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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Assessing electrification readiness in U.S. single-family homes based on a nationwide survey of electrical panel capacities

Electrification of residential buildings is a key strategy for increasing the use of renewable energy sources. Central to this transition is understanding the capacity of existing electrical infrastructure—specifically electrical panels—to safely and effectively manage increased electricity demands from electrification technologies. However, comprehensive nationwide data on electrical panel capacities in U.S. single-family homes is currently lacking. To address this gap, we conducted a nationwide survey of single-family homes, collecting detailed data on electrical panel capacities, breaker slot availability, major electric and gas appliances, electrical panel models, and home characteristics such as construction year and floor area. Photographic documentation was used to verify electrical panel data and appliance information. Results show that approximately 60% of surveyed homes have electrical panels rated at ≥200 amperes (A), indicating that a significant portion of the existing housing stock can accommodate additional electric loads. However, 31% of homes possess panels rated at ≤100 A, potentially restricting their ability to adopt new electric appliances without significant upgrades. Panel capacities positively correlate with both home size and construction year, with newer and larger homes generally better suited for electrification. Homes with higher-capacity panels tend to have fewer gas appliances, reflecting a gradual shift toward electric technologies. Conversely, homes with lower-capacity panels frequently rely on multiple gas appliances, highlighting substantial electrification challenges. Additionally, approximately 3% of surveyed homes had potentially hazardous electrical panel models, emphasizing important safety considerations in the residential electrification process. Our findings underscore the need for targeted policies, financial incentives, and infrastructure investments designed specifically to address infrastructural and safety barriers, particularly in older and smaller homes, to support equitable and efficient electrification across the U.S. residential sector.

Gul, Sadia↗
DOE OSTI2023

A mesoscale crystal plasticity model to predict room-temperature deformation and martensitic transformation of high-strength Quenching and Partitioning (Q&P) Steels and validation with synchrotron X-ray diffraction

Renowned for the superior mechanical properties and adeptness at cold-forming, Quenching and Partitioning (QP) steels have gained prominence as a promising candidate material in fabricating safety-critical components in various industries. The pertinent research on QP steels focus on the martensitic transformation of the Retained Austenite (RA) phase during cold-forming, a crucial mechanism that substantially influences the overall strength and ductility of QP steels. The austenite stability and transformation rate heavily rely on the local strain path and the initial microstructure, which is challenging for analytical prediction. In this paper, a mesoscale model is developed to capture the deformation and transformation kinetics of QP steels inside the microstructure. The model integrates the detailed explicit microstructure, acquired from characterization experiments, into a high-resolution finite element (FE) mesh. It distinctly model the deformation and interaction between the various phases and the effect on the transformation of RA. The model is validated with high energy X-ray diffraction (HEXRD) data, and shows excellent capability in predicting the asymmetric stress-strain behavior under uniaxial tension and compression, as well as the martensitic transformation rate. The model is used to investigate the strain and load partitioning effect of surrounding matrix to the transformation of RA, offering insights into the complex behavior of QP980 and facilitates further material development.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Evaluating the Taylor hardening model in polycrystalline Ti using high energy X-ray diffraction microscopy

High energy X-ray diffraction microscopy (HEDM) was employed to index nearly 1000 grains in a polycrystalline Ti specimen and characterize their deformation during an incremental tensile test. For each grain, the positions of its associated diffraction peaks were used for analyzing its evolving crystal orientation and stress tensor. The azimuthal breadth of each peak at different load steps was measured, allowing measurement of initial yielding and providing an estimate of the dislocation density evolution in each grain. Furthermore, the Taylor hardening model was evaluated grain by grain using the above data, indicating that it can represent hardening in most grains. The yield stress and the strain hardening coefficient for all grains were statistically analyzed with respect to grain orientation, grain size, slip systems, and the surrounding neighborhood to examine how the yield stress and hardening are correlated.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electrochemical Salt Wasteform Development: A Review of Salt Treatment and Immobilization Options

