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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Estimating internal moisture generation rates in recently constructed, occupied homes in the southeastern United States

Internal moisture generation (IMG), or moisture generated by building occupants via activities such as respiration, cooking, bathing, and cleaning, is a critical input required for design, analysis, and simulation of building enclosure and heating, ventilation, and air conditioning (HVAC) systems. Based on previously published values, ASHRAE Standard 160-2021 provides guidance for estimating IMG rates for moisture control design analysis, which is based on occupied home datasets collected in the 1980s and 1990s. Residential energy use simulation software also utilizes estimates for IMG for energy rating, energy analysis, and code compliance calculations, as specified in ANSI/RESNET/ICC Standard 301. Data quantifying IMG rates in newer homes is useful in determining the continued relevance of current design and simulation guidance, and whether the guidance represents conditions found in new housing stock. ASHRAE Research Project 1844, conducted by the Florida Solar Energy Center (FSEC), a research institute of the University of Central Florida, estimated IMG rates in newer occupied homes built since 2013 in the southeastern US using a moisture balance model approach. Furthermore, the project obtained occupied home data in cooperation with a US Department of Energy Building America research project to characterize indoor air quality (IAQ) in newer US homes, along with presence, functionality, and occupant use of control measures. Full-scale laboratory homes operating with known IMG rates were used to validate a moisture balance model and quantify the accuracy of estimates obtained when the model is applied to data from occupied homes with unknown IMG rates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Direct measurement of the electron turbulence-broadening edge transport barrier to facilitate core–edge integration in tokamak fusion plasmas

Abstract The integration of a high-performance core and a dissipative divertor, or the so-called ‘core–edge integration,’ has been widely identified as a critical gap in the design of future fusion reactors. In this letter, we report, for the first time, direct experimental evidence of electron turbulence at the DIII-D H-mode pedestal that correlates with the broadening of the pedestal and thus facilitates core–edge integration. In agreement with gyrokinetic simulations, this electron turbulence is enhanced by high η e ( η e = L n / L T e , where L n is the density scale length and L T e is the electron temperature scale length), which is due to a strong shift between the density and temperature pedestal profiles associated with a closed divertor. The modeled turbulence drives significant heat transport with a lower pressure gradient that may broaden the pedestal to a greater degree than the empirical and theoretically predicted pedestal width scalings. Such a wide pedestal, coupled with a closed divertor, enables us to achieve a good core–edge scenario that integrates a high-temperature low-collisionality pedestal (pedestal top temperature T e,ped > 0.8 keV and a pedestal top collisionality ν * ped < 1) under detached divertor conditions. This paves a new path toward solving the core–edge integration issue in future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Online accelerator optimization with a machine learning-based stochastic algorithm

Abstract Online optimization is critical for realizing the design performance of accelerators. Highly efficient stochastic optimization algorithms are needed for many online accelerator optimization problems in order to find the global optimum in the non-linear, coupled parameter space. In this study, we propose to use the multi-generation Gaussian process optimizer for online accelerator optimization and demonstrate that the algorithm is significantly more efficient than other stochastic algorithms that are commonly used in the accelerator community.

Zhang, Zhe (ORCID:0000000281430381)↗
DOE OSTI2020

Appendix Q: Recommendations for Developing Molecular Assays for Microbial Pathogen Detection Using Modern In Silico Approaches

