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COMSOL Multiphysics includes tools to support 5G, IoT design

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COMSOL announced the latest advances in its COMSOL Multiphysics software to support microwave and RF engineers working on 5G, IoT, automotive radars and satellite communications. With these tools, designers can model different PCB materials and study how they affect the performance of microwave and millimeter wave circuits. Several of the application examples to guide designers will be introduced at the International Microwave Symposium (IMS) 2019.

“We are particularly excited to demonstrate how to set up and run a simulation to design and evaluate a Grounded Coplanar Waveguide (GCPW) line,” said Jiyoun Munn, technical product manager of the RF Module at COMSOL. “Connectors and low loss materials are the key components across all electronic devices and systems. Their reliability is critical in circuits that transmit and receive information.”

The use of simulation to achieve low insertion loss and reliable circuit performance in a design, requires choosing accurate material properties such as relative dielectric constant and loss tangent, while also considering surface roughness effects in the computer model.
“As the frequency increases, maintaining the impedance become more complex, as small quirks arising from the geometry or selected materials can be magnified,” explains Bill Rosas, Cofounder of Signal Microwave. “Simulation allows us to ensure that these critical pieces of RF infrastructure are optimized for 5G communications.”

Designing components ready for 5G, IoT, automotive radars and satellite communications will require multiphysics modeling. Using COMSOL Multiphysics microwave and RF designers can couple electromagnetic simulations with heat transfer, structural mechanics, fluid flow, and other physical phenomena, allowing them to represent coupled physics effects as they would occur in the real world. That means being able to accurately investigate designs and fully benefit from the virtual prototyping capabilities multiphysics simulation offers.

COMSOL
www.comsol.com/rf-module

MapleSim 2019 improves performance, increases modeling scope

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Maplesoft announced a new release of MapleSim, the advanced system-level modeling tool. From digital twins for virtual commissioning to system-level models for complex engineering design projects, MapleSim helps organizations reduce development risk, lower costs, and enable innovation. The latest release provides improved performance, increased modeling scope, and more ways to connect to an existing toolchain.

Simulation is faster for all customers in MapleSim 2019 due to more efficient handling of constraints when preparing the model, resulting in more compact, faster simulation code without any loss of fidelity. These results mean that MapleSim’s industry-leading speeds have gotten even better, saving time and enabling more real-time applications. In addition, models developed in MapleSim and then exported for use in other tools also run faster in the target applications.

New built-in and add-on components and expanded support for external libraries means that engineers can create more models, faster, in MapleSim 2019. The new release expands the scope of models that can be created using pre-existing components, with additions to hydraulics, electrical, multibody, and more. As well, the MapleSim Engine Dynamics Library from Modelon is a new add-on library that provides specialized tools for modeling, simulating, and analyzing the performance of combustion engines. This component library is especially useful for representing transient engine responses, and can be used for analyzing engine performance, performing emission studies, controls development, hardware-in-the-loop verification of vehicle electronic control units, and more.

Toolchain connectivity is essential to many MapleSim customers, and MapleSim 2019 offers important advances in toolchain integration. Improvements include additional options for FMI connectivity, including support for variable-step solvers, as well as fixed-step, for running imported models in MapleSim and exporting models to other tools. In addition, the new B&R MapleSim Connector add-on gives automation projects a powerful, model-based ability to test and visualize control strategies from within B&R Automation Studio, and to export simulation data for motor, servo, and gearbox sizing within SERVOsoft®.

“System level modeling has proven to be an invaluable tool for companies embarking on challenging engineering design projects, especially in the areas of automation and the creation of digital twins. Models can be used to both verify a design, as well as act as a virtual test bench for the machine’s control software – all before prototypes are built,” said Chad Schmitke, Senior Director, Product Development, Maplesoft. “Whether an organization wishes to develop their own models or work in partnership with the Maplesoft Engineering Solutions team, the improvements in performance, scope, and connectivity in MapleSim 2019 offer benefits to everyone.”

MapleSim is available in English, Japanese, and French.

Maplesoft
www.maplesoft.com

ASCENT unveils 2020 Autodesk Courseware roadmap

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In conjunction with the Autodesk 2020 software releases, ASCENT Center for Technical Knowledge has released its fundamental guides for the core software titles: AutoCAD, Civil 3D, Inventor and Revit. As an Autodesk Authorized Publisher, ASCENT has also published their 2020 Courseware Roadmap that includes over 60 titles planned for release throughout 2019.

 

“While our team is known for our off-the-shelf, comprehensive Autodesk courseware, we also see many design engineering firms request help creating custom documentation,” says Paul Burden, director of product development for ASCENT. “Users can quickly become productive when learning from blended content consisting of reference, video, and project elements that reflects their unique in-house workflows and processes. In addition, many of our Autodesk Training Center customers and Academic clients benefit from courseware assembled from our extensive library of learning modules. Using bespoke collections of our standard modules enables them to offer a roster of differentiated classes giving students unique learning experiences and varied course options.”

