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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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DOE OSTI2023

An extended focused assessment with sonography in trauma ultrasound tissue-mimicking phantom for developing automated diagnostic technologies

Medical imaging-based triage is critical for ensuring medical treatment is timely and prioritized. However, without proper image collection and interpretation, triage decisions can be hard to make. While automation approaches can enhance these triage applications, tissue phantoms must be developed to train and mature these novel technologies. Here, we have developed a tissue phantom modeling the ultrasound views imaged during the enhanced focused assessment with sonography in trauma exam (eFAST). The tissue phantom utilized synthetic clear ballistic gel with carveouts in the abdomen and rib cage corresponding to the various eFAST scan points. Various approaches were taken to simulate proper physiology without injuries present or to mimic pneumothorax, hemothorax, or abdominal hemorrhage at multiple locations in the torso. Multiple ultrasound imaging systems were used to acquire ultrasound scans with or without injury present and were used to train deep learning image classification predictive models. Performance of the artificial intelligent (AI) models trained in this study achieved over 97% accuracy for each eFAST scan site. We used a previously trained AI model for pneumothorax which achieved 74% accuracy in blind predictions for images collected with the novel eFAST tissue phantom. Grad-CAM heat map overlays for the predictions identified that the AI models were tracking the area of interest for each scan point in the tissue phantom. Overall, the eFAST tissue phantom ultrasound scans resembled human images and were successful in training AI models. Tissue phantoms are critical first steps in troubleshooting and developing medical imaging automation technologies for this application that can accelerate the widespread use of ultrasound imaging for emergency triage.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Interpreting Transformers for Jet Tagging

Machine learning (ML) algorithms, particularly attention-based transformer models, have become indispensable for analyzing the vast data generated by particle physics experiments like ATLAS and CMS at the CERN LHC. Particle Transformer (ParT), a state-of-the-art model, leverages particle-level attention to improve jet-tagging tasks, which are critical for identifying particles resulting from proton collisions. This study focuses on interpreting ParT by analyzing attention heat maps and particle-pair correlations on the $\eta$-$\phi$ plane, revealing a binary attention pattern where each particle attends to at most one other particle. At the same time, we observe that ParT shows varying focus on important particles and subjets depending on decay, indicating that the model learns traditional jet substructure observables. These insights enhance our understanding of the model's internal workings and learning process, offering potential avenues for improving the efficiency of transformer architectures in future high-energy physics applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Citizen and machine learning-aided high-resolution mapping of urban heat exposure and stress

Abstract Through conversion of land cover to more built-up, impervious surfaces, cities create hotter environments than their surroundings for urban residents, with large differences expected between different parts of the city. Existing measurements of ambient air temperature and heat stress, however, are often insufficient to capture the intra-urban variability in heat exposure. This study provides a replicable method for modeling air temperature, humidity, and moist heat stress over the urban area of Chapel Hill while engaging citizens to collect high-temporal and spatially-resolved air temperature and humidity measurements. We use low-cost, consumer-grade sensors combined with satellite remote sensing data and machine learning to map urban air temperature and relative humidity over various land-cover classes to understand intra-urban spatial variability of ambient heat exposure at a relatively high resolution (10 m). Our findings show that individuals may be exposed to higher levels of air temperature and moist heat stress than weather station data suggest, and that the ambient heat exposure varies according to land cover type, with tree-covered land the coolest and built-up areas the warmest, and time of day, with higher air temperatures observed during the early afternoon. Combining our resulting dataset with sociodemographic data, policymakers and urban planners in Chapel Hill can use data output from this method to identify areas exposed to high temperature and moist heat stress as a first step to design effective mitigation measures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Q3 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q3: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis. • Benchmark between two first wall heat flux mapping methods, identify importance of various heat flux sources and physics impact of using fully coupled CESOL vs post-analysis evaluation. 2. Generate medium fidelity parametrized CAD. • Generate parametrized CAD components for the CAT example case via either user-defined modules called within the geometry generation or by defeatured/parametrized CAD, including DCLL blanket matched to divertor boundary and magnets. Define materials, labels, and boundary conditions for passing the mesh to CFD tools. 3. Demonstrate multiphysics magnet analysis. • Demonstrate magnet analysis workflow called from the FREDA workflow, and 4. Demonstrate nuclear analysis. • Add model to OpenFOAM and/or other codes possibly including Diablo to account for tritium diffusion in solids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Latent heat thermal energy storage performance maps enabling fast & accurate building energy simulations

