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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DIRAC current, upcoming and planned capabilities and technologies

DIRAC is the interware for building and operating large scale distributed computing systems. It is adopted by multiple collaborations from various scientific domains for implementing their computing models. DIRAC provides a framework and a rich set of ready-to-use services for Workload, Data and Production Management tasks of small, medium and large scientific communities having different computing requirements. The base functionality can be easily extended by custom components supporting community specific workflows. DIRAC is at the same time an aging project, and a new DiracX project is taking shape for replacing DIRAC in the long term. This contribution will highlight DIRAC’s current, upcoming and planned capabilities and technologies, and how the transition to DiracX will take place. Examples include, but are not limited to, adoption of security tokens and interactions with Identity Provider services, integration of Clouds and High Performance Computers, interface with Rucio, improved monitoring and deployment procedures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Geospatial Capabilities to Couple Hazard and Social Vulnerability Data in Water Distribution Criticality Analysis

A resilience analysis of a water distribution system is greatly enhanced by the integration of up-to-date geospatial data describing the water system, hazards, and surrounding community. The Water Network Tool for Resilience (WNTR), an open-source Python package designed to simulate and analyze the resilience of water distribution systems, was recently updated to incorporate geographic information system (GIS) data into the resilience analysis. This paper describes the GIS capabilities and includes a case study using the drinking water distribution system model for a large city in Pennsylvania. The case study focuses on potential pipe damage from landslides and on pipes that are particularly difficult to repair. The analysis couples data on hazards, social vulnerability, and the location of emergency services to identify and prioritize high-impact critical infrastructure for mitigation. Results demonstrate that pipes can be prioritized for mitigation based on water shortage and vulnerable populations that are affected. In conclusion, the methods can be adopted for general use and are available as part of the WNTR software.

GIS, landslide↗
DOE OSTI2024

What next: Further implosion space exploration on the path to NIF extended yield capability

We present quantitative motivations and assessments of various proposed and ongoing directions to further improving yields and target gain of igniting indirect-drive implosions at the National Ignition Facility (NIF). These include increasing compression and confinement time, improving hohlraum and ablator efficiency, and further increasing peak power and laser energy. 1D hydroscaled simulations, augmented by analytic 1D theory, have been used to project yield improvements for each of these implosion optimization tracks, normalized to the best current performing 4 MJ shot. At current NIF capabilities of 2.2 MJ, 450 TW, we project several paths could reach 15 MJ yield levels. We also expect several key implosion physics questions will be addressed in attempting to reach this yield level. These include demonstrating to what extent lower adiabat designs leading to higher compression will increase gain and efficiency, and whether we can reduce residual kinetic energy and ablator-fuel mix that is probably limiting the current burn-up fraction. For an envisaged NIF upgrade to EL = 3 MJ at fixed 450 TW peak power, scaling capsule size and fuel thicknesses faster than pure hydroscaling should allow for yields that could reach up to 60–80 MJ, depending on the efficiency gains realized in increasing deuterium-tritium fuel thickness, reducing hohlraum losses, and switching to lower Z ablators. The laser-plasma instability and beam transmission scaling in these larger hohlraums is shown to be favorable if the spot size is increased with hohlraum scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Introducing new resonant soft x-ray scattering capability in SSRL

Resonant soft x-ray scattering (RSXS) is a powerful technique for probing both spatial and electronic structures within solid-state systems. Here, we present a newly developed RSXS capability at beamline 13-3 of the Stanford Synchrotron Radiation Lightsource, designed to enhance materials science research. This advanced setup achieves a base sample temperature as low as 9.8 K combined with extensive angular motions (azimuthal ϕ and flipping χ), enabling comprehensive exploration of reciprocal space. Two types of detectors—an Au/GaAsP Schottky photodiode and a charge-coupled device detector with over 95% quantum efficiency—are integrated to effectively capture scattered photons. Extensive testing has confirmed the enhanced functionality of this RSXS setup, including its temperature and angular performance. The versatility and effectiveness of the system have been demonstrated through studies of various materials, including superlattice heterostructures and high-temperature superconductors.