Autodesk 2020 Learning Guides Now Available from ASCENT:

ASCENT’s offerings include learning materials for students, instructors, professionals and individuals, designed for self-paced learning, instructor-led training, and on-the-job reference. Learning Guides include practice exercises and, in applicable guides, Autodesk Certification Objectives to help those preparing for Autodesk Professional Certification Exams. Instructor Guides contain the same instructional content as a Learning Guide, plus include answers to the chapter review questions, timing suggestions to help deliver the course, and instructor presentation files.

Simulation On-The-Go with COMSOL Client for Android

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COMSOL announces that COMSOL Client for Android is  available. Researchers, engineers, and students can perform simulation tasks from their Android devices, such as phones, tablets, and Chromebooks simply by connecting to the COMSOL Server software which runs the computations remotely.

COMSOL Client for Android expands on the capabilities of the Application Builder and COMSOL Server by enabling you to take your simulation applications on the road, without being limited by your device hardware. Providing field technicians or sales representatives with the power of COMSOL Multiphysics directly on their Android devices allows them to bring the R&D work on site or to the sales pitch.

“COMSOL Server allows users to run simulations through web browsers or desktop-installed clients,” explains Daniel Ericsson, Applications Product Manager, COMSOL. “COMSOL Client for Android expands on those capabilities by introducing a more seamless user experience on Android devices.”

“Using COMSOL Multiphysics and its Application Builder I can create models and build apps based on them. This allows other departments to test different configurations for their particular requirements and pick the best design,” comments Sam Parler, Research Director at Cornell Dubilier.

The Application Builder and COMSOL Server were developed to make multiphysics modeling more accessible to a wider audience. The Application Builder allows simulation specialists to create custom-made applications based on their multiphysics models. With COMSOL Server, organizations have been able to deploy industry-specific analysis tools in a streamlined and quick to implement format that can be scaled for global benefit. COMSOL Client for Android has made the convenience of running simulation applications as easy as ordering a rideshare.

Just like COMSOL Client for Windows, the simulations are run on remote servers, so you are not limited by your device hardware. Administrators continue to have full control over who can access and run the apps by using COMSOL Server. Android users will have the latest version of a simulation application each time they open the app.

COMSOL
play.google.com/store/apps/details?id=com.comsol.androidclient

ANSYS Cloud: Direct cloud HPC access through ANSYS Mechanical, ANSYS Fluent

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Bruce Jenkins | Ora Research

“Engineering simulation has long been constrained by fixed computing resources available on a desktop or cluster,” observes industry leader ANSYS. “Today, however, cloud computing can deliver the on-demand, high-performance computing (HPC) capacity required for faster high-fidelity results offering greater performance insight. To leverage the combined benefits of cloud computing and best-in-class engineering simulation, ANSYS is partnering with Microsoft Azure to create a secure cloud solution: ANSYS Cloud.”

Within ANSYS Mechanical and ANSYS Fluent, the company says its users can “easily access HPC in the cloud directly—without the need for any additional setup. Access the hardware and software you need, when you need it—pay only for what you use.”

Capabilities

Built-in cloud HPC access—ANSYS Cloud delivers easy access to on-demand HPC resources from within your ANSYS environment. Using your ANSYS tools, prepare your simulation models on your desktop. Simply select a pre-configured hardware, then submit your jobs directly to the cloud. You won’t have to wait in HPC cluster queues or reduce your model size to fit desktop constraints. Job progress may be monitored from your desktop or through a web-based cloud portal.

The ANSYS Cloud is optimized for ANSYS solvers. Choose from a set of pre-defined hardware configurations depending on the needs of your model.

Ready-to-use cloud service—Mechanical and Fluent users can “easily access ANSYS Cloud without involving their information technology (IT) teams. Without the need for complex software installations or cloud-side setups, users are free to focus on solving their engineering problems. And, without having to build in-house solutions or rely on third-party vendors, businesses can avoid costly upfront investment and delays.” ANSYS Cloud is a “ready-to-use solution that is ANSYS-tested and certified, and fully-supported by ANSYS HPC and solver experts.”

“Completely secure workflows”—ANSYS Cloud provides a “highly robust and completely secure environment for running simulations in the cloud. At the Azure data centers, where simulations are run and data are stored, access is strictly controlled. The solution combines Microsoft Azure’s best practices with custom encryption for added security.” Both data at rest and in motion are encrypted.

Leveraging Azure Virtual Networks, ANSYS Cloud offers a “separate, secure network architecture for each customer: only you can access your data.”

