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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Distribution System Research Roadmap; Energy Efficiency and Renewable Energy

The scope of the U.S. Department of Energy's Energy Efficiency and Renewable Energy (EERE) office covers a number of distributed energy resource (DER) technologies, including distributed photovoltaics, smart buildings, wind, water, behind-the-meter-storage, and electric vehicles. The impact of these technologies on the distribution system is often assessed with an individual technology focus. Similarly, different technology offices often leverage different sets of tools, leading to analyses that are not comparable. EERE sought the ability to assess the impact of integrating multiple DER technologies, and to comprehensively address DER integration challenges across the portfolio of EERE technologies. This project built on existing work understanding technical challenges, mapped out the key research questions, assessed relevant capabilities across the national laboratory network, identified key gaps, and produced a research roadmap to inform EERE investment decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Cybersecurity and Digital Components: Supply Chain Deep Dive Assessment

The report “America’s Strategy to Secure the Supply Chain for a Robust Clean Energy Transition” lays out the challenges and opportunities faced by the United States in the energy supply chain as well as the federal government plans to address these challenges and opportunities. It is accompanied by several issue-specific deep dive assessments, including this one, in response to Executive Order 14017 “America’s Supply Chains,” which directs the Secretary of Energy to submit a report on supply chains for the energy sector industrial base. The Executive Order is helping the federal government to build more secure and diverse U.S. supply chains, including energy supply chains. As the energy sector has become more globalized and increasingly complex, digitized, and even virtualized, its supply chain risk for digital components – the software, virtual platforms and services, and data – in energy systems has evolved and expanded. All digital components in U.S. energy sector systems are vulnerable and may be subject to cyber supply cha in risks stemming from a variety of threats, vulnerabilities, and impacts. This includes digital components in all systems within the ESIB, namely those systems operated by asset owners across different energy subsectors (e.g., electricity, oil and natural gas, and renewables) and the systems operated by a worldwide industrial complex with capabilities to perform research and development and design, produce, operate, and maintain energy sector systems, subsystems, components, or parts to meet U.S. energy requirements. Supply chain risks for digital components including software, virtual platforms and services, and data have grown in recent years as increasingly sophisticated cyber adversaries have targeted exploiting vulnerabilities in these digital assets. Supply chain risks for digital components in energy sector systems will continue to evolve and likely increase as these systems are increasingly interconnected, digitized, and remotely operated.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

The extended Vinet analytical equations of state

When testing new materials models, it is often not possible to use tabulated Equations of States (EOS) since the model might only be available in a smaller specialized research code without capability to read in tables. In such cases a versatile and easy to implement analytical EOS is needed. In this report I derive, give, and discuss all formulas necessary for implementing the thermodynamically complete extended Vinet EOS 3 into codes. While similar to a Mie-Grüneisen (MG) EOS, this Vinet EOS is based on an isotherm and substantially easier to correctly implement than a MG EOS. In the extended Vinet the isotherm’s density dependence is given as a power series in density to accommodate for higher density behavior which normally requires the Hugoniot based MG.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Parameterization of the β and γ phases of Tin using the Vinet and Mie-Grüneisen Equations of State

When testing new phase aware materials models, it is often not possible to use tabulated Equations of States for the phases since the model might only be available in a smaller specialized research code without capability to read in tables. These EOS parameterizations for two of the solid phases of Tin were developed for testing the Kinetic Phase Transition model by Carl Greeff, LANL. They are based on two isotherms per phase obtained from work in progress by Carl Greeff, and their phase boundary corresponds fairly well to SESAME 2162. A full machinery is applied for the parameterization of the Vinet EOSs while the Mie-Grüneisen parameterizations are translated from the Vinet EOSs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

