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Interpretation & Importance of Mass Participation in Modal Analysis

We often come across the dynamics or vibration problems in most of the product development across all industries. We have gained enough knowledge through the degree of Bachelors or Masters, with an example of the famous engineer disastrous design of “Tacoma Narrows Bridge-1940”, that considering the dynamics effects in design is quite critical. Generally, a dynamics problem is categorized into linear or nonlinear dynamics. This blog is related to the linear dynamics and nonlinear dynamics will be discussed in length in another blog. The most commonly heard terminology which we stumble upon in the design of such vibrating products is “natural frequencies“, “resonance“, “eigenmodes” etc. We have many linear dynamics simulation techniques such as “Harmonic Analysis“, “Random Vibration“, “Response Spectrum“, “Transient Analysis“, “Acoustic Analysis“, etc based on the loading it undergoes and also on the output we are interested in. But all these dynamics simulations start with the first step called “Modal Analysis“.

Modal Analysis

What makes something unique is an identity of its own, right? What if I say natural frequency is the identity of a body? Let’s see why. Assume you are imparting energy (striking) to a body. What will happen is obvious, the body will start to vibrate. But the vibrational frequency will be in its natural frequencies. It doesn’t matter how much or where you give the energy it will always vibrate in its natural frequencies, period. This is why the base of any dynamic analysis is said to be modal analysis as it shows its identity or behavior.

The modal analysis calculates natural frequencies and mode shapes of the designed model. It’s the only analysis that doesn’t require any input excitation or loads, which also makes sense, as mentioned before natural frequencies are independent of the excitation loads. Natural frequency depends only on two things mass and stiffness.

Why do we need to do the modal analysis?

Yes, we can find natural frequencies, and mode shapes through modal analysis but why to do it? Let me explain that through an example, when you ride a motorcycle, sometimes you might have experienced vibration in your handle. Some bikes have too much vibration that, you can’t even use your rear mirror. This is because the handle’s natural frequency is matching with engines RPM.

Structure borne noise: A structure makes peak noise when it’s vibrating in its natural frequency.

Whirling of shafts: To find the critical RPM of a shaft so that, crossing the critical speed will be done with precautions to avoid resonance.

Avoiding resonance is always preferred, thus shifting or modifying natural frequency can help to control, above mentioned issue. Natural frequency depends on only two parameters, modifying them will help to design a dynamic body part.

As an engineer, I always go in search of the physical meaning rather than proving by an equation. But at times equations are unavoidable.

Now let us see how we can get the natural frequency of a system.

Excitation force Equation of any dynamic system can be represented as

Every natural frequency is associated with each mode shape and mode shape represents the displacement behavior. There is enough material on the internet which explains mode shape. Right now, let’s concentrate on the “Mass Participation Factor” other important information from modal analysis, which would assist us in the simulation of other linear dynamic simulations. What is mass participation in general? Consider a 3 massed system as shown below.

The figure shown above is a mode of the system. Here masses participating in the X direction are M1 and M2 and thus total mass participation is M1 +M2. The only difference in FEA is that instead of lumped masses, the system will be discretized by elements.

Now let’s see ANSYS modal Analysis. Here I’m taking a cantilever beam, with 0.8478 kg. Having a cross-section of 3*60*600.

As you can see from the participation factor calculation. I have solved the first 12 natural frequencies. In this table, ANSYS solver calculates only frequency and Participation factor ie 1st and 4th column. Every other column is calculated from these two values. Let’s look at the most important column one by one.

As you can see this ratio is in direct comparison with total mass, which gives a better clarity on how much of the total mass participation is extracted. In other words, the sum of the effective masses in each direction should equal the total mass of the structure. But clearly, this depends on the number of extracted modes.

The same logic is for rotational mass participation. But here you might get ratios bigger than 1. Then, there can be confusion as mass participating is more than the total mass of the system? The answer is, participation factors for rotational DOFs are calculated about the global origin (0,0,0). The calculated effective mass essentially contains a moment arm (effective mass multiplied by the distance from centroid). Thus, the effective mass for the rotational DOFs can be greater than the actual mass and the participation factors can be greater than 1.0.