We describe the use of in silico approaches to improve the process of molecular assay development and reduce time and cost by utilizing available databases of whole genome pathogen sequences combined with modern bioinformatics and physical modeling tools. Well-characterized assays are needed for accurately detecting pathogens in environmental and patient samples and also for evaluation of the efficacy of a medical countermeasure that may be administered to patients. The polymerase chain reaction (PCR) remains the gold standard for pathogen detection due to the simplicity of its instrumentation, low cost of reagents, and outstanding limit of detection (LOD), sensitivity, and specificity. However, creation of such PCR assays often involves iterations of design, preliminary testing, and thorough validation with clinical isolates and testing in relevant matrices, which can be time consuming, costly, and result in suboptimal assays. Since formal validation (e.g., for Emergency Use Authorization [EUA] or Food and Drug Administration [FDA] licensure) of an infectious disease assay can be very expensive and can require extensive time of development, having a well-designed assay up front is a critical first step. Yet, many assays described in the literature utilized limited design capabilities and many initially promising assays fail the validation process, resulting in increased costs and timelines for successful product development. While the computational approaches outlined in this document by no means obviate the need for wet lab testing, they can reduce the amount of effort wasted on empirical optimization and iterative redesigns and also guide validation studies. The proposed computational approaches also result in higher performing assays with better sensitivity, specificity, and lower LOD and reduce the possibility of assay failure due to signature erosion. To provide clarity, an extensive glossary of defined terms is provided.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Structured illumination for surface-resolved grazing-incidence X-ray scattering

Grazing-incidence (GI) scattering techniques are widely used to characterize thin films, offering high surface sensitivity and insight into morphology and structure. However, these approaches typically provide statistical averaged information due to elongated footprint or limited spatial resolution due to beam size. Here we introduce a method that combines structured illumination with GI X-ray scattering and leverages our computational imaging approach to resolve local structural details. We demonstrate that our method captures local features of an organic semiconductor thin film without the need for sample rotation as in tomography. The method expands GI techniques from statistical averaging to high-resolution imaging, thereby providing the capability for detailed analysis of local material properties, such as domain shape, orientation and polymorphism, which are critical for advancing material design towards more efficient and tailored materials.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU

In the graph data structure like adjacency matrix, the connectivity of two nodes can be sufficiently represented using only 1 bit, but they are generally treated as 32-bit full-precision in state-of-the-art graph frameworks to adopt common sparse format such as CSR. Meanwhile, bit-level parallelism has recently be explored to have high-performance potential and low storage requirement on GPUs with dense bit-tiles. To fill the gap, our solution is a hierarchical storage format that contains the bit-indexing base and dense bit-tile units. Inherently, the granularity of the bit-tile is an essential factor in achieving both storage compression and GPU parallelism. How to find a sweet spot that trades off between avoiding sparsity and exploiting is comprehensively researched in this work. In the experiment, we evaluate the proposed storage format and algorithms on modern generation GPUs, including Pascal and Volta, to figure out critical software co-designs in conjunction with existing hardware-specific optimization.

Chen, Jou-An↗
DOE OSTI2022

Designing an Intrusion Proof Adjustable Speed Drive System Controlling a Critical Process

In this paper, an intrusion proof adjustable speed drive system controlling a critical process in an industrial control system is detailed. In such a system, should the motor speed sensor signal data be compromised and/or altered via a cyber-attack, the system can potentially be unregulated, over speed and/or malfunction thereby disrupting the critical process. The proposed active detection scheme detailed in this paper introduces a private (secret) random signal termed as "watermark" into the inverter control signal that determines the PWM gating signals of the DC-AC inverter powering the motor. The watermarking signal introduced into the PWM modulation for the DC-AC inverter is shown to propagates its unique signature, which appears in all sensors signals at the inverter output such as voltage/current/speed used to control the motor. Now employing the measured data (from sensors), two statistical variance tests are conducted to identify anomalies if any in the presence of the watermarking signal. It is shown when an intrusion occurs to manipulate the sensor data to disturb and/or destabilize the process, the proposed tests immediately display a high value indicating a compromise in sensor data. It is shown that the proposed system is capable of immediate detection of a sophisticated attacks such as record/reply attack in which the actual speed sensor is disconnected and a prerecorded speed signal from the past of the same magnitude is played back to the controller. Several types of cyber-attacks such as speed reduction/increase including vibration have been tested. Extensive simulation results verify the proposed concepts. Experimental results will be discussed in the conference presentation.

