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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Data Based Shock Test Specification

It is vital that avionic packages used for testing and certifying the reliability and safety of U.S. nuclear weapons with platform aircraft survive exposure to shock environments during transportation and delivery. The objective of this research was to characterize the response to these transportation shock environments delivering accurate shock test specifications in order to set laboratory programming material and device certification rigor. Responses to shock events were analyzed in the frequency domain via the Shock Response Spectrum (SRS). Shocks were then grouped based on respective behavior of maximum response accelerations which were pseudorandomly resampled and compared to test data to form test specifications based on the MinerPalmgren hypothesis. In addition to discovering significant over testing in current shock specifications, a new systematic, data-driven approach to designing shock specifications was formulated.

42 ENGINEERING↗
NASA NTRS1980

An accelerated test design for use with synchronous orbit

The Naval Weapons Support Center at Crane, Indiana has conducted a large scale accelerated test of 6.0 Ah Ni-Cd cells. Data from the Crane test have been used to develop an equation for the description of Ni-Cd cell behavior in geosynchronous orbit. This equation relates the anticipated time to failure for a cell in synchronous orbit to temperature and overcharge rate sustained by the cell during the light period. A test design is suggested which uses this equation for setting test parameters for future accelerated testing.

Mcdermott, P. P.↗
DOE OSTI2020

Use of the Tool to Support Renewable Energy Auctions Processes (RE Data Explorer)

Renewable energy auctions are now a common competitive approach to procure low-cost renewable power around the world. Ensuring a successful auction process increasingly depends on the capabilities of auction designers and participants to identify actionable and defensible insights from large data sets (on renewable energy resources and complementary data) to both attract potential investors and address stakeholder concerns. The Renewable Energy (RE) Data Explorer is a user-friendly geospatial analysis tool for analyzing renewable energy potential and informing decisions. Developed by the National Renewable Energy Laboratory (NREL) and supported by the U.S. Agency for International Development (USAID), RE Data Explorer performs visualization and analysis of renewable energy potential that can be customized for different scenarios. RE Data Explorer can support prospecting, integrated planning, policymaking, and other decision-making activities to accelerate renewable energy deployment. The broader RE Explorer website provides guidance and information to link the RE Data Explorer geospatial analysis tool to key decision areas. This document provides information on how the RE Data Explorer can be used to support renewable energy auction processes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A Robust Neural Network for Extracting Dynamics from Electrostatic Force Microscopy Data

Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consuming to analyze and calibrate. Here, we design and train a regression neural network (NN) that accelerates and simplifies the extraction of local dynamics from SPM data directly in a cantilever-independent manner, allowing the network to process data taken with different cantilevers. We validate the NN’s ability to recover local dynamics with a fidelity equal to or surpassing conventional, more time-consuming, calibrations using both simulated and real microscopy data. We apply this method to extract accurate photoinduced carrier dynamics on n = 1 butylammonium lead iodide, a halide perovskite semiconductor film that is of interest for applications in both solar photovoltaics and quantum light sources. Lastly, we use SHapley Additive exPlanations to evaluate the robustness of the trained model, confirm its cantilever-independence, and explore which parts of the trEFM signal are important to the network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Viral Dynamic Models During COVID‐19: Are We Ready for the Next Pandemic?

Mathematical models have been used for about 30 years to improve our understanding of virus-host interaction, in particular during chronic infections. During the COVID-19 pandemic, these models have been used to provide insights into the natural history of acute SARS-CoV-2 infection, optimize antiviral treatment strategies, understand factors associated with transmission, and optimize surveillance systems. The impact of modeling has been accelerated by the availability of unprecedented multidimensional immune data from animal and human systems, which enhanced partnerships between experimentalists and theorists and led to exciting new modeling and statistical developments. In this mini review, we examine the lessons learned from the COVID-19 pandemic and discuss the main insights provided by mathematical models of viral dynamics at the different stages of the outbreak. Although we focus on respiratory infection, we also consider the new areas for development in anticipation of future acute infections from new or reemerging pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Determination of the parton distribution functions of the proton from ATLAS measurements of differential W ± and Z boson production in association with jets

