish between compressive and tensile strengths. So I'm a little perplexed as to which model would be best for the timber non-linear analysis.
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In general wood does not behave non linear as there are no non linear effects seen in the bodu vibration of musical insturments made of wood. The non linar part there is the bowed string.
Any material can become non linear a very large amplitudes and/or strong excitation. Maybe the effects kick in earlier for low frequency vibrations e.g. In bridges or similar.
However, in general wood does behave linar in the acoustic and vibrations meaning of the issue.
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Dear Reader,
I am trying to perform Rietveld refinement with irf function for crystalline nanoparticles. During the refinemnt, I did not get results for the volume and compression shown in the Fullprof microphone file. Why does this happen?
Please see attached sample file .
Best regards,
rafai hadjira
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The attached image does not give any hint, it is the standard text introducing the content of the *.mic file. It would be better to post both the *.pcr and your *.irf file.
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I am working with an energetic material. using a classical forcefield how can I calculate isothermal compressibility by volume fluctuation formula, and coefficient of thermal expansion by the enthaply-volume fluctuation formula for a solid in LAMMPS?
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I think there is no direct keyword to compute these thermodynamic properties in LAMMPS.
In NPT ensemble, you need to calculate volume fluctuation (for isothermal compressibility) and cross-correlations of enthalpy and volume (for thermal expansion coefficient). (see Allen and Tildesley, Computer Simulation of Liquids)
using thermo_style command, like
thermo_style custom step temp pe press vol enthalpy,
you will be able to print instantaneous values in log file during simulation. After that, a little bit of post-processing will be needed to get the desired property.
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I have modelled solid slab and I have assigned bottom face of slab as Elastic support but that elastic support is needed to be modelled for compression only spring.
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The option is available under workbench.
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lateral slenderness ratio of compression flange is defined as l/ry where l is the span of the beam and ry is the radius of gyration of compression flange in y direction. can anyone explain me how to find this ratio if the beam dimensions are as follows.
l=span=960 mm
thickness of compression flange= 8mm
width of the beam =125 mm
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The ratio of the effective length to the appropriate radius of gyration is the value
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The normal procedure to make Co2 gas into solid
1)Compression and cooling method.
Could please suggest some ideas to make co2 gas into co2 solid? ( cost - effective method)
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Buying dry ice can be cheaper, of if you have gas supply then use something like this: https://www.belart.com/frigimat-cub-dry-ice-maker.html
Kind regards,
Rob
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Hello,
Does anyone know of a paper where the constants are given for a given hyper elastic model that that can predict the constitutive behaviour of a polymer in tension for a stress of 2 MPa and strain of 0.35 mm/mm and in compression with a stress of -2 MPa and strain of -0.7?
Thank you in advance!
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Thank you Harold Berjamin .
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When modelling the softening behavior of quasi-brittle materials as concrete, mesh sensitivity is very important unless we use a regularization technique. In tension there are many available in the literature, but what are the techniques available for compression?
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Not quite, but thank you for your answer
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Compression test to composite materials needed to be simulated by Ansys but the material doesn’t exist in Ansys library
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Thank you Andrey Skleznev
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I want to simulate compression loading on the prosthesis socket using Abaqus software. I don't have an idea to draw this socket by Abaqus because it's shaped unsymmetrical. So, please, can anyone help me to overcome this issue?
My warmest regards.
Hussein
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Due to its limited tools, the ABAQUS sketch module is not the best choice for creating complex geometries. You should use CAD software products such as (CATIA, SolidWorks, etc.) and then import .step or .iges files into ABAQUS.
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What young modulus should we use while inputting the modulus value of material in the split hopkinson software? I have done some tensile tests on UTM as attached in figure. however the split hopkinson is compressive in nature? Also modulus is different at different strain rates.
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Thanks