Kuo, Cheng-Tai [SLAC National Accelerator Laborato↗
DOE OSTI2025

Accelerated Irradiation Testing and Post-Irradiation Characterization: U.S.-Based Capabilities for Advanced Nuclear Systems and Radioisotope Production

Irradiation experiments and post-irradiation examinations, together referred to as irradiation testing (IRT), are prerequisites for nuclear fuel and material qualification for the deployment of new and advanced reactors, as well as radioisotope production, thereby ensuring regulatory compliance. Qualified research and test reactors (RTRs) and testing facilities are essential to enable IRT to verify performance and safety under prototypical reactor conditions. In the past, qualification of new fuels or structural materials required about 20 years. Synergist strategies, advanced tools, and qualified methods are needed to greatly reduce this timeframe of IRT and radioisotope production. This study, termed accelerated-IRT, focuses on identifying gaps and leveraging U.S.-based RTRs and material testing capabilities, leveraging the preliminary evaluation and qualification of selected RTRs to provide a generic as well as specific-case solution paths forward, ensuring adherence to stringent regulatory standards. Furthermore, IRT and radioisotope production utilizing qualified RTRs necessarily includes modeling and simulation to support the design (i.e. neutronics, thermal, and structural aspects) and manufacturing of irradiation test specimens, vehicles, capsules, apparatuses, and flow loops. In addition, IRT can be improved by applying advanced manufacturing techniques and in-pile sensors and instrumentation, as discussed in this study.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches

Abstract A real-time capable core Ion Cyclotron Range of Frequencies (ICRF) heating model on NSTX and WEST is developed. The model is based on two nonlinear regression algorithms, the random forest ensemble of decision trees and the multilayer perceptron neural network. The algorithms are trained on TORIC ICRF spectrum solver simulations of the expected flat-top operation scenarios in NSTX and WEST assuming Maxwellian plasmas. The surrogate models are shown to successfully capture the multi-species core ICRF power absorption predicted by the original model for the high harmonic fast wave and the ion cyclotron minority heating schemes while reducing the computational time by six orders of magnitude. Although these models can be expanded, the achieved regression scoring, computational efficiency and increased model robustness suggest these strategies can be implemented into integrated modeling frameworks for real-time control applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

On Building Predictive Digital Twin Incorporating Wave Predicting Capabilities: Case Study on UMaine Experimental Campaign - FOCAL

The response of floating wind turbines (FWT) are susceptible to stochastic wave variations. For the optimal operation of FWT, a comprehensive understanding of the phaseresolved wave dynamics and the consequential system response is crucial for real-time monitoring and control. A multi-variate, multi-step, long short term memory (MLSTM), a type of recurrent neural network (RNN) is used to capture complex system dynamics for real-time application. Results indicate that the integration of a wave prediction-reconstruction (WRP) model substantially enhances prediction accuracy by 50% on average relative to the baseline model. The improvement is consistent across various wave extremity and prediction horizons, thereby significantly broadening the scope for timely and precise predictive capabilities.

17 WIND ENERGY↗
DOE OSTI2024

A comparison of the neutron detection efficiency and response characteristics of two pixelated PSD-capable organic scintillator detectors with different photo-detection readout methods

Here, we characterize the performance of two pixelated neutron detectors: a PMT-based array that utilizes Anger logic for pixel identification and a SiPM-based array that employs individual pixel readout. The SiPM-based array offers improved performance over the previously developed PMT-based detector both in terms of uniformity and neutron detection efficiency. Each detector array uses PSD-capable plastic scintillator as a detection medium. We describe the calibration and neutron efficiency measurement of both detectors using a 137 Cs source for energy calibration and a 252 Cf source for calibration of the neutron response. We find that the intrinsic neutron detection efficiency of the SiPM-based array is (30.2 ± 0.9)%, which is almost twice that of the PMT-based array, which we measure to be (16.9 ± 0.1)%.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Genomics and physiology of Catenibacillus, human gut bacteria capable of polyphenol C-deglycosylation and flavonoid degradation

