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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Next-Generation Analysis and Visualization Platform for Manufacturing and Engineering Workflows (Final Report)

Advanced manufacturing and engineering are fundamental to the economic strength and national security of the United States. With the introduction of advanced modeling and simulation practices in manufacturing and engineering over the last several decades, we are producing better products, more quickly, and at decreased cost. Through the adoption of high-performance computing (HPC) enabled workflows, in small- to medium-sized manufacturers and engineering firms, which employ fewer than 500 people, is renewing United States manufacturing and engineering. Despite successes, there are significant barriers to widespread adoption of these tools. Our Phase I SBIR project, Next-Generation Analysis and Visualization Platform for Manufacturing and Engineering Workflows, aims to address several of these barriers. Our project helped us evaluate the feasibility and benefits and mitigate risks of asynchronous processing for analysis and visualization workflows. We evaluated the impact of asynchronous, non-blocking communication can have on the user experience in a complex visualization application. Besides the impact on users, we wanted to understand the impacts on developers (development application programming interfaces (APIs))and generated applications (robustness and stability). Any asynchronous platform implementation is bound to rely on multiple threads which can make the programming model extraordinarily complex and prone to bugs. If not managed carefully, the complexity and resulting instability would be an unacceptable evolution for widely used production tools like ParaView and putting the success of the Phase II project at risk.

42 ENGINEERING↗
DOE OSTI2021

Influence of Business Models on PV-Battery Dispatch Decisions and Market Value

PV-battery hybrid projects dominate interconnection queues in some regions in the United States, but few projects have been operational long enough to assess how the hybrid capabilities may be used in practice. We interview plant operators and analyze empirical dispatch data for eleven large-scale PV-battery hybrids in three organized wholesale markets in the United States. We use the dispatch data and wholesale market prices to estimate the market value of our sample hybrids in 2020. The empirical increase in market value of a PV-battery hybrid relative to a standalone PV plant varies by project and ranges from $\$$1 to $\$$48/MWhsolar. The premium is driven by market, location, technical characteristics of the PV and battery asset, and battery dispatch strategies. In contrast to the widespread assumptions in the PV-battery hybrid modeling literature, only three of the eleven project operators optimize battery usage for wholesale market revenue as merchant plants. Instead, the majority of operators in the sample have alternate objectives. For example, load-serving entities target peak load reductions, incentive program participants focus on compliance with program requirements, and large energy consumers prioritize resiliency and utility bill minimization. Understanding prevalent dispatch signals and the degree of alignment with system-wide grid needs can increase the market value of PV-battery hybrids.

14 SOLAR ENERGY↗
DOE OSTI2017

Best Practices of Uncertainty Estimation for the National Solar Radiation Database (NSRDB 1998-2015): Preprint

It is essential to apply a traceable and standard approach to determine the uncertainty of solar resource data. Solar resource data are used for all phases of solar energy conversion projects, from the conceptual phase to routine solar power plant operation, and to determine performance guarantees of solar energy conversion systems. These guarantees are based on the available solar resource derived from a measurement station or modeled data set such as the National Solar Radiation Database (NSRDB). Therefore, quantifying the uncertainty of these data sets provides confidence to financiers, developers, and site operators of solar energy conversion systems and ultimately reduces deployment costs. In this study, we implemented the Guide to the Expression of Uncertainty in Measurement (GUM) 1 to quantify the overall uncertainty of the NSRDB data. First, we start with quantifying measurement uncertainty, then we determine each uncertainty statistic of the NSRDB data, and we combine them using the root-sum-of-the-squares method. The statistics were derived by comparing the NSRDB data to the seven measurement stations from the National Oceanic and Atmospheric Administration's Surface Radiation Budget Network, National Renewable Energy Laboratory's Solar Radiation Research Laboratory, and the Atmospheric Radiation Measurement program's Southern Great Plains Central Facility, in Billings, Oklahoma. The evaluation was conducted for hourly values, daily totals, monthly mean daily totals, and annual mean monthly mean daily totals. Varying time averages assist to capture the temporal uncertainty of the specific modeled solar resource data required for each phase of a solar energy project; some phases require higher temporal resolution than others. Overall, by including the uncertainty of measurements of solar radiation made at ground stations, bias, and root mean square error, the NSRDB data demonstrated expanded uncertainty of 17 percent - 29 percent on hourly and an approximate 5 percent - 8 percent annual bases.

