ALBUQUERQUE, N.M. – Sandia National Laboratories and industrial giant Caterpillar Inc. have signed their first umbrella Cooperative Research & Development Agreement (CRADA), opening the door to a wide range of scientific research.
“This agreement will lead to an expanded relationship with Caterpillar,” said Vic Weiss, the Sandia business development specialist who helped negotiate the CRADA. “It’s a strategic collaboration.”
The labs had a pair of standard CRADAs with Caterpillar a decade ago, each dealing with a specific project in diesel combustion. The umbrella CRADA has a broader scope, covering multiple projects in a variety of categories over three years.
The CRADA authorizes work in computer and computational science, information and data analysis, mathematics, engineering science and high-performance computing. Technical categories include simulation design exploration, advanced analytics, multi-physics engineering modeling and simulation and high-performance computing. The agreement includes training, education, technical support and staff visits.
“We’re excited about this new CRADA. We hope to do many new projects with Caterpillar in different technical areas,” Weiss said. “These agreements benefit our partners and Sandia by allowing us to do more research and advance our scientific knowledge. We learn when we partner with industry.”
CRADA partners share the cost of research, inventions, copyrights and patents. Legal terms and conditions are negotiated just once, so each new project does not have to go through that process.
Caterpillar is the world’s leading manufacturer of construction and mining equipment, diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. The company is looking to Sandia to help it develop advanced modeling and simulation technologies for virtual product development.
The first project under the agreement focuses on optimization in support of Caterpillar’s product engineering, said Jim Stewart, manager of Sandia’s Optimization and Uncertainty Quantification department.
“Caterpillar wants to work with us on software capabilities to help do optimization studies on their engineering designs,” Stewart said.
The work will involve Sandia’s Dakota open-source software tool that helps researchers adjust and assess the accuracy of computational simulations. Dakota shortens design cycles and cuts development costs.
“Caterpillar’s interest in Dakota initiated the discussions about a CRADA,” Stewart said. “Dakota is installed in their system but they have a need to tailor it in ways to make it work better for them.”
Chris Ha, a manager in Caterpillar’s Information Analytics Division, said the company “is excited to collaborate with Sandia in the optimization and uncertainty quantification space focused around Dakota.”
“We recognize that Sandia is one of the world’s leading experts in these fields, and this relationship will help enable opportunities for Caterpillar to leverage such expertise,” he said.
Sandia will provide training and research. Another effort will combine the capabilities of Dakota and a newer software package, Pyomo (Python Optimization Modeling Objects), to provide a wider range of optimization capabilities. Pyomo is a Sandia-developed open-source tool for formulating and manipulating algebraic models within the Python programming environment.
“We’ve had an interest in getting Dakota and Pyomo to work together in the software sense,” Stewart said. “This is something we’ve wanted to do and now we can through this CRADA.”
Stewart said the project will lead to other avenues of research. “The aim is to get some good work started and build from it in future projects.”
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Sandia National Laboratories is a multi-program laboratory operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin company, for the U.S. Department of Energy’s National Nuclear Security Administration. With main facilities in Albuquerque, N.M., and Livermore, Calif., Sandia has major R&D responsibilities in national security, energy and environmental technologies and economic competitiveness.
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