Hybrid Solving Methods for Effective Antenna Placement

In a previous article, I mentioned about design & analysis of antenna using electromagnetic simulation and important aspects to be considered. In this article, I explain effect of a platform on radiation characteristics and how hybrid solving methods can help towards effective antenna placement.

It has become routine for automotive OEMs to integrate different types of antennas in their vehicles. In recent years, many industry professionals have been focusing on implementing projects related to Internet of Things (IoT). There’s ever-growing demand for IoT integration for consumer electronics, vehicles and so on. Consequently, estimating actual performance of the antenna with any platform (vehicles, electronic devices and buildings) is becoming challenging!

In recent years, automotive industry is introducing Advanced Driver Assistance Systems (ADAS) for automating and enhancing the vehicle system and its safety. The growing interest for wireless connectivityHybrid Solving Methods relies more and more on integrated antenna solutions customized for optimal system performance, and any failure can cause the delay in a critical product launch. ANSYS provides the technology for the various solution techniques for simulating individual antenna to final placement for estimating various characteristics.

Hybrid Solving Methods for Antenna Placement

You can easily assess the effect of the platform on the performance of the antenna using Hybrid Solving Methods. You can apply traditional approaches such as the finite element method (FEM), Finite Difference Time Domain (FDTD) to problems of moderate electrical size.  Significant computational resources are necessary for these numerical methods. Therefore, we will need to further extend the capability of FEM to the solution of electromagnetic radiation and scattering problems. These could involve disjoint obstacles such as reflector antenna systems, antennas mounted on large platforms, and antennas in the presence of radome structures. To achieve this, several methods such as method of moments (MoM), high frequency techniques such as Physical Optics (PO) and Shooting & Bouncing Rays (SBR+) have been hybridized with FEM.

Furthermore, the below schematic will allow you to select an appropriate solution technique based on the geometric & material complexity and electrical size of the problem that you wish to solve.

Hybrid Solving Methods
Decision Criteria for Selecting Hybrid Solving Methods (Courtesy: ANSYS, Inc.)

Hybrid Solving Methods provide the solution for

  • Radiation Patterns of the Antenna after mounting it on the proposed platform
  • Coupling between Antennas placed on the platform.
  • Optimal Position for an Antenna over given platform.
  • Faster Computation Times
Finite Element Boundary Integral (FEBI) & SBR+

Among the several hybrid solving methods, I’ll focus on FEBI and SBR+ in this section. In both these methods, you simulate a part of the antenna with FEM. Then, you simulate the platform effects with either integral equations or high frequency techniques. To effectively calculate currents near the antenna, you need to analyze the antenna using the FEM and feed these results into FEBI or SBR+ methods.

In general, electrically large problems could be solved with FEBI technique & electrically larger problems can be solved with SBR+ technique. For a smaller problem scope, FEM will do the trick! Since both the hybrid methods are equally applicable for many problems, you’ll need to be aware of the subtle reasons for selecting the most appropriate method that is relevant to the platform. We can help you with this if you need any assistance!

The combined simulation with feed network analysis is also possible with the help of ANSYS Circuit Simulator. With this, you can interface field solver results with those from FEM-Hybrid Techniques.

Relevance to ADAS Applications

When we think about non-monitored drivingHybrid Solving Methods, the ADAS system can handle all the situations: partial or full scenarios. Toyota President Aikido Toyoda recently said to ensure ADAS system safety, we need 8.8 billion miles of testing of autonomous vehicle design. This is not only expensive, but also impractical. ANSYS-Powered Simulations have a crucial role in ADAS because of availability of multiple software tools for different kinds of analysis and easy integration with others.

You can simulate Radar Antennas in Autonomous Vehicles with HFSS and conduct initial placement simulation with hybrid methods (FEBI or SBR+). We can simulate different driving scenarios that accounts for other vehicles, buildings, trees etc. by including detailed physics. This is possible by using HFSS SBR+. These virtual test results can be used to test & validate control algorithms and vehicle dynamics.

Summary

ANSYS Electromagnetic Simulation Software provide the necessary requisites to validate design and placement of the antennas for different applications. In addition, Hybrid Solving techniques provide for various benefits including faster computation times, optimal position studies among others.

Going a step further, you can extend these studies to ADAS applications by integrating results from ANSYS Electronics Simulation Software.

I hope the article was useful to you. If you wish, you can download a recent Webinar on Antenna Design and Placement using ANSYS Software. Of course, please feel free to reach out to me if you have any questions.

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Porous Media: Top 3 Modeling Challenges

In this article, I will describe a fairly common procedure to model porous media accurately and address frequently-asked questions.

Tesla Model 3 was recently launched amid much media reporting. In fact, Elon Musk tweeted to his followers about filtration. There was an article which said that Tesla’s Model X purifies air in less than 2 minutes!

So, how does Tesla make it possible? Porous media cane help them achieve this. By porous, we can infer a substance to have minute interstices through which fluid may pass through it. Porous material is permeable if the interstices are interconnected or continuous thereby making a fluid to flow through them. Massive amount of consolidated energy wastage (due to improper combustion and left of un-burnt particles) happens due to this impure air. For efficient fuel burning, there is the pressing need to filter air before passing it through any combustion device. Another application that is quite relevant to this topic is of air conditioners – all pervasive at homes and our workplaces. In all these applications, impure air passes through a series of filters. The interstices present in these porous zone filter holds off solid dust particles and parses clean air.

These concepts are ubiquitous in nano- and micro-scale applications, oil reservoirs and geophysics applications, electronics cooling, thermal insulation engineering, nuclear waste repository, biomedical, biological and environmental applications, grain storage and enhanced recovery of petroleum reservoirs among many others. Today we need to explore innovative approaches to effectively apply existing porous media technologies to these applications. These porous media play a vital role in gas turbine inlet filtration systems. A typical pollution eliminator contains different type of filters such as bag filters, cartridge filters, EPA (Efficient Particulate Air), HEPA (high efficiency particulate air) and ULPA (Ultra Low Particulate Air) filters etc.: each filter has a specific purpose and level of efficiency.

Fluid Flow Effects in Porous Media
Porous Media Flow
Example of Porous Zone with minute interstices through which fluid can pass through (Courtesy: ANSYS Inc.)

Design and shape of the filter plays a crucial role in evading compressor surge and improving the performance of a system as a whole. It is very crucial to keep the flow conditions at a minimum total pressure drop by adopting a filtration system that suits the operational environment.

