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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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At least 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Performance Audit Report: Automated Meteorological Monitoring Stations, Lawrence Livermore National Laboratory

The Waste and Air Quality Offices Group at the Lawrence Livermore National Laboratory operates two main meteorological monitoring sites near Livermore, California. The primary met tower (Site 200) is located in the northwest corner of the lab and consists of a fifty-two (52) meter tower with vertical wind speed sensors, horizontal wind speed and direction sensors and air temperature sensors at fifty-two (52) meters, twenty-three (23) meters and ten (10) meters. In addition, there is a temperature and humidity probe at ten (10) meters. At two (2) meters there are upward and downward facing solar and infrared radiation sensors, an air temperature sensor, barometric pressure sensor and a temperature and relative humidity probe. At ground level there is a tipping bucket rain gauge located to the southwest of the tower. The datalogger, communication peripherals and the barometric pressure sensor are housed in a small building near the tower. The Site 300 met site is located approximately 10 miles east of Livermore within the boundary of the LLNL blast test site. This site also consists of a 52-meter tower which is configured the same as the 52-meter tower at Site 200. There is also a building at this site that houses the datalogger, communication peripherals and the barometric pressure sensor. At both Site 200 and Site 300, data are collected by Ethernet with telephone modem collection as a backup. The data collection interval for both sites is fifteen (15) minutes via workstations running Loggernet software located at the main lab facility. The audits of the Lawrence Livermore National Laboratory’s two automated meteorological stations located near Livermore, California were performed on October 24 & 25, 2023. These audits were performed under the guidelines of the Quality Assurance Handbook for Air Pollution Measurement Systems, Volume IV, Version 2 and the On-Site Meteorological Program Guidance for Regulatory Modeling Applications, U.S. EPA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Universal Input-Output Model of GFM Functions and Data-Driven Verification Methods

An overarching goal of the UNiversal Interoperability for grid-Forming Inverters (UNIFI) Consortium is to develop vendor agnostic specifications and guidelines that ensure interoperability of gridforming (GFM) inverter-based resources (IBRs) without requiring vendors or system operators to reveal proprietary information. These UNIFI principles and specifications are envisioned to apply to a wide range of technologies and systems. The initial work on the UNIFI principles and specifications has focused on performance requirements and high-level aspirational principles outlined in [1]. Going forward, a key question is how to translate such high-level requirements and principles into rigorous specifications that can be enforced and validated for a wide range of IBRs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

An Assessment of Machine Learning Applied to Ultrasonic Nondestructive Evaluation

In the United States, the nuclear industry performs inservice inspection (ISI) through nondestructive examination (NDE) methods in accordance with guidelines specified in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), Section XI, Rules for Inservice Inspection of Nuclear Power Plant Components. Ultrasonic nondestructive testing and evaluation (NDT&E) is one of the more commonly used techniques for inspecting Class 1 structural components in nuclear power systems. As the number of qualified NDE inspectors declines, the nuclear industry is looking to take advantage of advances in automation to enhance inspection capabilities. Advances in computational power, cloud-based computing, and machine learning algorithms make automated data analysis possible. Machine learning (ML) has shown huge potential in automated data analyses for ultrasonic NDE in the context of weld inspections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

COBRA-SFS Version 6.2.1 User Guide: A Thermal Hydraulic Analysis Code for Spent Fuel Storage and Transportation Casks

This document is an updated and reduced version of the complete documentation of the COBRA-SFS thermal analysis code (COolant Boiling in Rod Arrays – Spent Fuel Storage) (Michener et al. 1995). This manual provides the analyst with input instructions and fundamental guidelines for contrasting models using COBRA-SFS. COBRA-SFS is designed to analyze the dry storage and transportation casks that house spent or used nuclear fuel. The primary focus and application is on square light water reactor fuel assemblies, however the code also has the capability to model hexagonal assemblies and is will suited to any geometry that can be defined as an extruded 2-D map.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Complete Evaluation on Advanced Reactor Machine Learning Subversion Attacks (Final)