Ideally, the ratio of effective mass to total mass can be useful for determining whether or not a sufficient number of modes have been extracted for the “Mode Superposition” for further analysis. Modal superposition is a solution technique for all linear dynamic analyses. Any dynamic response can be calculated as the sum of the mode shapes, that are weighted with some scaling factor (modal coefficient). Also, the time step of the transient simulation is calculated based on the most influential mode in the modal analysis.

Modal analysis is usually done without considering any force or working environment. This assumption is taken by considering mass and stiffness to be constant. But at times this doesn’t work, like a pressurized vessel or pipe. As compressive or tensile force changes the stiffness. In such cases, we have to do a prestressed Modal Analysis.

In some cases, like rotating shafts with motors, turbines, the natural frequency will not match with the working condition. This is because, for different RPM, stiffness also changes,(Centrifugal force changes). In these cases, we need to consider the rotational speed of the shaft. In ANSYS Modal Analysis (Rotodynamic Analysis) rotational speed with Coriolis effect can be directly given to find the critical speed of the shaft.

Modal analysis is a prerequisite for all linear dynamics analyses like Harmonic, Random vibration, and Response spectrum analysis. Hence Modal Analysis plays a huge role wherever you are trying to find out vibration characteristics of a design. Thereby it is relevant for most industries like Rotating machines, construction, automobile, Machine tool, agricultural equipment, and Mining.

Engineering Simulation opens up a huge range of possibilities. Since CAE–simulation requires more than just software, we at CADFEM help our customers to adopt simulation for success in every phase of product development, thereby enabling them to realize their product promise.

Please click here to understand more about NextGen Engineering Simulation Possibilities.

Please feel free to connect with us at marketing@cadfem.in or +91-9849998435, for a quick Demo on this Product.

Author Bio:

Mr. Vineesh Vijayan, Application Engineer

CADFEM India

Mr. Vineesh Vijayan has done his Master of Technology in Machine Design. With good expertise in Structural Simulation currently, he is contributing his efforts to CADFEM India as an Application Engineer.

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Open the Door to Material Optimization

Introduction:

The world is evolving at a quantum speed with transforming technology. The human life cycle has enriched to tend towards advancement in every sector. Businesses have adopted the transformation & obtained the benefits of technology involved in their mainframe process to become multi-billion companies. Making the product a hero in every story, Engineering the product or designing a physical product demands focus on four major factors; Design, Analysis, Manufacturing, and Materials. Though the first three factors are digitally transformed, the materials field is still lagging. This article exclusively focuses on optimizing your right material choices.

Let’s start with an example of a company facing a similar conundrum.

Background:

Referring to the case of an OEM, that manufactures an industry renowned product.

Due to the stringent industry standards and to stay ahead of the competition, the company decided to optimize their existing product and its performance. Following the advancement, they relied on simulation results for quick feedback from different design iterations. Furthermore, parametric optimization yielded them even better results compared to the manual design iterations. Overall, they were able to achieve a 9% Reduction in Weight and a 5 % Increase in Efficiency through Design Optimization.

Much to the Team’s surprise, the product manager wasn’t satisfied with this result. Hence, he assembled his team to initiate an experiment with different material types.

The broader idea of this activity was to understand how he could improve his product and cut down costs to the company, thereby naming this activity as Material optimization.

Optimized Product = Design Optimization + Material optimization

Following the superior’s directive, the team started dedicating their efforts to bring the best out of current results, in terms of cutting costs, reducing development time & raising standards of performance. Four of his team members heading the R & D were investigating the case study with different ideas as below.

The first member tried to use the existing available material data with him to see if he can get the best possible combination;

The second member tried to use the materials preferred by his company to avoid supply chain issues;

The third member tried to reach out to suppliers/consultants for a piece of advice on material choices; and

The fourth member tried to browse on the internet for material data.

However, none of the above approaches answered the below questions

Which material to choose?
Is there a better material choice available?
Is there a cheaper solution?
Is the chosen data, reliable?

This is where companies need a tool like, Granta Selector which does answer the above questions.

Granta Selector is a tool that can help optimize your material choices, which not only has material properties of metals, plastics, polymers, ceramics and various other classes of materials but also has features like search, plot and compare your choice of materials as shown in the pic.

