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[Due to the increasing size of the archives, each topic page now contains only the prior 365 days of content. Access to older stories is now solely through the Monthly Archive pages or the site search function.]

Sandia team develops autoignition model designed for efficient, accurate engine simulations

May 12, 2016

Researchers at Sandia National Laboratories have developed a model for how diesel engines autoignite. Understanding the fundamental processes that produce autoignition can lead to designs that improve engine efficiency and reduce emissions by optimizing the timing and location of ignition.

Sandia postdoctoral researcher Layal Hakim, working with mentors and Sandia principal investigators Guilhem Lacaze and Joe Oefelein, designed and implemented an optimized chemical model that describes autoignition of a diesel fuel surrogate and quantifies the degree of uncertainty in the model.

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Ricardo Software to partner with Modelon to expand IGNITE simulation package capabilities

April 26, 2016

Ricardo Software will partner with Modelon to expand Ricardo’s IGNITE product capabilities. IGNITE is a physics-based system simulation package operating in Modelica (earlier post) focused on complete vehicle system modeling and simulation. With comprehensive powertrain and thermofluid component libraries, users can quickly and accurately model conventional to highly complex vehicle system models, hybrid-electric, full electric and novel vehicles.

In the upcoming 2016 product release, planned for May, IGNITE users will have instant access to Modelon’s advanced OPTIMICA Compiler Toolkit, a Modelica and Functional Mock-up Interface (FMI) based computational platform for system design.

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Argonne VERIFI team improves code to enable up to 10K simultaneous engine simulations; paradigm shift in engine design

April 09, 2016

A team of scientists and engineers with the Virtual Engine Research Institute and Fuels Initiative (VERIFI) (earlier post) at the US Department of Energy’s Argonne National Laboratory recently completed development of engineering simulation code and workflows that will allow as many as 10,000 engine simulations to be conducted simultaneously on Argonne’s supercomputer, Mira.

These simulations are typical “engineering-type” smaller scale simulations, which are used routinely for engine design within industry. This massive simulation capacity has opened up a new capability for industrial partners seeking new advanced engine designs.

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TriboForm Engineering launches tribology simulation software for metal-forming processes; Volvo, Mercedes-Benz, Škoda launch customers

February 28, 2016

TriboForm Engineering, a spin-out from the University of Twente in The Netherlands, introduced its TriboForm software at Triboforum 2016, a triennial industry conference. Tribology is a branch of mechanical engineering that describes the contact between materials under different conditions. In metal-forming processes, tribology plays a key role through the relative motion and interaction between the applied sheet material, the lubrication and the tooling.

TriboForm is a software solution for the simulation of friction and lubrication in metal-forming processes. With unique physically-based simulation technology, TriboForm enables its users accurately to simulate friction and lubrication conditions quickly and then directly integrate the results in metal-forming simulations.

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Federal-Mogul Powertrain cuts engine valve development time using new simulation model

January 28, 2016

Federal-Mogul Powertrain has developed a simplified transient dynamic simulation model of valve closing action in order to predict dynamic loading on engine valves. By improving the accuracy of calculated deformation and stress under load, the technique enables valve fatigue life to be estimated more reliably and helps to ensure optimum material selection from the early stages of a new engine design.

In the design of intake and exhaust valves for combustion engines, especially those with a high degree of forced induction by supercharging or turbocharging, particular attention is paid to the loading conditions during valve closing.

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Researchers develop computer model for crash injury risks based on precrash occupant position

November 13, 2015

Researchers led by Ashley Weaver, assistant professor at the Virginia Tech-Wake Forest University Center for Injury Biomechanics, have developed a method to compute crash injury metrics and risks as functions of precrash occupant position.

The process allows for quantification of the sensitivity and uncertainty of the injury risk predictions based on occupant position to understand further important factors that lead to more severe motor vehicle crash injuries. The modeling results provide details not available from using crash test dummies (anthropomorphic test devices, or ATDs).

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NSF-funded supercomputing project to combine physics-based modeling with massive amounts of data

September 11, 2015

The National Science Foundation will provide $2.42 million to develop a unique facility for refining complex, physics-based computer models with big data techniques at the University of Michigan. The university will provide an additional $1.04 million. The focal point of the project will be a new computing resource, called ConFlux, which is designed to enable supercomputer simulations to interface with large datasets while running.

ConFlux will enable High Performance Computing (HPC) clusters to communicate seamlessly and at interactive speeds with data-intensive operations. The project establishes a hardware and software ecosystem to enable large scale data-driven modeling of multiscale physical systems.

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New Argonne engine simulation project investigating effects of uncertainties on engine function; targeting gasoline compression ignition

August 25, 2015

Researchers at the US Department of Energy’s Argonne National Laboratory are launching a new simulation project from the Virtual Engine Research Institute and Fuels Initiative (VERIFI) (earlier post) to investigate how multiple variables—uncertainties—interact simultaneously to impact the functioning of an engine.

A primary focus of the research will be enabling a new generation of gasoline compression engines that operate on the basis of low-temperature combustion. A gasoline compression engine combines many of the benefits of diesel and gasoline engines by using compression to ignite the fuel in the same manner used by diesels. Vehicle manufacturers have shown interest in pursuing low-temperature combustion as an innovative route to more efficient engines.

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CONVERGE code optimization yields three-fold increase in engine simulation speed

June 10, 2015

Researchers at the US Department of Energy’s Argonne National Laboratory are partnering with Convergent Science, Inc. (CSI), to speed up a key piece of modeling and simulation software to ensure those cycles are used as effectively as possible, reducing product development time and resulting in better engines and savings for consumers.

The research is part of Argonne’s Virtual Engine Research Institute and Fuels Initiative (VERIFI), which is working with CSI to optimize the company’s CONVERGE code, a CFD (computational fluid dynamics) program widely used in industry to conduct modeling and simulation for engine design. (Earlier post.) While the effort has been ongoing for more than two years, it has recently moved into a code optimization phase that is showing dramatic gains.

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Sandia RAPTOR turbulent combustion code selected for next-gen Summit supercomputer readiness project

May 28, 2015

RAPTOR, a turbulent combustion code developed by Sandia National Laboratories mechanical engineer Dr. Joseph Oefelein, was selected as one of 13 partnership projects for the Center for Accelerated Application Readiness (CAAR). CAAR is a US Department of Energy program located at the Oak Ridge Leadership Computing Facility and is focused on optimizing computer codes for the next generation of supercomputers.

Developed at Sandia’s Combustion Research Facility, RAPTOR, a general solver optimized for Large Eddy Simulation (LES, a mathematical model for turbulence), is targeted at transportation power and propulsion systems. Optimizing RAPTOR for Summit’s hybrid architecture will enable a new generation of high-fidelity simulations that identically match engine operating conditions and geometries. Such a scale will allow direct comparisons to companion experiments, providing insight into transient combustion processes such as thermal stratification, heat transfer, and turbulent mixing.

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