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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

ISD3: a particokinetic model for predicting the combined effects of particle sedimentation, diffusion and dissolution on cellular dosimetry for in vitro systems

The development of particokinetic models describing the delivery of insoluble or poorly soluble nanoparticles to cells in liquid cell culture systems has improved the basis for dose-response analysis, hazard ranking from high-throughput systems, and now allows for translation of exposures across in vitro and in vivo test systems. Complimentary particokinetic models that address processes controlling delivery of both particles and released ions to cells, and the influence of particle size changes from dissolution on particle delivery for cell-culture systems would help advance our understanding of the role of particles ion dosimetry on cellular toxicology. We developed ISD 3 , an extension of our previously published model for insoluble particles, by deriving a specific formulation of the Population Balance Equation for soluble particles. ISD3 describes the time, concentration and particle size dependent dissolution of particles, their delivery to cells, and the delivery and uptake of ions to cells in in vitro liquid test systems. The model is modular, and can be adapted by application of any empirical model of dissolution, alternative approaches to calculating sedimentation rates, and cellular uptake or treatment of boundary conditions. We apply the model to calculate the particle and ion dosimetry of nanosilver and silver ions in vitro after calibration of two empirical models, one for particle dissolution and one for ion uptake. The results demonstrate utility and accuracy of the ISD 3 framework for dosimetry in these systems. Total media ion concentration, particle concentration and total cell-associated silver time-courses were well described by the model, across 2 concentrations of 20 and 110 nm particles. ISD 3 was calibrated to dissolution data for 20 nm particles as a function of serum protein concentration, but successfully described the media and cell dosimetry time-course for both particles at all concentrations and time points. We also report the finding that protein content in media has effects both on the initial rate of dissolution and the resulting near-steady state ion concentration in solution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Measurement of Fission Product Concentration Profiles in AGR-3/4 TRISO Fuel Graphitic Matrix and Nuclear Graphites

The third Advanced Gas Reactor (AGR) irradiation experiment, AGR-3/4, was designed to investigate the migration of fission products in fuel compact graphitic matrix and reactor graphite components. Using destructive methods, radial fission product concentration profiles were measured for gamma-emitting fission products (e.g., Ag-110m, Cs-134, and Eu-154) and beta-emitting Sr-90 in irradiated graphitic and graphite components from six different AGR-3/4 irradiation capsules. These new measured concentration profiles can now be compared to non-destructive measurements and fission product transport simulations and will be used to derive new diffusivities and sorptivities to support refinement of fission product transport models and high-temperature gas-cooled reactor (HTGR) source-term analyses. Each capsule in the AGR-3/4 experiment had four fuel compacts in the middle of two concentric rings of graphitic matrix material, PCEA graphite, or IG-110 graphite. In addition to the approximately 1898 tristructural isotropic (TRISO) coated particles in each compact, there were 20 designed to fail (DTF) particles coated only in pyrocarbon so that they released fission products into the surrounding cylindrical rings of carbonaceous materials. Destructive sampling of the rings involved machining/milling material from around the circumference of the rings, collecting that material, and performing radiochemical analyses on it. Milling operations were performed in multiple steps or segments, and each segment was generally 0.508 mm (0.020 in) thick. Knowing the radial position at which each segment was milled, the volume of the milled material at each segment, and the fission product content in each segment, the radial fission product concentrations were constructed for select isotopes in each ring. Ag-110m profiles had the most variation. Some profiles were peaked at an inner or outer surface. Some were peaked at the middle of the ring wall thickness. Some increased radially outward, and some decreased radially outward. These types of variations and the fact that the measured profiles do not generally compare favorably with the transport model employed for AGR-3/4 may adversely impact the ability to extract reasonable transport parameters for this isotope. In many cases, the Cs-134 profiles decreased somewhat linearly in the outward radial direction, and in cursory comparisons, the shapes of these profiles appeared similar to those from model predictions. The step changes in concentration across the inner-outer ring gap were generally consistent with the model predictions as well. In some cases, there were local maxima in concentration at the outer surface of the rings. This suggests that fission products could have transported in the small gaps between the inner ring and the outer ring and between the outer ring and the sink ring such that some portion of a given fission product can bypass diffusion through the ring itself. The analysis of the small nubs on the outer surfaces of some of the outer rings revealed fission product concentrations in the nubs that were often higher than in the outermost segments of the rings. This further supports the hypothesis that short-circuit, gap transport occurred, causing relatively high surface concentrations on the outer surfaces of the rings. Eu-154 and Sr-90 profiles tend to have very similar shapes, suggesting that they transport via the same mechanisms. The observed profiles were indicative of a transport process where the isotopes are sorbed on the inner surface of the ring, but diffusion into the ring from that surface is quite slow. Some elevated concentrations of Sr-90 (relative to Eu-154) on the outer surface of a ring suggested that rapid, gas-gap transport of gaseous precursor Kr-90 and volatile Rb-90 could have occurred prior to their decaying to Sr-90. Overall, the Eu 154 and Sr-90 profiles were still very similar, which indicates that the transport of short-lived Sr-90 precursors is not a major effect. In some capsules, the qualitative Sr-90 behavior across the ring gaps was consistent with the model (using the available legacy Sr-90 transport parameters), but in other capsules the model was inconsistent with the measurements and seems to underestimate the amount of Sr-90 in the outer rings. The total ring Sr-90 inventories were estimated for all the rings that were subject to physical sampling. These results will be used to adjust the predicted particle and/or compact releases used in the AGR-3/4 fission product transport model. Given the different irradiation temperatures among the capsules and the rings, it was not possible to discern fundamental differences in the transport of isotopes within the different carbon materials, i.e., graphitic matrix, IG-110, or PCEA. It may be possible to do this in the course of determining transport from the concentration profiles in future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Regime-specific Cloud Vertical Overlap Characteristics from Radar and Lidar Observations at the ARM sites