The genusCatenibacillus(familyLachnospiraceae, phylumBacillota) includes only one cultivated species so far,Catenibacillus scindens,isolated from human faeces and capable of deglycosylating dietary polyphenols and degrading flavonoid aglycones. Another human intestinalCatenibacillusstrain not taxonomically resolved at that time was recently genome-sequenced. We analysed the genome of this novel isolate, designatedCatenibacillus decagia, and showed its ability to deglycosylateC-coupled flavone and xanthone glucosides andO-coupled flavonoid glycosides. Most of the resulting aglycones were further degraded to the corresponding phenolic acids. Including the recently sequenced genome ofC. scindensand ten faecal metagenome-assembled genomes assigned to the genusCatenibacillus, we performed a comparative genome analysis and searched for genes encoding potentialC-glycosidases and other polyphenol-converting enzymes. According to genome data and physiological characterization, the core metabolism ofCatenibacillusstrains is based on a fermentative lifestyle with butyrate production and hydrogen evolution. BothC. scindensandC. decagiaencode a flavonoidO-glycosidase, a flavone reductase, a flavanone/flavanonol-cleaving reductase and a phloretin hydrolase. Several gene clusters encode enzymes similar to those of the flavonoidC-deglycosylation system ofDoreastrain PUE (DgpBC), while separately located genes encode putative polyphenol-glucoside oxidases (DgpA) required forC-deglycosylation. The diversity ofdgpAanddgpBCgene clusters might explain the broadC-glycoside substrate spectrum ofC. scindensandC. decagia. The otherCatenibacillusgenomes encode only a few potential flavonoid-converting enzymes. Our results indicate that severalCatenibacillusspecies are well-equipped to deglycosylate and degrade dietary plant polyphenols and might inhabit a corresponding, specific niche in the gut.

Genetics & Heredity↗
DOE OSTI2025

Design of the EIC hadron storage ring stripline injection kicker with a novel impedance tuning capability

The Electron-Ion Collider (EIC), to be built at Brookhaven National Laboratory, will be a high luminosity (~10 34 cm –2 s –1 ) nuclear science facility. To facilitate EIC experiments, the existing yellow ring of the Relativistic Heavy Ion Collider (RHIC) will be reconfigured to serve as the Hadron Storage Ring (HSR). Designing a stripline injection kicker for the HSR beams, with high magnetic rigidity (~ 82 Tm), poses some technical challenges due to the required large pulsed voltage with long flattop duration, very fast rise time, expected shorter bunch spacing, and potential heating due to higher peak current. In addition, minimizing impedance mismatch in the transition region between the feedthrough and the stripline electrode is challenging. This paper focuses on the mechanical design and optimization of the HSR injection kicker, highlighting a novel impedance tuning capability achieved through an innovative kicker aperture adjustment mechanism. We comprehensively cover the design, including impedance optimization (both beam coupling and characteristic), beam-induced heating, and thermal analysis, and investigation of the maximum electric field due to high voltage signal excitation to ensure safe and reliable operation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Demonstration of new MeV-scale capabilities in large neutrino LArTPCs using ambient radiogenic and cosmogenic activity in MicroBooNE

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing and interpreting MeV-scale energy depositions, or blips, present in their data. We demonstrate new calorimetric and particle discrimination capabilities at the MeV energy scale using reconstructed blips in data from the MicroBooNE LArTPC at Fermilab. We observe a concentration of low-energy (<3 MeV) blips around fiberglass mechanical support struts along the time projection chamber edges with energy spectrum features consistent with the Compton edge of 2.614 MeV 208 Tl decay 𝛾 rays. These features are used to verify proper calibration of electron energy scales in MicroBooNE’s data to few percent precision and to measure the specific activity of 208 Tl in the fiberglass composing these struts, (11.7 ± 0.2⁢(stat) ± 3.1⁢(syst)) Bq/kg. Cosmogenically produced blips above 3 MeV in reconstructed energy are used to showcase the ability of large LArTPCs to distinguish between low-energy proton and electron energy depositions. An enriched sample of low-energy protons selected using this new particle discrimination technique is found to be smaller in data than in dedicated corsika cosmic-ray simulations, suggesting either incorrect corsika modeling of incident cosmic fluxes or particle transport modeling issues in geant4.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A new HVdc Substation Architecture with Higher Power Transfer Capability

