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Simulation Software

Market for CAE / Simulation software will reach $6.1 bn in 2020

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Cambashi, a leading global industry analyst and market consulting firm, together with partner intrinSIM announced its latest COVID-adjusted CAE/Simulation market data & forecast, which indicates the CAE (computer-aided engineering) market has been growing in double-digit figures and will continue on that path excluding 2020.

“These growth rates illustrate the beginning of the Simulation Revolution, which will continue to grow as more organizations realize that Engineering Simulation is a Key Driver to the Business Drivers that enable increased competitiveness,” said Joe Walsh, intrinSIM. “While 2020 will present lower growth rates, and Cambashi expects negative growth from e.g. the automotive industy, growth overall is still expected to be positive,” said Petra Gartzen, Senior Consultant, Cambashi.

Going forward, the trends that were driving adoption of simulation have not gone away because of COVID-19. The need to develop new, greener versions of any kind of product will accelerate, especially in industries generating vapor trails. And COVID-19 is also opening up new opportunities especially around modeling air flow, people movement, and space organization in any kind of building – be that a factory, a museum, an office, transport, etc. – where people spend significant amounts of time in close proximity. The need to provide a safe working environment to get industries back to some kind of normal situation could also result in new linkages between CAE and BIM vendors and CAE and IIoT/Connected Application technology providers.

Cambashi
www.cambashi.com/CAE

Ansys Discovery reduces engineering labor costs by 26%

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Ansys Discovery expands on the developments delivered by Ansys Discovery Live. It combines interactive real-time simulation, high-fidelity Ansys solver technology and direct modeling in one tool — powering cross-team collaboration to cost-effectively develop products.

“Discovery equips our team with a better understanding of the physics behind our products early in the design process, enabling them to meet customer requirements more precisely, avoid overengineering and eliminate uncertainties,” said Stefan Macho, head of R&D Simulation, HAWE Hydraulik. “This has resulted in improved product performance, increased design efficiency and shortened product development cycles.”

Discovery combines instant physics simulation, accurate high-fidelity simulation and interactive geometry modeling into one easy-to-use interface. Conducting real-time, rapid iterative design explorations, more engineers can explore larger design spaces and quickly answer critical design questions earlier in the product design process.

Driving widespread adoption of simulation, Ansys Discovery offers an intuitive user experience built for the design engineer, delivers industry-leading fidelity in the analysis stage with embedded Ansys flagship solvers and provides tremendous speed to support design engineering workflows. Teams can innovate more designs in less time, provide rapid design exploration and deliver detailed insight into product performance.

Said Mark Hindsbo, general manager, design business unit, Ansys, “Discovery enables engineers to bring simulation upfront in the ideation and design phase of product development, uncovering risks early before the costs to correct them become high or difficult to change.”

Ansys will showcase Discovery’s next generation user experience and real-time simulation capabilities at a virtual launch event on July 29, 2020 at 11 a.m. EDT. Visionary leaders will deliver dynamic insights on the product, perform cutting-edge technology demonstrations, share real-world customer successes and answer questions during interactive breakout sessions. Registration is free but space is limited. To register, please click here.

Ansys
www.ansys.com

Ex-MSC VP Doug Neill founds Computational Engineering Software for integrated computational materials engineering

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Bruce Jenkins | Ora Research

Doug Neill, a 22-year MSC Software veteran whose career includes 11 years as VP of the company’s R&D group, has founded a new company providing software and services for ICME—integrated computational materials engineering. Computational Engineering Software, LLC’s mission is to help engineering and manufacturing organizations “optimize your composite design through advanced simulation.”

CES details the heretofore unsolved problems it is attacking: “Current composite design is nearly 100% empirical. In aerospace, the building-block process requires thousands (or hundreds of thousands) of tests of increasing complexity, from simple laminate coupons to structural elements, to details to components to full-scale test, to develop the design space. Design is constricted by what laminates have been tested. Exploring new design concepts or materials isn’t feasible because of the testing required.”