The complete system architecture has undergone comprehensive testing, including detailed penetration testing, ANSYS says. Because new security threats continuously emerge, the solution’s security is regularly audited by a third party.

“Economical on-demand pricing”—Pay-per-use access to both cloud hardware and ANSYS software is available on Microsoft Azure and enabled through ANSYS Elastic Licensing. Rather than locking into a longer-term lease, users purchase a pool of ANSYS Elastic Units (AEU) based on their short-term cloud-computing needs.

How this works: “Using your existing licenses, prepare your model using your on-premise hardware. When you submit your simulation job for analysis in the cloud, use your pool of AEUs.”

AEUs are consumed at a specified hourly rate that varies with the choice of hardware configuration and solver type (i.e., Mechanical or Fluent). For example, a Mechanical simulation on a small hardware configuration (1 node, 12 cores) will consume 13 AEUs/hour, whereas the same simulation on a medium configuration (3 nodes, 36 cores) will consume 18 AEUs/hour.

Your pool of AEUs (shared with other users in your organization) is charged based on your cloud runtime (in fractions of an hour). Consumption of AEUs may be tracked using the cloud portal, which is accessed via a desktop or mobile web browser.

“With this combination of traditional licensing (leased and paid-up for steady workflows) and pay-per-use licensing (for in-cloud, flexible capacity),” ANSYS says, “you can optimize your company’s investment in simulation.”

Remote job monitoring

Easily monitor the progress of your simulation from within the desktop installation of Mechanical and Fluent or from a web-based cloud portal. Job monitoring tools provide full access to the solver transcript, a graphical view of convergence parameters and real-time access to debug information when help is needed.

You can also view a summary of your simulation jobs via a web-based cloud portal, which can be accessed from your desktop or mobile device. Using the cloud portal, you can track total consumption of AEUs and even share your simulation jobs with your peers and ANSYS support.

Cloud-based 3D results visualization

With ANSYS Cloud, users can review and validate the results of their simulations while their data are in the cloud. “Innovative post-processing technology leaves the heavy data in the cloud, transferring only requested information to you for 3D rendering in your web browser,” ANSYS says. This approach “avoids heavy network usage and eliminates the latency typical of virtual desktop approaches. The performance is unmatched for all-size models.”

Users can plot scalar and vector fields and visualize results on existing parts, planes, isosurfaces and isovolumes. When needed, “download the data to your desktop for detailed post-processing using your familiar desktop applications.”

ANSYS, Inc.

Microsoft Azure

Maple 2019’s data analysis capabilities identify biomarkers of several cancers

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The ability to leverage complex data as a strategic asset is becoming increasingly critical, but the current labor market has a shortage of resources in big data analytics. Companies are faced with several challenges related to the inadequate resources necessary to process data. A long-time Maple user and quantum mechanics researcher, Marvin Weinstein, refers to the problem of extracting meaning from large data sets as, “How do we find a needle in a multi-dimensional haystack, when we don’t know what a needle is, and we don’t know if there is a needle in the haystack?”

Dynamic Quantum Clustering (DQC) accomplishes this feat by creating a density map of data using DQC’s proprietary Maple library, and Maple 2019 visualization tools. The result of a DQC analysis is a Maple animation that provides a visual record of the complex computations going on behind the scene. According to Marvin, Maple animations have been a big part of DQC’s success because they reveal answers without the complex mathematics. He says that, “these animations sell our product because they leverage the human ability to spot patterns developing in time and space.”

With Maple’s prototyping abilities and customizable features, Marvin was able to get DQC up and running within a week. Marvin confesses that “whenever I can avoid having to do things [manually], I do so.” By using the DQC compiled library within Maple, it was possible for Quantum Insights to have a powerful GUI without having to build the interface from scratch. Marvin believes that time is often wasted with unnecessary coding and analysis tasks, and exploits many of the built-in features of Maple to save time drive his research forward.

The core of DQC is an algorithm that maps a problem of unsupervised clustering to a problem in quantum mechanics. It uses quantum evolution to identify correlated information and reveals the details of the process through a Maple animation. This animation typically reveals hidden and unexpected insights into complex data. Marvin asserts that the aim of DQC is to “let the data speak for itself.” The advantage of working without making assumptions or hypotheses, without cleaning the data, and without the need for expert knowledge means that DQC is a data exploration method that is faster, cheaper and more efficient than current methods.