The power transferred through high voltage direct current transmission (HVdc) systems is increasing with increased resilience and reliability needs as well as large scale deployment of renewable energy systems. In this paper, a new HVdc substation (SS) architecture with higher power transfer capability is proposed. The HVdc converters or valve groups (VG) are connected in series and parallel fashion such that the total power rating of the SS is increased. The control challenges associated with such SS architecture are identified and appropriate control modifications are proposed. The same is verified through PSCAD based simulations.

Jaldanki, Sreenivasa↗
DOE OSTI2025

Exploring Capability of Multimodal Foundation Model for Image-based Fault Detection of Photovoltaic Modules

Multimodal Foundation Model (MFM), like ChatGPT and Gemini, have emerged as powerful tools for their exceptional natural language processing capabilities and their emerging potential in image analysis. This paper investigates the application of MFMs for photovoltaic (PV) fault detection through image analysis, focusing on ChatGPT 4.0 and Gemini 1.5 Pro. Three types of PV images and the corresponding common PV faults are detected: bird droppings using visible images, cell cracks via electroluminescence (EL) images, and hotspots using infrared (IR) images. Among the two models, Gemini 1.5 Pro demonstrated superior performance, achieving near-perfect results with an average F1 score of 0.97, consistently outperforming ChatGPT 4.0 in accuracy and reliability. Unlike traditional machine learning (ML) models, MFMs can operate in a zero shot manner that does not require additional training by the user, and the input images are not limited by size, angle, scope, or PV technology. The strong adaptability and user-friendliness make MFM a promising tool for analyzing PV images and advancing health monitoring for PV modules.

Li, Baojie↗
DOE OSTI2025

Machine learning-driven design and self-sensing capabilities of automotive bumper lattices for adaptive impact response

We present a novel approach to design an automotive bumper energy absorber using carbon fiber reinforced polymer composites, optimized to meet conflicting performance requirements for two distinct impact scenarios. The design must satisfy both a low-speed (2.5 mph) pendulum intrusion test, simulating vehicle-to-vehicle collisions, and a high-speed (25 mph) leg flexion test, replicating pedestrian impacts. These tests demand opposing deformation characteristics: high flexibility (deformation < 85 mm) for the former and high stiffness (deformation < 22 mm) for the latter. To address these contradictory requirements, we developed a machine learning (ML) framework for inverse optimization of lattice designs and material selection. Unlike traditional iterative design processes, our ML model directly outputs optimal design parameters and material choices based on target performance inputs. The energy absorber was fabricated using advanced additive manufacturing techniques, including extrusion deposition and digital light processing. The integration of carbon fibers provides multifunctionality to the bumper structure, enabling self-sensing capabilities through changes in electrical resistivity under compression. This electrical response demonstrates high repeatability under multiple cycles at 2% compression and exhibits distinct signatures during crack formation under high deformation. This research offers adaptive performance through innovative design methodologies and smart material integration. The approach has potential applications in various fields requiring adaptive energy absorption and real-time structural health monitoring.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗
DOE OSTI2024

Expanded genome and proteome reallocation in a novel, robust Bacillus coagulans strain capable of utilizing pentose and hexose sugars