Navigating through the world of Artificial Intelligence (AI) in nuclear reactors and their Instrumentation and Control (I&C) systems demands a careful, deliberate journey. AI’s capability to manage massive datasets and streamline control systems has indeed carved out a significant role in various sectors, including nuclear energy. However, while AI, and particularly Large Language Models (LLMs), bring a lot to the table in terms of operational efficiency and anomaly detection, they also expose the sector to a new breed of cybersecurity threats, like Inference Attacks, Adversarial Attacks, and Trojan Attacks. This guide is designed to be a straightforward manual, diving deep into the intertwining worlds of AI and cybersecurity within nuclear reactors, and tailoring insights for three crucial audiences: I&C Vendors/Developers, Nuclear Regulators, and Nuclear Reactor Operators and Cyber Defense Teams. (1) Section 2, directed at I&C Vendors/Developers, will provide a clear and focused look at several cybersecurity attacks, offering practical recommendations and detailed scenarios related to AI cybersecurity. This section isn’t just about identifying problems but also about giving solid, usable solutions. (2) Section 3, meant for Nuclear Regulators, gets straight to the point about regulations, policy suggestions, and guidelines that are needed to lay down a robust, secure, and ethical foundation for the application of AI in nuclear operations. The focus is on making sure that everything adheres to international standards and laws while being practicable and clear-cut. (3) Section 4, aimed at Nuclear Reactor Operators and Cyber Defense Teams, offers an exhaustive exploration and technical reports, with clear recommendations and scenario analyses vital to protect operational environments and guarantee the secure application of AI in nuclear reactor operations. The goal is simple: as we step into an era where AI becomes a fundamental element of our technological and energy infrastructures, this guide is here to act as a clear, direct handbook, ensuring that AI is implemented within the nuclear sector in a manner that is secure, responsible, and practical. It’s about striking a balance – optimizing the undeniable benefits offered by AI while securing and shielding against potential cyber threats as we move through this new and complex landscape.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Modeling and Policy Pathways to Decarbonize South Asia’s Industrial Sector

The industrial sector is responsible for one-third of global greenhouse gas emissions, and industrial decarbonization will be an essential component of limiting emissions and mitigating climate change (Rissman et al., 2020). This holds true for South Asian countries as they work toward their stated commitments to reducing emissions in the coming years. India has pledged to reduce the emissions intensity of its gross domestic product (GDP) by 33–35% by 2030 (Government of India, 2016) and announced at COP26 a target of reaching net-zero CO 2 emissions by 2070, a goal that will require rapid decarbonization of energy-intensive industries (WEF, 2021). Bangladesh’s Nationally Determined Contributions include a commitment to reducing greenhouse gas emissions by 6.73% to 15.12% by 2030 (Ministry of Environment, Forest and Climate Change, 2021). While these Nationally Determined Contributions do not explicitly target emissions reductions in industry, Bangladesh’s Energy Efficiency and Conservation (EE&C) Master Plan highlights industry as an important sector for EE&C (Sustainable and Renewable Energy Development Authority, 2015). Sri Lanka has pledged carbon neutrality by 2050, including a reduction in industrial greenhouse gas emissions (Ministry of Environment, 2021). Nepal’s commitment to net-zero greenhouse gas emissions by 2050 includes plans to establish guidelines and technology transitions facilitating industrial decarbonization (Government of Nepal, 2020).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Industrial Assessment Center

