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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2024

Human Subjects in Energy Technology and Policy Research Symposium Report

The inaugural Human Subjects in Energy Technology & Policy Symposium was held virtually on October 17 and 19, 2023. The symposium gathered professionals supporting and conducting research to develop and deploy energy technologies and policies, with the goals of increasing awareness of what constitutes human subjects research in this field of research, promoting best practices from the proposal stage through study completion, and fostering a culture of collaboration. This report is a summary of this Symposium.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2022

NASA's Responsible AI Plan

Artificial Intelligence (AI) is an integral part of today’s process of conducting science and technology development. At NASA, AI has become an integral and important tool for researchers, engineers, data scientists, and technologists in pursuing the ground-breaking discoveries that we are known for, including the command and controlling of our spacecraft and other supporting infrastructures. Consequently, research and engineering efforts incorporating AI have permeated almost every area of our work. It is contributing to NASA’s drive toward the future, not just of space science, but for society here at home. We are dedicated to continuing the use of AI in a safe and fully transparent approach so that the public can have high confidence in the outcomes and benefits. We believe that the plan outlined here will be responsive and contribute to the call for openness across the federal government. NASA is committed to responsible use of AI in all of its activities and in all phases of development and deployment of its space and terrestrial programs missions. NASA does not deliberately focus on “AI Research” as a separate field (we have no single “AI office” or “AI program”), rather NASA uses AI to build tools for its programs. This plan, being put forward, adheres to the Responsible AI (RAI) principles set and laid down by the White House in its Presidential Executive Order 13960. Our research, engineering and technical communities have been made aware of these guidelines and we are committed to an on-going process of educating and monitoring its implementation to ensure adherence to those principles. The vast majority of NASA’s use cases, which number almost 75 today, are geared toward analyzing the petabytes of data that NASA collects from its fleet of spacecraft across all disciplines, in human space exploration, and in aeronautics, etc.

Artificial Intelligence↗
NASA NTRS2022

NASA's Responsible AI Use Cases

This submission consists of NASA's Responsible Artificial Intelligence (RAI) Use Cases. These RAI Use Cases are to be made public, pursuant to the Presidential Executive Order 13960, Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government. They were collected from NASA's practicing AI research community and cover the gamut of NASA's AI activities. These Use Cases will be updated annually as required by the Executive Order. The information included consists of the NASA Center, a summary of the goal, the AI techniques being applied, information on training data, and information on source code.

Artificial Intelligence↗
NASA NTRS2022

Supporting Responsible Machine Learning in Heliophysics

Over the last decade, Heliophysics researchers have increasingly adopted a variety of machine learning methods such as artificial neural networks, decision trees, and clustering algorithms into their workflow. Adoption of these advanced data science methods had quickly outpaced institutional response, but many professional organizations such as the European Commission, the National Aeronautics and Space Administration (NASA), and the American Geophysical Union have now issued (or will soon issue) standards for artificial intelligence and machine learning that will impact scientific research. These standards add further (necessary) burdens on the individual researcher who must now prepare the public release of data and code in addition to traditional paper writing. Support for these is not reflected in the current state of institutional support, community practices, or governance systems. We examine here some of these principles and how our institutions and community can promote their successful adoption within the Heliophysics discipline.

Machine learning↗
NASA NTRS2023

NASA's Responsible AI Use Cases

This submission consists of summary use cases for NASA's Responsible Artificial Intelligence (RAI). These RAI Use Cases are to be made public, pursuant to the Presidential Executive Order 13960, Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government. They were collected from NASA's practicing AI research community and cover the gamut of NASA's AI activities. These Use Cases will be updated annually as required by the Executive Order. The information included consists of the NASA Center, a summary of the goal, the AI techniques being applied, information on training data, and information on source code.

Artificial Intelligence↗
DOE OSTI2024

AGN-201 Digital Twin Concept of Operations

The AGN-201 is a nuclear reactor at Idaho State University (ISU) and is currently being used in the development of a digital twin (DT) with Idaho National Laboratory (INL). The goal is to create a DT (called the AGN-201 DT) which can monitor an operating nuclear reactor to determine when the reactor is being operated normally; normal operations are any operations that is declared by the ISU staff. To accomplish this, researchers at INL developed a DT ecosystem which can ingest data from the AGN-201 reactor. This data is fed into a series of machine learning (ML) and reactor physics models. The ML and reactor physics models assess the data and determine if the reactor is operating normally. Event(s) that are flagged as anomalies are investigated by the INL staff to determine if any undeclared experiments were conducted. The AGN-201 DT was verified in July/August 2023, when the ISU staff performed undeclared experiments and the INL staff were able to assess the anomalous events and determine what likely caused each event. This project was a steppingstone to promote the use of DTs for international safeguards and marks the first time a DT was able to monitor a nuclear reactor for this purpose. This document provides the concept of operations (CONOPS) for the AGN-201 digital twin (DT). The CONOPS describes how the AGN-201 and AGN-201 DT are expected to operate and details how each are established.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