Apart from the features mentioned above, Granta selector has:

FE export tool to export simulation ready material data to most of the FE platforms
synthesizer tool to estimate material and process cost
Eco Audit tool to estimate the environmental impact of the selected material at the early stage of the design.

To use how to use above-mentioned tools, click here to understand how Tecumseh, a global leader of commercial refrigeration compressors used Granta Selector to reduce development time by three-fold and saved millions of euros of cost savings from making the right materials decisions.

please click here for more information on Material optimization.

Please feel free to connect with us at marketing@cadfem.in or +91-9849998435, for a quick Demo on this Product.

Author Bio:

Mr. Gokul Pulikallu, Technical Lead-South

CADFEM India

Mr. Gokul Pulikallu has done his Bachelor of Technology & he is carrying 9 years of experience in the field of structural Mechanics simulation and optimization. His main focus is Design Optimization & Material Optimization and helps customers adopt these technologies efficiently.

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ANSYS Structures R19 – Release Update

This post discusses latest developments and enhancements in ANSYS Structures R19 applications. Maximize your RoI and productivity with the latest ANSYS release.

Today’s ever-changing and increasingly-competitive world makes life complicated for product developers such as you. Hence, you are perpetually in a race to launch better products and increase profitability.

In order to help you realize your product promise, we are glad to introduce you to ANSYS Structures R19 with various improvements and additions. As a result of the new release, you’ll find exciting and innovative technologies which make the development of complex products effortless with help of improved solver capabilities, better usability, integration of complex physical phenomenon and solver scale-up using HPC.

Enhanced Utility and Scale-Up

This year ANSYS brings in some radical changes to help you capitalize on your current and future ANSYS investments. Starting off, the following will enhance the utility of ANSYS for many applications and help in speeding up run time.

The inclusion of small sliding algorithms helps significantly reduce the time involved in contact detection by performing contact search only at the beginning of the analysis. So, this leads to faster solutions.

Additions to the user interface such as Selection Clipboard helps you save selection information intermittently. Hence you can retrieve it whenever necessary to define BCs, Named Selection, etc.
Material Plots help in visualizing material assignments to the components and also to have a holistic understanding of materials in the assembly.
Improvements in meshing and contact algorithm is another development. Therefore, this will lead you to a faster problem definition in the interactive environment of ANSYS Mechanical.

ANSYS Structures R19 Update — Speedup with DMP Scaling

Compute with 4 cores as default across entire ANSYS Mechanical (Pro, Premium, Enterprise) product lineup. Hence more value for your investments!
Achieve 3X scale-up using HPC with improved Structures R19 Solvers and utilize HPC Pack across entire ANSYS product portfolio. Therefore, your problems run faster and better!

Effortless Modelling of Complex Phenomena

Increased use of simulations across various industries requires engineers to simulate complex phenomenon. ANSYS Structures R19 helps make simulation of complex physical phenomena seem effortless.

SMART: Separating, Morphing, Adaptive and Re-Meshing Technology (SMART) makes simulation of Fatigue Cracks easy and interactive. SMART fracture capabilities simulate crack growth without the need for crafted meshes.
Coupled Physics: New 22X elements help in achieving a magnetic coupling of Structural and Thermal with Magnetic DOFs.
Enhanced FSI coupling allow faster data transfer between CFD and Structural Solvers.

ANSYS Structures R19: Other Noteworthy Enhancements

Additional data import from external models
Element Birth and Death as Native Mechanical Feature
Quick and Easy RST import
Improved NLAD-based Simulation for physics involving Large Strains
Beam to Beam Contacts
Higher Scaling in DMP

In conclusion, this article serves as a good foundation to further understanding. There is much more to learn about ANSYS Structures R19. Join us on April 12 for the ANSYS Structures R19 Update Webinar to get the details! Register now.

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ANSYS Fluids R19 – Release Update

This post discusses latest developments and enhancements in ANSYS Fluids R19 applications. Maximize your RoI and productivity with the latest ANSYS release.

How we use simulations has changed drastically since its inception. A couple of decades back simulations were majorly used for research purpose. But today it is used for various applications ranging from airplanes to microfluidics. Simulations have also evolved to handle more complex problems in smaller run times. ANSYS, a leading simulation software company is constantly innovating to make simulation easier to use and at the same time making them more robust. With every release, the GUI is getting better and the solver is getting smarter. Hence, without further ado, let’s take a dive into a few enhancements in ANSYS Fluids R19.