Established in 1990, San Diego State University’s (SDSU) Industrial Assessment Center (IAC) is proud of its years of service. During this period, it has served over 620 small and medium-sized manufacturing plants in Southern California. SDSU/IAC’s efforts to transfer state-of-the-art technologies to industry have increased revenues, cultivated creativity, improved energy efficiencies, and benefited the environment. The Center has contributed to the region's economic growth and stability by assisting small and medium size companies to better compete in the global market. It has helped mitigate climate change by reducing greenhouse gas emissions. IAC activities have fostered productive relationships between the University and local industry, assisted industrial sectors to improve their energy efficiency and enhance their manufacturing productivity, in turn impacting the material and working conditions of their employees. In addition to financial savings and environmental benefits, we have trained tens of students who became energy specialists in various companies. Thus, a substantial benefit of the IAC has been the ongoing training of engineering faculty and students. All IAC graduates were offered jobs before or within weeks of their graduation. The activities of the SDSU/IAC have expanded the institutional expertise of the College and improved the knowledge base of the faculties involved leading to several related publications, master’s theses, and senior student projects. Significant number of peer-reviewed publications of the IAC director at SDSU have greatly benefitted from the experience of the Center. As a result of this extensive exposure to manufacturing processes, the SDSU/IAC has grown to be an integral component of SDSU’s engineering research and training. We have successfully built upon these established achievements and academic excellence. IAC service to industry is particularly vital in Southern California, a region with one of the highest manufacturing concentrations in the country. SDSU/IAC has understood and implemented the overall objectives of DOE’s IAC program and guidelines except for the pandemic years when the country’s manufacturing sector was put in dire stress. In addition to student training and service to industry, IAC’s contribution to state and local governments as well as utility companies to assess energy policies and design rebate and incentive strategies cannot be undermined.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Driving the Shift to Energy-Efficient and Climate-Responsible Commercial Refrigeration Equipment in Chile

This report provides an overview of global and Chile-specific market trends, technological advancements, and policy developments related to commercial refrigeration equipment, with an emphasis on refrigerated display cabinets. Section 2 examines CRE market trends at the global and Chilean levels. Section 3 presents CRE energy consumption and the latest technological options for improving energy performance. It also discusses low global warming potential (GWP)1 refrigerant options for CRE. Section 4 provides a cost-effectiveness analysis. Section 5 reviews other regional energy efficiency standards and labeling programs and offers potential standard requirements for Chile. Section 6 concludes the report by summarizing key findings and conclusions. Finally, Appendix A provides detailed guidelines intended as a starting point to inform policies and programmes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

ORNL Contributions to the ENDF/B-VIII.1 Library [Slides]

For uranium and plutonium isotopes, evaluation work is converging to a stable configuration with an overall satisfactory benchmark performance (more information on the validation tests after CSEWG). Strontium evaluation was included in the repository library and successfully tested by processing codes relative to an alternative quantification of the external function. Cerium covariance matrices were updated to address review comments on the magnitude of the uncertainty. For future uncertainty quantification, theoretical observables should be properly decoupled from current measured guidelines. Tests to correctly include LP (from resonance parameters) fitted to measured energy-averaged data are in progress. Current ENDF files contains experimental LP data.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Additive Manufacturing of Dissolvable Mandrels

ORNL collaborated with Mitsubishi Chemical America to investigate different grades of vinyl alcohol co-polymers as a potential feedstock material for large-scale material extrusion additive manufacturing (AM). Dissolvable polymers and can find potential applications in AM tooling for complex, hollow, and trapped composite structures without the need for specialized molds and tools. This CRADA Phase I work involved analysis of three different developmental grades of vinyl alcohol co-polymers for thermal and rheological properties, followed by print trials on the Big Area Additive Manufacturing (BAAM) system using these materials. Finally, printed part properties, including mechanical and thermal performance, as well as dissolvability were evaluated. The properties and performance evaluated in this phase of the project have provided guidelines to further develop these vinyl alcohol co-polymers to enable large-scale printing at high deposition rates and obtain parts that satisfy high temperature molds and dies requirements.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Refined Method to Translate Solar Data Quality Assessment Flags to Estimated Measurement Uncertainty

