Discrete Element Method for better Mining Operations

The mining and mineral processing industry operate in a very high tonnage range which makes the equipment more prone to damage and wear. This also means that testing new designs at plant scale would lead to material wastage and time loss.

Another aspect that differentiates the mining and mineral industry from others is the fact that the raw material keeps changing from season to season. In the rainy season, the material will be wet and sticky and in summer it will be dry. This requires the design engineers and researchers to come up with a design that can work in both these conditions.

Discrete Element Method is a proven tool for designing and troubleshooting equipment. Mining and Mineral companies across the globe have included DEM in their development process and routinely use them for troubleshooting. In this blog,

What value will a DEM tool add?

Any simulation technology will help the user to get a deeper insight into their equipment/process. Testing at the plant scale also becomes an easy task as there will not be any material loss and downtime of the plant required.

Let’s take a very simple example of a chute. In case of a decrease in throughput of the chute, it becomes difficult to understand the underlying reason sometimes. Identifying the right area where material clogged will be really helpful in increasing the throughput. A DEM simulation can show the velocity profiles of all the particles inside the chute which help us identify the faulty region. Getting this type of insight from the real chute will be difficult as that would require us to have a chute made of transparent material which is impractical at plant scale.

What processes will I be able to design/troubleshoot?

Almost all mining-related processes can be handled using DEM. Here is a non-exhaustive list:

  • Excavation at the mining site
  • Wagon loading and unloading
  • Primary crushing
  • Stockpile
  • Conveying operations
  • Screening/sorting
  • Blast furnace
  • Fluidized beds
  • Packed beds

Is DEM capable of handling real-life material loading conditions? RockyDEM uses the power of multi-GPU processing to make plant scale simulations reasonable. Figure X shows a comparison of CPU vs GPU vs multi-GPU. Using multi-GPU will help us make these simulations way faster when compared to CPU. But that’s not it, with the new modules being introduced inside RockyDEM, the data saving time has decreased which would lead to total time-saving. Also, the advanced contact detection method helps reduce overall simulation time. We can further reduce the simulation time by using the Coarse Grain Model.

Figure x- Scalability using CPUs, GPUs and multi- GPU`s

How can I be sure that the simulation results are accurate?

All the models are implemented in Rocky are well-validated which means that we do not have to worry about the models predicting the behavior if supplied with accurate inputs. The most important input required will be material properties. To extract the material properties and correlate them to simulation parameters, calibration is required. For example, an angle of repose test which can be performed in the lab should also be performed with RockyDEM virtually and the same behavior should be replicated. Properly calibrated material properties will provide us with a highly accurate result.

I would also like to understand the effect of particle flow on my equipment, how can RockyDEM help me with that?

RockyDEM has some in-built post-processing capabilities which can be used to plot contours of stress and force on the equipment. RockyDEM is also integrated with ANSYS products like ANSYS Mechanical. So, the force maps from RockyDEM can be transferred to ANSYS Mechanical and a structural simulation can be performed to evaluate deformation, etc.., We can also perform a transient coupled analysis with ANSYS Mechanical.

We answered a few questions which any mining company might have while thinking about adopting simulations. Keep an eye on this space.

Author Name: Mr. Ishan Vyas (Application Engineer at CADFEM India)

Profile Bio: Mr. Ishan has completed his bachelor’s in Chemical Engineering with minors in Material Science. He is currently associated with CADFEM as an Application Engineer in the CFD and DEM domain. He holds an experience primarily in the areas of applications related to Chemical, pharma, oil, and gas industry involving both CFD and DEM codes. The Simulation of Chemical processes implementing DEM for New product development deeply interests him. He is an avid reader and loves Adventure sports.