In this article, I will discuss some of these developments however, I recommend you to join the upcoming webinar that I will deliver on April 17.

Enhancements for Spray Modelling

The new feature in ANSYS Fluids R19 would significantly reduce the computational effort needed for spray nozzle designers to optimize product performance. CFD has been used for modelling sprays for a while now. Multiple approaches are available for spray modelling namely, full resolution (resolving all the length scales in the spray), semi-empirical (uses empirical correlation for droplet break up and stability analysis to generate droplet data), etc. ANSYS Fluids R19 has significantly enhanced spray modelling using VOF (volume of fluid)-to-DPM (discrete phase modelling) approach. As a result, you can directly track interface instabilities and surface tension effects that result in ligament and droplet formation. Due to this, you’ll get fast, accurate spray breakup and droplet distribution with minimal effort.

ANSYS Fluids R19 - Simulation of Fuel Injector — Simulation of high pressure fuel injector spray (Fluent R19)

ANSYS Fluids R19 - Spray Jet Simulation — Simulation of a Spray Jet in Cross Wind (Fluent R19)

Accurate Preventive Maintenance

Engineers seeking to maximize up time and optimize preventive maintenance programs need to reliably predict the location and extent of erosion in pipelines that are carrying particle-laden flows. Previously, static meshes could not account for structural changes in the pipe caused by erosion and its subsequent impact on fluid flow, thereby reducing prediction accuracy. New technologies in Fluent R19 automatically couple structural changes due to erosion with a dynamic mesh so that the simulation more fully captures the degradation arising from erosion.

ANSYS Fluids R19 - Erosion Modeling — Erosion Modeling

More Computational Power

To empower the users with more computational power, significant changes have been made to the High-Performance Computing (HPC) solution.

High-Performance Meshing Technologies that help in meshing the complex geometries at lightning speed. Higher Productivity.
All core solver technologies utilize four (4) cores without HPC License Checkout. HPC products add on top of these four cores. Hence, this gives you more value for money.

ANSYS Fluids R19: Other Noteworthy Enhancements

Blade flutter modelling
Risk assessment for Urea Solid Deposition for SCR
Lagrangian wall film
Thermolysis model
Local residual scaling for multiphase
Shar/Dispersed discretization schemes with Mixture Multiphase
FSI: Accurate leakage flows through narrow gaps
Species mass transport improvements
Cavitation modelling improvements
Native rolling ball fillets
Variable shroud gap
New Workbench templates

In conclusion, this article has only covered the tip of the iceberg. There is much more to learn about ANSYS Fluids R19. Join us on April 17 for the ANSYS Fluids R19 Update Webinar to get the details! Register now.

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ANSYS HFSS R19 – Release Update

This post discusses latest developments and enhancements in ANSYS HFSS R19 applications. Maximize your RoI and productivity with the latest ANSYS release.

With the advent of one more new year, ANSYS has released a new Electromagnetics Suite with a new, dynamic and user-friendly interface. Evidently, the new release also comes with more computation power and new license packaging which will deliver an incredible amount of value to the current and future customers. In addition, ANSYS follows the tradition of taming complexities and spurring the productivity with every new version. Consequently, there are several new features announced in ANSYS HFSS R19 for you to consider!

In this article, I will discuss some of these developments however, I recommend you to join the upcoming webinar that I will deliver on April 10.

ANSYS HFSS R19 - ED 2018 — Electronics Desktop 2018

Taming Complexities

ANSYS 19 tames complexity by supporting and empowering engineers with tools that amplify your engineering effectiveness, performance, speed and ease of use.

ANSYS HFSS R19 delivers an all-new Radar Cross Section (RCS) calculations, by integrating Savant (HFSS SBR+) capabilities into ANSYS Electronics Desktop for tighter integration for large-scale problems. More so, this capability is based on ANSYS’ industry-leading shooting-and-bouncing ray plus (SBR+) method to predict far-field radar signatures for 3-D target models. The powerful and accurate asymptotic methods of HFSS SBR+ allow our users to solve computationally large simulations very quickly and is a great asset for engineers designing military and aerospace applications, such as advanced target recognition systems and stealth technology

RCS Simulation in ANSYS HFSS R19 — RCS Simulation

Spurring Productivity

With every new release, ANSYS promises deliver solutions that greatly enhance productivity and create a more seamless workflow at every stage. Therefore, ANSYS has constantly been empowering engineers to accomplish more in shorter timelines.

