New Cadence Clarity 3D Transient Solver Delivers up to 10X Faster System-Level EMI Simulation

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System design teams can quickly and accurately simulate large and complex hyperscale, automotive, mobile, and aerospace and defense systems

Cadence Design Systems, Inc. (Nasdaq: CDNS) today expanded its system analysis product line with the introduction of the Cadence® Clarity 3D Transient Solver, a system-level simulation solution that solves electromagnetic interference (EMI) system design issues up to 10X faster than legacy 3D field solvers and offers unbounded capacity. Built on Cadence’s massively parallel matrix solver technology, the Clarity 3D Transient Solver handles workload levels that previously required time-consuming and expensive anechoic test chambers to test prototypes for electromagnetic compatibility (EMC) compliance. The new solver is capable of simulating large designs that until now have been impractical or unable to be solved, reducing respins and accelerating time to market. This makes it ideal for many complex applications in the hyperscale computing, automotive, mobile, and aerospace and defense markets. For more information, please visit www.cadence.com/go/claritytransient.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20201013005380/en/

The Cadence Clarity 3D Transient Solver quickly and accurately simulates large and complex hyperscale, automotive, mobile, and aerospace and defense systems, ensuring EMC compliance without expensive test chambers. (Photo: Business Wire)

“As a premier engineering service provider, Ultimate Technologies focuses on quick, efficient and first-time-right designs,” said Satoshi Utsumi, CEO of Ultimate Technologies, Inc. “The Clarity 3D Transient Solver from Cadence allows us to simulate with test-measurement accuracy so we can predict what will be measured during EMI testing, thereby ensuring our customers pass EMI compliance checking on the first pass while dramatically reducing the number of prototype designs. This allows us to shave up to three months off automotive ECU design cycles, reducing design cycle time by as much as 30 percent. With Clarity 3D technology, we can quickly iterate and improve design quality

InVeris Training Solutions Rebrands from Meggitt to Shape Future of Simulation and Live-Fire Training

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Inveris Logo Stacked Color No Tag

InVeris Training Solutions

On July 1 of this year, Pine Island Capital Partners acquired Meggitt Training Systems. We had an opportunity to interview several principal members of the newly rebranded company, InVeris Training Solutions, as the new name and logo debuted on October 7. But first, a brief history lesson.

If you are old enough to have been working in law enforcement back in the early 1980s, you’ll likely remember that super-cool, high-speed, no-drag training system called FATS or Firearms Training Systems, Inc. Founded in Atlanta, Georgia in 1984, FATS was the first interactive projected training system that allowed for training law enforcement and military personnel with firearms… but no bullets being fired. This made the training inherently safer and, over time, less costly. FATS steadily evolved over time so that the video simulations could branch, resulting in multiple possible outcomes for a given scenario beginning. In 1990, FATS delivered its first virtual training system to the United States Marine Corps.

Across the past 36 years since its introduction, the system has continued to evolve and improve to include lane marksmanship systems, an indirect fire training system and even a simulated mortar system. In 1996 they began integrating 3D CGI environments, greatly enhancing their ability to provide an even greater depth of branching options and potential outcomes to all simulations. We could go on, but the bottom line is that FATS never sat on its laurels; it continued to evolve and continually improve, gaining in capability and value to both law enforcement and military training.

In 2008 Meggitt PLC acquired FATS and combined it with live-fire training specialist Caswell International to form Meggitt Training Systems. The name may have changed but the aggressive evolution did not and further increases in capability and programming occurred every year from 2014 on. Perhaps

AI researchers challenge a robot to ride a skateboard in simulation

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AI researchers say they’ve created a framework for controlling four-legged robots that promises better energy efficiency and adaptability than more traditional model-based gait control of robotic legs. To demonstrate the robust nature of the framework that adjusts to conditions in real time, AI researchers made the system slip on frictionless surfaces to mimic a banana peel, ride a skateboard, and climb on a bridge while walking on a treadmill. An Nvidia spokesperson told VentureBeat that only the frictionless surface test was conducted in real life because of limits placed on office staff size due to COVID-19. The spokesperson said all other challenges took place in simulation. (Simulations are often used as training data for robotics systems before those systems are used in real life.)

“Our framework learns a controller that can adapt to challenging environmental changes on the fly, including novel scenarios not seen during training. The learned controller is up to 85% more energy-efficient and is more robust compared to baseline methods,” the paper reads. “At inference time, the high-level controller needs only evaluate a small multi-layer neural network, avoiding the use of an expensive model predictive control (MPC) strategy that might otherwise be required to optimize for long-term performance.”

The quadruped model is trained in simulation using a split-belt treadmill with two tracks that can change speed independently. That training in simulation is then transferred to a Laikago robot in the real world. Nvidia released video of simulations and laboratory work Monday, when it also unveiled AI-powered videoconferencing service Maxine and the Omniverse simulated environment for engineers in beta.

A paper detailing the framework for controlling quadruped legs was published a week ago on preprint repository arXiv. AI researchers from Nvidia; Caltech; University of Texas, Austin; and the Vector Institute at the University of Toronto contributed to the

New Simulation Technology Helps Get the Jump on Wildfires

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The Sonoma-Lake-Napa Unit (LNU) wildfires in California burned nearly 200,000 acres before finally being contained. But in the process, the California Department of Forestry and Fire Protection (CAL FIRE) was able to deploy a simulation technology that helps firefighters predict the actions of a wildfire and deploy resources more quickly where needed. 

The data has always been available, but only within silos and compiling that data traditionally took hours or days. The technology, developed by Technosylva, was partially deployed by CAL FIRE in July during the LNU fires and showed a rapid spread of the wildfire. 

“We’re rolling it out over a three-phased implementation period,” said Christine McMorrow, CAL FIRE resource management communications officer. “Our first phase went live July 31 in four fire units at our training centers and regional and Sacramento command centers.”

Phase two was scheduled to go live Oct. 1 in half of the CAL FIRE units. The final phase will be introduced at the end of the year, McMorrow said. “By the end of the year, all of our units across the state and command centers will have the technology.”

Fuel and weather data is analyzed in real time, creating simulations of the wildfire’s potential movement and providing situational awareness and critical intelligence to fire managers on the ground. 

“It’s pulling together different data sources that fire managers use to make on-the-ground decisions, and it does it in real time, and can be used on a desktop computer and our commanders have it on their smartphones, so it’s very mobile and highly powerful,” McMorrow explained. 

“They’re using it to plan resources, locate where fire lines can get cut within a reasonable time frame, work with the sheriffs’ departments on evacuation planning and predict areas where there is the greatest potential for staging and deployment,” she