During filtration, fluid experiences certain changes such as:

  • static pressure rise due to diffusion,
  • reduction in the flow energy, thereby making it more laminar based on the porous medium’s permeability,
  • heat transfer effects through the porous zone, etc.

Today simulation plays a significant role in understanding filter performance and filter housing design to deliver adequate air flow distribution by translating a physical scenario into a math-based numerical model. As simulation engineers, we will need to model porous media to recreate these effects.

Using ANSYS FLUENT interface, I will explain the process here onward. In ANSYS FLUENT, porous media model adds a momentum sink in the governing momentum equations. You can model this in two ways:

  1. Using cell zone conditions
  2. Porous jump boundary conditions, especially if our only concern is about the pressure drop.

The approach to model porous media using porous jump boundary conditions is useful when we don’t have all the necessary flow transport properties. With this approach, however, you can expect a decline in accuracy because you need to assign the boundary conditions only on the surfaces. This makes it critical for the solver to understand a sudden rise in the pressure value at the imposed location.

Modeling Porous Media using Cell Zone Conditions

Once you import your meshed model into ANSYS FLUENT, you can edit the fluid cell zone condition. Here you will find options like Frame Motion, 3D Fan Zone, Source Terms, Laminar Zone, Fixed Values and Porous Zone. By selecting the Porous Zone feature, you will find input options mainly related to Inertial and Viscous resistances and direction vectors.

Inertial and Viscous resistances are the coefficients combined with other parameters of the Hagen-Darcy’s equation. This equation calculates pressure drop across the porous zone. This zone provides the capability to model pressure drop inside the fluid volume in the axial direction. The pressure drop in this medium is contributed due to viscous and inertial resistances; we can define it as:

∆p = ∆pViscous +  ∆pInertial

where the pressure drop due to viscous resistance is given as the product of viscous resistance coefficient, thickness of the porous zone, viscosity of the fluid and the velocity of the flow. Since we provide viscosity, thickness (from the geometric model), velocity of the fluid (as calculated by the solver at the corresponding place in the domain through iterations) and the coefficient (user input values), solver calculates the pressure drop attributed due to this viscous effect loss.

Similarly, the pressure drop due to inertial losses is given as the half product of inertial resistance coefficient, square of the velocity of the fluid, thickness of the porous zone and density of the fluid. Take sufficient care while entering coefficient values into the software; sometimes the values may be given of the negative exponential order. Confusion arises because coefficient is represented as C¹= 1/K. In the software, you need to enter the value of K to accurately account for the right coefficient value.

Porous Media Flow
Cut Section View. Sample model of an inlet filtration unit for a gas turbine generator. Blue-colored components act as walls while inlet and outlet. I mounted the three series of weather hoods at the front intakes air from atmosphere through porous zone packed beds arranged beneath.
Porous Media Flow
Streamlines on a planar section colored with pressure as variable, originating from the inlet
Porous Media Flow
Total pressure drop in the planar section view. The blue colored region is due to the lack of fluid presence at that region.
Achieve Faster Convergence

Occasionally, the convergence rate slows down when the pressure drop is relatively large in the flow direction. For example, when the coefficient value of C² is large or permeability (alpha) is low, convergence rate is slower. You can resolve this by providing a good initial guess for the pressure drop across the medium. You can obtain the initial guess from two ways:

  • by performing standard initialization, or
  • by supplying an initial flow field without the effect of the porous region by temporarily disabling the porous media model.
Frequently-Asked Questions: The Top Three
  1. Direction vectors, especially for conical or cylindrical faces, are automatically calculated by ANSYS FLUENT. Engineers fail to check if the direction vectors are normal to the surface. If the direction vectors are not normal to the surface, then results will be incorrect. Be careful, there!
  2. Does every porous flow application have pressure losses due to the combination of both the viscous and inertial effects? The CADFEM’s Support Hotline gets this question quite often. The answer is no. For laminar flows, you’ll not find any inertial effects. Whereas for flows through a planar porous media (not a standard industrial use case though), you’ll not find viscous effects as well.
  3. I don’t have the either of the viscous or inertial coefficient values. With information about pressure drop across the porous zone, can I simulate the fluid flow? This one is tricky because the pressure drop is due to the combined effect of both the inertial and viscous effects. Without knowledge about the significant contribution to the pressure loss due to either effect, it’s impossible to accurately model the flow. However if you are willing to ignore one of the two effects, then you can utilize the information about pressure drop to model the flow.

It’s not difficult to model porous flow problems, however you need to right software and the right partner to guide you through the solution. Talk to us, and we’ll glad to help you!

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Robustness Evaluation – Why Bother?

This article will explain how ANSYS optiSLang can be used for robustness evaluation in virtual product development.

A successful product. Isn’t that the goal for every product company? It begins right from the step where engineers come up with world class product innovations to getting the right marketing mix that brings commercial success. Is every product successful? No. Is every product with a great design successful? Maybe.

The Symptom
Robustness Evaluation - Why Bother?
Courtesy: Android Authority

More often than not, we find market leaders stumble with product failures. The infamous Samsung’s Note 7 will come to your mind instantly. Hundreds of users were at the forefront of dangerous incidents where phones caught fire due to short-circuiting. Samsung conducted severe internal testing and several independent investigations. They found that, in certain extreme situations, electrodes inside each battery crimped, weakened the separator between the electrodes, and caused short circuiting. In some other cases, batteries had thin separators in general, which increased the risks of separator damage and short circuiting. Economics-wise, the incident caused Samsung to recall 2.5 million devices, lose over $5 billion and damaged its reputation.

Faulty Takata airbags’ inflators contained a defect that cause some of them to explode and project shrapnel into drivers and passengers. 50+ people worldwide lost their lives due to this design failure. 70 million Takata airbag inflaters were to be recalled at a cost of $9 billion to its automaker customers. For a Tier-I supplier, this liability was so huge that they filed for bankruptcy.

Such glaring errors after product launch, with severe economic implications, aren’t limited to Samsung and Takata alone. Honda, Michelin and many more companies have been involved in product recalls due to design failures.

Obviously, such design flaws need to be mitigated. Isn’t it?

The Probable Solution

To preempt design failures, today’s engineers use state-of-the-art engineering technology. Traditionally, product development teams used extensive prototyping and testing to validate design variants during the design life cycle. Of course, this is cumbersome, expensive and time-consuming.