14 SOLAR ENERGY↗
DOE OSTI2020

Statistical Tests for Diagnosing Fission Source Convergence and Undersampling in Monte Carlo Criticality Calculations [Slides]

There is a very strong need for statistical testing to determine fission source convergence in Monte Carlo criticality calculations. Automation of such tests will greatly streamline and support the work carried out by NCS practitioners. Recent R&D work has shown that no single statistical test for convergence is sufficiently reliable, robust, and “guaranteed.” However, a combination of several standard statistical tests for the similarity of distributions, coupled with a high-fidelity estimate of the fission-matrix source is sufficiently robust, reliable, and repeatable that convergence can be “guaranteed.” During the course of the EG-AMCT studies, a number of statistical metrics and tests were proposed for diagnosing clustering and undersampling. None of these was robust and reliable enough for practical use in production codes. However, the expert group efforts came close. Some recent R&D work stemming from those past efforts has been very successful and promising. This Sub-Group will provide international input and collaboration on the development and implementation of statistical tests for convergence, with the primary goal of having the MC codes automatically detect convergence (or lack thereof). Newly proposed statistical tests to detect undersampling (after convergence) will also be reviewed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Why Plan for Utility-Scale Solar?

The Solar@Scale project is a DOE Solar Energy Technologies Office-funded collaboration between the American Planning Association and International City/County Management Association (ICMA) to provide best practices and guidance for local communities in planning for large-scale PV development. As a member of the Solar@Scale advisory committee, I have been asked to present on trends and land use projections for large-scale solar to demonstrate why local governments will likely see growing demand for solar energy development. These slides represent an introduction to projections from NREL's Standard Scenarios, Cambium, LBNL's Utility-Scale Solar report, and other data sources on the level of solar energy development that can be expected across the country.

48 EE - Weatherization and Intergovernmental Progr↗
DOE OSTI2022

Domestic and International Standards for Nuclear Criticality Safety – Overview and Status

The domestic and international consensus standards for nuclear criticality safety (NCS) have provided guidance for staff performing hands-on work in operations with fissionable materials. These consensus standards have contributed directly to the significant reduction in the rate of criticality accidents in process facilities since the 1940s. The last known criticality accident inside the United States was in 1978 (nearly 43 years ago) at the Idaho Chemical Processing Plant, and outside the United States, an accident occurred at Tokai-mura, Japan, in 1999 (23 years ago). The domestic consensus standards for NCS include the American Nuclear Society (ANS) standards. The ANS Standards Board, the NCS Consensus Committee, and the ANS-8 Subcommittee oversee the development and maintenance of these standards. There are currently eighteen standards in the ANS-8 series. Currently, there are six ANS-8 standards in revision mode and eleven in a maintenance mode with one new standard under development. The international consensus standards for NCS calculations, procedures, and practices are maintained and developed within the International Organization for Standardization (ISO), Technical Committee 85 on Nuclear Energy, Subcommittee 5 on Nuclear Fuel Technology, and Working Group 8, “Nuclear Criticality Safety.” Eleven standards are currently available, three standards are in revision mode, and two standards are development. This paper provides the NCS community with an overview and status report of domestic and international NCS consensus standards to stimulate interest and to support their continued development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

The role of client engagement in successful project delivery - 15599

Projects, managed using one of the standard methodologies, are the primary vehicle used by most organizations to effectively deliver their strategic objectives in a timely and high quality manner. Most projects at ANSTO with a strong nuclear technology component require the active engagement of the end user, sponsor and subject matter experts for making key decisions during the project delivery phase to ensure best value for the organization. In 2009, after a review of ANSTO's project governance and management processes, a number of changes to the governance of internal projects were made. This included the establishment of a project governance structure that includes a two-point accountability framework, where the Project Client, together with the Project Manager is held accountable for the project delivery. While the two-point project accountability framework is not a conventional approach in project management, the experience from the project managers and stakeholders at ANSTO indicates that it provides a robust, consistent and practical approach for managing projects. The challenges of the two-point accountability framework are primarily related to the clarity of roles and goals, particularly from the Client perspective. This is an area that needs further attention. Overall, this approach allows better coordination of input from the project sponsors, end users and subject matter experts for day-to-day decision making through the life-cycle of the project. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Practice Summary: Improved Reliability via Optimization in Residential Microgrids