This article presents a new set of proton parton distribution functions, AT-LASepWZVjet20, produced in an analysis at next-to-next-to-leading order in QCD. The new data sets considered are the measurements of W + and W - boson and Z boson production in association with jets in pp collisions at $\sqrt{s}$ = 8TeV performed by the ATLAS experiment at the LHC with integrated luminosities of 20.2 fb -1 and 19.9 fb -1 , respectively. The analysis also considers the ATLAS measurements of differential W ± and Z boson production at $\sqrt{s}$ = 7TeV with an integrated luminosity of 4.6 fb -1 and deep-inelastic-scattering data from e ± p collisions at the HERA accelerator. An improved determination of the sea-quark densities at high Bjorken x is shown, while confirming a strange-quark density similar in size to the up- and down-sea-quark densities in the range x ≲ 0.02 found by previous ATLAS analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Effect of zeolite type, temperature, and pH on Stage III glass alteration behavior for two nuclear waste glasses

We report long-term laboratory scale static alteration tests (up to 1500 d) were conducted on two low-activity waste glasses (LAWA44 and IDF18-A161) at S/V = 2000 m –1 . Tests were seeded with either analcime, clinoptilolite, zeolite P1, or zeolite P2 to induce Stage III glass alteration behavior. The effect of several parameters on glass Stage III behavior was studied with consideration of several variables, including temperature (22 °C – 90 °C) and pH (floating or initially set using KOH at values from 9.5 to 11.5). Temporal solution data and solids characterization at the end of the experiments are reported. Solution data demonstrated the occurrence of a sustained rate acceleration at temperatures down to 40 °C and the activation energy for these Stage III rates was determined for both glasses. Three major secondary phases were identified at the end of the experiments for both glasses: zeolite P1, zeolite P2, and/or analcime (along with minor phases: zeolites, clays, carbonates). The identification of the crystalline phases at the end of the experiment often differed from the zeolite seed phase. In addition, the use of the Avrami equation showed unimpeded zeolite growth (3-dimensional) in certain conditions, suggesting that in certain conditions the glass dissolution rate is controlled by zeolite formation kinetics whereas in other conditions the glass corrosion process impeded zeolite formation kinetics. The morphological evolution of the samples revealed the growth of the zeolites which completely fill the intergranular space in the powder bed. These results are discussed with regards to previous seeded and unseeded Stage III dissolution rate experiments performed on low- and high-activity nuclear waste glasses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Bipolar plate flow channel designs for vanadium redox flow battery: a review

Vanadium redox flow battery is one of the preferred systems for grid scale energy storage due to long service life (>20000 cycles), higher efficiency (>85 %), deep discharge capability (>95 % DoD), and inherent scalability and safety. Among system components, flow field is most critical as it governs electrolyte distribution, mass transport and hydraulic performance. Here, this review examines emerging flow channel geometries, highlighting the impact of channel width (0.66 to 1.5 mm), depth (1 to 1.5 mm) and land width (0.5 to 1.5 mm) can reduce pressure drop to <10 kPa while enabling power densities above 600 mW.cm -2 . A key finding is that low channel width to depth ratio (<1) enhances voltage and energy efficiencies by improving under rib convection. The review also provides an overview of progress and perspective in bipolar plate materials, manufacturability, and shunt current mitigation strategies for stack scaling up. Cost analysis emphasizes the influence of flow field designs on the levelized cost of storage and pathways towards the US DOE's $\$$0.05 per kWh energy generation cost target. In addition, opportunities for AI/ML/DT tools assisted design and data driven optimization strategies are also outlined to accelerate next generation flow field development.

Efficiency optimization↗
DOE OSTI2021

Two–Dimensional Idealized Hadley Circulation Simulation for Global High Resolution Model Development

A new framework for the development of global high resolution models using a vertical- meridional, two-dimensional pole-to-pole domain is proposed. Compared with the three-dimensional global model, the two-dimensional framework can simulate cloud-scale convection at significantly reduced computational cost, data volume, and turn-around time, and accelerate the development phase. Although idealized, it allows for simulation of various clouds and scale interactions under a wide range of environmental conditions, even though zonal waves such as mid latitude storms cannot be simulated. Physics schemes can be tested and assessed over a full array of simultaneously occurring cloud regimes. The framework can serve as an intermediate step between a one-dimensional simulation and a full three-dimensional global model. Using this framework, we analyze the resolution dependencies of simulated clouds and the Hadley circulation in a range of global high resolution models by performing multiple 1000-day simulations; for some resolutions tested, for example, 2 km horizontal resolution, three-dimensional simulation is not feasible at the present time. Analysis shows that both horizontal and vertical resolution determine the properties of the Hadley circulation and clouds, and that the differences among the simulated Hadley circulations are understood as differences in scale interactions influenced by resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