The company cites typical complaints from users of traditional tools and methods:

  • “We can’t explore new design concepts. We have no reliable way to quickly evaluate them without testing, and there’s no time for that.”
  • “We’ve done 30,000 coupon tests and we still don’t know why our matrix is failing.”
  • “For our chopped-fiber parts, we have to proof-test every design change, and one in every eight parts in production. Why can’t we have an analysis method that will give us a reliable margin of safety, like we do for metals?”

What CES proposes is to “allow you to break out of the restrictive building-block process by using analysis to examine the constituent materials (i.e., fiber and matrix) independently, and find where the onset of failure in the material occurs—hence the name Onset Analysis. When does my matrix start to become critical? When does my fiber become critical? When (and where) is a delamination likely to start? When will the fiber overcome shear-lag and start to unload? Those are the critical questions in design that Onset Analysis can answer, for any layup, any geometry, without a mountain of test data.

“Onset Analysis also enables you to look at your design under extreme environments, like elevated temperatures, moisture, cold dry, or even the extreme cold of space applications.”

How this differs from older composite simulation methods

CES says that previous failure criteria such as Hashin, Tsai-Hill, Tsai-Wu and others “assume that a ply is a homogeneous material, and ignore the fact that there are fibers in a matrix and out-of-plane loads. They’re engineering approximations—curve fits of specific ply failure tests that create a failure envelope.”

By contrast, the company describes Onset Analysis as “actually a throwback to a classical way of doing things. It’s essentially the von Mises approach, evolved and adapted for composites. In Onset, we separate the strains in the fiber and matrix, looking at the full 3D state of strain, and evaluate them independently.”

Not “damage progression”

CES emphasizes that Onset Analysis is not the traditional “damage progression” approach to composite failure analysis. “From a design standpoint,” it notes, “if your material has failed prior to its target load, the design has failed. Why go further?”

The Onset Analysis methodology instead “looks for the beginnings, the onset, of failure in the material as design criteria instead of catastrophic failure. Of course in composite design, it would be impractical (and unnecessarily limiting) to design to the first microscopic critical value, so our analysis can also look for the initiation of higher-order events, like fiber unloading, initiation of delaminations or even estimates of laminate unloading. All of this without damage progression.”

Onset Analysis can be used to evaluate static strength of composite details including bolted joints, bearing, bearing-bypass, and especially matrix-dominant problems such as bonded joints and bonded repairs. “It is the only current method that can accurately assess matrix issues,” the company declares. The method can also be used to look at problems such as compression after impact (CAI) and fatigue.

Offerings

Composite simulation—“Use critical properties of the fiber and matrix to predict critical matrix and fiber failures and compute margin of safety, for any layup or geometry, without laminate testing.”

Consultation—“We bring industry-leading expertise in composite performance to your design and analysis challenges.”

Software development—”Our experts in software development process, frameworks and execution can help set up your team for success.”

People

CES’s key people introduce themselves:

Doug Neill, CEO and founder—“I am an innovation-focused, action-oriented, transformational software executive with decades of experience in the computer-aided engineering (CAE) space. At CES, we believe that the ICME materials revolution is stagnating due to a lack of pragmatic, easy-to-use and fast methods for validation of designs comprised of ICME materials. I have spent my entire technical career focused on automated design and design engineering simulation tools. Our company brings this focus and passion to our customers so that they can innovate new structural concepts and effectively and efficiently unlock the benefits of engineered materials. We have a great team of software and engineering experts to assist you.

“I spent 22 years at MSC Software Corporation and was Vice President of the R&D group for 11 of those years. Prior to that, I helped a startup as the Business Development head to position new FE-based design software. At the beginning of my career, I spent 15 years working on the development and application of directed-search automated multidisciplinary optimization software in aerospace and later the CAE industry.”

See our interview with Neill in his VP role at MSC Software published in this blog in 2017.

Jon Gosse, Ph.D.—“I believe that simulation, done right, can radically transform industry. In my 33 years at The Boeing Co., I worked with many talented engineers and scientists to develop practical approaches to evaluating composite design, and applied those methods to solve intractable problems on some of the most important programs in the company. My goal is to bring that knowledge to the world and revolutionize how industry designs with composites and other advanced materials.”