Electrochemical reprocessing, also referred to as pyroprocessing, is a technique for recycling actinides from used nuclear fuel (UNF) to produce fuel for future reactors. Here, UNF is dissolved in a molten salt (e.g., LiCl-KCl eutectic) within an electrorefiner. After UNF dissolution, fission products are released into the electrolyte salt and converted to chlorides. This paper discusses wasteform options for processing the base electrolyte salt with the fission product salts as well as just the rare-earth fission products (as RECl 3 , REOCl, or REO x ) with the intent of finding optimal methods for reducing total waste salt volumes or partitioning the salt for alternate wasteform options. Furthermore, two of the more detailed partitioning options discussed herein include halide removal from the salt (dehalogenation), which accounts for more than half of the salt on a molar basis, and RE fission product removal for wasteforms with high-RE loadings. Wasteform properties are compared with emphasis on wasteform volume starting from a given amount of (1) total salt cations or (2) RE cations. Comparisons are also made of wasteform chemical durabilities, with the data available from like testing methods. A main conclusion from this work is the justification of subsequent salt processing after electrorefiner operations for achieving significant wasteform volume reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Hydrogen Uptake Kinetics of 1,4-Bis(phenylethynyl)benzene Rubberized O-Rings: Measurements, Modeling, and Comparison with Additional Forms of Organic Getters

A class of molecules called “hydrogen getters” can react with, or scavenge, H 2 in applications where the hydrogen presence and/or buildup are not desirable. One such “getter”, 1,4-bis(phenylethynyl)benzene or DEB, can be incorporated into a silicone matrix in the form of an O-ring for added flexibility, environmental resiliency, and convenient use as a gasket in sealed applications. However, the performance and kinetics of this DEB-loaded rubberized O-ring have not yet been characterized. Here in this work, the hydrogen uptake kinetics of the rubberized DEB O-ring were extracted by the isoconversional analysis from isothermal isobaric data under conditions of 13,332 Pa H 2 and 305–325 K. The isoconversional and cylindrical diffusion approximations were then used to predict and model the hydrogen uptake of rubberized DEB O-rings under any arbitrary condition, as illustrated in this work for the simple case of a constant rate of hydrogen generation/input. In comparison with other Pd/carbon-based/organic getter systems, these rubberized DEB O-rings provide a type of hydrogen getter material with enhanced flexibility and catalyst protection in applications where an O-ring seal is needed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Distinct Gas-Particle Partitioning and Viscosity Characteristics of Secondary Organic Aerosols Derived from α-Pinene versus Ocimene

Secondary organic aerosols (SOA) have complex, multicomponent composition that controls particle viscosity and gas-particle partitioning, key factors to their atmospheric evolution. This study investigates the chemical composition, volatility and viscosity of SOA formed by ozonolysis of cyclic α-pinene (PSOA) and acyclic ocimene (OSOA) monoterpenes. Using Temperature-Programmed Desorption combined with Direct Analysis in Real-Time ionization and High-Resolution Mass Spectrometry, we determined the molecular composition and saturation mass concentration of individual SOA constituents. These data enabled gas-particle partitioning and viscosity estimates under varied atmospheric conditions. PSOA, composed of higher molecular weight and less oxidized species, shows higher condensability and viscosity under high total organic mass (tOM) loadings. Here, in contrast, OSOA, consisting of more oxidized, lower molecular weight species, exhibits greater sensitivity to tOM, with viscosity increasing significantly upon dilution. Poke-flow experiments support this trend, indicating that OSOA undergoes more dynamic compositional and phase changes during atmospheric aging. These observations reveal distinct dynamic trends in the atmospheric transformations and reactivity of SOA from cyclic and acyclic monoterpenes, with the latter showing greater compositional changes during aging that alter viscosity and diffusion. This highlights the importance of incorporating such dynamic transformations into atmospheric models to improve predictions of SOA atmospheric loadings, lifetimes, and impacts.

cyclic and acyclic monoterpenes↗
DOE OSTI2026

Development and Validation of the Near-Miss Safety Score (NMSS) Framework for Heavy-Duty Vehicle Safety Assessment