Alotaibi, Faris↗
DOE OSTI2023

A Machine Learning Framework to Deconstruct the Primary Drivers for Electricity Market Price Events

As the electricity grid is moving towards a 100% Renewable Energy Source Bulk Power Grid, the overall operations of the power system operations and electricity markets are changing. The electricity markets are not only dispatching resources economically but also taking into account various controllable actions like renewable curtailment, transmission congestion mitigation, and energy storage optimization to make sure the grid is operating reliably. As a result, price formations in electricity markets have become quite complex. Traditional root cause analysis and statistical approaches are rendered inapplicable to analyze and infer the main drivers behind price formation in the modern grid and markets with variable renewable energy (VRE). In this paper, we propose a machine learning analysis framework to deconstruct some primary drivers for price formation in modern electricity markets with high renewable energy and the outcomes can be utilized for various critical aspects of market design, renewable dispatch and curtailment, operations, and cyber-security applications. The framework can be applied to any ISO or market data and in this paper it is applied to open-source publicly available datasets from California Independent System Operator (CAISO) and ISO New England.

machine learning (ML), electricity markets, Renewa↗
DOE OSTI2024

Preliminary Assessment of Additively Manufactured Cooling Channel Performance for Helium-Cooled Blanket Concepts

Sufficient cooling of the blanket first wall remains a critical challenge for the design and deployment of fusion power plants. Helium has been targeted as a potential blanket coolant due to its inertness and low neutron interactivity, among other advantages. However, the low thermal mass of helium creates a need for heat transfer enhancements in coolant channels to provide adequate cooling to the blanket’s first wall. Toward this end, a series of ribbed flow channels of various rib cross sections and configurations has been produced via additive manufacturing (AM) to study the efficacy of AM for first wall heat transfer enhancement and the optimization of heat transfer geometries. Helium cooling performance is studied in AM test articles at 4 MPa operating pressure, Reynolds numbers up to 197 000, and outer surface heat fluxes up to 42 kW/m 2 in the recently commissioned helium flow loop experiment (HFLE). Preliminary results of this study are presented herein. Heat transfer performance of nominally smooth (i.e., featureless) AM channels is quantified via measured Nusselt numbers and friction factors and compared to off-the-shelf smooth pipe experiments. Results are compared to existing correlations and used to discuss the effects of the AM processes on thermal-hydraulic performance. It is seen that the inherent roughness of the AM channels leads to an increase in both heat transfer coefficient and pressure drop when compared to the conventional pipe. In conclusion, recommendations are made for future studies based on these findings and additional considerations for the deployment of AM blanket cooling components.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bubble Transport through a Porous Lattice with an Applied Inlet Flow

Within gas-evolving electrochemical systems, bubbles negatively impact performance by covering electrode active sites for reactions, blocking electric field lines, and obstructing liquid electrolyte flow causing pressure buildup. Recent additive manufacturing advances have enabled tuned porous electrode microstructures to be created, but producing systems that maximize electrochemical throughput and minimize bubble impact remains challenging. Thus, improved physical understanding of and modeling capabilities for bubble behavior are critical to improve electrolyzer design. To address this need, this study examines rising stage bubbles within a lattice with an applied liquid flow—an underexplored regime that strongly influences an electrochemical bubble’s fate. Notably, theoretical predictions and resolved bubble simulations are complemented by experiments from a 3D-printed visualization cell that matches the simulation geometry. The minimum threshold flow rate to achieve bubble breakthrough is found to be larger for higher porosities and for smaller bubbles. Different-sized bubbles decrease expected electrochemical performance in different ways; smaller bubbles tend to stay stuck but cover less solid surface, while larger bubbles more readily break through but cover more surface while in the lattice. The bubble trajectory, deformation, and contact area provide insight into these different behaviors. These findings provide design guidelines toward creating more effective electrolyzers.