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Wield Enabling Tool to Master CFD Meshing

The quality of essential simulation output depends absolutely on getting the mesh right. The kind of refinement and the type of mesh used should go by physics in place. For instance, a flow with dominant turbulence generation from the boundary layer separation needs a better focus on the boundary layer refinement to keep the Y+ = 1. A premixed combustion simulation in a SI engine will require an LES turbulence model and therefore a mesh refinement in the bulk to capture about 80% of turbulence kinetic energy there. Cases with moving parts in a fluid flow have to mesh with a priority to avoid negative volumes through dynamic meshing. Narrow gaps, a long list of parts in a big automobile assembly, etc.., are some overhead complexities demanding diligent craftsmanship.

This blog article shall apprise on the befitting advantages of “Ansys Fluent meshing” to thrive through such challenging meshing tasks

Endorsing motivators to adopt and benefit from Ansys Fluent Meshing

  • Generates polyhedral meshes, polyhedral prisms can easily uphold mesh quality for refined boundary layer regions.
  • Offers wrapping advantage to mesh large assemblies.
  • Parallel mode execution without using any HPC licenses, consistent speed scale-up.
  • Can run with both Solver and Pre-post license.

I choose to narrate some of my recent personal experiences as a CFD user to shed more light on these features of flair, which is worth a deep dive. Going by its craft, an electric motor meshing pursuit is the best fit to kick off this section.

While performing a Conjugate heat transfer analysis for an electric motor I faced few challenges with mesh generation. Fluent meshing with its guided task-based workflows and best in place algorithm helped in meshing complex geometry with good quality within less time & economical mesh count. In this post, I will be discussing the fluent meshing approach & how it helped with the pre-processing for motor thermal analysis.

For the electric motor analysis, I was able to achieve conformal mesh with good mesh quality but the mesh count was higher initially. Higher mesh count will consume more solving time & hence I was looking up for options that can help me reduce the mesh count & still preserve the mesh quality. One of the reasons for high mesh count was the proximity settings where the solids were also meshed with a fine sizing to maintain conformal mesh. So, a non-conformal mesh approach was utilized with solids having a bit coarse mesh which provided an advantage to generate a fine mesh to the fluid regions. With fine-mesh confined to the fluid regions, mesh count with a non-conformal approach was reduced to ~60%. But with non-conformal mesh, I had to invest time in assigning the mesh interfaces, which eventually consumed more time as multiple mesh interfaces are involved.

The same model was tried in fluent meshing under the conformal polyhexcore mesh approach, this time with prism boundary layers included. 8 cores were used for parallel meshing which exponentially reduced the meshing time. The mesh count was reduced to 40% compared to the tetrahedral mesh & the mesh quality was within the acceptable limits. For the boundary layer resolution as well, the polyhedral prisms helped in maintaining the quality compared to tetrahedral prisms within narrow air gap regions. Results for the 3 cases were compared & there was a good agreement. So, from this experience, I observed that fluent meshing can help in reducing the pre-processing time to a greater extent & I would highly recommend this approach. In the next part, I will be discussing more regarding various capabilities provided in fluent meshing which will highlight the extent to which fluent meshing can simplify pre-processing work.

Fluent meshing is developed with the capabilities to provide native polyhedral mesh which helps in reducing the mesh count while preserving the mesh quality. It is integrated with fluent to form a single-window workflow for CFD simulations. So, one can switch directly from fluent meshing into fluent setup, solution & post-processing module. Additional advantages are parallel meshing where one can utilize parallelization over multiple cores not just for accelerating solving but also meshing which can reduce the pre-processing time drastically. Polyhedral prisms can fit in narrow gaps without suffering distortion compared to triangular prisms which are good for boundary layer resolution. The task-based workflows provide a guided stepwise meshing approach using which one can setup meshing parameters & can edit them later if the mesh resolution is not as expected. Fluent meshing can perform conformal mesh for Watertight geometry by capturing all detail features within the geometry. In case of poor quality with surface or volume mesh, one can add a “improve mesh” option which activates the auto node movement option to improve the quality of mesh to the desired value. Apart from tetrahedral, hex-core & polyhedral meshing, Fluent meshing offers a unique option of polyhexcore or Mosiac meshing technology.