Over the past few decades, engineering simulations have opened up a whole new range of possibilities for the design engineers. ANSYS, Inc., the market leader for engineering simulations, provides state-of-the-art technology to simulate systems involving mechanical, fluid, electrical, electronic and semiconductor components. With added insight, design engineers are able to test a lot more design variants on a virtual platform using this technology.

Consequently, the benefits – innovation, lowered cost of product development, higher product profitability and faster time-to-market. The staggering economic benefits and tremendous value on the offer have prompted several product companies to introduce simulations upfront using a Simulation-Driven Product Development approach.

Companies like Samsung and Takata were power users of engineering simulations. They used technology extensively in their design phase and perform virtual tests to validate designs. Only validated designs were put through production, QA and then sent off to the market. Despite simulating and validating designs, these companies witnessed monumental product failure in the market that caused loss of life, led to economic losses and damage to their reputation.

If they used simulation-driven product development, what went wrong?

The Cause

While the probable solution can mitigate and even eliminate design failures, there are other forces at play that you will need evaluate carefully. Hence it is imperative to understand the root cause for occurrence of design failures despite conducting extensive state-of-the-art simulations.

Many design engineers often undermine or do not consider one important aspect due to lack of proper understanding. Variability. Just as design parameters such as thickness or physical loads can be varied to test different design variants, some parameters display inherent variability.

Let me explain it with a material parameter: Young’s Modulus. If you’re an engineer by qualification, you would’ve come across the Universal Testing Machine (UTM) in your freshman or sophomore year of college. To test the Young’s Modulus of any given material (say steel), the UTM pulls a material specimen at extreme ends to create tension. Using mathematical calculations, you’ll arrive at a number close to 210 MPa as the Young’s Modulus of mild steel. Let’s say you repeat this test for 99 other specimens of the same material. Each test result will be different and it will never be the same. Other than the odd case of a faulty UTM apparatus, there’s only one reason for that. Natural Scatter.

The Hero: Robustness Evaluation

Such variability (statistical) will lead to variability in the performance parameters of the product. Obviously this is quite important and engineers need to assess designs for variability well ahead of product launch. For variability, you have only one way to assess designs for product failure or risks: Robustness Evaluation.

Robustness Evaluation with ANSYS optiSlang

The preferred choice of tool for robustness evaluation is ANSYS optiSLang. For better understanding, there is a lot of material available in more detail. Instead of reading, you may also want to consider watching these webinars here and here.

Can you attribute lack of design robustness to any other product failures that you have witnessed? Do you have alternate views? Please let me know in the comments section.

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Maximize Fracking Profitability with ANSYS

This article explains how ANSYS and few other tools can be used to perform hydraulic fracturing, or commonly known as fracking, to reduce costs and increase profitability of shale gas projects.

Shale Gas

Shale gas is a form of natural gas trapped within shale formations. Because of its abundance, shale gas is a lot cheaper than it has been in years. Hydraulic fracturing or fracking helps in extracting it efficiently.

According to American Enterprise Institute, “the direct benefit of increasing oil and gas production includes the value of increased production attributable to the technology. In 2011, the USA produced 8.5 trillion cubic feet of natural gas from shale gas wells. Taking an average price of $4.24 per thousand cubic feet, that’s a value of about $36 billion, due to shale gas alone.” As a result of increase in fracking, natural gas imports in United States reduced by 25 percent between 2007 and 2011.

What is Fracking?

The term simply means creating fractures using hydraulic fluids. In this technique, production teams pump huge volumes of water and proppant at high pressure into the gas well. They also mix a few chemicals, which improve fracking performance, along with the water during pumping. Shale layers, being less permeable, minimize the flow of the natural shale gas trapped.

Fracking is useful in creating a connected fractured network between pores of the rock through which natural gas escapes out. In the first step, production teams drill horizontally along the shale layers. From the perforations, specialists pumps water into the rock. Since water is sent in with high pressures, the shale layers fractures. Once the pressure is decreased, they retrieve water from the shale layers leaving behind sand particles. However, the proppant dwells in the rock layers keeping the cracks open thereby allowing gas to escape.

Benefits and Disadvantages of Fracking

Fracking helps in accessing the natural shale gas trapped deep down beneath the earth. With traditional methods of extraction, we cannot exploit this energy potential. Recently-developed methods of vertical and horizontal drilling added favor to fracking. They permit drilling thousands of feet deep inside the ground in order to access the trapped shale gas.

It is said that shale gas causes lesser air pollution when compared to other dirty fuels like coal and oil. However there are ways in which fracking itself can cause more devastating effects such as air emissions and climate change, high water consumption, water contamination, land use, risk of earthquakes, noise pollution, and health effects on humans.

Economic Benefits of Simulation

To achieve an optimal design for a gas well, standard industry practice is to conduct a large number of field trials that require high capital investment and time which significantly increases the project value.

In order to obtain a profitable production of shale gas, I recommend you to use a fully coupled 3D hydraulic-mechanical simulation. Obviously the costs of such simulation are a lot lower than traditional methods. Many of our customers in the Oil & Gas industry have yielded better output with a higher project profitability.

You can find the schematic view of simulating Hydraulic Fracture below.Schematic view for fracking simulation

Essential Pre-Requisites for Simulation

We gather the input data for simulation from different physics such as geology, petrophysics and geomechanics. From the geology of the rock structure, we extract the lithology and layering, altitudes of beddings and natural fracture data. Accurate determination of petrophysical properties for both the reservoir and fluid contents is necessary. We also need to consider features like porosity, permeability and saturation for the reservoir. It also includes evaluating the properties that help in determining the hydrocarbon concentrations in the reservoir and its ability to produce the gas.

Along with the surface and sub-surface properties of the rock, the in-situ stress parameters also have same importance in simulation. I also account for elastic properties and strength parameters of intact rocks. The geomechanical studies of the rock structure also reveal the strength parameters of natural fractures, if any. Using multiPlas, I model these rock-specific material parameters and joints.

Of course, gathering this data can look daunting to you. However our expertise combined with strengths from Dynardo GmbH – the leading global experts in simulation of hydraulic fracturing – can help!

Fracking Simulation – Readying the Model

In the simulation of fracking process, I use a sequential coupled hydraulic-mechanical modeling approach. Therefore, I construct two models – a hydraulic flow model and a mechanical model simultaneously.