Guo, Jack [Lawrence Livermore National Laboratory ↗
DOE OSTI2026

Solvent–Diluent Engineering of Normal-Concentration Organosulfur Electrolytes for High-Voltage Lithium-Ion Batteries

Enabling high‑voltage batteries depends critically on rational electrolyte design. Conventional carbonate electrolytes with LiPF 6 suffer from insufficient oxidative stability, motivating the use of lithium bis(fluorosulfonyl)imide (LiFSI) for its superior high‑temperature and high‑voltage performance. However, LiFSI is relatively costly, and its electrolytes often require high concentrations to suppress aluminum current collector corrosion in cathode architectures and to adequately passivate electrode interfaces. Here, a low‑concentration LiFSI electrolyte is realized by combining a high‑voltage organosulfur solvent, ethyl methyl sulfone (EMS), with a non‑solvating fluorinated diluent, fluorobenzene (FB). Extended cycling of LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) full cells to 4.5 V reveals substantial long‑term performance advantages over conventional carbonate electrolytes. Comparison with a popular cyclic sulfone, tetramethylene sulfone (TMS), shows that ring‑containing structures such as TMS strongly influence passivation behavior, ultimately limiting performance and narrowing the viable operating window. Overall, EMS is identified as a uniquely stable solvent for LiFSI‑based electrolytes operating at moderately high voltages.

Dato, Michael A. [Argonne National Laboratory (ANL↗
DOE OSTI2025

EDX ClaiMM

EDX ClaiMM is a centralized data & analytical platform designed to revolutionize U.S. critical minerals and materials (CMM) activities. By providing a robust digital infrastructure, ClaiMM will accelerate the combination, leveraging, and rapid utilization of vital data, advanced tools, and cutting-edge research advancements in CMM. This adaptive digital research hub connects the CMM community to essential knowledge products and offers access to interoperable datasets, databases, models, software, and tools from the National Energy Technology’s (NETL’s) Energy Data eXchange (EDX) and other authoritative sources, serving both public and private sectors. EDX ClaiMM delivers AI-informed solutions to address fundamental knowledge gaps and fosters the innovation of new techniques for enhanced characterization and recovery of CMMs within the U.S. By leveraging cloud-hosted, scalable digital infrastructure, ClaiMM meets public–private applied energy needs. It equips the CMM community with priority digital resources that harness on-site and cloud compute capabilities, enabling big data storage, advanced processing, analytics, and visualization.

Critical Materials; Critical Minerals; Rare Earth ↗
DOE OSTI2020

Enduring Transuranic Liquid Waste Volume Forecast and Constituent Evaluation (FY20)

The “FY11 Radioactive Liquid Waste (RLW) Influent Boundary Condition Assessment and Forecast” report provided influent volume forecasts that were critical in establishing the design capacity for the new Radioactive Liquid Waste Transuranic (RLW-TRU) capability. The design for the new RLW-TRU capability was paused as the final design was being completed and prior to the transition of the new management and operations contract for Los Alamos National Laboratory (LANL). Recently, NNSA has directed the project to restart and complete the design effort. As part of the restart process, LANL was asked to validate or document any material changes in the influent volumes or constituents that formed the design basis for the new capability. This analysis updates the transuranic liquid waste influents volumes, incorporating the changes in the LANL program of record since the FY11 assessment, and includes a cursory validation of influent constituents. The results of the FY19 update to influent volume forecasts shows: 1) the influent volume of 29,000 L should continue to be used as the project design-basis; 2) There have been no material changes in the operational processes that would change the constituents of concern from either a treatment or material compatibility perspective.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

An Assessment of Evaluation Practices of Low- And Moderate-Income Solar Programs

As concerns about social equity and clean energy rise, state and local governments, utilities, and non-profit organizations are offering at least 41 active programs in 21 states to promote solar adoption as a way to reduce energy bills for low- and moderate-income (LMI) households while meeting other policy goals such as job creation and clean energy generation. A new study from Berkeley Lab looks at how those programs are being evaluated. The report provides background on how they seek to address LMI household energy burdens and gives a brief discussion of the art and science of program evaluation, drawn from decades of experience in energy efficiency programs. It then turns to how LMI solar programs are currently being evaluated, highlighting trends among evaluation methods, metrics tracked, and best practices employed. A few programs are explored in more depth to illustrate notable practices that could be applied to other program evaluations. These LMI solar programs are mostly young, operate on tight budgets, and vary considerably in their design and stated goals. Consequently, well-designed program evaluation is critical to better understand what works, what could be improved, and how to maximize program impacts under budget constraints.