Climate and numerical weather prediction models require assumptions to represent the vertical distribution of subgrid-scale clouds, which have radiative transfer implications. In this study, nearly 25 years of ground-based radar and lidar observations of vertical cloud profiles at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site are utilized to derive cloud vertical overlap characteristics from the Cloud Type (CLDTYPE) data product. Here, the cloud vertical overlap characteristics are further separated by cloud regime by considering seven cloud types (i.e., low cloud, congestus, deep convection, altocumulus, altostratus, cirrostratus, and cirrus) as well as periods of shallow cumulus. The decorrelation length scale (i.e., exponential transition from maximum to random overlap with layer separation) is found to vary by cloud regime, ranging between 0.04 km for cirrostratus paired with cirrus to 4.58 km for low cloud paired with cirrus at SGP. Cloud vertical overlap characteristics are also considered for other ARM sites including the Tropical Western Pacific (TWP), North Slope of Alaska (NSA), and Eastern North Atlantic (ENA) sites amongst other shorter term ARM deployments globally. The decorrelation length scale ranged globally from 1.03 km in the Arctic Ocean to 3.06 km in Manacapuru, Brazil. Globally, the decorrelation length scale by cloud regime exhibited similarities (e.g., for cirrus paired with cirrus) and differences (e.g., congestus paired with cirrus). The results could help inform development of cloud vertical overlap assumptions within operational numerical weather prediction models and potentially improve prediction of radiative fluxes for weather, climate, and renewable energy forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Predicting a Sharp Decline in Selectivity for Catalytic Esterification of Alcohols from van der Waals Interactions