One of DQC’s major accomplishments thus far has been the identification of several biomarkers strongly correlated with multiple cancers. According to Marvin, TCGA analysis was selected as the initial step towards cancer research because cancer is a problem that everyone understands to be a big deal, and “we’ve all lost people we love to cancer.” The hope was that better clustering methods would allow mRNA from various tumor samples to better classify tumors into biologically relevant groups. The study identified 48 of 73,000 mRNA expressions that defined all five different cancer types. This analysis, published in Nature Scientific Reports, has demonstrated the ability to provide an accurate diagnosis of cancer type, based on molecular information alone, and has further revealed significant sub-typing of cancer cells, beyond what pathologists can currently achieve. The sensitivity to variation in mRNA expression patterns is the “holy grail” of precision medicine, because it promises to tell us which tumors are likely to respond to a drug and which tumors will not respond. Moreover, the analysis showed that DQC significantly outperformed tSNE-HDBScan, the current gold standard clustering method used in cancer data analytics.

Now, Marvin is working in pharmacogenomics to offer better diagnosis and treatment methods for cancer and other diseases. His company, Quantum Insights, is working towards developing effective, data-driven strategies. While Quantum Insight’s initial focus was cancer, the goal is to expand this research into other healthcare applications. Marvin believes that the DQC technique will help save lives wherever better analytics are required. Other successful applications of his research include Alzheimer’s data, detection of contraband nuclear material, analysis of the Sloan Digital Sky Survey Data, and other areas that utilize large amounts of data.

Maplesoft
www.maplesoft.com

Democratizing Simulation: delivering measurable results

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By Robert Farrell

Through the process of “democratization” organizations can safely put the power of engineering simulation into the hands of those who are not experts in using CAE software, including product designers, new engineers and even those in technical sales and customer support. This resulting Democratizing of Simulation accelerates design validation, which in turn shortens time to market with more innovative products. But what are the challenges, benefits, and enabling technologies of this democratization movement; and what results are companies actually seeing today?

Product development leverages intelligent Computer-Aided Design (CAD) models. This is no great revelation; it’s been this way since the early 1980s. About that same time the engineering world began to investigate ways to analyze these models to simulate performance. This created a need that was filled by a new breed of engineer who would develop expertise in the domain of numerical simulation – the CAE Analyst.

“Portfolio of simulation apps displayed in an e-handbook browser. (Courtesy of ESRD, Inc.)”

Software tools quickly emerged enabling these experts to painstakingly create elaborate mathematical finite element models for replicating real-world conditions and helped reduce the number of required physical prototypes. The process came to be known as “simulation;” and the results were measurable improvements in time-to-market, quality and costs. Since that time industry has embraced simulation and continued to invest in the tools and resources to support its on-going use and development.

The expert dilemma
The ability to apply advanced training, software tools, methods, expertise, and experience is as much an art as it is a science. Consequently there remains a relatively small fraternity of CAE experts – many early pioneers, or direct disciples thereof. These are the custodians of a level of expertise and experience relied upon to perform key analysis. It has been estimated there are an order of magnitude more product designers and engineers who consume the results of simulation than those who perform the simulation.

The problem is twofold. Limited expert resources create unnecessarily long analysis processes. This reduces the number of design alternatives that may be evaluated thereby stifling innovation. Second, as this generation exits the workforce there is concern that much of their knowledge will retire with them. The truth is that analysis/simulation is a critical competitive advantage for those who possess it. So what’s the answer?

Democratizing simulation
Today, there are a limited number of simulation experts and a sharply growing demand for simulation. Consequently, the resident expert is often a bottleneck. But what if a way existed to capture and reuse such knowledge and engineering judgment throughout the product development team? Democratizing Simulation is the term that is used for the techniques and approaches that allow product designers and engineers, without expertise in the use of simulation tools, to safely perform even advanced simulations and leverage the results in the design process.

Expanding the number of those capable of performing simulations safely and robustly reduces experts’ workload and allows designs to be validated more quickly while exponentially expanding the number of design alternatives that can be evaluated. Also, the simulation automation techniques that are used make the experts themselves more efficient and accurate. The results are measurable improvements in product quality, time to market, and product innovation. Additionally spreading the workload allows CAE experts to focus on more sophisticated or critical simulations. This further elevates the role and value of the expert in the organization while allowing their expertise to be leveraged by many others.

Gaining traction
More than five hundred engineers, designers and business professionals gathered in Cleveland last summer at the NAFEMS Conference on Advancing Analysis & Simulation in Engineering. The event included a growing number of sessions on Democratizing Simulation including fourteen presentations, two workshops, and a roundtable.

“It’s clear that it is no longer a question of whether democratized simulation will occur; or if it’s worthwhile to implement. Instead, the focus is on when it will become the industry norm,” said NAFEMS Americas Vice President, Matt Ladzinski. “Most presentations were real-world success stories detailing the challenges and ROI of implementation. It’s noteworthy that while none concluded that democratization is an easy process, all felt that the ROI is well worth the effort and intend to expand democratization within their organizations. These companies are the forerunners of the next generation of simulation users, when complex simulation technology vanishes behind a façade that will allow huge numbers of non-experts to safely leverage its power.”