3D model with different soil layers for fracking simulation
3D model with different soil layers

To account the strength and stress anisotropies of the rock structure, I need to consider a 3D model. These variables help us to constantly monitor the behavior of fracking process. To capture the anisotropic nature of the rocks, you’ll need strength and stress anisotropies of the rock matrix and fracture system.

Sequentially Coupled Hydraulic-Mechanical Analysis in ANSYS

In ANSYS Mechanical, we start with a transient hydraulic flow analysis (analogous to transient thermal analysis) to understand the pore pressure field. The pressure increases in the fracture-initiated locations due to the pumping of fluid and low permeability of rock. If the pressure is large enough, the rock starts to fail and fractures open up. As a result, the permeability of the rock structure increases and changes the pressure distribution in the hydraulic flow model. From a mechanical perspective, pressure increase changes the effective stresses within the rock. After every fluid time increment, change in the mechanical forces from pore pressure change will be introduced into the mechanical analysis. The forces on every discretization point of the smeared continuum are computed from the pore pressure gradient.

I setup the coupling inside ANSYS in an explicit manner. Consequently, one iteration cycle is performed for every time step. The time step needs to adequately represent the progress of the fracture growth. At each time step, a transient hydraulic flow analysis starts first. Then the mechanical analysis with the updated pressure field from the hydraulic flow model is conducted. The mechanical analysis results in updated stress, plastic strain fields and hydraulic conductivities. i apply the updated hydraulic conductivities to the hydraulic model in the subsequent time step.

Crack expansion in the model while performing fracking analysis
Crack expansion in the model

In mechanical analysis, the development of fractures is represented by a plastic model in ANSYS. As a result, I cannot directly measure fracture openings and hence I’ll need to calculate it based on the plastic strains.

Model Calibration & Optimization of Fracking Paramaters

Because of large number of statistically-varying and reservoir parameters, the reservoir model needs advanced calibration procedure. At first, I will need to calibrate numerical parameters such as maximum permeability of open joints or energy dissipation at pore pressure frontier.

After calibration of all the parameters, I identify the most important parameters contributing to maximum crack volume using optiSLang software. As you will recognize, maximum crack volume correlates to maximum shale gas output. I validate the behavior of such important parameters and then calibrate the analysis model to the field measurements. I use the calibrated model later in order to optimize the simulated volume and predict the gas production rate of the wells.

Summary & Outlook

Evidently, application of simulation to the fracking process will underline its predictability. Simulation cut downs the costs of field trials, brings down the time-to-market thereby significantly increases the project profitability.

If you’re into gas exploration, you should contact us filling this form or by writing to sales@cadfem.in. We’ll be glad to explain some of our recent projects that have benefited customers in Oil & Gas industry.

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ANSYS License Management Made Easy!

Virtual Product Development has enabled companies to predict with confidence that their product will thrive in the real world, helping them to the solve the most complex problems which are limited only by imagination. This wouldn’t have been possible without ANSYS, the market leader in engineering simulations, that is used by many companies spanning enterprises to startups. Consequently, one of the prime goals of these product companies is license management – manage software license requirements among different teams effectively without affecting team’s productivity or asset utilization.

In this article, I will describe the new developments in ANSYS 18.0 that will make it easier for managers and license administrators to manage licenses better.

How To Get Started?

To begin with, the first step in managing the licensing resources is to track current usage of these resources. Previously, tracking and preparing the reports of ANSYS software license usage was always a tedious manual task of looking into the log files and searching for a specific license. As a result, one common question I received on CADFEM’s support hotline -“Is there a better way to track our license usage?” With the release of ANSYS 18.0, this job has eased to a certain extent.

With ANSYS 18.0, License Management Center provides the tools which help license administrators to obtain effective reports from the usage log files. Therefore, reports can be extracted about anything from current usage to peak usage and license denials in a tabular or a histogram form for a requested duration.

ANSYS License Management Center

Opening the ANSYS License Management Center will open up the license manager in the default browser.

  • Windows: Start -> Programs -> ANSYS Inc. License Manager -> ANSYS License Management Center
  • Linux:
    License Management
    License Management Center

    /ansys_inc/shared_files/licensing/start_lmcenter

New subsection has been added for reporting with 4 options. We will discuss each of these options in brief.

Current License Usage

With the View Current License Usage option, you can track current license usage. It highlights all available licenses on the server along with the maximum number of licenses. It also reports the current total license usage along with the license usage per user; different color for each user. In addition, clicking on Show Tabular Data will provide you more information about user count, user names, hostname and Start date in tabular format.

License Management
Current License Usage

Also, you can obtain similar data from Client ANSLIC_Admin Utility for older versions of ANSYS. For the manager and organization, the most important report is the licenses usage over a period of time. Next three options will help them in getting it.

License Usage History
License Management
License Usage History

This option helps in tracking the usage of license for a given period of time. Click on License Usage History and choose the duration and then click on Generate to obtain the histogram for the given duration. Once the data is generated, you get the option of monitoring the data for a specific license. Even a customized duration can be specified to track a particular license usage.

License Management
License Usage History – Specific License Type
Peak License Usage

License usage history report can be confusing at times even for experienced users. Hence if you want to track more simplified averaged peak usage per day for a given period of time, please select Peak License Usage option. By following similar steps as for License Usage History, select the time period and hit generate.

License Management
Peak License Usage

Here you will have more options for filtering out the data with respect to licenses type and months of specific interest. Along with it, you can also extract data for a complete week (24/7) or only for working days (24/5). Clicking on Show Tabular Data provides daily, weekly and monthly average of each license in a tabular form. Now, that’s going to be quite useful for the managers and licenses administrators.

License Management
Peak License Usage: Tabular Form
License Denials

Similar to Peak License Usage, the License Denials option will show the average denial of license due to insufficient licenses or for any other reason for a day for requested time duration. This helps in tracking the requirement and planning for future needs.

License Management
License Denials

Though the Reporting Tool in ANSYS doesn’t include more sophisticated options and filtering methods, it allows managers to track the license usage in many different ways without manually going through log files or investing in third-party tools.

License Management Made Easy

Thanks to ANSYS 18.0, License Management Center is even more potent and useful for you – the department heads, managers and license administrators. You can monitor license usage in real-time or historically, evaluate peak license demands and license denials. As a result, this new feature will allow you to evaluate asset utilization, manage internal license demands, forecast the need to acquire additional license among others.

