Search NASA⌕ Search
Home/Archive/DOE OSTI

DOE OSTI · 2327052

3.0 - MOOSE: Enabling massively parallel multiphysics simulations

Giudicelli, Guillaume·Lindsay, Alexander·Harbour, Logan·Icenhour, Casey·Li, Mengnan·Hansel, Joshua E.·German, Peter·Behne, Patrick·Marin, Oana·Stogner, Roy H.·Miller, Jason M.·Schwen, Daniel·Wang, Yaqi·Munday, Lynn·Schunert, Sebastian·Spencer, Benjamin W.·Yushu, Dewen·Recuero, Antonio·Prince, Zachary M.·Nezdyur, Max·Hu, Tianchen·Miao, Yinbin·Jung, Yeon Sang·Matthews, Christopher·Novak, April·Langley, Brandon·Truster, Timothy·Nobre, Nuno·Alger, Brian·Andrs, David·Kong, Fande·Carlsen, Robert·Slaughter, Andrew E.·Peterson, John W.·Gaston, Derek·Permann, Cody
View original source ↗Export metadata ↓

Abstract

The development of MOOSE has kept accelerating since the last release, with over 2,100 pull requests merged over the last 30 months that involved nearly fifty contributors across close to a dozen institutions internationally. The growth in MOOSE's capabilities and downstream applications is reflected in the growth of the community. User support provided on the GitHub discussions forum has steadily increased to nearly 50 daily interactions. New simulation projects, notably to model advanced nuclear reactor and fusion devices, are driving a significant expansion of the capabilities. This paper reports on these developments, with several major released features, new physics modules, and key improvements to the user experience and simulation workflow.

Explore related subjects

22 GENERAL STUDIES OF NUCLEAR REACTORS97 MATHEMATICS AND COMPUTINGFinite-elementFinite-volumeFrameworkMOOSEMultiphysicsMultiscaleParallel

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Giudicelli, Guillaume, Lindsay, Alexander, Harbour, Logan, Icenhour, Casey, Li, Mengnan, Hansel, Joshua E., German, Peter, Behne, Patrick, Marin, Oana, Stogner, Roy H., Miller, Jason M., Schwen, Daniel, Wang, Yaqi, Munday, Lynn, Schunert, Sebastian, Spencer, Benjamin W., Yushu, Dewen, Recuero, Antonio, Prince, Zachary M., Nezdyur, Max, Hu, Tianchen, Miao, Yinbin, Jung, Yeon Sang, Matthews, Christopher, Novak, April, Langley, Brandon, Truster, Timothy, Nobre, Nuno, Alger, Brian, Andrs, David, Kong, Fande, Carlsen, Robert, Slaughter, Andrew E., Peterson, John W., Gaston, Derek, Permann, Cody. 2024-03-22. 3.0 - MOOSE: Enabling massively parallel multiphysics simulations. https://doi.org/10.1016/j.softx.2024.101690

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

DOE OSTI2026

ZiaCore Critical Experiment Demonstrates Key Technologies for Nuclear Energy Systems

ZiaCore is a LANL Laboratory Directed Research and Development (LDRD) project focused on developing and demonstrating key technologies for future nuclear energy systems. The project itself was split into three tasks: 1) Design of the ZiaCore Reactor, a UO2 fueled, graphite and zirconium-hydride (ZrH) moderated, heat pipe cooled micro-reactor 2) Development of the ZrH and heat pipes components 3) Performance of a critical experiment with a representative portion of the ZiaCore reactor incorporating the ZrH and heat pipes developed and made at LANL.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Operating Experience Data Analysis for Digital Instrumentation and Control System Reliability and Risk Assessment in Nuclear Power Plants

The implementation of advanced digital instrumentation and control (DI&C) systems in U.S. nuclear power plants (NPPs) can bring significant advancements in reliability, monitoring, and control capabilities. However, these systems also introduce new challenges, particularly in assessing risks such as common-cause failures (CCFs) and establishing robust reliability estimates for DI&C components. Addressing these challenges is critical for ensuring the safe and efficient operation of NPPs. Recently, Idaho National Laboratory was tasked by the U.S. Nuclear Regulatory Commission (NRC) to conduct a DI&C reliability study using operating experience data from the nuclear industry. The two operating experience data sources for the study are the Institute of Nuclear Power Operations’ Industry Reporting and Information System (IRIS) and the NRC’s Licensee Event Report database which is hosted at Idaho National Laboratory at https://lersearch.inl.gov/LERSearchCriteria.aspx. This report provides a comprehensive examination of DI&C systems, including their architecture, operational advantages, and associated challenges. It reviews existing industry DI&C studies and failure mode taxonomies, along with reliability data from various industries. Through a detailed analysis of these databases, the study provides insights into DI&C system performance. Considerations should be given to incorporate DI&C failure data into the NRC's Integrated Data Collection and Coding System and updating the Reliability and Availability Data System to support ongoing DI&C reliability studies. Recommendations are also provided for modeling DI&C reliability and CCF in probabilistic risk assessment, thereby supporting risk-informed decision-making and enhancing the reliability and safety of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