Eddy (Joe) Sharp—“In my 31 years at The Boeing Co. I had many roles. I began my career as a stress analysis, then moved to the development of Boeing’s internal stress analysis software, engineering methods and material allowables, and finally it was my privilege to manage a group of brilliant engineers and scientists working on bringing together structural simulation and materials science to improve composite materials performance. Working with them every day was like getting an advanced degree in a wide-ranging curriculum including solid mechanics, mechanics of composite failure, polymer science and molecular dynamics modeling.

“That background led to a passion for advanced materials and composite analysis, and building practical tools for engineers so they can focus on the design of their part, and not on the quirks and nuances of modeling with esoteric CAE packages.”

Kunaseelan Kanthasamy, Ph.D.—“I embrace the Art of the Possible and am reputed for ‘taking any fresh, blue-sky project from zero to full steam ahead.’ As a visionary thought leader, I continuously move people, products and companies forward, always connecting the customer’s needs to the end product. In pioneering next-generation digital technology, I build high-performance R&D teams and devise ways to differentiate businesses.

“I thrive in igniting energy around conceiving new products from legacies, capturing new product channels to grow business, strategically anticipating future customer needs, and guiding approaches to the distinctive aspects of doing business in other cultures. My technical acumen includes engineering new digital platforms, pre-NPI, NPI, TRR; enterprise solutions, VAST, RFID, FQC Code, NFC standards/platforms; industry security frameworks, cryptography, symmetric/asymmetric, hash functions, encryption/signatures, Digital Twin and Digital Thread.

“I have filed 36 patents and own 21, and won 16 product innovation awards.”

Computational Engineering Software, LLC

Integrated computational materials engineering

von Mises yield criterion

Structural analysis of a wheel fitted with a pneumatic tire

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Correctly defining boundary conditions is of vital importance when using finite element analysis (FEA). As with any simulation or calculation, if the input is rubbish, the output will also be rubbish. For structural analysis, the important boundary conditions are the fixtures preventing movement of the structure and the external forces acting on it.

Dr. Jody Muelaner, PhD CEng MIMechE

For wheels fitted with pneumatic tires, defining the boundary conditions properly can be particularly challenging. The forces acting on the rim of the wheel are caused by air pressure within the tire and by the ground reaction force transferred through the tire. Defining these forces in a realistic way requires some thought and without experience of this type of problem, the most significant force could easily be overlooked. Luckily, considerable work has been done in this area and so we can apply standard methods to correctly define the boundary conditions. This means that it’s not necessary to include the tire in the FEA and it can be represented by a few simple boundary conditions, determined by a combination of analytical and empirical methods.

Detailed models of tire-ground and tire-rim interactions
Before we get into the practical methods for applying boundary conditions to a wheel, let’s take a moment to consider the alternative. If we don’t make any assumptions about how the tire will impart forces on the rim, we would need to first model how the tire makes contact with the ground. This might be idealized as a toroidal or cylindrical face of the tire making contact with a planar ground surface. This would respectively result in a point or line contact initially, with corresponding infinite force. The tire then deforms to produce a contact patch. This type of contact analysis always requires an iterative solution but is relatively straightforward when the contact is between two linear elastic solids. However, although the compression of the air within the tire is elastic, the casing of the tire will undergo large deformations and there are significant damping effects. It is this damping that often accounts for most of the rolling resistance when a wheel rolls over a firm surface. Modeling these effects requires non-linear material models, adding significantly to the complexity of the analysis. The complexity doesn’t end there as the tire is not made up of a homogeneous isotropic solid material. Tires have anisotropic textile casings and bead wires, encased in a rubber matrix. Modeling this type of composite structure becomes extremely complex. It is only when all of this has been simulated that the deformation into a contact patch and the transfer of force from the ground into the rim can be determined.

Analysis of the forces acting on rim
A typical wheel consists of a central hub with a disk that supports the rim. The rim has flanges at each side which prevent sideways movement of the tire and bead seats which hold the tire radially. It is through the bead seats that the ground reaction force is transferred. The parts of a rim are labeled in the photo below.