R19 comes with a new interface. Specifically, the ribbon-based interface improved the overall flow from modeling to setup solving of the problem. As a result, users with little or no simulation experience can easily understand the simulation workflow, set up and solve high-frequency electromagnetic field simulations. Hence this would greatly increase the productivity and reduce the learning curve.
To empower the users with more computational power, two significant changes have been made to out our High-Performance Computing (HPC) solution. Furthermore, some notable improvements in the solver speed with GPU acceleration. Therefore, these developments would reduce the computation time for faster time to market.
- Now all core solver technologies utilize four (4) cores without HPC License Checkout. HPC products add on top of these four cores. Hence, greater value for your money!
- Finally, ANSYS has unified the electronics high-performance computing (eHPC) with the other ANSYS HPC licenses. One ANSYS HPC license for across all physics!! Consequently, this development will increase the productivity of your HPC licenses.

Therefore,with all these enhancements, ANSYS HFSS R19 delivers the most comprehensive set of solvers and HPC technologies in a single package on the market. In conclusion, users can now perform more comprehensive design exploration through simulation using the accurate and reliable gold standard technology of HFSS.

ANSYS HFSS R19: Other Noteworthy Enhancements

New Ribbon Interface for all Desktop Products helps streamline process
Auto-complete of the variable name
Optimetrics enhancements
Local editing of 3D component
Special selection and show/hide modes
ANSYS EMIT: RF Link Budget Analysis
Improved Phi Meshing Robustness
Added the Capacitor Library Browser to 3D Layout
Added TDR analyses for LNA and Imported solution
Top & Bottom surface roughness supported for metal layers in 3D Layout
Enable Field Links for Finite Array DDM
HFSS Transient solver included with HFSS
Enhanced GPU Acceleration of Direct Solver
SBR+ for RCS with PTD & UTD
Added Iron Python IDE command window for SIwave
New “Special Selection” Modes
“Simulation Setup” export/import added for all simulation types

Lastly, you should know that ANSYS, Inc. is currently working on many more additional improvements and is looking forward to introducing more features in upcoming updates.

Get Latest Updates?

Visit Here to download the latest software & update. Please reach out to support@cadfem.in if you facing any issue with the upgrade.

There is much more to learn about ANSYS HFSS R19. Join us on April 10 for the ANSYS HFSS R19 Update Webinar to get the details! Register now.

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Transfer Chutes Design with Rocky DEM

This article focuses on how engineering simulations help better design transfer chutes for their smoother functioning and enhanced equipment life.

Transfer chutes are used widely for handling bulk materials. They can be used to change the direction of material flow and transfer material from one conveyor to another conveyor. A chute might seem to be a petty component in a huge plant, but it plays a significant role. If you don’t design the chute properly, you’ll witness a high maintenance cost, increased downtime and particle breakage. On the other hand, a well-built transfer chute can help reduce noise, decrease damage to conveyor belts and transfer chute walls, and reduce dust formation.

Prior to getting to design, I will list down the essential requirements for a good transfer chute design:

Avoid material clogging
Minimal equipment wear
Minimal material degradation

DEM-Based Approach for Designing Transfer Chutes

Getting the optimum chute design is a time-consuming task because transfer chutes are not designed properly most of the times. For the above-mentioned design considerations, there are many constraints that you will need to apply while designing transfer chutes.

Discrete Element Method (DEM) can help designers such as you design better transfer chutes in lesser time. DEM can help you visualize the flow of particles (material) in transfer chute and provide useful data pertaining to each particle and all the boundaries in the chute. Needless to say, it is impossible to derive such level of detail from physical trials or finite element analysis. Besides providing much needed qualitative insights, DEM simulations enable you with the freedom to explore new designs and test them without the need for physical trials.