For More Information on task based Meshing watch the webinar

For dirty geometries with leakage and overlapping parts, an analyst has to spend hours preparing a watertight geometry for simulation. Fluent meshing is equipped with a Wrapping technology to capture the complex or dirty geometry. Developing a watertight geometry for components like engine or complex assemblies can be a time-consuming activity. Under hood analysis with complex & interfering geometries like engine, radiator & chassis can easily mesh with wrapping technology. Native cad file formats like STL & step or can be directly imported & part management can be performed to select the simulation model. While meshing a dirty geometry some complex features which have less impact on the simulation results can be overlooked using wrapping technology. In case the wrapper has missed any features of interest than using the edge feature extraction method one can fine-tune the wrapping function. Another option of Leakage detection allows the wrapper to patch the leakage in geometry below the provided threshold value thus eliminating the tedious need to work at the geometry level. Fault tolerant YouTube video.

For More Information on Wrapping Technology watch the Webinar

In a nutshell, fluent meshing can incorporate any type of geometry, and using the appropriate mesh strategy one can develop high-quality meshes with appreciable ease. Considering the type of complex products being deployed into the market, fluent meshing with wrapping technology and guided workflows is definitely the promising technology to reduce the overall pre-processing effort.

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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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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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Fluid Dynamics – ANSYS 18 Innovations

ANSYS Release 18 is packed with lot of innovative features for computational fluid dynamics. This article summarizes the various advancements in the new release.

As always, ANSYS has delivered continuous product advancements. The latest release features several beneficial capabilities.

With ANSYS 18, engineers can create better, more accurate computational fluid dynamics (CFD) simulations. Therefore, engineers new to CFD will benefit from greatly expanded capabilities in easy-to-use ANSYS AIM, including support for transient flows, non-Newtonian fluid viscosity and fluid momentum. In addition, ANSYS 18 includes new features and functionality that enables engineers to solve CFD problems with more accuracy than ever before. Further breakthrough harmonic analysis delivers accurate turbomachinery simulations up to 100x faster. ANSYS 18 also introduces CFD Enterprise, the first solution designed for CFD experts in organizations who need to solve the toughest problems.

Here are the release highlights.

GUI & Advances in Post-Processing

The new release has better CAD import, enriched post-processing, well-organized realization of different volumetric domains and surface boundaries. Also the sophisticated solution monitoring and elegant post processing views make up for a delightful user experience with ANSYS 18.

Fluid Dynamics: Velocity vectors and pressure contour in a pump-valve operation, now displayed with enhanced graphics in ANSYS Fluent
Velocity vectors and pressure contour in a pump-valve operation, now displayed with enhanced graphics in ANSYS Fluent

Better Physical Models
  • Heat Transfer and Combustion. Monte-Carlo radiation model helps capture high temperature radiation in solid domains with better ray tracing implementation. Further on, enhanced flamelet modeling gets combustion analysis running better with ANSYS 18.
  • Multiphase Flow Models. Chemical mixing and other fluid blending processes benefit by the convergence and significant speedup improvements for free surface transient flow simulations with the Volume-of-Fluid (VOF) method.
  • Turbomachinery Enhancements. You can solve blade flutter cases more efficiently by using harmonic analysis. In addition, flank-milled blades can now be better modeled with ANSYS BladeModeler.
Solver Enhancements

Lastly with solver enhancements, mesh adaption of polyhedral meshes in ANSYS Fluent is now possible with its improved execution. Another aspect is that of overset meshing which is ready to better support the aerodynamic community.

Fluid Dynamics: Flow impact on an offshore structure - Robust free surface flow simulation with enhanced VOF model of ANSYS Fluent
Flow impact on an offshore structure – Robust free surface flow simulation with enhanced VOF model of ANSYS Fluent


Do you want to learn more about ANSYS 18 innovations for computational fluid dynamics? Join our webinar on March 23. There’s a lot to learn!

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ANSYS 18.0 – The latest release is here!

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The day has arrived!! Most of our customers would’ve received announcement of the latest release – ANSYS 18. It’s time to rejoice and celebrate this new release.