The part of a tire which contacts with the ground is the tread. The tread generally has an approximately cylindrical outer surface, although it may be toroidal, especially for tires used on bikes, which lean into corners. In common usage, tread may only refer to the outer textured surface which makes direct contact with the ground but the term is used here to refer to the entire thickness of the horizontal part of the tire. The sides of the tire, which extend vertically to meet the tread at each size is known as the sidewall. The inner circumference of each sidewall is referred to as the bead. The bead is supported radially by the bead seat of the rim and is contained axially by the rim flange. The bead may contain wire to help it resist the radial force caused by the air pressure within the tire. The parts of a tire are shown below.

The air within the tire exerts uniform pressure on all internal faces of the tire and rim, the inflation pressure, P. The simplest boundary condition for the wheel is where any surfaces of the rim not covered by the tire are exposed to this pressure. Where the inflation pressure acts on the inside of the tread, it is contained by the tire casing and bead, causing internal hoop stresses in the tire but no reaction forces on the rim. Where the inflation pressure acts on the sidewall of the tire, it is resisted at the outer circumference of the sidewall by the tread and the inner circumference by the rim flange. The resulting reaction force, Fs, is an important boundary condition for the wheel. Note that in the below diagram, the force Fs is shown acting on the tire, the force acts on the wheel in the opposite direction.

To calculate the reaction force, Fs, we need to consider the axial component of the inflation pressure, and the area over which it acts. It acts over the area of the sidewall, projected onto the vertical plane, which is given by:

If we assume that the force on the sidewall is divided equally between the tread and the rim flange, the force is given by:

 

Ground reaction forces have three components: Radial force due to the vehicle’s weight, tangential force caused by acceleration and braking, and axial force caused by cornering. These forces are distributed according to a cosine function over a region of the bead seat and rim flange related to the tire’s contact patch. The range of this distributed load is given by an angle of loading, θ. There are no analytical methods to determine the loading angle. It depends on the shape of the rim, the shape and stiffness of the tire, the tire pressure, and the ground reaction force. The loading angle may be determined experimentally or a worst-case value may be used. To use the worst-case value, multiple simulations are carried out with different loading angles to determine how the angle affects the stress in the wheel. It can be assumed that it will not be smaller than the contact patch of the tire which can be easily observed. The ground reaction may create a cyclic loading in the wheel if the wheel contains periodic spokes. This is because the stress state when the ground reaction is centered on a single spoke is different from the stress state when the ground reaction is between two spokes. For every revolution of the wheel, each spoke will experience one cycle which should be taken into account for fatigue calculations.

There can be up to five forces acting on the rim, although axial and tangential reactions are not always present:
• Inflation pressure, P, acting uniformly on the internal faces of the rim, not in contact with the tire.
• Sidewall pressure reaction, Fs, acting on both rim flanges.
• Radial ground reaction, Fv, distributed sinusoidally over both bead seats
• Axial cornering reaction, FA, distributed sinusoidally over one of the rim flanges depending on cornering direction.
• Tangential braking or cornering reaction, FT, acts over the same region of the bead seats as the vertical ground reaction and is also sinusoidally distributed, with the tangential load transfer related to the normal force.

Practical issues of applying boundary conditions in FEA software
Before attempting to apply the tire forces to the rim, a few changes should be made to the solid model to simplify the analysis. Firstly, the faces of the bead seats must be split at the extents of the load angles. It is also a good idea to cut the wheel in half so that symmetry can be used to simplify the model. It may also be useful to de-feature the model to further reduce meshing and solution times. For example, by removing external fillets and other small features that won’t affect the stress significantly. It may even be worth extracting mid surfaces and meshing using shell elements.

In addition to the forces applied to the rim, fixtures will be needed at the hub. This is probably best achieved using a frictionless support on the inner face in contact with the hub and bolt connectors at the holes.