In the following sections, I’ll explain how Rocky DEM software will help you design high quality transfer chutes.

Avoid Material Clogging

Blockages in transfer chutes restrict the flow of material through the chute. Not only are blockages a detriment to the transport efficiency, but also they exert a lot of stress on the chute walls leading to serious damage. To make transfer chutes less prone to material blockages, impact angle should be decided based on material properties and inlet speed should also be tweaked accordingly.

Rocky DEM has all the capabilities necessary to address the needs for wet and dry material handling. Different material properties such as the rolling friction, static friction for particle interactions, elastic modulus, bulk density, adhesion coefficients can be accounted for. A unique capability of Rocky DEM is the availability of adhesion models that can replicate the flow of wet materials. This would foster the simulation of materials such as wet mortar in the construction industry or some crucial unit operations with wetting ingredients in the process industry.

Rocky DEM helps to model blockage and design better transfer chutes — Rocky DEM simulation showing blockage (blue colored particles are stationary)

Minimize Equipment Wear

Wear leads to increased maintenance cost not only for transfer chutes, but also for the conveyor belt. Abrupt changes in material flow direction is one major reason for surface wear. The smoother the flow, the lesser will be the damage to transfer chutes. The angle at which the material hits the walls of the chute largely affects the wear. This angle will depend on the material velocity and properties of the material. Modification can be done to the chute design to minimize wear, such as by adding a curved guide surface at the mouth of the chute to direct the flow and make it smoother.

As you will understand, making these changes in physical trials and capturing test data is cumbersome. With Rocky DEM, this task is just a few clicks away. You can use any CAD tool to make geometry changes and then bring it into Rocky DEM to simulate performance of modified designs. Rocky DEM will provide you wall impact force; using this, you can decide the optimum velocity and finalize the most suitable design for the transfer chute.

Rocky DEM simulations showing Instantaneous Shear Power for transfer chutes — Instantaneous Shear Power for a transfer chute

Rocky DEM simulations showing Mean Shear Power for transfer chutes — Mean Shear Power for a transfer chute.

Minimize Material Degradation

The quality of the end product decides its price. Undesired material breakage and extravagant segregation or degradation can lead to a poor quality process outcomes. Particle degradation occurs due to impact on chute and shear either from collisions with walls or with other particles. Information about the forces that a particle experiences can give an indication of how much damage will occur.

Rocky DEM not only provides forces on each particle, but also simulates breakage of particle under higher forces using models which are backed by years of research. You can visualize the particle actually breaking into fragments as it proceeds through the chute.

Rocky DEM: Helping You Engineer Better Transfer Chutes

Designing Transfer Chutes is a complex process and testing multiple designs is an expensive affair. However, Rocky DEM makes it simpler, cost-effective, lesser equipment maintenance and upkeep, and helps you to produce a better quality product. It has the ability to

analyze large number of particles quickly due to its multi-GPU capabilities,
represent particle shapes used in your industry, and
multiple post-processing options to help you analyze the data efficiently.

Quite clearly, Rocky DEM will help you and your organization minimize prototype costs and product development times. You’ll recognize that these benefits will further accelerate product launches into the market and fetch your organization higher profitability margins.

Still curious to know all of this actually works? I’m going to speak in a webinar called Assessing and Improving the Bulk Material Handling Practices with Rocky DEM Simulations on February 15th at 2:30 PM IST. Come, join me in an hour of learning how Rocky DEM simulations can help you save and generate more revenue for your bulk handling business.

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ANSYS Discovery Live: Simulations for ALL

This article introduces you to a new, revolutionary technology called ANSYS Discovery Live. This technology provides instantaneous simulation results through an interactive design exploration experience for fluids, structural, and thermal studies.

With the inception of 4th industrial revolution, also called Industry 4.0, every industry is changing rapidly with groundbreaking innovations. In turn, this has placed a severe strain on the product development cycle. Innovative products need to be brought faster to market to reduce opportunity cost. This context has only reinforced my belief to expand the Simulation-Driven Product Development approach like never before.

Engineering simulation, though utilized for industrial applications for several years, is still underused and used by experts. A decade ago, it was difficult to learn and master such a technology. Often executing a simulation task end-to-end took time to set up and run. In 2007, ANSYS, Inc. launched ANSYS Workbench as, what I believe was, the first step to democratize simulation adoption. Since then, and along with rapid advancements and easy availability of computer hardware, simulation adoption has grown leaps and bounds.