ANSYS 18.0 ushers in the era of pervasive engineering simulation – an era where all types of engineers use simulation throughout the entire product lifecycle. While simulation was once the primary domain of experts and used mainly for verification, it is now moving upfront in the development process to quickly evaluate changes in design. At the same time, it’s also moving downstream of the product lifecycle process to analyze real-time operational data from connected machines in the industrial internet.

By incorporating simulation into all segments of a product’s lifecycle, ANSYS 18.0 adds tremendous value by spurring innovation, reducing development and operational costs, and improving time to market. Whether your field is structures, fluids, electromagnetics, semiconductors, systems, embedded software or some multiphysics combination of these areas, ANSYS 18.0 is the simulation platform to achieve your engineering and business goals.

Digital Launch Event

To learn more about pervasive engineering simulation and ANSYS 18.0, we invite you to the digital launch event on January 31. During this event, the ANSYS CEO, Ajei Gopal, and numerous technology leaders from industry will talk about this exciting new release from ANSYS. Here’s the line-up of the speakers from ANSYS:

  • Ajei Gopal, President and CEO, ANSYS, Inc.
  • Andre Bakker, Senior Director Fluids Development, ANSYS, Inc.
  • Dale Ostergaard, Senior Director Software Development, ANSYS, Inc.
  • Larry Williams, Senior Director Electronics Products, ANSYS, Inc.
  • Sergey Polstyanko, Senior Director, Research and Development, ANSYS, Inc.
  • Eric Bantegnie, Vice President and GM Systems Business Unit, ANSYS, Inc.

In addition, you can also learn more about ANSYS 18.0 by visiting the “What’s New” section of the Customer Portal.

Current Customers – Next Steps

Current customers can download ANSYS 18.0 from the Download Center on the ANSYS customer portal.

You need a license manager upgrade to run ANSYS 18.0 products. Your current license keys will continue to function with the new 18.0 license manager. Support for operating systems, graphics cards, third-party CAD products and more is available on the Platform Support page.

If you need any support, please feel free to contact us.

Together with ANSYS, we are excited to bring you this latest release. This comes as the result of countless hours of work by 1,000+ professionals in the research and development organization. We believe it will exceed your expectations and provide considerable value in your engineering processes and product lifecycle.

May the force always be with you! 🙂

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Weekly Simulation Round-Up | Issue 5

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Welcome to a brand new edition of Weekly Simulation Round-Up. As usual, we present you the most interesting articles from this week. As you will notice, electronics is changing the game for product development.


Internet of Things – The Man Who Coined It

Today, Internet of Things is well-discussed as a topic that will revolutionize the way we live and design products. Kevin Ashton, the man who coined the phrase “Internet of Things,” explains what it is and why it matters in less than two minutes.

If you are further interested, do watch a longer version of his talk at 2015 Microsoft’s Future Decoded conference.


Using DEM to Improve Transfer Chute Design

Chutes are commonly adopted in conveying systems as a method of transferring bulk materials from one conveyor belt to another. A poorly designed chute or even the application of a chute out of its original design conditions (higher tonnage, different particle material, wet material, and so on) often lead to problems. This can result in  lower productivity, increased maintenance costs, higher wear rates, or even shut downs.

Rocky DEM, a state-of-the-art discrete element particle simulator, helps engineers design and/or optimize transfer chutes by simulating different scenarios, which reduces the costs of building and testing different configurations (read more).


Simulation Powering Wirelessly Charging Electric Vehicles

Qualcomm Inc, a global leader and innovator in wireless and mobile technologies, is committed to pushing the frontiers of innovation. As a validation of this statement, Qualcomm spent USD 5.5 billion on research and development in wireless and mobile technologies in 2014 alone — and USD 34 billion over the company’s life.

One team, headquartered in Munich, Germany, focuses primarily on making the incremental improvements and technology customizations. This will lead to broad adoption of the first-generation Qualcomm Halo WEVC (wireless electric vehicle charging) technology (read more).


Schiaparelli Mars Lander – What Went Wrong?