In this example, an inflation pressure of 0.345 N/mm2 (50 psi) was simulated. With a bead seat radius of 163 mm and a tread inner radius of 268 mm this results in a sidewall gives a reaction force of 24,525 N. The ground reaction force is 2 kN and the sinusoidal distribution can be applied using a bearing load. Because of the symmetry in the model these forces are halved.

The final von Mises stress results, following H-adaptive meshing, are shown below. The greatest stress occurs at the radius between the bead seat and the rim flange. This is a result of the bending stress caused by the sidewall reaction force. The ground reaction force has surprisingly little effect on the stress field, only increasing the peak stress by 3%. This really highlights how important it is to fully consider how the air pressure is transferred through the tire.

OnScale and Lexma launch Moebius LBM CFD Solver for advanced fluid dynamics simulations

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OnScale, a global leader in Cloud Engineering Simulation, announces the availability of the Moebius Lattice-Boltzmann Method (LBM) Computational Fluid Dynamics (CFD) solver on the OnScale Cloud Engineering Simulation platform.

“Moebius represents a step-change in CFD speed, power, and democratization for digital prototyping of devices involving fluid flows,” says David Freed, CTO of OnScale and a Digital Physicist with a 25-year track record of advancing LBM CFD technology at MIT, Exa Corporation, and Dassault Systѐmes. “Moebius running on the massively scalable OnScale Cloud Engineering Simulation platform will break barriers to innovation for a variety of applications such as lab-on-a-chip, MEMS, and medical diagnostic and treatment devices like next-generation ventilators and respirators.”

Airflow simulation in a UV sterilization chamber of an iPAP ventilator for COVID-19 patients.

Unlike Navier-Stokes CFD methods which simulate bulk fluid flow, LBM takes a kinetic theory approach to simulating fluid flows, which enables the simulation of complex biomedical and engineering problems, including multiphase flows (e.g. simulating control and management of multi-species droplets in microfluidic devices), particle transport (e.g. simulating sorting of blood and cancer tumor cells), and fluid-structure interaction (e.g. simulating efficient micro-scale actuators in MEMS applications). The resulting simulations provide unique insight and design guidance for engineers advancing new technologies.

Combining the power of the Moebius solver with the massive scalability of OnScale in the cloud enables both huge simulations and parallel execution of large numbers of simulations on cloud supercomputers.

“Integrating Moebius with the OnScale Cloud Engineering Simulation platform allows our team to focus on our mission – creating the world’s best LBM CFD solutions – while leveraging OnScale’s cloud supercomputer scalability and SimAPI for CAD import, model setup, data management, and viewing simulation results,” says Franck Pérot, CEO of Lexma Technologies. “We also get OnScale’s account management, billing, customer support, and marketing and sales automation features built-in.”

Fighting COVID-19 in Low-Income Countries: How Digital Prototyping Empowers Engineers to Advance the Design of Medical Devices

“With Moebius running on OnScale, we were able to optimize the design of our Intelligent Positive Air Pressure (iPAP) machine with UV disinfecting chamber,” says Shashi Buluswar, CEO of the Institute for Transformative Technology (ITT). “Using OnScale and Moebius to create Digital Prototypes of our device dramatically shortened our physical prototyping cost and time and allowed us to accelerate our goal of delivering critical iPAP devices to low-income countries to save lives during the COVID-19 pandemic.”

Left to right: Simulation iterations from a suboptimal design to an optimized configuration of the iPAP UV sterilizer chamber.

A critical design and engineering aspect of the iPAP device is the UV disinfecting chamber, which is intended to disinfect up to 99.9% of the air exhaled from a COVID-19 patient’s lungs. The ITT team needed to minimize size, cost, and heat generated by the chamber while maximizing the amount of time air spends in it. The team used Moebius running on OnScale to simulate many “Digital Prototypes” of the disinfecting chamber and process until converging on a winning, manufacturable design.