Greater Power to Design Engineers?

However, until late last year, I felt that there is a stronger need to foster a greater collaboration between the design and simulation engineers. From my experience, I have seen simulation engineers complain about “geometry cleanup for simulation of each design” on one end and design engineers complaining about “huge time taken by an analyst for each design validation” on the other end. With such a to and fro between both teams, there is such a huge market need that needed to be filled. Though there are many engineering simulation software products in the market, no one could democratize the simulation to potentially elevate the role of designers in product development. Although the design engineers have a very important role to play in the product development cycle, they have largely been restricted to developing CAD models at best.

In Fall 2017, ANSYS, Inc. conducted a webinar on a new, revolutionary technology that was going to “change how the simulation was done”. My colleagues from CADFEM Germany called it Das ist der Hammer (translation: it’s awesome). Rarely does a product match its hype, but several of us were blown away while watching the webinar on ANSYS Discovery Live (ANSYS DL). In a whole lot of ways, ANSYS DL is disruptive and it made me rethink how I have been doing simulations.

What is ANSYS Discovery Live?

ANSYS Discovery Live is the newest technology from ANSYS, Inc. HQ at Canonsburg, PA. With this technology, every engineer can use to perform instantaneous multiple physics simulation of virtual prototypes to understand the behavior of the product design.

The development team has leveraged on the advancements in Graphical Processor Units (GPUs), developed new discretization techniques along with their knowledge of advanced parallel solver technology. ANSYS DL is built on Direct Modeler tool called SpaceClaim platform to import and modify the solid geometry with ease. Once you define the physics and boundary conditions, you’ll get results in no time. This is instantaneous, real-time simulation! The technology in ANSYS DL has automated the steps of meshing, building the finite element model, solving and extracting the results in few seconds to give you an insight into your design.

Why is ANSYS Discovery Live Unique?

Instantaneous results show up for any change in geometry. No need to setup the simulation again. [VIDEO: 50 Simulations in 15 Minutes]
It combines GPU-based solvers for multiple physics.
You can easily integrate ANSYS DL with flagship ANSYS, Inc. products for advanced studies.

How does ANSYS Discovery Live change things?

Design engineers tell me frequently that several ideas go untested and they are totally dependent on the analysts. I could hardly do anything, but empathize with them. On the other hand, executing any simulation task leaves analysts with limited time to explore different design concepts.

With ANSYS DL, design and simulation engineers can quickly discover the behavior of their product live and instantaneously. ANSYS DL has created a fundamental shift by moving from design verification to experimenting and gaining deeper understanding. This is a huge benefit because you can evaluate several design iterations early in the design cycle. The ease of setting up the problem in ANSYS DL enables design engineers to quickly check the ideas in a shorter time frame. This also allows them to reduce dependency on the simulation engineer. The latter will still continue to perform traditional simulation tasks, but ANSYS DL gives design engineers more power to contribute to product development.

ANSYS DL marks the next step by ANSYS, Inc. to further democratize simulation adoption across different industries.

How can CADFEM help you?

Greater Understanding of Hardware for Simulations. Partnership with major brands such as HP and NVIDIA allows us to help you select the appropriate hardware for your simulation tasks.
Strong technical expertise will help you solve your engineering problem.

Download ANSYS DL & Attend Webinar

ANSYS DL is available as a Technology Preview until February 7. With this preview, you can test the pre-release locally on your machine by downloading or through your favorite internet browser.

Download ANSYS DL today. Also you must attend the ANSYS DL Webinar as we kick start the 2018 CADFEM Technical Webinar Series. You can do this by accessing the below links.

DOWNLOAD ANSYS Discovery Live (until Feb 7). You will need to register using a form and then you’ll get instant access to this exciting technology!
REGISTER for WEBINAR: Simulations are Now Accessible to Every Engineer (Feb 1 at 2:30 PM IST)

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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 connectivity 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 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 driving, 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:

Using cell zone conditions
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 = ∆p_Viscous + ∆p_Inertial

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.

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

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!
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.
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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