Bacillus coagulans, a Gram-positive thermophilic bacterium, is recognized for its probiotic properties and recent development as a microbial cell factory. Despite its importance for biotechnological applications, the current understanding of B. coagulans’ robustness is limited, especially for undomesticated strains. To fill this knowledge gap, we characterized the metabolic capability and performed functional genomics and systems analysis of a novel, robust strain, B. coagulans B-768. Genome sequencing revealed that B-768 has the largest B. coagulans genome known to date (3.94 Mbp), about 0.63 Mbp larger than the average genome of sequenced B. coagulans strains, with expanded carbohydrate metabolism and mobilome. Functional genomics identified a well-equipped genetic portfolio for utilizing a wide range of C5 (xylose, arabinose), C6 (glucose, mannose, galactose), and C12 (cellobiose) sugars present in biomass hydrolysates, which was validated experimentally. For growth on individual xylose and glucose, the dominant sugars in biomass hydrolysates, B-768 exhibited distinct phenotypes and proteome profiles. Faster growth and glucose uptake rates resulted in lactate overflow metabolism, which makes B. coagulans a lactate overproducer; however, slower growth and xylose uptake diminished overflow metabolism due to the high energy demand for sugar assimilation. Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) made up 60%–65% of the measured proteomes but were allocated differently when growing on xylose and glucose. The trade-off in proteome reallocation, with high investment in COG-C over COG-G, explains the xylose growth phenotype with significant upregulation of xylose metabolism, pyruvate metabolism, and tricarboxylic acid (TCA) cycle. Strain B-768 tolerates and effectively utilizes inhibitory biomass hydrolysates containing mixed sugars and exhibits hierarchical sugar utilization with glucose as the preferential substrate.

carbohydrate metabolism↗
DOE OSTI2026

New Time Integrators and Capabilities in SUNDIALS Versions 6.2.0-7.4.0

SUNDIALS is a well-established numerical library that provides robust and efficient time integrators and nonlinear solvers. This article overviews several significant improvements and new features added over the last 3 years to support scientific simulations run on high-performance computing systems. Notably, three new classes of one-step methods have been implemented: low storage Runge–Kutta, symplectic partitioned Runge–Kutta, and operator splitting. In addition, we describe new timestep adaptivity support for multirate methods, adjoint sensitivity analysis capabilities for explicit Runge–Kutta methods, additional options for Anderson acceleration in nonlinear solvers, and improved error handling and logging.

Computer science↗
DOE OSTI2024

Bridging New Observational Capabilities and Process-Level Simulation: Insights into Aerosol Roles in the Earth System

The spatial distribution of ambient aerosol particles significantly impacts aerosol–radiation–cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation–modeling integration, enabling an examination of how various assumptions about the organic–inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS–model–laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol–radiation–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Bacteria isolated from the grape phyllosphere capable of degrading guaiacol, a main volatile phenol associated with smoke taint in wine

Recent wildfires near vineyards in the Pacific United States have caused devastating financial losses due to smoke taint in wine. When wine grapes (Vitis vinifera) are exposed to wildfire smoke, their berries absorb volatile phenols derived from the lignin of burning plant material. Volatile phenols are released during the winemaking process giving the finished wine an unpleasant, smokey, and ashy taste known as smoke taint. Bacteria are capable of undergoing a wide variety of metabolic processes and therefore present great potential for bioremediation applications in many industries. In this study, we identify two strains of the same species that colonize the grape phyllosphere and are able to degrade guaiacol, a main volatile phenol responsible for smoke taint in wine. We identify the suite of genes that enable guaiacol degradation in Gordonia alkanivorans via RNAseq of cells growing on guaiacol as a sole carbon source. Additionally, we knockout guaA, a cytochrome P450 gene involved in the conversion of guaiacol to catechol; ΔguaA cells cannot catabolize guaiacol in vitro, providing evidence that GuaA is necessary for this process. Furthermore, we analyze the microbiome of berries and leaves exposed to smoke in the vineyard to investigate the impact of smoke on the grape microbial community. We found smoke has a significant but small effect on the microbial community, leading to an enrichment of several genera belonging to the Bacilli class. Collectively, this research shows that studying microbes and their enzymes has the potential to identify novel tools for alleviating smoke taint.

Castro, Claudia [United States Department of Agric↗