New challenges in oxygen reduction catalysis: a consortium retrospective to inform future research

In this perspective, we highlight results of a research consortium devoted to advancing understanding of oxygen reduction reaction (ORR) catalysis as a means to inform fuel cell science. We demonstrate how targeted collaborations between different institutions from academic, national lab, and industry backgrounds and different scientific disciplines like theory, experiment, and characterization can yield unique insights into fuel cell catalysts. We comment on such insights into material designs for platinum-group-metal alloys, transition metal oxides, and non-traditional materials including metal–organic frameworks; systems that have served as the foundational building blocks for our consortium. We also motivate a renewed focus on catalyst durability in light of emerging technological requirements and paths forward in understanding in situ and operando electrochemical stability. Lastly, we describe new frontiers ORR research can take and how emerging artificial intelligence tools can assist researchers in capturing data, selecting new experiments, and guiding characterization to accelerate the design and discovery of fuel cell catalysts. A main goal of sharing this perspective is to discuss the rationale for our future research plans based on our consortium work. However, we also hope to illustrate both the potential impact of a collaborative strategy with the hopes of inspiring a higher degree of Industry-Academia-National Laboratory collaboration and encourage other centers and consortiums to distill and share their findings in a similar perspective-type article. Together we hope to enable the fuel cell research community to engage in a discussion of strategies for research and accelerated development of catalysts with improved activity and stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Microsecond-latency feedback at a particle accelerator by online reinforcement learning on hardware

The commissioning and operation of future large-scale scientific experiments will challenge current tuning and control methods. Reinforcement learning (RL) algorithms are a promising solution due to their ability to dynamically adapt to changing environments and consider delayed consequences. In many real-world applications, RL policies must produce actions in real time, often within microseconds to milliseconds, imposing significant constraints on system latency and computational overhead that conventional machine learning libraries are not designed to handle. To control phenomena in real time at these timescales, RL needs to be deployed on-the-edge, namely on dedicated hardware located near the system it controls, without relying on a host CPU or cloud-based inference. In this work we present the design and deployment of an experience accumulator system in a particle accelerator. In this system, deep-RL algorithms run using hardware acceleration and act within a few microseconds, enabling the use of RL for control of phenomena like beam instabilities. The training uses the collected data offline to reduce the number of operations carried out on the acceleration hardware. The proposed architecture was tested in real experimental conditions at the Karlsruhe research accelerator, a synchrotron light source, where the system was used to control artificially induced horizontal betatron oscillations in real-time, with a control loop period of just 2.7 μs. The results showed a performance comparable to the commercial feedback system available at the accelerator, demonstrating the viability and potential of this approach. Due to the self-learning and reconfiguration capability of this implementation, a seamless application to other control problems is possible. Applications range from particle accelerators to large-scale research and industrial facilities.

FPGA↗
DOE OSTI2022

Measurements of the 96 Zr(α,n) cross section for astrophysics and applications

The reaction 96 Zr(α,n) plays an important role in ν-driven wind nucleosynthesis in core-collapse supernovae and is a possible avenue for medical isotope production. Here, cross section measurements were performed using the activation technique at the Edwards Accelerator Laboratory. Results were analyzed along with world data on the 96 Zr(α, n) cross section and 96 Zr(α, α) differential cross section using large-scale Hauser-Feshbach calculations. We find general agreement between our data, previous measurements, and a statistical description of the reaction. However, we find a larger cross section at low energies compared to prior experimental results, allowing for a larger astrophysical reaction rate. This may impact results of core-collapse supernova ν-driven wind nucleosynthesis calculations, but does not significantly alter prior conclusions about 99 Mo production for medical physics applications. The results from our large-scale Hauser-Feshbach calculations demonstrate that phenomenological optical potentials may yet be adequate to describe (α, n) reactions of interest for ν-driven wind nucleosynthesis, albeit with regionally-adjusted model parameters.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Performance and Durability of Heavy-Duty Fuel Cell Systems with an Advanced Ordered Intermetallic ORR Alloy Catalyst and Novel Support