Challenges
The vision and promise sound great; but admittedly, there are a few challenges.

Implementation
The biggest obstacle to widespread implementation is a general lack of understanding as to how or where to begin. Until now engineers were forced to scour the Internet and similar resources for bits of disjointed information. Too many web sites are all about selling something rather than educating their visitors. At the same time success stories were not well documented or readily available.

Quantifying the ROI
Often, the higher the business value, the harder it is to quantify. This is true of any business activity as it shifts from tactical to strategic importance. Quantifying the value of an expected reduction in cost or schedule can be challenging, but it is much easier than quantifying the value for increasing such things as quality, performance, or innovation.

Threat to the Status Quo
Democratizing anything represents a paradigm shift for organizations. And so Democratizing Simulation is often viewed as a direct threat by the CAE experts. Knowing the complexities of their job and unsure of how to accurately and completely replicate that knowledge for use by non-experts is understandably concerning. Consequently, CAE experts may be hesitant to endorse such an initiative. Still others may see it as diminishing their value in the eyes of the company. In no way is the role of the senior analyst diminished; nor are they being asked to relinquish control. To the contrary, through democratization techniques such as simulation applications, senior CAE analysts are taking on a more visible and important role as their expertise is now being leveraged throughout the company. Something in common amongst many of the Democratizing Simulation successes is the willingness of the CAE experts to champion the cause.

Democratization of 3D CAE Models + Results + Product Performance Information to improve data insights and fasten the design decisions. (Image courtesy of VCollab)

How it works: implementation
For those interested in taking a next step; or just want to learn more, there are multiple starting points for implementation. The most common include:
Intelligent automation templates

Template-based Simulation Automation has been used by many organizations to significantly improve the accuracy, consistency, repeatability, and efficiency of performing complex simulations. These intelligent automation templates embed the expertise of the experts in the form of rules that are automatically enforced when a template is executed. Templates not only allow non-experts to safely and robustly run simulations, but often also provide enterprise-wide standardization while making the experts more efficient and accurate.

Simulation apps
Equally important is the speed and ease of creating these templates. Specialty tools and Low-Code Development Platforms (LCDP) allow Simulation Applications (Sim Apps) to be created with little or no manual coding. This in turn allows those closest to the design process to build the Apps rather than relying on IT developers. Increasingly, Sim Apps are browser-based, and with authorized access into a corporate network one has access to the Apps without any need to have locally installed software, eliminating yet another historical constraint of simulation and modeling.

Simulation governance and standardization
All major industrial organizations employ numerical simulation in support of their engineering and business decision-making. Therefore using numerical simulation is no longer a differentiator. The differentiator is related to how safely and reliably numerical simulation is being used? Depending on the answer, numerical simulation can be a significant corporate asset or a potential liability. Whenever engineering or business decisions are based on the results of numerical simulation there is an implied expectation of reliability. Without such expectation it would not be possible to justify the time and cost of a simulation project. In fact, if simulation produces misleading information then it has a negative economic value.

System simulation
System simulation incorporates the end effects of all sub-systems and components in determining overall product performance. Throughout engineering design and simulation circles, system-level simulation has been synonymous to Model-Based Systems Engineering (MBSE), which the International Council on Systems Engineering (INCOSE) defines as a “formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases.”

Simulation Process & Data Management (SPDM) and the enterprise digital thread
Traditionally, simulation data, processes and experts have operated within various silos in the organization. Hence, this valuable expertise and data has not been an integrated part of enterprise engineering processes. Furthermore, organizations are now striving to manage their engineering data and processes in a more consistent manner, connecting these into what is being called a Digital Thread. Any engineering data that exists within silos is, by definition, left out of the Digital Thread – simulation data is such an example.

Aras Corp. believes that effective, enterprise-wide SPDM must be implemented within an open, vendor-agnostic PLM platform with a systems-centric approach and must be “invisible” to the simulation analysts.

High performance / cloud computing
From product prototyping to process design, High Performance Computing (HPC) can save businesses both time and money, while improving products and streamlining operations. Regardless of one’s experience level with HPC, in order to fully utilize it, you need access to three main components: hardware, software, and expertise.

HPC Hardware can consist of cloud-based resources, small departmental level clusters, or even powerful workstations. These are available from a variety of vendors, ranging from online ‘pay-as-you-go’ access, to large systems custom designed and installed in dedicated data centers.

CAE software can comprise of things such as solvers, meshers, visualization, and workflow managers, and so on. This software can range from very specialized, open-source packages available at no cost, to more generic commercial packages that can run across a wide scale of domains and resources.