Thermal energy storage (TES) using phase change materials (PCMs) has gained attention as an effective approach to manage energy demand fluctuations and shift peak building loads. PCM embedded heat exchangers (PCM-HXs) offer high energy storage density and low temperature variation during phase change, being suitable for load-shifting applications. However, this component is typically evaluated using computationally expensive methods, which present significant challenges when the ultimate goal is to assess the performance of PCM-HX integrated thermal energy storage systems in the full building context. In this paper, we present a methodology to generate highly accurate and computationally efficient PCM-HX performance maps which can be easily integrated into building energy simulation tools to analyze the feasibility of space conditioning systems with latent heat PCM-based TES. The performance maps are generated using a computationally efficient PCM-HX simulation tool based on a Generalized Resistance-Capacitance Model (GRCM) which can simulate arbitrary PCM-HXs with high accuracy and significantly less computational effort compared to full CFD simulations. The methodology was verified for a case study considering a 5-ton (~17.5 kW) air-to-water heat pump-thermal energy storage system (HP-TES), which was co-simulated in Modelica for a DOE prototype small-office building in Vienna, Austria, using Spawn of EnergyPlus™. The TES performance maps provided accurate predictions of PCM-HX behavior when used as Modelica component, with deviations within 2-4% while also achieving at least 103 computational time reduction. Leveraging this faster prediction capability, four PCMs with different melting temperatures for cooling (12°C, 16°C) and heating (31°C, 36°C) were assessed to investigate their impact on system performance. This work highlights the importance of robust PCM-HX models for efficient and high-fidelity building-level simulations, presenting new opportunities for advanced control strategy development and parametric analysis of TES configurations in a computationally efficient manner

Modelica Building Simulations↗

DOE OSTI2023

Geothermal Play Fairway Analysis, Part 2: GIS methodology

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Material Selection and Heat Transfer Model for PTUHS Device

The Path to Ultimate Heat Sink Device (PTUHS) is a passive safety system that utilizes a radiative heat transfer valve to control the rate at which heat is removed from a nuclear reactor pressure vessel (RPV) and dispersed into surrounding soil. The material selection for the PTUHS device is investigated, where the thermophysical properties are either maximized or minimized bases on what section of the PTUHS that material is being used for. Final recommendations of material choice are then presented. The heat transfer model of the PTUHS device is solved in ABAQUS, where a normal operating conditions and SCRAM conditions are solved. These temperature maps and heat flux of the system show the system's ability, where minimal heat is lost during normal operating conditions and system failure in a SCRAM scenario due to temperatures that were reached.

42 - ENGINEERING↗

DOE OSTI2024

Geothermal play fairway analysis, part 1: Example from the Snake River Plain, Idaho

The Snake River Plain (SRP) volcanic province overlies the track of the Yellowstone hotspot, a thermal anomaly that extends deep into the mantle. Most of the area is underlain by a basaltic volcanic province that overlies a mid-crustal intrusive complex, which in turn provides the long-term heat flux needed to sustain geothermal systems. Previous studies have identified several known geothermal resource areas within the SRP. For the geothermal study presented herein, our goals were to: (1) adapt the methodology of Play Fairway Analysis (PFA) for geothermal exploration to create a formal basis for its application to geothermal systems, (2) assemble relevant data for the SRP from publicly available and private sources, and (3) build a geothermal PFA model for the SRP and identify the most promising plays, using GIS-based software tools that are standard in the petroleum industry. The study focused on identifying three critical resource parameters for exploitable hydrothermal systems in the SRP: heat source, reservoir and recharge permeability, and cap or seal. Data included in the compilation for heat source were heat flow, distribution and ages of volcanic vents, groundwater temperatures, thermal springs and wells, helium isotope anomalies, and reservoir temperatures estimated using geothermometry. Reservoir and recharge permeability was inferred from the analysis of stress orientations and magnitudes, post-Miocene faults, and subsurface structural lineaments based on magnetics and gravity data. Data for cap or seal included the distribution of impermeable lake sediments and clay-seal associated with hydrothermal alteration below the regional aquifer. These data were used to compile Common Risk Segment maps for heat, permeability, and seal, which were combined to create a Composite Common Risk Segment map for all southern Idaho that reflects the risk associated with geothermal resource exploration and identifies favorable resource tracks. Our regional assessment indicated that undiscovered geothermal resources may be located in several areas of the SRP. Two of these areas, the western SRP and Camas Prairie, were selected for more detailed assessment, during which heat, permeability, and seal were evaluated using newly collected field data and smaller grid parameters to refine the location of potential resources. These higher resolution assessments illustrate the flexibility of our approach over a range of scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Effect of Magnetic Islands on Neoclassical Heat Diffusivity in a Global Tokamak Simulation

