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Miller, Jason M.

Publications and source records attributed to Miller, Jason M..

8 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

3.0 - MOOSE: Enabling massively parallel multiphysics simulations

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.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

2.0 - MOOSE: Enabling massively parallel multiphysics simulation

The last 2 years have been a period of unprecedented growth for the MOOSE community and the software itself. The number of monthly visitors to the website has grown from just over 3,000 to now averaging 5,000. In addition, over 1,800 pull requests have been merged since the beginning of 2020, and the new discussions forum has averaged 600 unique visitors per month. The previous publication has been cited over 200 times since it was published 2 years ago. This paper serves as an update on some of the key additions and changes to the code and ecosystem over the last 2 years, as well as recognizing contributions from the community.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Continuous Integration, In-Code Documentation, and Automation for Nuclear Quality Assurance Conformance

The Multiphysics Object Oriented Simulation Environment (MOOSE) is an open-source, finite element framework for solving highly coupled sets of nonlinear equations. The development of the framework and applications occurs concurrently using an agile, continuous-integration software package. Included in the framework is an in-code, extensible documentation system. Using these two tools in union with the repository management tools GitHub and GitLab, a software quality plan was created and followed such that MOOSE and a MOOSE-based application (BISON) have been shown to meet the American Society of Mechanical Engineers’ Nuclear Quality Assurance-1 standard. The approach relies heavily on automation for both testing and documentation. The resulting effort demonstrates that a rigorous software quality plan may be implemented that incurs a minimal impact on day-to-day development of the software, satisfying the stringent guidelines necessary to operate the software in a safety function within a nuclear facility.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

One-pot synthesis of high molar activity 6-[ 18 F]fluoro-l-DOPA by Cu-mediated fluorination of a BPin precursor

A one-pot two-step synthesis of 6-[ 18 F]fluoro-L-DOPA ([ 18 F]FDOPA) has been developed involving Cu-mediated radiofluorination of a pinacol boronate ester precursor. The method is fully automated, provides [ 18 F]FDOPA in good activity yield (104 ± 16 mCi, 6 ± 1%), excellent radiochemical purity (>99%) and high molar activity (3799 ± 2087 Ci mmol -1 ), n = 3, and has been validated to produce the radiotracer for human use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Continuous integration for concurrent MOOSE framework and application development on GitHub

For the past several years, Idaho National Laboratory’s MOOSE framework team has employed modern software engineering techniques (continuous integration, joint application/framework source code repos- itories, automated regression testing, etc.) in developing closed-source multiphysics simulation software (Gaston et al., Journal of Open Research Software vol. 2, article e10, 2014). In March 2014, the MOOSE framework was released under an open source license on GitHub, significantly expanding and diversifying the pool of current active and potential future contributors on the project. Despite this recent growth, the same philosophy of concurrent framework and application development continues to guide the project’s development roadmap. Several specific practices, including techniques for managing multiple repositories, conducting automated regression testing, and implementing a cascading build process are discussed in this short paper. Furthermore, special attention is given to describing the manner in which these practices naturally synergize with the GitHub API and GitHub-specific features such as issue tracking, Pull Requests, and project forks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

LESSONS FROM NUCLEAR ENERGY: BUILDING SNOW AND AVALANCHE SIMULATION TOOLS USING A COMMON OPEN-SOURCE FRAMEWORK

The Department of Energy (DOE) is currently investing millions of dollars annually into various modeling and simulation tools for all aspects of nuclear energy. An important part of this effort includes developing applications based on the open-source Multiphysics Object Oriented Simulation Environment (MOOSE; mooseframework.org) from Idaho National Laboratory (INL). Through the DOE and outside collaborators, MOOSE includes a large set of physics modules, including phase field, level set, heat conduction, tensor mechanics, Navier-Stokes, and porous media, among others. The phase-field module, in particular, is well-suited for micro-structure evolution simulations, including solidification, as shown in the figure. It was also used, in conjunction with the heat conduction module, to build a multiscale snow model (Pika) as presented at the 2014 International Snow Science Workshop (Slaughter et al., 2014). The snow science community should learn from the nuclear industry, and harness the enormous effort underway to build simulation tools that are open, modular, and share a common framework. In particular, MOOSE-based multi-physics solvers are inherently parallel, dimension agnostic, adaptive in time and space, fully-coupled, and capable of interacting with other applications. The snow science community must build on existing tools to enable collaboration between researchers and practitioners throughout the world, and advance the state-of-the-art in line with other scientific research efforts.

97 MATHEMATICS AND COMPUTING↗