14 SOLAR ENERGY↗
DOE OSTI2021

Materials Challenges and Opportunities for Energy Generation, Conversion, Delivery, and Storage (Applied Energy Tri-Laboratory Consortium Workshop Report)

This report documents the outcomes of the Tri-Laboratory Materials Workshop that was held July 31 and August 1, 2019 to begin addressing the needs, opportunities, and challenges associated with the development, fabrication, and testing of the needed materials and components for integrated hybrid energy systems (i.e., incorporating nuclear, fossil, and renewables for electric and thermal applications). This was accomplished by assembling the research program leads and principal investigators at Idaho National Laboratory (INL), National Energy Technology Laboratory (NETL), and National Renewable Energy Laboratory (NREL), who support the research and development of new technology and system integration. The team then identified and prioritized key materials development needs. This effort was intended to enhance communications and synergy among the Tri-Lab partners. Advanced functional and structural materials are central to transformative energy technologies for energy generation, conversion, delivery, and storage. With that in mind, the workshop focused on identifying and assessing the foundational materials research needs at both the basic and applied levels. Materials challenges include the ability to withstand harsh environments, such as high temperatures and pressures, corrosion, oxidation, or irradiation while maintaining flexible mission profiles and long service lifespans. Advanced energy system material challenges and needs range from materials for the capture, upgrading/concentration, storage, and delivery of low-grade heat to materials for high temperature environments that involve liquid metals, molten salt, and very high temperature gas heat delivery and storage systems. Material improvements are needed for hybrid energy systems due to accelerated corrosion and stress-fatigue failure of materials and equipment, which results from increased frequency and amplitude of thermal, mechanical, and electrical cycling of systems components. Multifunctional materials are needed for high temperature solid-oxide fuel cells, advanced electrochemical reactors, and in-process separation. Relative to materials manufacturing, application of advanced additive and subtractive methods need to be understood to develop both thin-layer homogenous materials and materials of graded composition. Materials modeling and machine learning will be critical to accelerate the design and production of power electronics, and nuclear reactor materials and fuel, as well as to gain an understanding of beneficial materials phenomena or deleterious microstructure evolution. There is also a need for standardized models, computational structures, data reporting protocols and modeling tools across the three laboratories. This would allow consistent results, analysis, and data sharing. Combining computational capabilities between the three laboratories (e.g., hardware, software) would greatly increase computational capabilities and throughput. The workshop identified the need for laboratories to anticipate and address problems that will occur during scale-up. Laboratory work must connect with industry to ensure that research focuses on processes that are scalable and marketable. Industry input and perspective are essential to guide laboratory research to meet these requirements and deploy new technology in industrial demonstrations. Another aspect of scale-up is the integration of multiple systems since new challenges often arise at the subsystem interfaces. Establishing a scale-up manufacturing demonstration/pilot plant, potentially as an industrial user facility, would be beneficial to the laboratories and industry. That modular scale-up manufacturing demonstration/pilot plant would allow researchers to find and resolve interface problems that cannot be identified by focusing only on individual parts. Communication exchanges among the organizers, attendees, and workshop survey responses indicate that the workshop was successful in achieving its goal to identify key technology gaps and research needs. Strong positive feedback was received on the sharing of ideas, capabilities, talent, and passion to move forward on the materials-related action items.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bridge Seismic Screening Tool (BSST), Version 2.0