There’s also a nice YouTube video that is a little more crisper than my article. It covers pretty most of the options that I have described in this article. If you are short on time, this video may help.

I would like to know if there are questions regarding license management that you’ve not been able to address so far. Maybe I can help? Hence please do use the comments section below to reach out to me. I’ll be glad to be of help.

I hope you found this article useful. Please feel free to share it with friends and colleagues. If you haven’t subscribed to this blog yet, please do so on the right side of this article or through this link.

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Boundary Layer Modeling using Inflation Layers

In contemporary Computational Fluid Dynamics, for practicing engineers and students, there lies an essential need for the know-how of “making a mesh better” to capture gradient information especially at the fluid-surface boundaries. Modeling the boundary layer becomes extremely important. Visualization of the mainstream flow is, of course, vital to understand the flow behavior. However to obtain a fairly accurate solution for a fluid flow problem, appropriate discretization or meshing of the fluid domain at the boundary layer holds the key.

What is Boundary Layer?

From theoretical fluid mechanics, we know that gradients of velocity and temperature exist within the boundary layer (Wikipedia). Obviously the fluid that is immediately in contact with the boundary will have the same velocity as the boundary. As we move away from the boundary, the velocity of the successive layers of the fluid will increase. Within the boundary layer, shear stresses are developed between layers of fluid moving at different velocities because of viscosity and the interchange of momentum as a result of turbulence. This can cause movement of fluid particles from one layer to the other. In all such flows where “the wall” participation brings considerable changes in the fluid flow, we observe that there is a non-linear variation in the velocity profile normal to the flow direction.

Boundary Layer Modeling using Inflation Layers
Typical profile of a boundary layer

Without accurately capturing these effects at the boundary, you wouldn’t have an accurate solution to such fluid flow problems. Hence, to ensure that you get a fairly accurate result, I will provide recommendations for meshing at boundaries.

Boundary Layer – Key Meshing Recommendations

Typically, the best way to capture effects in the boundary layer is by accommodating higher number of cells in the direction normal to the fluid flow. For mainstream flow, I wouldn’t expect gradients to change much. Hence I recommend reducing the mesh intensity in the flow direction. Within the boundary layer, I would suggest you to have elements with high aspect ratios (up to 100-1000); you can stack them in the direction normal to the wall.

You will need to choose element types that can be stacked one over the other. By doing so, you can marginally save the number of grid cells and time required for the computation. Apart from the conserving the mesh count, it is extremely important to model the boundary layer with sufficiently high quality of meshing elements. You will agree that a poor quality mesh will obviously result in a commensurate accuracy of the solution.

Modeling the Boundary Layer in ANSYS

In ANSYS Fluent, you can achieving cell/element stacking in the direction normal to the boundary using a feature called Inflation. Essentially, you can inflate the mesh with several layers from the surface of the boundary until you cover the boundary layer thickness fully. Tetrahedral elements, when subjected to high aspect ratios, suffer from poor geometric quality. In contrast, Prism elements, due to very high geometric anisotropy, even if they are subject to high aspect ratios, show no deterioration in the geometric quality.

Now, I will compare using prism elements to model the boundary layer instead of tetrahedral elements. Towards the end, I will draw comparison between these two types of elements.

Boundary Layer Modeling using Inflation Layers
Hybrid mesh with prism and tetrahedral elements

For a sample geometry, I have utilized the inflation feature to setup the growth of five inflation layers from the surface of the boundary. As you can see, prism elements are stacked over one another (inflated) in order to capture the boundary layer effects.

If the number of layers are specified as three, the meshing tool grows three layers of prism elements. Beyond the inflation layers, the rest of the fluid domain is meshed with tetrahedral elements. Therefore, the end result will be a hybrid mesh of prism and tetrahedral elements. You can control the inflation layers with parameters like growth rate.

The Benefits
Boundary Layer Modeling using Inflation Layers
Without Inflation
Boundary Layer Modeling using Inflation Layers
With Inflation

In the velocity contour plots, you can see the solution to the fluid flow problem with and without use of inflation. If you notice, the velocity gradients at the boundary are captured quite well when inflation is used. Do you work with applications that involve highly turbulent flows? In such cases, mesh inflation at the boundaries becomes extremely crucial.

In addition to capturing the boundary layer effects accurately, inflation also contributes to lesser element count and computational time. Considering this, I would advise you to use inflation for any wall bounded flow.

In this article, I explained the importance and the approach the use Inflation in the boundary layer. In my next article, I will describe ways to control the growth of the inflation layers using specific application(s).

P.S. If you’re interested, why don’t you attend one of our upcoming training courses for CFD and meshing?

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Demystifying Modal Analysis (Part I)

In this article, I will discuss about modal analysis – a topic that is standard, however I’ll strive to demystify it using a simple example and FAQs.

Motivation for Modal Analysis

As a mechanical engineer, life is always interesting because I can correlate the knowledge gained from books to real life scenarios. As a student, my professor gave a real example of a bridge failure due to marching soldiers. What followed was a very interesting lecture about dynamics. Until then, I never understood the power of the words such as dynamics, vibration and resonance. Of course, the example provided food for my thoughts to study more about how a bridge could fail due to lesser dynamic load compared to a heavier static load.

For those of you who are curious, the bridge was England’s Broughton Suspension Bridge that failed in 1831 due to the soldiers marching in step. The marching steps of the soldiers resonated with the natural frequency of the bridge. This caused the bridge to break apart and threw dozens of men into the water. Due to this catastrophic effect, the British Army issued orders that soldiers while crossing a suspension bridge must ‘break step’ and not march in unison.

Such failure has given rise to more emphasis on analyzing the structure (mechanical or civil) for dynamic loads if it undergoes any sort of vibrations. Traditionally test equipment have been used to experimentally monitor vibrations in new designs; this is costly however. We apply finite element analysis (FEA) to solve such problems. FEA solvers have evolved and today’s solvers are powerful not only in statics but in dynamics too.

Demystifying Modal Analysis

Modal Analysis: Getting Down to the Basics

In any dynamic/vibration analysis, the first step is to identify the dynamic characteristics of the structure. This is done through a simple analysis called Modal Analysis. Results from a Modal Analysis give us an insight of how the structure would respond to vibration/dynamic load by identifying the natural frequencies and mode shapes of the structure.