Southern Company is an electric utility that is embracing residential microgrids as a platform for distributed energy. The first residential microgrid in the southeastern United States was constructed in Hoover, Alabama, as a testbed for development. To operate the microgrid, we developed an optimization model for unit commitment and economic dispatch. We report the optimization model was implemented in a microgrid central controller and tested under various operational scenarios. Challenges also include developing a pricing algorithm to deliver price forecasts to the residential homes in the microgrid and open-source software restrictions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

FAIR Data and Interpretable AI Framework for Architectured Metamaterials (Final Report)

This research program established a transformative framework for the discovery and design of mechanical metamaterials, which are architected structures engineered to control physical phenomena like sound and vibration in ways natural materials cannot. To overcome the traditional reliance on trial-and-error, the project developed an interpretable Artificial Intelligence (AI) framework that moves beyond "black box" models to reveal the specific geometric patterns—such as "unit-cell templates"—that govern a material’s performance. A major breakthrough was the development of a hierarchical design method, which allows a single material to block vibrations across multiple frequency ranges simultaneously by layering patterns at different scales without them interfering with one another. This was further expanded to include irregular, graph-based designs that use spanning tree algorithms to ensure structural connectivity while allowing for customized, direction-dependent properties like stiffness and acoustic impedance. Beyond design, the project addressed the practicalities of real-world production by developing uncertainty quantification techniques that account for manufacturing defects and material variability, reducing the need for expensive physical testing by orders of magnitude. To speed up the discovery process, the team implemented Gaussian Process Regression and other surrogate models that provide accurate performance predictions at a fraction of the traditional computational cost. The AI-generated designs were successfully validated through fabrication of physical samples and wave propagation experiments, confirming their ability to accurately guide or reflect waves as predicted. By contributing these tools and high-quality FAIR benchmark datasets to the wider scientific community, this work provides a scalable foundation for advancing technologies in aerospace vibration control, medical imaging, and noise reduction.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Design, Fabrication, and Test Program for NREL's Wave-Powered Desalination System: Preprint

Starting in 2018, the U.S. Department of Energy's Water Power Technologies Office (WPTO), initiated the development of a prize competition as a foundational investment of Powering the Blue Economy, The prize encouraged the development of small, modular, cost-competitive wave-powered desalination systems. The National Renewable Energy Laboratory (NREL) was tasked with managing the prize, known as the Waves to Water Prize (W2W), and providing technical input based on prior desalination research performed at the lab. NREL partnered with the Coastal Studies Institute (CSI) and Jennette's Pier in North Carolina for their expertise in deploying research articles at the Jennette's Pier research facility. The prize consisted of five stages that included high-level concept proposals, numerical modelling, site- specific design, subsystem prototyping, and a final ocean demonstration. Due to the logistical risks of installing numerous prototypes in the ocean at the same time, NREL was tasked with designing and building a test article to de- risk the final event. The test article design needed to represent the technologies expected in the final stage of the prize. This meant that the design was expected to follow the same rules as the competitors, providing CSI with an opportunity to practice installations and develop a final logistics plan prior to the final event. After concluding the W2W event in April 2022, the NREL test article was redeployed in August 2022 to better understand the challenges of anchoring wave energy converters (WECs) in shallow water conditions with breaking waves. For the Spanish version of this report, see NREL/CP-5700-88482 (https://www.nrel.gov/docs/fy24osti/88482.pdf).

deployment↗
DOE OSTI2024

The Design, Fabrication, and Test Program for NREL's Wave-Powered Desalination System

Starting in 2018, the U.S. Department of Energy's Water Power Technologies Office (WPTO), initiated the development of a prize competition as a foundational investment of Powering the Blue Economy, the prize encouraged the development of small, modular, cost-competitive wave-powered desalination systems. The National Renewable Energy Laboratory (NREL) was tasked with managing the prize, known as the Waves to Water Prize (W2W), and providing technical input based on prior desalination research performed at the lab. NREL partnered with the Coastal Studies Institute (CSI) and Jennette's Pier in North Carolina for their expertise in deploying research articles at the Jennette's Pier research facility. The prize consisted of five stages that included high-level concept proposals, numerical modelling, site-specific design, subsystem prototyping, and a final ocean demonstration. Due to the logistical risks of installing numerous prototypes in the ocean at the same time, NREL was tasked with designing and building a test article to de-risk the final event. The test article design needed to represent the technologies expected in the final stage of the prize. This meant that the design was expected to follow the same rules as the competitors, providing CSI with an opportunity to practice installations and develop a final logistics plan prior to the final event. After concluding the W2W event in April 2022, the NREL test article was redeployed in August 2022 to better understand the challenges of anchoring wave energy converters (WECs) in shallow water conditions with breaking waves.