OnScale
ww.OnScale.com

Lexma Technology
www.lexma-tech.com

2020 & beyond: 6 more megatrends to watch in engineering modeling & simulation

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Bruce Jenkins | Ora Research

Early last year we reviewed in this blog post eight megatrends in engineering modeling and simulation that dominate the thinking and decision-making of engineering organizations and their technology providers today, and that we believe will continue to do so well into the years ahead. We wrote then:

This second decade of the twenty-first century is witnessing an explosion of invention and innovation in digital engineering technologies unrivaled since the 1980s, when so many foundational tools and methods were either created or brought to practical fruition. Here are eight megatrends that we believe will drive generational leaps forward in engineering modeling and simulation technologies, methods and work processes through 2020 and well beyond:

  • Simulation-led, systems-driven product development.
  • Democratization of engineering modeling and simulation.
  • Simulation app revolution.
  • Design space exploration.
  • Topology, materials and process optimization for additive manufacturing.
  • Simulation for the Industrial IoT and Industry 4.0.
  • Big-data analytics in simulation.
  • Cloud HPC for simulation.

Now, here are six more large-scale trends that we think are already beginning to drive major technology developments and end-user investments aimed at fostering cost, schedule, quality, performance and innovation improvements in the engineering and production of discretely manufactured products (many will benefit process manufacturers and other AEC industry participants as well):

  • 21st– century data management: Separate the data from the data model (Aras, Onshape, Frustum…).
  • From PIDO to fully automated design space exploration: 20+ years of evolution—then a revolution.
  • New requirements-management technologies that automatically link—via new systems-level engineering technologies—requirements fulfillment during the course of system-level product design (MapleSIM, Simulink…) back to digitally captured system requirements definitions (SysML, Rational Rhapsody…), and automatically track and report divergences and convergences between the two as the design evolves.
  • Generative design design space exploration: What’s alike? What’s different? When is each appropriate?
  • AI and ML (machine learning) in engineering modeling and simulation—the next steps beyond big-data analytics for simulation.
  • Further breakthroughs in co-simulation: Simultaneous instead of step-wise simulation of multiple physical domains, and at multiple (mixed) fidelities—0D, 1D, 2D, 3D; also 4D and 5D in AEC.

Previews

21st– century data management

Aras’s insight to separate the data from the data model makes them, a bit ironically, the technology vendor that will relieve legacy PLM vendors of the prohibitive burden of somehow hoisting their SQL-based PDM offerings into the cloud, yet still link them into today’s truly “open” world. Because Aras’s technology architecture has already done it for them, before them.

And without charging a penny for the technology. Aras makes its software available as freeware. Users can download, evaluate, and implement it in production usage—all for zero dollars. If users then need customization and integration to link into their unique multi-application environments, Aras is available to do this, for fair and reasonable service fees. An extraordinarily apt 21st-century business model, we think.

From PIDO to fully automated design space exploration: 20+ years of evolution—then a revolution

This breakthrough was sparked by HEEDS from Red Cedar Technology, a paradigm-disrupting startup that commercialized university-developed technology under the leadership of Bob Ryan, and was subsequently acquired by Siemens PLM. HEEDS has set a new direction now being pursued by almost every major DSE technology provider.

Generative design vs. contemporary design space exploration

When early adopters of generative design technology discover what fully automated design space exploration technology can do, will they feel underserved by their generative-design technology providers putting forth tools that still require, today, an arguably unnecessary exertion of effort by engineers and designers in making decisions that the software should be making for them?

Or, instead, is generative design an entirely appropriate technology for disciplines and end-user markets where not all problems and sought-for outcomes can be expressed in an entirely determinative manner? The jury is still out on this one, we believe. After users gain more experience with both approaches—and with continuing maturation of both technology classes—time will tell.

Looking forward

Watching the answers to all these questions take shape is going to be fascinating. We greatly look forward to following and reporting here on these and many more game-changing technologies and trends as they unfold in the quarters and years to come. Stay tuned!

Selected background reading

Aras acquires Comet Solutions

HEEDS MDO

MapleMBSE from Maplesoft radically expands accessibility of model-based systems engineering

CosiMate from Chiastek: Co-simulation conduit for multifidelity systems modeling

Cloud-native CAD will disrupt the PLM platform paradigm

Reduce overall simulation time

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Siemens Digital Industries Software announces the latest release of its Simcenter FLOEFD software, a CAD-embedded computational fluid dynamics (CFD) tool. Simcenter FLOEFD is part of the Simcenter portfolio of simulation and test solutions that help engineers simulate fluid flow and thermal problems quickly and accurately within their preferred CAD environment. The latest version offers new modules and improvements that can improve accuracy and solve rates.