Expertise that is available includes domains such as Computational Fluid Dynamics, Finite Structural Analysis, Bioinformatics, and so on. Companies needing expertise often start with external consulting “engineering service providers” who can assist with a specific project, before eventually directly hiring domain experts versed in a variety of technical skills.

Success stories surrounding Democratizing Simulation are plentiful and growing. Forward-thinking companies are taking advantage of available tools and resources to supercharge innovation, quality and productivity with effective use of simulation. Here are some documented examples:
GKN Driveline implementation results:
–Removes the bulk of routine analysis work and tedious report creation from the CAE Expert role, freeing them to work on more complex problems
–Allows a non-expert user to investigate many iterations and establish design-intent before expert involvement
–Data interrogation remains available for expert users, but is not required to execute the process
–Automation activity drives process refinement and structure, creating a globally consistent methodology

American Axle & Manufacturing implementation results:
–Average 75% time reduction for each analysis iteration
–Approximately $130,000 in annual cost savings at a single engineering site
–Improved quality through globally enforced standards and practices which remove human error
–Ability to run many more Noise Vibration & Harshness (NVH) analysis iterations, leading to more design decisions, earlier
–Ability to redeploy resources as less experienced engineers are now able to safely run simulations

Where to learn more
A new on-line resource community was launched in June, 2018 to support industry’s growing interest in the Democratization of Simulation. The Revolution in Simulation (www.Rev-Sim.Org) initiative is a collaborative effort among subject matter experts, industry end-users, professional associations, and solution providers. They all share a common mission to educate, advocate, innovate and collaborate through an open, non-commercial community to further advance engineering simulation for experts and non-experts alike to help ensure a significant, exponential increase in the use of simulation and simulation data.

“Rev-Sim provides access to the largest collection of educational materials including success stories, industry news, whitepapers, blogs, presentations, videos, webinars, best practices and technical reference materials to help individual professionals and their companies fully exploit the latest advances in simulation,” said Rev-Sim co-founder Rich McFall. “Perhaps most exciting is that the initiative is a true collaboration among topic experts, end users, thought leaders and solution providers including ANSYS, Aras, ASSESS, Beyond CAE, EASA, ESRD, ESTECO, Front End Analytics, Kinetic Vision, Modelon, NAFEMS, Ohio Supercomputer Center, PLM Alliances, UberCloud and VCollab. These innovative organizations are providing the expertise and funding to support this growing industry-wide movement to make engineering simulation more accessible, efficient, and reliable.”

Smart Engineering Simulation Apps: Ply-by-ply modeling and automatic lamination using 3D-solid elements enable the creation and deployment of this App in a Desktop CAE-Handbook.

Get on board
Democratizing Simulation isn’t some futuristic vision. It’s here and now and it’s delivering measurable and sustained results. Design and product development organizations, manufacturers, suppliers, software vendors and other solution-providers should begin taking steps to learn more and to join this revolution, this next generation of simulation methodologies and usage.

The confluence of simulation methodologies, software, automation templates and processes, and affordable high performance computing platforms, aided by the advent of mobile devices with ubiquitous high-bandwidth access to the Internet, has the potential to increase the number of users of simulation by an order of magnitude, over the next five to ten years.

Aras lays out strategy for acquired Comet Solutions technology

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Bruce Jenkins | Ora Research

“You probably saw our recent acquisition of Comet Solutions and thought, ‘Why’d they do that?’” writes Aras senior vice president of strategy Marc Lind. “Well, that’s a good question.” For background, see our Aras acquires Comet Solutions: Giant leap forward in simulation at enterprise scale, published here last September.

“As everyone knows,” Lind observes, “the amount of simulations being conducted has increased substantially over the past decade, and is projected to grow exponentially moving forward with the:

  • Need to further reduce physical testing,
  • Complexity of smart connected product design / MBSE,
  • Push for predictive maintenance through Digital Twins.”

Aras says it views simulation “in the context of the overall systems engineering process together with configuration and change, variants, requirements, validation testing and others. The fact that simulation management is completely disconnected from mainstream engineering processes is a problem—no closed-loop traceability/digital thread.”

Simulation will increase exponentially across the lifecycle, Aras predicts.

“Persistent problems”

According to Aras, what its largest customers say is that “simulation process and data management (SPDM) from the other major PLM providers are primarily standalone systems optimized for their own tools sets [and] treat others as second-class citizens.”

The result? When simulation environments are “isolated in silos, bad things happen:

  • Simulation results aren’t used or are too late to be useful,
  • Models get out of sync with the product design,
  • Wrong design gets simulated.”