Heavy-duty commercial vehicles present unique safety challenges due to their size, articulation dynamics, and operational complexity. As Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) become more common in Class 8 tractor-trailers, traditional crash-based metrics are no longer sufficient to evaluate safety performance. This study introduces the Near-Miss Safety Score (NMSS)—a quantitative, physics-informed framework developed as a leading indicator of safety for advanced commercial vehicle technologies. NMSS quantifies how close a vehicle or operator comes to a collision or safety-critical event by integrating vehicle kinematics (relative distance, velocity, and acceleration) with driver or system response latency and time-to-collision. A modifier function adjusts the base score for vehicle-specific and environmental factors such as trailer articulation, load distribution, braking condition, and roadway environment. The framework enables systematic evaluation of ADAS/ADS performance under a range of operational and degraded conditions. By capturing near-miss dynamics rather than relying on crash data, NMSS provides a proactive approach to risk assessment, accelerates technology validation, and enhances interpretability for regulators and fleet operators. The proposed NMSS was validated using data collected from a motorcoach platform, demonstrating the framework’s applicability to heavy-duty safety evaluation and performance benchmarking. Results and key insights are presented in this paper.

Siekmann, Adam [ORNL] (ORCID:0000000284653935)↗
DOE OSTI2026

Microwave Vortex Motion Characterization of Nb$_{3}$ Sn Coatings for Applications in High Magnetic Fields

In this work, microwave measurements carried out in dielectric-loaded resonators exposed to high magnetic fields are exploited to yield the surface impedance of Nb$_3$ Sn superconducting coatings deposited via two different techniques: vapor tin diffusion, and DC magnetron sputtering. The obtained data lead to qualitative interpretations on both the Nb$_3$ Sn superconducting properties, and vortex-dynamics and pinning, of each coating separately, as well as simple distinctive features when comparing those. When examining the respective surface impedances at varying field, it is expected that the studied films perform at substantially diverse magnitudes of flux-flow resistivity, but also in well-differentiated pinning regimes, yet the obtained surface resistances of both samples are comparable, thus demonstrating that there is room for film optimization at the expense of certain compromise between the parameters involved.

Nb3Sn↗
DOE OSTI2022

Bayesian optimized collection strategies for fatigue strength testing

Abstract A statistical framework is presented enabling optimal sampling and analysis of constant life fatigue data. Protocols using Bayesian maximum entropy sampling are built based on conventional staircase and stress step methods, reducing the requirement of prior knowledge for data collection. The Bayesian Staircase method shows improved parameter estimation efficiency, and the Bayesian Stress Step method shows equal accuracy to the standard method at larger step size allowing experimentalists to lessen concerns of loading history. Statistical methods for determining model suitability are shown, highlighting the influence of protocol. Experimental validation is performed, showing the applicability of the methods in laboratory testing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

cuAlign: Scalable Network Alignment on GPU Accelerators

Given two graphs, the objective of network alignment is to find the best one-to-one mapping of vertices in one graph (??) to vertices in the other (??), such that the number of overlaps is maximized. We say that edges(??, ??) ???and(??', ??') ??? are overlapped if ?? is mapped to ??' and ?? is mapped to??'. Network alignment is an important optimization problem with several applications in bioinformatics, computer vision and ontology matching. Since it is an NP-hard problem, efficient heuristics and scalable implementations are necessary. In this work, we introduce a new framework that combines the concepts of intra-network proximity using vertex embedding,Belief Propagation (BP) and approximate weighted matching, and provides qualitative improvements up to22%over state-of-the-art approaches. We also provide scalable implementations on GPU accelerators, demonstrating up to19×speedup for Belief Propagation and 3× speedup for approximate weighted matching relative to previous multithreaded implementation. A combination of combinatorial and algebraic kernels within the network alignment algorithm poses significant hurdles for parallelization. Load imbalance and irregular DRAM traffic limit achievable performance on GPUs. Our novel approach identifies and exploits unique structural proper-ties of the BP-based algorithm and employs code fusion to reduce data movement between different steps of the algorithm. Using a diverse set of inputs, we demonstrate qualitative improvements of our algorithms, and performance gains of our GPU-accelerated implementation. We believe that our work will enable algorithmic improvements and practical applications of network alignment.