desalination↗
DOE OSTI2017

Two-Stage Adaptive Restoration Decision Support System for a Self-Healing Power Grid

Power outages cost American industries and businesses billions of dollars and jeopardize the lives of hospital patients. The losses can be greatly reduced with a fast, reliable, and flexible self-healing tool. This paper is aimed to tackle the challenging task of developing an adaptive restoration decision support system (RDSS). The proposed RDSS determines restoration actions both in planning and real-time phases and adapts to constantly changing system conditions. The comprehensive formulation encompasses practical constraints including ac power flow, dynamic reserve, and load modeling. Here, the combinatorial problem is decomposed into a two-stage formulation solved by an integer L-shaped algorithm. The two stages are then executed online in the RDSS framework employing a sliding window method. The IEEE 39-bus system has been studied under normal and contingency conditions to demonstrate the effectiveness and efficiency of the proposed online RDSS.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Ion Coulomb Crystals in Storage Rings for Quantum Information Science

Quantum information science is a growing field that promises to take computing into a new age of higher performance and larger scale computing as well as being capable of solving problems classical computers are incapable of solving. The outstanding issue in practical quantum computing today is scaling up the system while maintaining interconnectivity of the qubits and low error rates in qubit operations to be able to implement error correction and fault-tolerant operations. Trapped ion qubits offer long coherence times that allow error correction. However, error correction algorithms require large numbers of qubits to work properly. We can potentially create many thousands (or more) of qubits with long coherence states in a storage ring. For example, a circular radio-frequency quadrupole, which acts as a large circular ion trap and could enable larger scale quantum computing. Such a Storage Ring Quantum Computer (SRQC) would be a scalable and fault tolerant quantum information system, composed of qubits with very long coherence lifetimes. With computing demands potentially outpacing the supply of high-performance systems, quantum computing could bring innovation and scientific advances to particle physics and other DOE supported programs. Increased support of R$\&$D in large scale ion trap quantum computers would allow the timely exploration of this exciting new scalable quantum computer. The R$\&$D program could start immediately at existing facilities and would include the design and construction of a prototype SRQC. We invite feedback from and collaboration with the particle physics and quantum information science communities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

Integrated Data Collection Analysis (IDCA) Program - KClO 4 /Carbon Mixture

The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of a mixture of KClO 4 and activated carbon—KClO 4 /C mixture. This material was selected because of the challenge of performing SSST testing of a mixture of two solids. The mixture was found to be insensitive to impact, friction, and thermal stimulus, and somewhat sensitive to spark discharge. This effort, funded by the Department of Homeland Security (DHS), ultimately will put the issues of safe handling of these materials in perspective with standard military explosives. The study is adding SSST testing results for a broad suite of different HMEs to the literature. Ultimately the study has the potential to suggest new guidelines and methods and possibly establish the SSST testing accuracies needed to develop safe handling practices for HMEs. Each participating testing laboratory uses identical test materials and preparation methods wherever possible. Note, however, the test procedures differ among the laboratories. The results are compared among the laboratories and then compared to historical data from various sources. The testing performers involved for the KClO 4 /carbon mixture are Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), Indian Head Division, Naval Surface Warfare Center, (NSWC IHD), and Air Force Research Laboratory (AFRL/RXQL). These tests are conducted as a proficiency study in order to establish some consistency in test protocols, procedures, and experiments and to understand how to compare results when these testing variables cannot be made consistent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