Modal Analysis is based on the reduced form of dynamic equation.

Demystifying Modal Analysis

As there is no external force acting and neglected damping, the equation is modified to:

Demystifying Modal Analysis

I have skipped the derivation part of natural frequency as it is easily available in textbooks. Natural frequency is substituted back into the equation to find out the respective mode shapes. These natural frequencies are the eigen values whereas the respective mode shapes are its eigen vectors. Natural frequencies & mode shapes in combination are called as modes.

Eigen vectors represent only the shape of deformation, but not the absolute value. That’s the reason it is called as mode shape. It is the shape the structure takes while oscillating at a respective frequency. Important point to remember is the structure has multiple modes and each mode  has a specific mode shape. If any load is applied with same frequency as natural frequency in the same direction as mode shape, then there will be increase in magnitude of oscillation. With no further damping, the scenario will lead to a failure due to a phenomena called resonance. To avoid this phenomena in dynamics, calculating the modes carries great importance.

Frequently-Asked Questions

Having said that, questions will certainly arise. In my opinion, these are the most commonly asked questions in support calls by customers using ANSYS.

  • Why do frequencies from simulation don’t match the test results?
  • Why are deformation and stresses in modal analysis very high?

From equation (3), it is clear that natural frequency of structure depends on its stiffness and mass. In order to accurately capture frequencies in FEA, the following points are important for you:

  • You need to capture mass of the structure and connecting/ignored members accurately.
  • Your mesh can be coarse, but enough refinement so that you can accurately capture the stiffness of the structure. If you are interested in the local modes in slender members, then you’ll need to perform local mesh refinement.
  • You need to define appropriate boundary conditions in forced modal analysis in order to capture realistic frequencies.
  • You need to accurately model the contact between different bodies in an assembly since they affect the stiffness of the structure drastically.

For the second question, a lot of confusion exists when the modes extracted in modal analysis show deformation magnitude. In Equation (2), you will see that no external load is applied on structure. This will make you wonder where these values come from? Let’s have a look with an example of simple cantilever beam.

Demystifying Modal Analysis
Fig. 1 – Mode shape & stress shape of Cantilever Beam

Fig. 1 shows its extracted mode shape 1 & stress shape 1 from modal analysis. I observe deformation to be as high as 253 mm and stress as 4,914 MPa which is far greater than the ultimate strength of Steel i.e. 500 MPa. You may wonder, why did we get these high values?

This happens because the FEA solver returns the mode shape (not the deformation magnitudes) as output. By this, I mean that magnitude of the mode shape is arbitrary (as seen in Fig. 1). The high value is because of a scale factor that’s chosen for mathematical reasons and does not represent anything real for the model. However this value helps us in relative measurement. Let’s take the example of the first mode. Maximum deformation occurs at the free end compared to any other location. This changes with the change in mode.

Since we have deformation, you can compute corresponding stresses and strains. Once again, these are relative values. If you ask the FEA solver for stresses & strains, it will use the same scaled deformation magnitudes and calculates stresses & strains. They are referred to as stress shape & strain shape (not to be confused with stress state or strain state) because no loads are applied. The magnitude of stresses and strains are useless but their distributions are useful to find hot-spots in the respective modes.

Conclusion

Modal analysis offer much more than just the frequencies and mode shapes. This analysis is primarily the stepping stone for linear dynamics studies to calculate the actual deformation due to different kinds of dynamics loads. Modal analysis has many secondary applications which I will discuss in my next blog.

 

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Drop Test Analysis with Bolt Pre-Stresses

This article introduces a time-saving and a smart approach for drop test analysis with pre-stresses using LS-Dyna. 

Many products that are subject to handling during transport, installation, or repair are at risk of being dropped. Granted, handlers generally try to avoid these types of mishaps. When equipment is out of your hands, its safe transportation is out of your control. One way to ensure that your product survives its journey from the factory to the point of installation is to perform drop test analysis and verify that it survives without damage. That way, your company isn’t answering warranty claims from customers who received damaged goods that left your warehouse in mint condition.

Although the methodology for drop test is fairly standard, it is challenging to capture the finer details that happen in reality. This article introduces a time-saving and a smart approach for drop test analysis with pre-stresses using LS-Dyna.

Motivation

While drop test problems involving huge appliances, the effects of bolt-load or pre-stresses are generally ignored. However, in some cases, it is desirable to have a pre-stress loading of a structure before performing a transient dynamic analysis or, simply, drop test analysis. This is because nowadays the product safety has increased the demand for accurate simulation models.

In this article, I used LS-DYNA. It is a highly advanced, general-purpose, nonlinear, finite element program that is capable of simulating complex real world problems.

Firstly engineers need to perform a pre-stress analysis for the bolts before conducting the drop test analysis. Then you will need to integrate the stresses and strains obtained from the pre-stress analysis into the drop test analysis setup.

Drop Test with Included Pre-Stresses (two-step method)

In LS-DYNA, I define bolt pre-load (non-iterative loading type) using *INITIAL_AXIAL_FORCE_BEAM (Type 9 beams only) and *INITIAL_STRESS_SECTION (solid elements only). These keywords work with *MAT_SPOTWELD. The failure models apply to both beam (Type 9) and solid elements (Type 1).

*INITIAL_AXIAL_FORCE_BEAM will pre-load beam elements to a prescribed axial force.

Screenshot of keyword in drop test analysis

In the above screenshot of the keyword, BSID is Beam Set ID. I define the preload curve (axial force vs. time) with *DEFINE_CURVE. LCID is the Load Curve ID.

The below video show the pretension in the beams.

*INITIAL_STRESS_SECTION will pre-load a cross-section of solid elements to a prescribed stress value. Pre-load stress (normal to the cross-section) is defined via *DEFINE_CURVE.

Screenshot of keyword in drop test analysis

In this screenshot placed above, ISSID is section stress initialization ID,  CSID Cross-Section ID, LCID Load Curve ID (pre-load stress versus time), PSID Part Set ID, VID Vector ID (direction normal to the cross section). You can define the vector if *DATABASE_CROSS_SECTION_SET is
used to define the cross section.

In the video, you can see the pre-stresses in solid elements when I used *INITIAL_STRESS_SECTION.

