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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.]

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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Argonne supercomputer helped Rice/Minnesota team identify materials to improve fuel production

April 29, 2015

Scientists at Rice University and the University of Minnesota recently identified, through a large-scale, multi-step computational screening process, promising zeolite structures for two fuel applications: purification of ​ethanol from fermentation broths and the hydroisomerization of alkanes with 18–30 carbon atoms encountered in petroleum refining. (Earlier post.)

To date, more than 200 types of zeolites have been synthesized and more than 330,000 potential zeolite structures have been predicted based on previous computer simulations. With such a large pool of candidate materials, using traditional laboratory methods to identify the optimal zeolite for a particular job presents a time- and labor-intensive process that could take decades. The researchers used Mira, the Argonne Leadership Computing Facility’s (ALCF) 10-petaflops IBM Blue Gene/Q supercomputer, to run their large-scale, multi-step computational screening process.

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ORNL VIBE open-architecture framework for improved EV battery design

April 06, 2015

VIBE provides an open architecture framework for pre-experimental design simulation as part of the CAEBAT program. Click to enlarge.

As part of the US Department of Energy’s (DOE) CAEBAT (Computer Aided Engineering for Batteries) activities (earlier post), scientists at Oak Ridge National Laboratory (ORNL) have developed a flexible, robust, and computationally scalable open-architecture framework that integrates multi-physics and multi-scale battery models.

The Virtual Integrated Battery Environment (VIBE) allows researchers to test lithium-ion batteries under different simulated scenarios before the batteries are built and used in electric vehicles. The physics phenomena of interest include charge and thermal transport; electrochemical reactions; and mechanical stresses. They operate and interact across the porous 3D structure of the electrodes (cathodes and anodes); the solid or liquid electrolyte system; and the other battery components. VIBE was developed by researchers in ORNL’s Computational Engineering & Energy Sciences group, led by Dr. John Turner.

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Extensive materials genome modeling study suggests best adsosrbent materials for natural gas storage already designed; 70% of ARPA-E target

February 03, 2015

Using a materials genome approach, a collaboration between EPFL, the University of California at Berkeley, Rice University, the Georgia Institute of Technology, Northwestern University, Lawrence Berkeley National Laboratory, and the Korea Advanced Institute of Science and Technology has searched for high-performance adsorbent materials to store natural gas in a vehicular fuel tank.

In their study, published in the RSC journal Energy & Environmental Science, they simulated more than 650,000 designs for nanoporous materials. They found that the best candidates for natural gas storage have already been designed—but that those best materials meet only 70% of the Advanced Research Projects Agency - Energy (ARPA-E) targets for natural gas storage on vehicles. (Earlier post.)

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