Xiang, Lizhi↗
DOE OSTI2022

Compressive strength of the plastic-bonded explosive surrogate idoxuridine under quasistatic and dynamic compression

Inert simulant materials, or “mocks”, are often used as surrogates for plastic-bonded explosives (PBX) in non-detonative tests in order to mitigate hazards. Mocks should reproduce as many non-detonative properties of the explosive as possible, including structural behavior in a variety of thermal and mechanical environments. Recently, the molecular crystal idoxuridine (IDOX) has been identified as an ideal mock for the main component in the explosive polymer-matrix composite PBX 9501, and has performed favorably under quasistatic loading conditions. Here, in order to assess robustness over a range of mechanical environments, plastic-bonded IDOX was compression tested from 0.001/s to 2000/s strain rates and compared to PBX 9501 historical data. Plastic-bonded IDOX showed good agreement to PBX 9501 across these strain rates, justifying continued development and production as a mock.

Burch, Alexandra C.↗
DOE OSTI2021

Fully Convolutional Spatio-Temporal Models for Representation Learning in Plasma Science

We have trained a fully convolutional spatio-temporal model for fast and accurate representation learning in the challenging exemplar application area of fusion energy plasma science. The onset of major disruptions is a critically important fusion energy science issue that must be resolved for advanced tokamak plasmas such as the $25B burning plasma international thermonuclear experimental reactor (ITER) experiment. While a variety of statistical methods have been used to address the problem of tokamak disruption prediction and control, recent approaches based on deep learning have proven particularly compelling. In the present paper, we introduce further improvements to the fusion recurrent neural network (FRNN) software suite, which delivered cross-machine disruption predictions with unprecedented accuracy using a large database of experimental signals from two major tokamaks. Up to now, FRNN was based on the long short-term memory (LSTM) variant of recurrent neural networks to leverage the temporal information in the data. Here, we implement and apply the "temporal convolutional neural network (TCN)" architecture to the time-dependent input signals. Furthermore, this allows highly optimized convolution operations to carry the majority of the computational load of training, thus enabling a reduction in training time, and the effective use of high-performance computing resources for hyperparameter tuning. At the same time, the TCN-based architecture achieves better predictive performance when compared with the LSTM architecture for various tasks for a representative fusion database.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Transverse Beam Tails and Beam Lifetime in the EIC Electron Storage Ring

For most storage ring design purposes it is sufficient to assume a Gaussian distribution of the electrons in a bunch. However, a more detailed knowledge of the population in the transverse tails beyond a few sigma is necessary to predict the beam lifetime and the synchrotron radiation load in the interaction region due to beam-gas scattering and the beam-beam interaction. This report presents simulations to determine the required vacuum level as well as to serve as input data for detailed synchrotron radiation simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Analysis of Conservation Voltage Reduction under Inverter-Based VAR-Support [Slides]

Conservation voltage reduction (CVR) is a common technique used by utilities to strategically reduce demand during peak periods. As penetration levels of distributed generation (DG) continue to rise and advanced inverter capabilities become more common, it is unclear how the effectiveness of CVR will be impacted and how CVR interacts with advanced inverter functions. In this work, we investigated the mutual impacts of CVR and DG from photovoltaic (PV) systems (with and without autonomous Volt-VAR enabled). The analysis was conducted on an actual utility dataset, including a feeder model, measurement data from smart meters and intelligent reclosers, and metadata for more than 30 CVR events triggered by the utility over the year. The installed capacity of the modeled PV systems represented 66% of peak load, but reached instantaneous penetrations reached up to 2.5x the load consumption over the year. While the objectives of CVR and autonomous Volt-VAR are opposed to one another, this study found that their interactions were mostly inconsequential since the CVR events occurred when total PV output was low.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Skewering the silos: using Brick to enable portable analytics, modeling and controls in buildings