The Regional Resiliency Assessment Program (RRAP) is a cooperative assessment of specific critical infrastructure within a designated geographic area and a regional analysis of the surrounding infrastructure that addresses a range of infrastructure resilience issues that could have regionally and nationally significant consequences. In 2018, DHS’s Cybersecurity and Infrastructure Security Agency (CISA) sponsored the Oregon Transportation Systems RRAP project in coordination with the Office of the Governor (under the oversight of the state resilience officer), the Oregon Office of Emergency Management (OEM), the Oregon Department of Transportation (ODOT), and other regional stakeholders (CISA 2021). This project focuses on assessing the impacts of a Cascadia Subduction Zone (CSZ) earthquake on state transportation systems and, in particular, how those impacts may affect the ability of emergency response efforts to move supplies into the region. The intended outcome of this analysis is the prioritization of transportation routes and modes for additional planning, investment, hardening, or other activities to enhance their resilience—and therefore, to enhance their ability to support response and recovery efforts following a CSZ earthquake. An important part of this transportation system-level assessment has been to assess the seismic vulnerability of the state highway system. In doing so, the RRAP project team used the Bridge Seismic Screening Tool (BSST) to assess, at a system-level, the potential impacts that a CSZ earthquake could have on state highway bridges (Bergerson et al. 2019).1 Argonne National Laboratory (Argonne), in collaboration with the Washington State Department of Transportation (WSDOT), originally developed the BSST as part of the 2017 Washington State Transportation Systems RRAP project, a sister project to the 2018 Oregon Transportation Systems RRAP project. Argonne updated the BSST during this more recent project in Oregon based on feedback from stakeholders and subject matter experts (SMEs) on the original version of the tool. The first step in the BSST is to assess the seismic vulnerability of roadway bridges following a CSZ earthquake to determine a projected or potential damage state. Damage states then help determine approximate reopening times for bridge crossings.2 This document provides details on the BSST methodology, the implementation of that tool to analyze the projected damage incurred in a CSZ earthquake scenario, and the determination of corresponding reopening times of interstate, state highway, and local bridges following such an event.

58 GEOSCIENCES↗
DOE OSTI2022

The Future of High Energy Physics Software and Computing (V2.1)

Software and Computing (S&C) are essential to all High Energy Physics (HEP) experiments and many theoretical studies. The size and complexity of S&C are now commensurate with that of experimental instruments, playing a critical role in experimental design, data acquisition/instrumental control, reconstruction, and analysis. Furthermore, S&C often plays a leading role in driving the precision of theoretical calculations and simulations. Within this central role in HEP, S&C has been immensely successful over the last decade. This report looks forward to the next decade and beyond, in the context of the 2021 Particle Physics Community Planning Exercise ("Snowmass") organized by the Division of Particles and Fields (DPF) of the American Physical Society.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Electron Cloud Simulations for the Electron-Ion Collider in Brookhaven National Laboratory

For high-intensity circular accelerators and storage rings, if the secondary electron emission yield (SEY) of the vacuum chamber surfaces is high, an EC (Electron Cloud) could build up with the passage of the circulating beam. The presence of EC can strongly affect the beam quality, such as transverse instabilities, transverse emittance growth, and beam loss. Furthermore, the heat load from EC can exceed the available cryogenic capability. For the RHIC superconducting (SC) arc magnets, to be used for the hadron storage ring of the Electron-Ion Collider (EIC), the dynamic heat load budget is 0.5 W/m to the 4.5 K stainless steel beam pipe. This can limit the maximum beam bunches or intensity of the EIC, hence diminishing the luminosity provided by the EIC. The EC has affected the beam instability and significantly contributed to cryogenic heat load in the Large Hadron Collider (LHC). Positron storage rings for which ECs have been a critical factor in the design and performance include KEKB in Japan and EC buildup remains one of the concerns for future high-intensity accelerators design. EC considerations have driven the SuperKEKB collider design and the positron damping ring for the proposed International Linear Collider (ILC). The LHC luminosity upgrade is contingent on reducing the bunch spacing to 25 ns; at this bunch spacing, severe EC buildup has been observed. The success of the upgrade is likely contingent on limiting EC buildup. To study the EC heat load, we did some EC simulations with PyECLOUD code for the dipole, quadrupole, sextupole magnets, and the warm (drift) section of the EIC hadron storage ring. PyECLOUD is an EC simulation code developed by CERN. The code has been validated and used to study EC in the LHC, SPS, and PS. To eliminate EC buildup, the sources of electrons must be minimized. First, we will reduce the production of electrons due to residual gas ionization by specifying the maximum gas density, which requires a vacuum chamber with low electron-stimulated desorption (ESD) yields and a sufficient (preferably distributed) pumping speed. Second, we should reduce the secondary electrons with a lower secondary electron yield (SEY) material.

43 PARTICLE ACCELERATORS↗