Resonant magnetic perturbations (RMPs) alter magnetic field topology via island formation and can modify core transport in toroidal fusion devices. Using the global gyrokinetic particle‐in‐cell code XGC‐S, originally developed for stellarator geometries, we quantify how island topology affects neoclassical heat transport in a circular tokamak with ($m,n$) = (5,2) RMP‐induced islands. Electron radial heat diffusivity exhibits a two‐peak structure with a dominant enhancement near the O/X‐point region and a secondary peak at the outer island boundary, whereas ion transport remains close to the neoclassical prediction. The observed electron diffusivity is strongly enhanced over the neoclassical baseline but remains well below the Rechester–Rosenbluth estimate, consistent with the non‐ergodic character of the island topology. The density dependence of diffusivity is weaker inside the islands than outside, indicating the presence of topology‐driven transport channels that do not depend strongly on collisionality. Two‐dimensional heat flux maps reveal an up–down antisymmetric structure at the island separatrices consistent with magnetic gradient and curvature drift effects, in contrast to the symmetric temperature flattening inside the islands. These results identify topology‐dependent avenues for electron heat transport in RMP‐perturbed cores and suggest regimes in which island geometry, rather than collisions alone, governs radial transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Reevaluating Contour Visualizations for Power Systems Data

Effective visual analytics tools are needed now more than ever as emerging energy systems data and models are rapidly growing in scale and complexity. Here we examined the suitability of colored contour maps to visually represent bus values in two different power system models: a dense 24k-bus distribution system and a 240-bus transmission system. In a quantitative analysis, we found that contour maps misrepresent power systems data, changing the statistical dispersion of the bus values, including the loss of extreme values. In a controlled empirical study with thirty professional power system research engineers, we found that these distortions significantly impact excursion identification tasks. Additionally, the engineers were less confident in their assessments using contour-based visualizations than glyph-based visualizations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

High-Resolution Thermal Profiling of a High-Power Diode Laser Facet During Aging

Here, we study the facet temperature distribution of a high-power diode laser over its lifetime using a noncontact, high spatial resolution CCD-based thermoreflectance technique. Based on the known correlation between non-radiative defects and heating, thermal maps can provide valuable information regarding the formation and evolution of small point defects that are at or near the facet during aging. In the laser under study in this work we measure the appearance of local hot spots on the facet, including concentrated hot spots that appear just before or just after COD and are correlated with loss of local light emission. The locations of these hot spots do not exhibit morphology changes in high-resolution SEM imaging of the facet, indicating that the related defects are too small to be observable in SEM or are located at some depth under the facet. Prior to COD, we measure a gradual facet temperature increase accompanied by a gradual optical power decrease and gradual facet optical absorption increase, indicating gradual degradation of the laser.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Geospatial characterization of low-temperature heating and cooling demand in residential, commercial, manufacturing, agricultural, and data center sectors for potential geothermal applications in the United States