Nearly all large commercial buildings have heating, ventilation and air conditioning (HVAC) systems, lighting systems, safety and other systems controlled by a computer—a dedicated server with a building energy management system (BMS). However, these BMSs are proprietary with each building’s assets (that is, fans, valves, pumps, and their setpoints) named and coded uniquely by the BMS vendor or engineer; building analytics and control algorithms are written specific to the assets and the building. Thus, any control updates or analytics to improve building performance—especially critical to reduce greenhouse emissions or improve load flexibility—are labor intensive and costly. The Brick schema was developed so the same analysis or control algorithms can work on a variety of buildings if each is digitally represented in a Brick data model. The goal of this project was to further the development of Brick to extend it beyond an academic project with demonstrated success in a small field study, to a practical choice for industrial and commercial stakeholders seeking to realize value from building data. To do this, we executed four objectives: (1) expand the Brick schema including its modeling capabilities and vocabulary, (2) develop tools for integrating Brick with existing digital technologies and representations in buildings, (3) develop an open-source analytics platform to facilitate use of Brick in delivering data value, and (4) demonstrate Brick-driven analytics and controls in real settings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Developing Methods to Assess Changes in Mechanical Properties of Shale Modified by Engineered Mineral Precipitation

Fractures in subsurface shale formations serve multiple purposes, for example, in the recovery of resources in hydraulic fracturing or as potential harmful leakage passages through caprocks that may contribute undesired fluids to the atmosphere or functional groundwater aquifers. A proposed method to seal or influence fracture properties is Ureolysis-Induced Calcium Carbonate Precipitation (UICP), a bio-mineralization technology driven by the enzymatic hydrolysis of urea, resulting in the formation of calcium carbonate. Sporosarcina pasteurii is a common microbe used as the source of the urease enzyme that catalyzes the chemical reaction. The resulting calcium carbonate can bridge the gaps in fractured shale and reduce fluid flow through fractures. However, there is little information on how this process affects the mechanical properties of the resulting biomineralized shale. This study represents the first step toward determining the influence of UICP treatment on shale material and its subsequent mechanical strength properties. This methods development study aims to determine the effect that temperature has on the tensile strength of intact, unfractured shale cores (2.54 cm (1 in) diameter, 5.08 cm (2 in) long). Tensile strength was determined indirectly using a modified Brazilian test where the splitting tensile strength is attained by applying a compressive load onto the core. Shale cores from Eagle Ford and Wolfcamp formations were tested at both room temperature and 60°C to determine if increased temperature influences the tensile strength of the rock. This data will help to assess the necessity of testing biomineralized cores at temperature. Though 60°C may not mimic subsurface temperatures of the shales used in this study, it was chosen due to limitations of the UICP process while still approaching temperatures of shale formations. This project aims to evaluate what effect temperature has on the mechanical properties of intact shale cores so that engineered or natural rock fractures that are sealed by biomineralization can be better understood.

Bedey, Kayla↗
DOE OSTI2026

Hydrodynamic Analysis and Optimization of Aquantis Marine Turbine: Cooperative Research and Development (Final Report)

The primary aim of this proposal is to improve the accurate prediction of hydrodynamic performance and dynamic load responses of the AQ10 floating axial-flow tidal turbine with a tri-cat mooring configuration. The validation of reduced-order modeling approaches with high-fidelity model will be implemented. Additionally, the frequency response domain, Response Amplitude Floating Wind (RAFT) toolbox plus an optimizer expanded for marine hydrokinetic turbines under the Submarine Hydrokinetic And Riverine Kilo-megawatt. Systems (SHARKS) program will be used for designing and exploring different key design parameters (platform dimension, mooring layout and its parameters) of next marine hydrokinetic (MHK) turbine generation.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Artificial Intelligence Techniques in Smart Grid: A Survey

The smart grid is enabling the collection of massive amounts of high-dimensional and multi-type data about the electric power grid operations, by integrating advanced metering infrastructure, control technologies, and communication technologies. However, the traditional modeling, optimization, and control technologies have many limitations in processing the data; thus, the applications of artificial intelligence (AI) techniques in the smart grid are becoming more apparent. This survey presents a structured review of the existing research into some common AI techniques applied to load forecasting, power grid stability assessment, faults detection, and security problems in the smart grid and power systems. It also provides further research challenges for applying AI technologies to realize truly smart grid systems. Finally, this survey presents opportunities of applying AI to smart grid problems. The paper concludes that the applications of AI techniques can enhance and improve the reliability and resilience of smart grid systems.

energy systems↗