Video Courtesy: LSTC

*INTERFACE_SPRINGBACK_LSDYNA allows LS-DYNA to create a DYNAIN file at the end of the simulation containing deformed geometries, residual stresses, and strains. This file sets me up for the next phase of analysis where I use it with the *INCLUDE keyword. However, the DYNAIN file neither includes contact forces nor contains nodal velocities. These quantities from the pre-stress analysis do not automatically carry over to the drop test.

Drop Test with Included Pre-Stresses – Both in One Step!

In the previous method, there is always manual intervention which can lead to unknown errors. Drop test of an appliance by considering pre-stresses in one step can be specified by using *DEFINE_TRANSFORM.

*DEFINE_TRANSFORM allows to scale, rotate and translate the appliance and you must define before you use the *INCLUDE_TRANSFORM command.

Screenshot of keyword in drop test analysis

Screenshot of keyword in drop test analysis

In the above screenshots, TRANSID refers to Transformation ID that is available in *DEFINE_TRANSFORM and the part which is specified in the file name will include the TRANSID.

The video below shows the drop test analysis of an appliance where *DEFINE_TRANSFORM allows the appliance to pre-stress and then the actual drop happens. The von-Mises stress contours show that the stresses get developed in the parts due to pre-stressing of the beams before the actual impact.

Saves time!

Using this approach, I can save about 20% of the time required to setup a pre-stress analysis and drop test analysis together. In addition, we can eliminate manual intervention.

Thanks to this, I get to submit my simulation jobs to the solver before I head into the weekend. I return in the following week to view and post-process the final results.

If you want to learn more about this, please talk to us.

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The Decade That Was …

In the CADFEM Journal (previously Infoplaner; in German), an announcement was made in the first issue of 2007 about the commencement of India business. This March, CADFEM Engineering Services India (CADFEM India) celebrates its 10th birthday – a decade in business. The company started out as a four person team with the vision that it could help customers in India recognize and realize the benefits of simulation-driven product development. 10 years on, the company has evolved into a confident engineering business, with over 50 colleagues, that has helped hundreds of engineers to realize their product promise.

The Decade That Was …

During this time so much has changed. The world has got smaller, faster and ever more changing. Technology has both been an enabler and a challenge to small businesses and large enterprises alike. As a responsible business, the company’s constant endeavour has been to offer customers the best-in-class solutions to their engineering problems. Today CADFEM India is proud to have gained trust from several local and global companies whose engineers rely on its products, services and know-how on a daily basis.

CADFEM India is a strong channel partner to ANSYS in India by offering the full range of physics (structural, fluids and electronics) across India. This partnership is helping CADFEM increase the rate of adoption of simulation in the country. The organization is structured towards providing and supporting customers with ANSYS software. Today the company has more than 40 engineers comprising of the core technical team, sales and marketing that engage customers in multiple areas of engineering analysis. The team is highly skilled to offer training programs for novices and experienced engineers on a plethora of engineering topics. Several customers, with origins in Germany, are long standing customers of CADFEM in India. CADFEM is the preferred simulation partner for customers owing the nature of strong and high-quality support. Deepak Joseph, the Head of Development (Truck) at Knorr-Bremse Technology Center India, and his team in Pune have been recipients of CADFEM’s technical support regularly. While thanking CADFEM for offering “extended support” to his team, Deepak recently said that CADFEM ”helped us understand ways to achieve accuracy.”

Listing of milestones of CADFEM India

All tools which are critical for success

CADFEM India offers several complementary solutions such as optiSLang (of Dynardo GmbH), Rocky DEM (particle simulations) and simulation-ready hardware. Since engineering simulation requires more than just software, CADFEM India supplies all the tools which are critical for success in simulation – all from one source. As a result, customers in India not only benefit by receiving leading software and IT-solutions, but also obtain support, consultancy and transfer of know-how. The core philosophy ingrained within every colleague is to ensure that customers realize the most return of their simulation investment. Dynardo’s CEO, Dr. Johannes Will, says “Over the last 7 years, CADFEM India has become an important partner for Dynardo to serve the optiSLang business in India as well as to support the Dynardo consulting activities. I personally enjoy that relationship and look forward to intensify the joint business success over the next years.” Since 2011, CADFEM India has organized the Indian edition of the Weimar Optimization & Stochastic Days. In 2016, over 80 attendees came together to discuss the topics of optimization and robust design for sixth year in a row.

In addition to the software business, many customers consider CADFEM India as a reliable engineering consulting partner. Several customers choose to contact CADFEM to seek simulation on demand. CADFEM India’s Managing Director, Madhukar Chatiri says that “this offers a good opportunity for us to demonstrate the power of ANSYS to the customer.” Over the years, CADFEM has solved many engineering problems in automotive, aerospace, consumer appliances, rotating machinery, watches, food & beverage and many more industries. One such example of a strong customer relationship is with Traunreut-based Bosch und Siemens Hausgeräte GmbH (BSH). For over two years from 2008, BSH worked intensively with two engineers from CADFEM India. As a result, there has been a strong partnership between BSH and CADFEM India. Speaking about this, Dan Neumayer, Head of Pre-Development at BSH said “we could have a mutual cultural understanding and a common way of thinking and working. This intensive learning forms a particularly important basis for our long-term cooperation and we see this as one fundamental success factor.”

Group Photo in the decade that was
Mrs. & Mr. Guenter Mueller while visiting CADFEM India in 2015
esocaet program starts in September 2017

One of the top most challenges for employers in India is the low number of engineers skilled with simulations. To bridge this demand-supply gap, CADFEM India has invested in ANSYS Authorized Training Centre that started in September 2015; over 50 engineers have graduated from this centre. Furthermore, CADFEM has partnered with PES University in Bangalore to bring the much-acclaimed esocaet Master Program in Applied Computational Mechanics to India. The esocaet program offers tremendous opportunities to engineers for continuous learning. The first course will begin in September 2017.

CADFEM India has been operationally profitable since many years – this has allowed the company to scale its investments in India consistently. The company has a long-term orientation, offers employees a lot of independence but functions as a responsible partner to customers. This allows the company to respond with agility to the dynamic needs of the market.

The company has geared up for the next decade of business in the Indian subcontinent. Having recognized the needs of the market, the company is betting big in the areas of Additive Manufacturing, Electronics and Digital Cities. CADFEM India has made another significant investment into the newest partner of CADFEM International – CADFEM SEA Pte. Ltd. in Singapore.

