Rapid CFD Using Machine Learning Algorithms (CRADA Final Report)

Technical Report · Fri Feb 03 04:00:00 EST 2023

DOI:https://doi.org/10.2172/3000138· OSTI ID:3000138

Castillo, Victor ^[1]; Mohassab, Yousef ^[2]

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1. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
2. Guardian Glass, LLC, Carleton, MI (United States)

This is a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (“LLNL”) and Guardian Glass, LLC ("Guardian Glass") to develop a fast-running emulator of the reactive Computational Fluid Dynamics (“CFD”) simulations needed to understand the complex reactions and flows in the glass melting, fining, and forming subprocesses. This CRADA project is sponsored under the High-Performance Computing for Manufacturing (“HPC4Mfg”) Program of the Department of Energy’s Advanced Manufacturing Office (“AMO”) within the Energy Efficiency and Renewable Energy (“EERE”) Office.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Guardian Glass, LLC, Carleton, MI (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Advanced Materials & Manufacturing Technologies Office (AMMTO)
• DOE Contract Number: AC52-07NA27344
• OSTI ID: 3000138
• Report Number(s): LLNL--TR-2012760; CRADA-TC02358
• Country of Publication: United States
• Language: English

Related Subjects

36 MATERIALS SCIENCE
97 MATHEMATICS AND COMPUTING