And Aras calls these problems “just the tip of the iceberg. Without a new approach to SPDM, many of the strategic imperatives/Digital Transformation goals that rely on simulation will not be attainable.”

New approach to simulation management/SPDM is required to avoid risks, Aras believes.

“Consistent needs”

Global companies “must be able to increase simulation coverage of all types while staying in sync with design/model changes,” the company insists. “They’ve got to rapidly conduct analysis on product variations, options and concepts with repeatable processes.” Which means that “SPDM needs to be able to handle the full range of commercial tools, along with custom in-house tools, Excel and others.”

Putting its finger on one of the thorniest challenges to date in integrated, full-lifecycle engineering modeling and simulation, Aras adds, “It also means SPDM must be capable of managing mixed-fidelity models (0D/1D/2D/3D) and a wide variety of different data types. You will need multiple representations of the same item, and engineering objects should be captured independent of the underlying tools.”

Accomplishing that requires “vendor-neutral/tool-agnostic data and processes in SPDM, and a deeper level of understanding and control over the models is required—not just at the file-level—which means a unified data model in the PLM platform.”

And finally, says Aras, “Scalability has been a big problem as well. A new level of scalability is necessary moving forward.”

Aras perspective

Aras believes that “better data management and tool chaining are necessary in SPDM because they’re foundational to Digital Thread enablement, closed-loop verification, and future scenarios like machine-driven analysis. SPDM should be ‘invisible’ so that analysts and experts don’t have to worry about:

  • Where the CAD file came from,
  • Which HPC cluster to run on,
  • Where results get stored,
  • Report generation.”
Aras’s goal is to make SPDM “invisible.”

“Our approach to SPDM shoots to eliminate these redundant administrative tasks, and expose results throughout mainstream engineering processes.,” the company says. “That means from concept engineering, detailed design, test, field operation and back to requirements across the full lifecycle as part of our PLM platform. We’re doing the same thing for simulation management that we’ve done for PLM: making it more open, scalable, flexible and upgradable.”

“To accelerate things,” the company explains, “we’ve acquired Comet Solutions—provider of best-in-class capabilities for simulation process management—which immediately enables repeatable process automation to complement our unmatched data management capabilities. While we’re working on SPDM projects with customers already, we’re going further and working to incorporate Comet into the Aras platform for even more seamless capabilities moving forward. We’re excited to have the Comet team join Aras and help drive our momentum in SPDM.”

Aras Simulation Process and Data Management

Aras white paper: Unlock Simulation’s Value Across the Product Lifecycle with an Open Platform Approach

Ora Research white paper: AAM Sees Dramatic Productivity Gains, Cost Savings from Automating NVH Analysis Process with New Comet NVH Driveline SimApp

Marc Lind, SVP Strategy, Aras

Malcolm Panthaki, VP of Analysis Solutions, Aras

OnScale raises $10 Million from Intel Capital and Gradient Ventures

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OnScale, an emerging leader in Cloud-enabled engineering simulation software, announces $10M in Series A funding led by Intel Capital and Gradient Ventures, Google’s AI-focused venture capital fund. Additional investors include Thornton Tomasetti, Stage 2 Capital, Cultivation Capital, and CampbellKlein.

OnScale, which has grown considerably since emerging from stealth in early 2018, will use the new investment to drive global expansion, respond to increasing demand, and accelerate development of its Computer-Aided Engineering (CAE) solutions for complex, real-world engineering applications.

OnScale CAE tools are based on proprietary multiphysics solvers that were developed and validated over 30 years by one of the largest engineering consulting firms in the world for DARPA, the U.S. Department of Defense (DOD), and large commercial customers. The CAE solvers were architected for highly parallel mainframe computers to handle very large engineering simulation problems and are a perfect fit for modern cloud-based, high-performance computing. OnScale was spun out of Thornton Tomasetti in 2017 and is led by Chief Executive Officer Ian Campbell, along with a strong leadership team with over 100 years of combined experience in CAE software.

The company has established a large and growing base of customers, including a number of Fortune 100 companies. OnScale gives engineers a wealth of design insights and highly accurate simulation results up to 100x faster than legacy CAE offerings. Current OnScale solutions address the simulation needs of Semiconductor and MEMS, 5G mobile, next-gen biomedical, infrastructure safety, and autonomous vehicle markets. The company is focusing on improving OnScale’s user interface, expanding the breadth of physics solver capabilities, and forming partnerships with other software companies to provide seamless engineering workflows.

“With strategic investors like Intel Capital and Google’s Gradient Ventures, OnScale is well positioned to help engineers of all disciplines solve their design challenges,” said Campbell. “Created for engineers, by engineers, our mission is to usher in the future of engineering. With this investment, we will continue to empower innovators who are creating the future of technology.”