ROTOR: Research to Operations and Operations to Research

PNNL’s Research to Operations/Operations to Research (ROTOR) Program fosters a cybersecurity operations to researcher collaboration, identifying hard problems and challenges for cyber defenders and bringing researcher science disciplines to these challenges. ROTOR allows PNNL’s cyber defenders to better protect the laboratory but also fosters innovation and incubation of solutions for our sponsor missions across DOE, DOD, DHS and the intelligence community. Our sponsors and their missions are faced with many of the same cyber defense challenges that PNNL faces. By using our own laboratory security operations environment as an innovation generator and testing ground, allowing research to be tested and tried, our sponsors are directly benefitted. PNNL is in a unique position to combine our world class research organization with enterprise cybersecurity operations. ROTOR is taking advantage of this to bring PNNL cybersecurity research projects into an operational environment within PNNL’s Cyber Security Operations Center. With ROTOR, PNNL researchers gain the advantage of operational experience and expertise and have an avenue for showcasing research in an operational environment. This helps to advance PNNL research, prove operability of PNNL projects to its sponsors, and provide real-world insight to real-world problems for our cybersecurity research agenda. ROTOR is the conduit for PNNL cybersecurity research to find its way to operational use. PNNL researchers and engineers are informed by real-world operations and operations has access to current PNNL research and engineering capabilities. All of this leads to improved reputation for PNNL as a provider of national security solutions that are tried and tested. To date, ROTOR has collaborated with six projects, enabling each to conduct operational work within the CSOC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

S&TR April-May 2023 (Corrosion Issue)

Corrosion damages and can ultimately destroy items from household appliances and personal vehicles to aircraft parts and reinforcing steel in bridges and roadways. As the article beginning on p. 4 describes, Lawrence Livermore researchers have developed capabilities for predicting the onset of corrosion in specific materials. Of particular interest to the Laboratory and its mission are impacts to weapon components stored in potentially corrosive environments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Multiphysics Multiscale Simulation Platform for Damage, Environmental Degradation, and Life Prediction of CMCs in Extreme Environments

This project successfully developed a multiphysics, multiscale computational framework to enhance the design and development of CMCs, with a focus on modeling highly nonlinear, time-dependent damage mechanisms and material degradation under extreme conditions, such as those experienced in turbine service environments. The project made significant advances in improving our understanding of progressive damage, oxidative degradation, and time-dependent inelastic deformation in CMCs, with particular attention to the role of uncertainties in predictions. Key outcomes include the integration of advanced material characterization, uncertainty quantification, and multiphysics constitutive models to predict the behavior of CMCs over their service life. A novel multiscale methodology was employed, which integrated microscale constituent behaviors with structural-scale responses, enabling the manufacturing defects in the microstructure that are prone to damage nucleation. Through the development of DL algorithms, the project advanced the prediction of damage initiation and crack propagation, taking into account the defect morphology and statistical variations across multiple scales. The framework was rigorously validated using thermomechanical experiments, which tested CMCs under various mechanical loadings at elevated temperatures, further enhancing the model's predictive capability. Overall, the research outcomes have provided a more accurate, reliable method for predicting CMC component life, significantly advancing material design, and improving component reliability in extreme environments. This work has strong implications for the optimization of turbine components and other high-performance applications where CMCs are used.

03 NATURAL GAS↗
DOE OSTI2025

DistOPF: Advanced Solutions for Distribution Optimal Power Flow Analysis - DistOPF v0.2 Documentation

To achieve an affordable and reliable energy system, research on power distribution system is often focused on integration of distributed generators, energy storage solution, EV charging, smart meters, and other advanced assets that may benefit from or require more advanced control and optimization techniques. Despite this focus on advanced distribution system topics, early researchers and grid scientists often start from scratch when developing optimization programs for power distribution systems. This report introduces DistOPF, a Python package that consolidates years of research into a versatile and modular tool. DistOPF provides researchers with essential capabilities to solve distribution system Optimal Power Flow (OPF) problems using standard network models. Additionally, it offers a platform to benchmark both new and existing algorithms against established test systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Advanced Materials and Next-Gen Tech Research Pave the Way for PV Everywhere

At NREL, we see potential for photovoltaics (PV) everywhere. Our research is unlocking capabilities to enable PV across a full range of applications and locations. You'll find unique breadth and depth in our PV resources and expertise, all concentrated within a single world-class lab complex.