Thermal demand for heating and cooling has been predominantly supplied by fossil fuel combustion in the United States, although low-carbon alternatives are extensively available including geothermal, solar thermal, and waste heat. Here, this study analyzed end-use energy consumption, fuel expenditure, and data center commissioned power data to geospatially characterize the U.S. low-temperature heating and cooling demand at the county level in residential, commercial, manufacturing, agricultural, and data center sectors and understand potential opportunities for geothermal applications. In the analysis, the regional-scale energy consumption data was incorporated with system efficiencies to address actual demand and was then disaggregated with weighting factors to the county level. The results indicated that total low-temperature heating and cooling demand is 16.7 EJ, combining heating demand of 10.8 EJ and cooling demand of 5.9 EJ. Overall, 59.9 % (10 EJ) of the low-temperature heating and cooling demand occurred in the residential sector. The heating and cooling demand visualized in maps represented that the geospatial distribution of heating and cooling demand in the residential and commercial sectors is governed by the number of housing units and climate zone designations, while heating and cooling demand in the manufacturing, agricultural, and data center sectors is dependent on the number and location of facilities. The results also demonstrated that geothermal heat pumps are broadly used in the residential and commercial sectors for heating and cooling in the U.S. Midwest, South, and Northeast regions but are limited in the West, implying great decarbonization potential in the future.

15 GEOTHERMAL ENERGY↗

DOE OSTI2026

Hyperspectral radiance mapping and chromatic correction for temperature measurement in laser-heated diamond anvil cells

In laser-heated diamond anvil cell (DAC) experiments, the effective heated region typically decreases in size with increasing pressure, leading to steeper thermal gradients. Under these conditions, chromatic aberration in the optical path from sample to detector can significantly create bias in spectro-radiometric temperature measurement. We present a radiance-mapping approach using a hyperspectral camera that records 25 spectral channels spanning 605–875 nm at each pixel in a single exposure, providing spatially and spectrally resolved radiance in each frame. This enables chromatic effects to be recorded and corrected in data processing. We developed a procedure for hyperspectral mapping, involving per-camera calibration, crosstalk removal, measured spectral throughput functions, and optional sub-pixel co-registration to minimize chromatic distortion. The calibrated radiance maps are then used to derive temperature maps of the laser-heated hotspots. For smaller heating spots, the radiance mapping approach reveals chromatic shifts that conventional spectro-radiometric methods cannot quantify. Ambient-pressure heating experiments confirm accurate temperature retrieval. At high pressure, application of the hyperspectral system to a platinum-heating experiment at 12 GPa demonstrates stable temperature reconstruction under steep thermal gradients. Beyond mitigating chromatic aberrations, the ability to diagnose optical artifacts separately from emissivity variations during controlled test experiments or in situ suggests a path toward more rigorous spectral emissivity analysis and improved modeling of thermal transport in laser-heated DAC experiments.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Quantitative trait locus (QTL) mapping and transcriptome profiling identify QTLs and candidate genes associated with heat stress response during reproductive development in Camelina sativa

Camelina sativa (L.) Crantz is a low-input oilseed crop that has great potential in providing sustainable feedstock for biofuels and bioproducts. Climate change is threatening production of camelina with rising global temperatures. Elucidating the genetic response to high temperatures is essential for successful breeding of heat-tolerant camelina varieties. Here, we report a combinatorial approach to identifying candidate genes associated with heat stress by quantitative trait locus (QTL) mapping and comparative transcriptome profiling. A population of recombinant inbred lines (RILs) was grown in a controlled growth chamber under the high-temperature regimes for 14 days beginning at the onset of the reproductive stage. Several traits related to seed production were evaluated at maturity. The QTL analysis identified several regions with co-located traits on chromosomes 8, 10, and 12. Two RILs with contrasting phenotypic responses to heat stress were chosen for gene expression profiling via RNA sequencing. Multiple pathways and genes were found to be strongly affected by heat stress, and many genes expressed differently between the two RILs. Several genes identified within the QTL regions were considered strong candidates that may control heat tolerance during reproduction in camelina. These studies provide resources for future studies that may assist in improving the heat tolerance of camelina.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Local convection characteristics of inline arrangement of Kagome-shaped unit cells in a square duct