“As technology systems become more complex, next-generation computer aided engineering software will become integral to design and deployment,” said Dave Flanagan, vice president and senior managing director at Intel Capital. “OnScale’s highly scalable CAE solution leverages the power of the cloud and advanced multiphysics to model highly complex systems, helping customers solve the toughest design challenges”. Investment Director Arun Chetty will join OnScale’s board.

“Leaps in technology require paradigm shifts in engineering, and the combination of world-class multiphysics solvers, AI, and highly scalable cloud-based HPC provide an opportunity for such a paradigm shift in how we create world-changing technologies. That is why we’re excited to welcome OnScale and its team of software experts to the Gradient portfolio.” said Zach Bratun, Partner, Gradient Ventures.

OnScale
onscale.com

Mcity test concept assesses driverless vehicle safety before they take on public roads: Rebuilding consumer confidence after crash deaths

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Bruce Jenkins | Ora Research

Mcity at the University of Michigan has outlined a test-track-based concept for evaluating the safety of highly automated vehicles before they’re tested on public roads that could emerge as a model for a voluntary standard for safety testing. Mcity is a public-private partnership led by U-M to accelerate advanced mobility vehicles and technologies.

Mcity’s mission is “driving the future of mobility.” In 2014 the University of Michigan launched Mcity as an “advanced mobility research center…to cultivate the diverse expertise and resources required to realize the potential of emerging mobility technologies, and their commercial and economic viability.” Mcity describes itself as “leading the transition to a new world of connected and automated vehicles. Our work goes beyond technology and considers all aspects of the future of transportation and mobility.”

Test track project comes after two highly publicized autonomous-vehicle fatalities stoked consumer fears about safety of driverless vehicles

The new test track project comes after two highly publicized autonomous-vehicle fatalities stoked consumer fears about the safety of driverless vehicles, and slowed development of these technologies “that have the potential to save lives, conserve energy and expand accessibility to transportation,” Mcity said. The Mcity ABC Test concept would create an independent safety assessment for highly automated vehicles (HAVs). It would be a key element in a three-pronged approach to HAV testing, along with simulation and on-road evaluation.

“Highly automated vehicles must be developed in a responsible way to fully realize their promise as a useful tool that will benefit society,” said Mcity Director Huei Peng, the Roger L. McCarthy Professor of

Mechanical Engineering at U-M, who is leading the Mcity ABC Test project. “The Mcity ABC Test is an approach that can help rebuild public trust and accelerate the development of these potentially life-changing vehicles.”

The crash of an Uber Level-4 automated vehicle prototype in March 2018 killed a woman as she was crossing a street in Arizona when the car’s sensors failed to detect her. A Level-4 vehicle can drive itself without human intervention. Five days later, a man was killed on a California highway when the Level-2 automated Tesla car he was driving using Tesla’s “Autopilot” highway assist system failed to notice the driver’s inattention and did not turn off or disable the technology. Instead, the car crashed into a roadside barrier and caught fire. In a Level-2 vehicle, the driver is expected to pay attention at all times and take over driving when necessary.

Recent surveys by groups including JD Power found that as many as half or more of U.S. consumers are concerned about the safety of driverless vehicles.

ABC test: Accelerated evaluation, Behavior competence, Corner cases

The ABCs of the three-part test include “Accelerated evaluation, Behavior competence and Corner cases.”

Accelerated evaluation concentrates on the most common risky driving situations. Behavior competence puts vehicles through a set of scenarios that correspond to major motor vehicle crash frequency. Drawing from a variety of sources, Mcity compiled a list of 50 such scenarios, of which 35 were chosen for near-term focus, including 16 scenarios for low-speed, path-following Level-4 vehicles. Corner-case testing focuses on situations that test the limits of automated vehicle performance and technology.

Mcity researchers are working on executing the Mcity ABC Test beginning with three accelerated evaluation behaviors, and the 16 behavior competence scenarios for low-speed Level-4 vehicles, such as the driverless shuttles Mcity is operating on U-M’s North Campus. Mcity will pursue funding support needed to prove the Mcity ABC Test concept.

Researchers are developing the ABC test concept using the Mcity Test Facility, U-M’s controlled, real-world environment for testing connected and automated vehicles. The ABC test could be scaled for larger test facilities as well, such as the American Center for Mobility in Ypsilanti Township, Mich. U-M is a founding partner of ACM.

Access the white paper

A comprehensive white paper outlining the crucial need that inspired the Mcity ABC Test protocol, along with specific test components, was released January 15, 2019 at the AutoMobil-D symposium at the North American International Auto Show at Cobo Center: “Mcity ABC Test: A Concept to Assess the Safety Performance of Highly Automated Vehicles”.

Mcity

American Center for Mobility

U-M Transportation Research Institute