14 SOLAR ENERGY↗
DOE OSTI2022

Irradiation Experiments and Thermal Analysis for Reactor System Design and Analysis at INL

Idaho National Laboratory (INL) is the nation's lead nuclear laboratory working to enhance reactor systems' safety, security, economics, and efficiency. Research and development (R&D) programs at INL support the current fleet of nuclear reactors for safer operation and newer reactors technology design, development, demonstration, and deployment. A major focus of INL's mission is the reactor system design and analysis supported by the irradiation experiments and thermal analysis of advanced and current-generation nuclear fuels and materials. The irradiation experiments and thermal analysis provide a deeper understanding of basic radiation damage processes that can determine the basis for performance improvements and verification of modeling assumptions. These experiments and analyses include experiment management: design, fabrication, characterization, irradiation, and post-irradiation examination. This research involves thermal, neutronic, and material investigation using the INL's Advanced Test Reactor (ATR) and Transient Reactor Test (TREAT) facilities. The results from these experiments and analysis are required to develop the regulatory basis for deploying new or modified fuels and materials. This seminar talk will also provide a general overview of the INL's research facilities, ongoing research programs, core capabilities, and opportunities for students and faculties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

ARIES 2022

An annual report of ARIES FY 2022 research highlights and capabilities, partner impacts, engagement and outreach, and messages from DOE and an External Advisory Board member.

clean energy↗
DOE OSTI2023

Gas delivery system for environmental transmission electron microscope

A portable, compact gas delivery system can support an environmental transmission electron microscope. Environment transmission electron microscopy provides researchers a unique capability of assessing a material's surface conditions at atomic resolution in a variety of reactive and oxidizing environments. The ability to precisely control the analysis chamber's environmental conditions over time is key to the success of a typical surface analysis. The gas delivery system provides the correct balance or pressure delivery precision, contamination control, and gas isolation.

Nogan, John Joseph↗
DOE OSTI2025

Analysis of SPND Material Candidates for Real-Time Neutron Spectrum Monitoring Poster

The future of the nuclear industry will be shaped by advanced reactor designs requiring innovative instrumentation for safe operation. A key area of innovation is the ability to accurately and reliably monitor the neutron energy spectrum during operations, which would also enhance the experimental capabilities of existing research reactors. To address this need, our research focuses on the potential use of Self-Powered Neutron Detectors (SPNDs) for real-time neutron spectrum monitoring. We investigated various candidate materials for SPNDs by evaluating their energy-dependent reaction rates. Promising materials were further modeled using MCNP to determine the free electron production per neutron across the neutron energy spectrum, approximating their energy-dependent signal sensitivity. Our findings identified Samarium (Sm) and Gadolinium (Gd) as top candidates for thermal neutrons, Hafnium (Hf) and Thulium (Tm) for epithermal neutrons, and Tantalum (Ta) for fast neutrons. These materials will undergo future experimental validation to confirm the modeled responses and assess their feasibility for real-time neutron spectrum measurements.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Advanced Interactive 3D Visualization Tool for Customizable Analyses of Tomography Datasets in Material Science

Current methods for visualizing and analyzing 3D tomography datasets in materials science often lack the interactivity and depth required for detailed structural insights. This limitation restricts a researchers' ability to accurately interpret complex data, which is critical for advancing material innovations and understanding structural properties. To address this issue, we have developed a novel, web-based interactive 3D visualization and analysis tool from the Trame framework that offers customizable features to enhance data interpretability. The tool allows users to adjust parameters such as visible range, slice planes, data rotation, and layering, providing a more detailed and dynamic view of complex structures. Its user-friendly web interface increases the accessibility and ease of use for both novice and experienced researchers, to visualize large volumetric datasets. The tool supports a diverse range of data formats, making it versatile for various research applications. Unique capabilities include real-time data manipulation, automated feature detection, context-sensitive feedback, and real-time volume calculations and distributions per sliced region or layer, alongside the ability to quickly generate high-quality screenshots and videos for presentations and reports. These advancements offer a comprehensive solution for enhanced 3D data exploration, significantly improving the analysis process and communication of results in materials science.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Lessons Learned from Open-Source Software Training Toward Expanding the Fusion Workforce