Transient liquid crystal thermography experiments have been conducted to determine detailed convective heat transfer coefficients at the endwalls of lattice-frame configurations based on Kagome-shaped unit cells. Kagome unit cells with porosity of 0.88 were arranged in an inline manner, where two such arrangements were studied. In the first arrangement, a total of ten unit cells were placed next to each other along the streamwise direction resulting in a continuous configuration. In the 2nd arrangement, alternate unit cells from the continuous configuration were dropped, resulting in a discrete configuration which featured a total of 5 Kagome unit cells. Due to the asymmetric nature of the strut connections within the unit cell, the convective heat transfer coefficient maps were determined for the two opposite walls where the struts meet the endwalls. Transient liquid crystal experiments were conducted for Reynolds number ranging between 10,000 and 30,000. Here, the study was focused on the developing nature of flow along the streamwise direction and the local convection characteristics for continuous and discrete arrangement of unit cells. For the continuous configuration, the Nusselt number ratios (N u /Nu 0 ) varied between 3.15–3.46 and 2.75–2.89 for the two walls A and B, respectively. For the discrete configuration, convective heat transfer coefficients varied between 2.56–2.71 and 2.09–2.40 for the two walls. Kagome unit cells have the potential to be fabricated through inexpensive manufacturing routes such as wire-woven method and these unit cells find their applications in the areas which require different heat transfer levels on opposite walls.

Kagome↗

DOE OSTI2024

Electrification Options for Multi-Family Water Heating in Cold Climates - Final Report

In multi-family buildings, large water storage tanks in centralized domestic hot water (DHW) systems can serve as thermal energy storage (TES) batteries to mitigate grid impact. These systems offer demand shift and efficiency benefits, significantly reducing peak power consumption, particularly in cold climates. This study evaluates the load-shifting benefits of a centralized heat pump water heater (HPWH) system equipped with a CO2 heat pump in multi-family buildings through simulation. The heat pump system and water storage tank are sized using design-day sizing. A finite-element-based stratified tank model and CO2 heat pump performance map from a commercial DHW product are used. Annual simulations are conducted to assess the benefits of the centralized DHW system for energy efficiency improvements, load shifting, and emission reductions. These simulations incorporate utility tariffs and marginal grid emission data from Los Angeles and Chicago. In Los Angeles, using a water tank as a thermal battery achieves 7.4% utility cost savings and 10.2% emission reduction. In Chicago, compared to HPWH conventional operation without preheating, TES-enabled central HPWH provides 15% utility cost savings and 13% emission reduction. The case study demonstrates that the demand reduction potential of central CO2 HPWHs is significant in cold climate regions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Geospatial Characterization of Low-Temperature Heating and Cooling Demand in the United States: Preprint

Geothermal resources at temperatures below 150 degrees C have great potential as energy sources for various direct-use applications including heating and cooling in residential and commercial buildings. This study geospatially quantifies U.S. heating and cooling demand in residential, commercial, and manufacturing sectors; heating demand in the agricultural sector; and cooling demand in data centers at the county level through end-use energy consumption, expenditure, and commissioned power analyses. Heating and cooling demand in the residential sector was estimated using energy consumption data obtained from the U.S. Energy Information Administration accounting for different U.S. climate zones. For commercial sector analysis, the end-use major fuel energy intensity at the census division level was disaggregated to the county level with respect to principal building activities. Heating and cooling demand analysis for the manufacturing sector was based on end-use energy consumption for direct-use total process categorized by the North America Industry Classification System. Fuel expenditures in the U.S. Department of Agriculture Farm Production Expenditures were examined for heating demand analysis in the agricultural sector, particularly for the greenhouse, nursery, and floriculture production category. Lastly, commissioned power for data centers in the United States were explored for cooling demand analysis. Results indicated a significant fraction of U.S. primary energy consumption is used for low-temperature heating and cooling applications. Heating and cooling demand in residential and commercial sectors is significantly affected by the number of housing units and climate zone designations, while heating and cooling demand in manufacturing and agricultural sectors and data centers are mainly dependent on the number of facilities and their locations. Maps were generated visualizing where heating and cooling demand is high and, overlain with geothermal resource maps, can indicate locations where geothermal energy can supply this heating and cooling demand.

cooling demand↗

DOE OSTI2023

Geospatial Characterization of Low-Temperature Heating and Cooling Demand in the United States

cooling demand↗