The software helps users frontload CFD simulation early into the design process to understand the behavior of their concepts and eliminate the less attractive options. The software can reduce overall simulation time by as much as 65-75% and offers up to 40 times user productivity enhancement. Part of the Xcelerator portfolio, Simcenter FLOEFD also helps design engineers contribute to the creation of a highly accurate digital twin.

The new Electronics Cooling Center module combines existing best electronics-specific capabilities and integrates new ones from Simcenter Flotherm software inside the CAD-embedded interface to enhance electronics cooling functionality. A second new module helps users create a compact Reduced Order Model (ROM) that solves at a faster rate, while still maintaining a high level of accuracy. The Power Electrification module can now simulate an electrical device as an electro-thermal compact model, which can save significant user and computational time.

Siemens Digital Industries Software
www.sw.siemens.com

Generative design for flow applications

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Flow driven generative designer is a new application from Dassault Systèmes. Its intended use is to give users or designers access to simulation capabilities for fluid optimization.

As many designers know, the process of creating a part is typically based on experience and intuition. Generative design, however, offers a different approach. Generative design programs use boundary conditions, set by the designer, to drive and simulate how a part should look. Applications for flow driven generative design include powertrain design, HVAC, jet propulsion, injection molding, and valve and piping design.

Within the program, designers are encouraged to ask different questions. For example, rather than ask, ‘Does this shape meet the requirements?’, the question changes to ‘Which shape best meets the requirements?’

According to Colin Swearingen, generative design expert at Dassault Systèmes, “optimizing fluid flow for a particular component is a difficult process as it incorporates a number of aspects of engineering.” These aspects create an “over-the-wall” process where various engineering disciplines such as CAD, analysis, simulation, manufacturing, PLM and so on, are siloed and there is little collaboration.

One of the risks of siloed engineering is an increase in the number of data translation errors that can compromise a design. Another drawback is the lack of expertise in more than one engineering discipline. Few companies have designers who are experts in CAD, CFD, and analysis.

Thus, in a typical traditional design process, a designer begins with a design space and sets up boundary conditions. In the case of fluid, what are the inlet conditions and what are the outlet conditions? Are there any other restraints that need to be applied to the model?
Then the design is handed off to an analyst, who must then mesh the data and prepare it for a CFD model run.

The new shape also needs to be validated. In a typical design process, that’s a different tool that is used to compute the flow analysis as opposed to optimizing the shape to begin with.
So, designers do their best version of the design. However, it quickly becomes an iterative process every time a change is made.

The flow driven generative program is in the 3DEXPERIENCE platform, which also includes other engineering tools, such as CAD, simulation, analysis, optimization, and manufacturing. All of these are unified into one environment so that a designer can streamline the design process. This platform makes the process intuitive, helping users optimize the design earlier and eliminates all the data translations required in other tools and platforms.

In Flow driven generative, once the designer is satisfied with the initial iteration of the design, they simply click a button to begin a simulation. Then, they can run a flow analysis without leaving the design program.

File exchange is not needed in this process, and no data translation is necessary. Said Swearingen, “It’s intuitive, easy to use, and we really streamline the process. What we see is about a 10-times faster turnaround time.”

The program includes a design assistant that prompts the designer to answer specific boundary questions that help the program create a design.

Noted Swearingen, the program leverages best in class TOSCA fluid technology in the background. Tosca fluid and many of the Tosca applications are typically known as an expert tool. However, that’s being run in the background here. The designer is getting access to this simulation capability without needing to be a full-fledged expert in the program.

The goal of the Flow driven generative program is to remove the bottlenecks that make it cost prohibitive to explore optimized parts. Another goal is to develop a seamless collaboration with design and simulation departments. “In a unified environment,” said Swearingen, “it’s enabling collaboration and opening doors for users in a much more streamlined and efficient manner, to tackle the problems that arise with this type of workflow.”