RAPID Manufacturing Institute Final Report

The Rapid Advancement of Process Intensification Deployment (RAPID) Manufacturing Institute, founded in 2017, is a public/private partnership between the U.S. Department of Energy and the American Institute of Chemical Engineers (AIChE). RAPID promotes the development, deployment and commercialization of Process Intensification (PI) and Modular Chemical Process Intensification (MCPI) technologies, enabling U.S. manufacturing to reduce energy consumption, improve process efficiencies and lower investment and operating costs. This mission was carried out through parallel work breakdown structure elements including the establishment of committees to guide the operations and technical direction of RAPID, the establishment of management practices and institute processes, education and workforce development (EWD), and six technical focus areas for the development of technologies to advance PI and MCPI. Throughout the initial six-year cooperative agreement, RAPID worked to meet performance metrics which focused on the operation and sustainment of the institute, education and workforce development and the development of PI and MCPI for the advancement of U.S. manufacturing. All these metrics were successfully met through a total of 43 projects which leveraged $\$$70M Federal with $\$$90M cost share. As a result of these efforts, 84 private and public organizations were brought together by RAPID as members to co-invest in R&D, commercialization and deployment of innovative technologies. In the research portfolio, 82% of the 38 projects achieved > 20% energy efficiency improvement. A RAPID Test Network was developed with 51 testbed facilities to enable access to resources, facilities, tools, and expertise. Eight EWD programs were also developed with over 13,000 impressions. RAPID’s efforts to research, develop, demonstrate, and deploy high-impact PI and modular process technology solutions have enabled reduced energy use, increased sustainability, and improved profitability for U.S. manufacturing.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Radiation Simulation using Wi-Fi Signal Strength and Frequency

For routine radiological operations, lost radioactive sources, decommissioning and cleanup of nuclear facilities, and radiological terrorist events such as Radioactive Dispersive Devices (RDDs) or Radiological Exposure Devices (REDs), individuals are tasked with accurately locating both point and distributed sources of radiation. Radiation workers must often practice these tasks, whether part of initial training or periodically as part of formal or informal exercises or drills. In such circumstances, it is desirable to have an accurate recreation of a radioactive source, including a method of detecting it, which does not include dangerous amounts of radiation. The goal of this research was to develop a radiation simulation technology that uses IEEE 802.11x W-LAN protocol, i.e. Wi-Fi sources and detectors for these, as an inexpensive, precise and accurate method of replicating sources of gamma radiation. For this work, existing 802.11x sources were used. Software was developed for use with an Android smartphone to detect the presence of these sources. The measurements followed the expected behavior as a function of distance from the sources, mimicking that of gamma radiation, thus demonstrating the fundamental principle of operation. The ultimate system will be used in an outreach program to interest students in the radiation protection field.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

A review of criticality dosimetry at the Y-12 National Security Complex and practical importance of dose accuracy in emergency response

A nuclear criticality results in the emission of both neutron and gamma radiation and can produce doses to personnel near the event that exceed 0.1 Gy (10 rad). The primary purpose of nuclear accident dosimetry is to rapidly identify affected personnel in need of prompt medical treatment and to reassure personnel who have been only minimally exposed. While accurate dosimetry is desired, it must be recognized that dose determinations made from whole-body dosimeters or simple triage methods are very rough estimates and contain significant uncertainties. Even when accounting for factors like varying neutron energy spectra, mean photon energies, body orientation within the radiation field, and transient effects on dosimeter response, etc., the end value is a dosimetric quantity defined for very specific radiological conditions and determined within a simple phantom usually at a single depth. Of more importance is the biological response to the radiation, which will vary by person and can be affected by the individual’s radiation sensitivity, age, gender, mass, and underlying health conditions. The overall biological, person-specific response to a given dose cannot be precisely determined except by patient symptom observation and individual biological dosimetry (e.g. chromosome analysis, lymphocyte ratios, etc.). This work describes and discusses the criticality accident dosimetry program at the Y-12 National Security Complex, a United States Department of Energy National Nuclear Security Administration facility. In conclusion, the primary goals of the Y-12 accident dosimetry program are, among others, the rapid identification of significantly exposed persons, prompt routing of exposed workers for medical evaluation and treatment, and the ultimate processing of dosimeters to assign doses to personnel.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

Three‐phase probabilistic load flow in radial and meshed distribution networks

With the introduction of higher levels of renewables and demand response programs, traditional deterministic power system tools fall short of expectations. Probabilistic load flow (PLF) takes into account the inconsistency or the unknown loads, and generation in the fundamental load flow analysis. This study proposes a PLF solution for both balanced and unbalanced, radial and weakly meshed networks without explicitly using the Y ‐bus matrix. It allows for discrete probability density functions as input variables without having to assume a predefined distribution. The nodal voltages and the power flows can be calculated independently from one another. The proposed method is applied to the IEEE 123 Node Test Feeder and the IEEE 13 Node Test Feeder in both its original radial configuration and a modified mesh configuration, including a load replaced with a wind turbine. The results are validated by comparison of the proposed method's solutions to those obtained using cumulants and Monte Carlo simulation. The proposed PLF method provides an accurate and practical way for finding the solution to stochastic problems occurring in power distribution systems allowing for real‐system data to be analysed.

Melhorn, Alexander C.↗