Integrating solar resource uncertainties due to radiometer measurement performance and operational data quality assessment can provide improved estimates of economic bankability, system design performance, and compliance of solar energy conversion systems. Estimating radiometer measurement uncertainty is an established procedure consistent with recognized best practices and international guidelines. SERI QC is a robust solar data quality assessment software tool that has been in continuous use for more than three decades. This report, the fourth of six for the Data Quality and Uncertainty Integration Project, presents a refined algorithm description for software to translate solar resource data quality assessment results into estimated uncertainty values in a Solar Resource Operational Uncertainty Integrator (SROUI) application. This algorithm requires three-component solar irradiance measurements - global horizontal irradiance, direct normal irradiance, and diffuse horizontal irradiance - collected at 1- to 60-minute intervals, as described in the previous deliverables. The development of this report as Deliverable 6.4 was an iterative process that included reviews and feedback from the project team on initial drafts designed to refine how the new software could best support determining solar resource data uncertainty. The results of this effort will contribute to the final software system development by National Renewable Energy Laboratory staff.

14 SOLAR ENERGY↗
DOE OSTI2024

Web-Based Weatherization Assistant Getting Started Guide

This guide provides introductory information on how to get started in using the web-based Weatherization Assistant audit tool and running the National Energy Audit Tool, Manufactured Home Energy Audit, Multifamily Tool for Energy Audits, and Health and Safety Audit. For new users, this guideline also outlines how you can create a client and start an audit for that client. The Weatherization Assistant is a family of advanced audit tools designed specifically to help states and local weatherization agencies implement the US Department of Energy (DOE) Weatherization Assistance Program. The Weatherization Assistant is developed and maintained by DOE’s Oak Ridge National Laboratory (ORNL). It applies engineering and economic calculations to assist states and agencies in selecting energy-efficient retrofit measures that meet government criteria for cost effectiveness and that can be installed in homes of low-income families enrolled in the program. The Weatherization Assistant can be used to select and rank measures for individual houses, or to establish a priority list of weatherization measures for nearly identical housing types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Mechanical Material Handling Coordinator (43321) [Slides]

Upon successful completion of this course, participants will be able to assess a load handling activity in order to develop a mechanical materials handling plan following safety guidelines and LANL policies.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Inaugural Symposium of the Institute for Sustainable Energy and Environment, Virginia Commonwealth University

The Inaugural Symposium of the Institute for Sustainable Energy and Environment (ISEE) was held in Virginia Commonwealth University, Richmond, Virginia during April 26 – 28, 2023. The symposium addressed issues and challenges in energy and environment and highlighted the use of clean renewable energy to mitigate the adverse effects of fossil fuels and the greenhouse gases it produces. These issues are complex as the involve educating the public that the climate change is real, it is caused by the use of fossil fuels, it requires scientists and engineers to understand the fundamental science in the production and storage of renewable energy, it requires industries to manufacture and distribute the equipment necessary for commercial application of these technologies, it requires policy makers to put together policies and guidelines to make the transition from fossil fuels to renewable energies efficient, and it requires social scientists and educators to address environmental justice issues and create a workforce to sustain the transition. The symposium considered all the above issues with a diverse list of speakers from the federal and state government, industrial partners, and experts from science and technology to social sciences and public policy. Speakers from the White House Office of Science and Technology Policy, Department of Energy, universities, and non-governmental agencies discussed the challenges and solutions in Plenary as well as Panel sessions. The talks were recorded with permission from the speakers and the panelists and were put in the ISEE website. The participants included students, postdoctoral fellows, and professors from Virginia Commonwealth University and local area Historically Black College and Universities (HBCU) such as Virginia State University and Norfolk State University. The $5000 fund awarded by the Department of Energy were used to support the participation of students, postdoctoral fellows, and faculty from the HBCU institutions. The technical program the list of participants is provided later in the document.