In 2016, the company was recognized as one of the 20 Most Promising Engineering & Design Solution Providers in India by the popular CIO Review magazine. Madhukar still fondly recalls the day when he formulated the vision for the Indian business in his mind. He adds “What a journey it has been for many of us! While waiting for our connecting flight at Mumbai airport, Guenter Mueller discussed the idea of a joint company in India. We thank our customers and partners for choosing to work with us. It has been and is our pleasure to serve the engineering market in India in the past decade.”

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How Fatigue Made Me Fall From The Chair?

This article explains the setup of a simple fatigue analysis in ANSYS Workbench using an example. For beginners, this article demystifies fatigue analysis.

Context

When I was ten years old, I was fond of a chair which was small and easily movable. After school, I used to sit on it and watch Aladdin tales on the television. One day, as usual, I sat on it. Suddenly the chair got broke in half and I fell on the floor in front of my sister. For obvious reasons, I got embarrassed and my sister made fun of me the whole day. I slept that day with few unanswered questions.

Why did the chair fail when it was working fine for a few years? Why didn’t it fail on the first day I sat on it?

Illustration of a broken chair as a result of fatigue
My broken chair! 🙁
Motivation

Fast forward to my engineering days, I was told that cyclic loading on any structure can make that structure fail – fatigue failure. Only then I could understand why my beloved chair failed.

Many of you might have heard stories like the one mentioned above or even experienced it yourself. However, the fact that majority of structures irrespective of their size experience a phenomenon like fatigue is real. If a simple structure with a simple load cycle could fail because of fatigue, imagine a complex structure with a complex loading cycle. Yes, the consequences are catastrophic for the manufacturer as well as the user.

According to NBS report, “between 80-90 % of all structural failures occur through a fatigue mechanism.” Incorporating fatigue simulation upfront into the product development cycle plays a vital role in optimizing the structural integrity of your product and it significantly reduces the cost of failure.

In this article, a simple fatigue analysis is shown which was carried out using ANSYS Fatigue Tool. If you wish to conduct the analysis as per FKM guidelines, you’ll be interested this CADFEM ANSYS Extension.

Workflow

For a fatigue analysis, static structural or transient analysis is a prerequisite. To achieve this, I consider a simple chair geometry for static structural analysis; appropriate loads and boundary conditions were defined. I define a point mass of 75 kg to act on the chair. This loading can be considered as a misuse for a child’s chair. Resultant static stress (24 MPa) did not exceed the yield strength (54 MPa) of the assigned material.

There! I got the answer to one of the questions from my story. The chair didn’t fail on the first day I sat on it because the load applied on the first day was not sufficient enough to exceed the yield strength of the material.

Analysis setup for fatigue study
Loads and Boundary Conditions
Results of static structural analysis before fatigue analysis
Equivalent von-Mises Stress

 

 

 

 

 

 

 

Setting up the analysis

Subsequent to the setup of static structural analysis, I launch the ANSYS Fatigue Tool using the following steps.

Setting up fatigue analysis
Solution>Insert>Fatigue>Fatigue tool

Analysis Type

ANSYS Fatigue Tool offers two methods to calculate fatigue life.

  • Strain Life
  • Stress Life

While strain life approach is widely used, at present, because of its ability to characterize low cycle fatigue (<100,000 cycles), stress life approach addresses high cycle fatigue (>100,000 cycles).

Specifying details in the fatigue tool
Details View of Fatigue tool

I chose the stress life approach to execute this example and subsequently I defined the appropriate S-N (Stress–Cycles) curve in the engineering data.

Loading Type

Contrary to static stress, fatigue damage occurs when stress at a point changes over time. Therefore, it is essential to define the way the load could repeat after a single cycle, in other words the type of fatigue loading determines how the load repeats over time.

Accordingly, I chose zero-based loading type for the current example, which means I apply the load and remove it, thereby resulting in an equivalent load ratio of 0. For a fully-reversed loading, I would apply a load and then apply an equal and opposite load which will result into a load ratio of -1.

Applying zero-based loading in fatigue analysis
Zero-Based loading

In both the cases the amplitude of load remains constant. Therefore looking at the single set of simulation results will give you an idea where fatigue failure might occur.

Mean Stress Theory

Now that I have defined analysis and loading types, I need to choose a mean stress theory.

Zero Mean Stress loading for fatigue analysis
Zero Mean Stress loading

Mean stress is the average of maximum and minimum stress during the fatigue load cycle. Mostly, fatigue data is assumed for zero mean stress, which means fully reversed loading. However, fully reversed loading conditions (zero mean stress) are rarely met in engineering practice. Hence Mean Stress Correction Theory has to be chosen to account for mean stress.

For stress life approach: If experimental data at different mean stresses exist, I can account for the mean stress directly by interpolating different material curves. However, it is unlikely to have experimental data at all mean stresses. Therefore, several empirical relations are available including Goodman, Soderberg and Gerber theories which use static material properties (yield strength and tensile strength) and S-N data to account for mean stress. In general, I don’t advise you to use empirical relations if multiple mean stress data (S-N curves) exists.

Different Mean Stress Theories for Fatigue Analysis
Different mean stress correction theories (Goodman Theory is highlighted)

Goodman Mean Stress Theory is a common choice for plastic materials, whereas Gerber Theory is a common choice for ductile metals. For the current analysis, I chose the Goodman Theory.

Fatigue Life

Like any other result in ANSYS Workbench, fatigue life can be scoped on a geometric entity. For stress life with constant amplitude loading, life at that point will be used if the equivalent alternating stress is lower than the lowest alternating stress defined in the S-N curve

For this example, 3,100,000 cycles is the expected life of the chair. This means that a person of 75 kg can sit on this child’s chair for 3.1 million times. If he ignores and continues to sit beyond the expected life, very soon he might face the same fate as the boy in the story.

Fatigue life extracted from ANSYS Fatigue Module
Fatigue life extracted from ANSYS Fatigue Tool
Conclusion

Wasn’t it easy? Yes, it is easy to perform this analysis provided you have the material data. In case you are not aware, ANSYS Mechanical Pro, Premium, Enterprise and ANSYS AIM offer ANSYS Fatigue Tool.

What are you waiting for? Start realizing your product promise using ANSYS products.

P.S. Just in case you were wondering what happened after the chair broke, my mother bought us a brand new chair the next day!

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