Ordered PtCo intermetallic (OIM) catalyst (L1 0 -PtCo/C) is a promising candidate as the oxygen reduction reaction (ORR) catalyst in hybrid fuel cell systems (FCS) for class-8 heavy duty (HD) trucks. Compared to a baseline annealed Pt on high surface area carbon (a-Pt/HSC) catalyst, its mass activity (MA) is 71% higher initially and 144% higher after 90,000 potential cycles in an accelerated stress test (AST). Analysis of the AST data indicates that the ORR kinetic constants do not change with aging and the degradation in the OIM catalyst activity is linearly proportional to the loss in the electrochemically active surface area (ECSA). Several operational strategies are investigated to mitigate catalyst degradation and achieve 25,000-h electrode lifetime and 2.5 kW g −1 Pt utilization on a HD truck duty cycle including load sharing with the hybrid battery, regulating the radiator fan power to maintain the coolant temperature close to 60 °C, clipping the maximum cell voltage below 850 mV, limiting the ECSA loss to 55%, and oversizing the active area of the membrane electrode assemblies by 20%. Drive cycle simulations indicate that the lifetime average voltage degradation rate is about 1.8 μV h −1 and the integrated stack and FCS drive cycle efficiencies decrease by 3.5 to 3.9%.

25 ENERGY STORAGE↗
DOE OSTI2025

Host Onboarding Tool (HObT) v1.0.0

The Host OnBoarding Tool (Hobt) is a publicly accessible, web-based software designed to organize and share information about microbial hosts under development at the Agile BioFoundry (ABF). It streamlines the assessment, tracking, and sharing of information related to microbial host development and provides a centralized platform where users can rapidly evaluate hosts' readiness for various bio processes. HObT leverages the Tier System, a standardized host development framework that organizes and assesses microbial hosts based on their readiness for biomanufacturing. Each tier outlines key targets—including genetic tools, growth conditions, omics data, and predictive models—needed to transform new or emerging microbes into established production platforms. By applying clear criteria for advancement, the Tier System helps users quickly evaluate each organism's current development status, identify gaps in available knowledge or tools, and prioritize future strain improvement efforts. Through its user-friendly interface, HObT encourages contributions of new data and insights from researchers, fostering collaboration and accelerating host development. By providing structured guidance for microbial strain advancement, HObT and the Tier System support more systematic, rapid, and cost-effective development of non-traditional microbial hosts, ultimately enhancing the efficiency and impact of biomanufacturing research and applications.

Plahar, Hector [Lawrence Berkeley National Laborat↗
DOE OSTI2020

Andes Data Analysis System at the Oak Ridge Leadership Computing Facility

Andes is a (704)-node commodity-type Linux® cluster. Each of Andes’s 704 nodes contain two 16-core 3.0 GHz AMD EPYC 7302 processors with AMD’s Simultaneous Multithreading (SMT) Technology and 256GB of main memory. Andes also has nine large memory GPU nodes. These nodes each have 1TB of main memory and two NVIDIA K80 GPUs with two 14-core 2.30 GHz Intel Xeon processors with HT Technology.

AMD EPYC↗
DOE OSTI2025

MuSIKAL: Multiphysics Simulations and Knowledge Discovery through AI/ML Technologies

Under the MuSiKAL project, we developed a framework for a coastal digital twin (DT) platform capable of integrating diverse data resources, configuring multiscale model simulations, performing SciML‐accelerated predictions, with applications primarily driven by storm surge and heavily rainfall events impacting the Gulf Coast of the U.S.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Requirements and Overview of the LAMP PDM Vault

The Los Alamos Neutron Science Center (LANSCE) is located at Technical Area 53 (TA-53) at Los Alamos National Laboratory in Los Alamos, New Mexico. LANSCE is driven by an 800 mega electron volt (MeV) proton accelerator that delivered first beam in 1972. The LANSCE accelerator is unique in that it accelerates both H- (to full energy of 800 MeV) and H+ ions (up to 100 MeV currently but has accelerated high-power H+ beam to 800 MeV in the past) and supports five separate experimental areas that operate simultaneously with each having different timing and beam current requirements.

43 PARTICLE ACCELERATORS↗