08 HYDROGEN↗
DOE OSTI2024

Facilitating Implementation of High-Volume Fly Ash Use in Pre-cast Concrete Construction to Increase Beneficial Utilization

The main goal of this project was to increase the beneficial use of fly ash as a supplementary cementitious material for precast concrete applications. A major focus was to develop balanced concrete mix design strategies which collectively satisfy the follow objectives: 1) increase fly ash beneficial use by at least 15% in the precast concrete industry, 2) maintain or exceed stringent structural property requirements (e.g., compressive strength at initial prestress, modulus of rupture, etc.), 3) exhibit little or no additional cost relative to conventional mixtures, and 4) mitigate detrimental environmental consequences inadvertently caused by increased beneficial use. Outcomes from this project include recommendations for design guidelines and code provisions for sustainable concrete mix designs, facilitating diversion and harvesting of large quantities of fly ash from landfills or impoundments, and multiple frameworks for incorporating discarded fly ash materials (i.e., landfilled or ponded fly ash after separating the impurities) in concrete construction.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Best Practices Guide for Energy-Efficient Data Center Design

This guide provides an overview of best practices for energy-efficient data center design which spans the categories of information technology (IT) systems and their environmental conditions, data center air management, cooling and electrical systems, and heat recovery. IT system energy efficiency and environmental conditions are presented first because measures taken in these areas have a cascading effect of secondary energy savings for the mechanical and electrical systems. This guide concludes with a section on metrics and benchmarking values by which a data center and its systems energy efficiency can be evaluated. No design guide can offer “the most energy-efficient” data center design but the guidelines that follow offer suggestions that provide efficiency benefits for a wide variety of data center scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Bottom-up design of actinide materials from molecular clusters: Demonstration of a general-purpose simulation capability leveraging machine-learned atomic potentials

Actinide thin-film coatings such as uranium dioxide (UO 2 ) play an important role in nuclear reactors and other mission-relevant applications, but realization of their potential requires a deep fundamental understanding of the chemical vapor deposition (CVD) processes used for their growth. The slow experimental progress can be attributed, in part, to the standard safety guidelines associated with handling uranium byproducts, which are often corrosive, toxic, and radioactive. Accurate simulation techniques, when used in concert with experiment, can improve laboratory safety, material durability, and deliverable timeframes. However, state-of-the-art computational methods are either insufficiently accurate or intractably expensive. To remedy this situation, in this project we suggested a machine-learning (ML) accelerated workflow for simulating molecular clustering toward deposition. As a benchmark test case, we considered molecular clustering in steam and assessed independent components of our workflow by comparing with measured thermodynamic properties of water. After analyzing each component individually and finding no fundamental barrier to realization of the workflow, we attempted to integrate the ML component, a Sandia-developed tool called FitSNAP. As this was the first application of FitSNAP to atoms and molecules in the gas phase at Sandia, the method required more fitting data than was originally anticipated. Systematic improvements were made by including in the fit data diatomic potentials, molecular single-bond-breaking curves, and symmetry-constrained intermolecular potentials. We concluded that our strategy provides a feasible pathway toward modeling CVD and related processes, but that extensive training data must be generated before it can be of practical use.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine Learning Solutions for a Stable Grid Recovery

Grid operating security studies are typically employed to establish operating boundaries, ensuring secure and stable operation for a range of operation under NERC guidelines. However, if these boundaries are severely violated, existing system security margins will be largely unknown, as would be a secure incremental dispatch path to higher security margins while continuing to serve load. As an alternative to the use of complex optimizations over dynamic conditions, this work employs the use of machine learning to identify a sequence of secure state transitions which place the grid in a higher degree of operating security with greater static and dynamic stability margins. Several reinforcement learning solution methods were developed using deep learning neural networks, including Deep Q-learning, Mu-Zero, and the continuous algorithms Proximal Reinforcement Learning, and Advantage Actor Critic Learning. The work is demonstrated on a power grid with three control dimensions but can be scaled in size and dimensionality, which is the subject of ongoing research.

24 POWER TRANSMISSION AND DISTRIBUTION↗