Recently the martian lander crashed on the red planet prompting the European Space Agency to summon an investigation. Mission scientists recovered data from the lander before its untimely demise. By performing simulations of Schiaparelli’s control systems using this lander data reproduced this fatal cascade of events (read more).


Turbulence – What a Drag It Is When You Drive

Turbulence is a nightmare for several air travelers. It can spill your drink, bounce you off the roof of the cabin if you haven’t fastened your seat belt—and even bring a plane down. Airline pilots are super aware of it. Turbulence refers to the swirly chaotic movement of fluid particles. While most feared and destructive in air travel, turbulence is all around us and occurs every time you drive. Here’s an article from ENGINEERING.com talks more about this phenomenon. (read more).

Image of a racing car with streamlines around it and a stress contour plot on its surface.


So, folks, that was all for this week. We will be back again with a new edition next week. Do feel free to share your feedback or questions with us.

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Weekly Simulation Round-Up | Issue 4

Banner for Weekly Simulation RoundupWelcome to this edition of Weekly Simulation Round-Up. As usual, we bring you the most interesting articles from this week.


Computational Fluid Dynamics for Patient-Specific Surgeries

In this article, a researcher of Cardiothoracic Surgery from the Shanghai Children’s Medical Center talks about simulation-driven medical surgeries. He states that “the long-term prognosis for babies born with single ventricle heart defects can depend on the location of vascular connections made during corrective surgery”. Based on the babies’ cardiovascular anatomy, the medical center researchers employ ANSYS CFD to determine the optimal personalized surgery for improving surgical effectiveness and to obtain a better quality of life for children (read more).


Simulation of “Material Other Than Grain” Separation Process

For farmers engaged in grain production, separation of stones, straw and dust from grains is a regular activity. Can simulation techniques help such farmers to reduce cost and time-to-market, and increase grain production ramp-up? The answer is yes!

Using Rocky DEM, a state-of-the-art discrete element particle simulator, along with computational fluid dynamics performed using ANSYS Workbench, the material other than grain (MOG) separation process can be simulated. There’s potential for the MOG equipment makers to redesign or improve for higher separation efficiency.


Optimus Prime, anyone? 

Antimon is a BMW 3-series car that transforms into a robot in under 30 secs. It converts from a BMW into a grand robot completed with powerful arm movements and a Transformers-like face. It took the company eight months to complete Antimon using an actual car (Watch on YouTube).


Diamonds Convert Nuclear Waste into Clean Energy

British Scientists have developed a method of turning nuclear waste into batteries using diamond. By encapsulating a short-range radioactive material in an artificial diamond, small electrical charge can be generated even after insulating harmful radiation. Researchers estimate that a carbon-based battery would generate 50% of its power in 5,730 years (read more).


Structural Design Optimization of Electrical Transformer Tanks

One of our customers, Crompton Greaves Ltd., presented their experiences with optimizing structural design of their electrical transformer tanks. To achieve this, their engineers used the state-of-the-art tool for optimization and variation analysis – optiSLang and ANSYS Mechanical. Through this exercise, they were able to obtain ~10% weight reduction and over 17% reduction in Equivalent Stress (read more).


So, folks, that was all for this week. We will be back again with a new edition next week. Do feel free to share your feedback or questions with us.

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Weekly Simulation Round-Up | Issue 2

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I wish you a Happy New Year! Hope you had a great start to 2017. In this edition of the Weekly Round-Up, I’m sharing my favorite posts on how simulation has helped in thermal drying of automotive body-in-white, reconstruction of historic Berlin City, PCB support design and design & development of smart cities.


Simulation-Driven Development of a Drying Oven (Case Study)

High-quality standards apply to the drying process of car body paints. In this case study, you will understand how “with simulations of the oven behavior in the design phase, an optimized oven design was found which fulfills the required criteria of the drying process.” In the process of applying simulations, the customer said “virtual technology helped to avoid expensive changes after the oven is built, and to gain more insight into the manufacturing process (read more).”