Within the United States (U.S.), the Fusion Innovation Research Engine (FIRE) Collaboratives seek to accelerate fusion technology development through wide-ranging community-driven research activities that bring together industry, laboratories, research institutes, and academia. Increasing the maturity of key components and systems for future fusion power plants (FPPs) toward commercialization, will, by necessity, increase the need for knowledgeable engineers, designers, and researchers in industry capable of integrating and further improving these technologies within industry FPP concepts. Further, various modeling and simulation packages support these programs and are under-development within them to drive design iteration and the development of FPP digital twins. To derive the greatest benefit from model output and capabilities, training these same specialists will be vital. Thus, the development of effective and accessible software onboarding and professional development opportunities focused on fusion will be key to keeping the pace of growth high in the coming decade and beyond. A similar need exists within the advanced fission reactor community, driven by an ever-growing need for carbon-free baseload power for industrial and data center applications. Within the U.S. and around the world, several open-source packages and frameworks exist to support this endeavor, and two we will highlight here are the Multiphysics Object Oriented Simulation Environment (MOOSE) framework and OpenMC. These packages, notably, are also being utilized in the FIRE Collaboratives program. In this presentation, we will highlight the lessons learned from over 30 years of combined software development and training experience, focused on developing strong technical software foundations within the nuclear workforce, from students to professional engineers & scientists. We will connect this experience to present and emerging needs in the fusion energy community, and, finally, will outline possible paths forward to develop a large, robust, global fusion workforce.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Privacy Preserving Federated Learning for Advanced Scientific Ecosystems

We present a framework to provide privacy preserving (PP) federating learning (FL) across multiple computational and experimental facilities. This work joins the compute capabilities of National Energy Research Scientific Computing Center (NERSC) and Oak Ridge National Laboratory Research Cloud (ORC) with simulated experimental data, such as those produced at the SLAC National Accelerator Laboratory and Spallation Neutron Source (SNS). We describe the software infrastructure developed to provide privacy for computational and experimental networks. We developed algorithmic privacy across the federated system by embedding database security, computation, and communication into the federation architecture, utilizing scientific tools developed by the experimental community.

Archibald, Rick [ORNL] (ORCID:0000000245389780)↗
DOE OSTI2024

Role of Nuclear Science User Facilities (NSUF) in Nuclear Energy Materials Research

The Nuclear Science User Facilities (NSUF) is one of a diverse number of U.S. Department of Energy (DOE) user facilities established to provide researchers with the most advanced tools of modern science. The NSUF is unique and represents a consortium of capabilities distributed across the U.S. at twenty-one institutions. The NSUF is centered at and managed from the Idaho National Laboratory (INL), where it was originally founded, but it coordinates activities at twenty “partner” institutions that include universities, the Center for Advanced Energy Studies (CAES), national laboratories, and a nuclear industry vendor. These institutions have capabilities that include neutron, ion, and gamma irradiation, hot cells, advanced materials characterization equipment, and high-performance computing resources. Many of these capabilities were beyond reach for most researchers before NSUF. The NSUF provides researchers to access these capabilities at no cost to nuclear energy researchers to produce the highest quality research results to increase understanding of advanced nuclear energy technologies important to DOE-NE and support national priorities by adapting to the needs of DOE-NE programs, industry, and new innovative concepts for sustainable nuclear future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

A GPT‐4 Reticular Chemist for Guiding MOF Discovery**

Abstract We present a new framework integrating the AI model GPT‐4 into the iterative process of reticular chemistry experimentation, leveraging a cooperative workflow of interaction between AI and a human researcher. This GPT‐4 Reticular Chemist is an integrated system composed of three phases. Each of these utilizes GPT‐4 in various capacities, wherein GPT‐4 provides detailed instructions for chemical experimentation and the human provides feedback on the experimental outcomes, including both success and failures, for the in‐context learning of AI in the next iteration. This iterative human‐AI interaction enabled GPT‐4 to learn from the outcomes, much like an experienced chemist, by a prompt‐learning strategy. Importantly, the system is based on natural language for both development and operation, eliminating the need for coding skills, and thus, make it accessible to all chemists. Our collaboration with GPT‐4 Reticular Chemist guided the discovery of an isoreticular series of MOFs, with each synthesis fine‐tuned through iterative feedback and expert suggestions. This workflow presents a potential for broader applications in scientific research by harnessing the capability of large language models like GPT‐4 to enhance the feasibility and efficiency of research activities.

Chemistry↗