Dassault Systèmes
www.3ds.com

Improve simulation time and accuracy

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The latest release of Simcenter™ STAR-CCM+ software, part of the Simcenter portfolio of simulation and test solutions for optimizing design, includes improvements to simulation time and accuracy, and enhanced collaboration. These features give customers a comprehensive digital twin to drive predictive simulations. In this release, Siemens is introducing a new parallel polyhedral mesher for faster, more effective meshing, as well as a model-driven adaptive mesh refinement (AMR) solution. The latest release also includes automatic coupled solver control for reduced set up time. Convergence speed is improved through a collaborative virtual reality (VR) feature in a CFD code for enhanced team collaboration on simulation results.

The fully-rewritten parallel polyhedral mesher builds meshes up to 30 times faster than in serial, for a consistent mesh regardless of the cores used and a more effective mesh distribution with the same accuracy and robustness. New adaptive mesh refinement (AMR) technology intelligently refines the mesh based on the physics. This can lead to less user interaction as well as computational overhead and reduces overall mesh size.

Collaborative VR in Simcenter STAR-CCM+ allows teams across the globe to interact in the same immersive virtual environment in real time, enhancing communication and decision-making. Multiple VR clients can now be connected and synchronized to the same simulation, with avatars showing the location of other users and providing the ability to tether users to get the same experience.

Simcenter STAR-CCM+ is an integrated solution for computational fluid dynamics (CFD) and multiphysics simulation that brings automated design exploration and optimization within the grasp of all simulation engineers. Simcenter and Simcenter STAR-CCM+ are part of Xcelerator portfolio, Siemens’ integrated portfolio of software, services and application development platform.

Siemens Digital Industries Software
www.sw.siemens.com

Latest Simcenter 3D enhancements deliver better insight into product performance

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Siemens Digital Industries Software announced the latest version of Simcenter 3D software, part of the Simcenter portfolio of simulation and test solutions. Simcenter 3D helps product engineering teams be more productive and produce consistent simulation results with a unified, easy-to-use shared platform covering most simulation disciplines. The latest version delivers the most comprehensive, fully-integrated CAE solution on the market today, to help optimize design and deliver innovations faster and with greater confidence.

The latest release of Simcenter 3D includes many improvements in four key areas:

Multidiscipline Integration: Simcenter 3D offers new simulation methods that increase realism and deliver better insight into product performance. Industrially validated rotor dynamics simulation capabilities have been extended, to include nonlinear connection elements, for example, allowing engineers to minimize rotational unbalance and unnecessary external forces in applications such as aircraft engines, gas turbines, automotive engines, industrial equipment, and even electronics, for example when computer disk drives spin at high rates.

Improved Simcenter 3D rotor dynamics simulation solutions allow you to minimize rotational unbalance and unnecessary external forces in applications such as aircraft engines, gas turbines, automotive engines, industrial equipment, and even electronics.

Faster CAE Processes: New Noise Vibration and Harshness (NVH) composer tool helps engineers quickly create system-level finite-element (FE) models, starting from subassembly models such as an automotive body-in-white, door, suspension, and more. Automating the full-vehicle FE model increases process speed and helps reduce human error.

Ties to the Digital Thread: The seamless integration with data management from Simcenter is extended to enhanced ties to the physical testing group. Deeper test/analysis correlation capabilities from Simcenter 3D, such as new pre-test planning for determining sensor locations, can help determine the best methods to use for physical testing and increase confidence that simulations are accurately predicting real-world results.

Open and Scalable: Simcenter 3D is an open environment where engineers and designers can gain the benefits of faster CAE processes by using Simcenter 3D in connection with other CAE solvers. Added support for cyclic symmetry can help engineers simplify the modeling and simulation process for components when using the Abaqus solver.

Simcenter 3D and the Simcenter portfolio are part of the Xcelerator portfolio, Siemens’ integrated portfolio of software, services and application development platform.

Siemens Digital Industries Software
www.sw.siemens.com