Optimization of PCB Supports During In-Circuit Testing

Current automobile industry is driven by interacting electronic controls for which electrical verification tests needs to be carried out. This presentation by Robert Bosch, one of our oldest customers, at the 6th Optimization and Stochastic Days 2016, explains lots of interesting things. Their work explains that “engineer uses judgement and experience to place the supports, and does trials in simulations! Can this be eliminated.” The article then goes on to describe how optiSLang was used to optimize the number of PCB supports to aid the engineers (read more).


Role of CFD in Reconstruction of Berlin City Palace

The Berlin City Palace was a royal and imperial palace in the centre of Berlin. It was heavily damaged in World War II and later destroyed during conflict. Today this important historic site is being rebuilt and ANSYS CFD simulation has played and important role in helping “engineers optimize the many, and often conflicting, requirements of the climate-control system. Engineers are confident that the palace will meet all requirements, including energy conservation, comfort, artistic preservation and costs (read more).”


University of Cape Town uses Rocky DEM to Simulate Particle Behavior

University of Cape Town is gaining multiple advantages using Rocky DEM. In this interview, Dr. Indresan Govender says how “Rocky DEM will be instrumental in extending theories to include realistic shapes.” In addition, he adds by saying that “Rocky is the only DEM package that handles proper shapes. Other packages artificially achieve this by clumping spheres together. Rocky’s main advantages are realistic particle shapes and extension to GPU computing. (read more).


Building Digital City Twins

The combination of semantic 3D city model with numeric simulation offers a great potential for risk reduction. With the 3D City Model, you achieve illustrative scenarios for many applications, such as the analysis of dangerous situations and the planning of necessary preventive measures. Also complex consequences like climate change in the city are getting clearer and more visible (read more).

Thank you! Hope you have found this week’s posts interesting.

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Weekly Simulation Round-Up | Issue 1

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Welcome to the Weekly Round-Up! In this, we’re sharing posts that start from the importance of the Big Data, Healthcare to the breaking medical pills. We hope you’ll enjoy this post.


Maintaining Power and Signal Integrity

The article from ANSYS Advantage Magazine says that “the ever-changing hardware that supports big data and the Internet of Things must be fast, reliable and quickly developed. Simulation is important to ensure first-pass success by keeping pace with Big Data & Internet of Things, PCB/Chip Speed & Reliability are paramount (read more).”


CFD Modeling for Cardboard Packaging Ventilation

CFD simulation is used to model cardboard boxes to regulate temperature during pre-cooling, transport and storage. According to this article, “packaging ventilation must therefore be designed keeping in mind various parameters such as: type of packaging, type of holes, external and internal packaging structure, type of product, product shape and size, etc (read more).”


Patient-Specific Hip Implantation Methods

ANSYS software simulates the stress and strain on bones of individual patients to study a new hip implantation method. In an ANSYS Advantage magazine article, they say that “increasing numbers of patients are suffering from pain, stiffness or difficulty in moving due to osteoarthritis in their hips.”

The article goes on to add saying that “doctors typically recommend hip replacement surgery for patients with pain so severe that it limits everyday activities or reduces their range of motion. In hip replacement surgery, a damaged hip joint is surgically replaced with an artificial implant. The surgeon removes the head of the femur with a saw and then attaches a ball that is anchored by a shaft extending into the femur. A mating cup is attached to the pelvis (read more).”


Great Molasses Flood of 1919

Live Science brings an article from the archives. Apparently “a bubbling flood of molasses sent a towering wave of goo down the streets of Boston in 1919. It caught everything from horses to humans in its sticky grasp, killing 21 people, injuring 150 more and flattening buildings in its wake. Now, scientists have figured out why the deluge of viscous sweetener was so deadly (read more).”


Studying Breakage of Medical Pills

Simulation of material fragmentation is easier than ever now! Rocky DEM can simulate the division of a pharmaceutical pill (or any other particle) and then analyze of the behavior of the material. Such complex breaking phenomenon is possible with Discrete Element Modeling using Rocky DEM (read more).

That’s it for this Weekly Roundup! See you next week.

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