Controlling the selectivity of catalytic reactions is a critical aspect of improving energy efficiency in the chemical industry; thus, predictive models are of key importance. Herein the performance of a heterogeneous, nanoporous Au catalyst is predicted for the complex catalytic self-coupling of the series of C 2 -C 4 alkyl alcohols, based solely on the known kinetics of the elementary steps of the catalytic cycle for methanol coupling, using scaling methods augmented by density functional theory. Notably, a sharp decrease in selectivity for ester formation with increasing molecular weight to favor the aldehyde due to van der Waals interactions of reaction intermediates with the surface was predicted and subsequently verified quantitatively by experiment. Furthermore, the agreement between theory and experiment clearly demonstrates the efficacy of this approach for building a predictive model of catalytic behavior for a homologous set of reactants using a small set of experimental information.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Predicting a Sharp Decline in Selectivity for Catalytic Esterification of Alcohols from van der Waals Interactions

Controlling the selectivity of catalytic reactions is a critical aspect of improving energy efficiency in the chemical industry; thus, predictive models are of key importance. Herein the performance of a heterogeneous, nanoporous Au catalyst is predicted for the complex catalytic self-coupling of the series of C 2 –C 4 alkyl alcohols, based solely on the known kinetics of the elementary steps of the catalytic cycle for methanol coupling, using scaling methods augmented by density functional theory. Notably, a sharp decrease in selectivity for ester formation with increasing molecular weight to favor the aldehyde due to van der Waals interactions of reaction intermediates with the surface was predicted and subsequently verified quantitatively by experiment. Further, the agreement between theory and experiment clearly demonstrates the efficacy of this approach for building a predictive model of catalytic behavior for a homologous set of reactants using a small set of experimental information.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Sootblowing optimization for improved boiler performance

A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

42 ENGINEERING↗
DOE OSTI2013

Sootblowing optimization for improved boiler performance

A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

42 ENGINEERING↗
DOE OSTI2019

Ab initio study of phosphorus effect on vacancy-mediated process in nickel alloys – An insight into Ni 2 Cr ordering

The development of long range order in nickel-chromium alloys is of great technological interest but the kinetics and mechanisms of the transformation are poorly understood. The present research utilizes a combined computational and experimental approach to elucidate the mechanism by which phosphorus accelerates the ordering rate of stoichiometric Ni 2 Cr in Ni-Cr alloys. A series of Ni-33%Cr-x%P samples (in atomic percent) were fabricated with phosphorus concentrations, x = <0.005–0.1 at.% and aged between 373 and 470 °C for times up to 3000 h. The first-principles modeling considers fcc Ni with dilute P as a reasonable approximation for the complex Ni-Cr-P alloy system. Calculation results show a pronounced enhancement of vacancy transport by vacancy-solute pair diffusion via consecutive exchange and rotation jumps of vacancies associated with the phosphorus atom. The energy barriers of these two migration paths are at least 0.35 eV lower than that of vacancy-atom exchange in pure Ni solvent. The analytical diffusion model predicts enhanced solvent diffusion by 2 orders of magnitude for 0.1 at.% P at 400–500 °C. The model prediction is in good agreement with the evolution of micro-hardness. We characterize the micro-hardness result by a kinetic ordering model, showing a significant decrease of the activation energy of ordering transformation. These results help gauge the risk of industrial alloys developing long range order which increases strength but degrades ductility and toughness. Specifically, minor alloying additions that bind with excess vacancies and lower the vacancy migration barrier can greatly accelerate hardening via Ni 2 Cr precipitation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

HydraGNN_OPF_GFM_2026 - Ensemble of predictive graph foundation models for power grid applications

This dataset supports research on graph foundation models for optimal power flow (OPF) on electric grids using HydraGNN. It contains heterogeneous graph representations of PGLib-OPF cases spanning systems from 14 to 13,659 buses, together with packed HDF5 datasets for pretraining, feasibility classification, and N-1 contingency analysis. The release includes OPF solution data, downstream fine-tuning datasets, pretrained HeteroSAGE and HeteroHEAT model checkpoints, hyperparameter-optimization summaries across multiple heterogeneous GNN architectures, and aggregated fine-tuning results for sample-efficiency studies. The dataset is designed to enable scalable training, evaluation, and transfer-learning studies for OPF surrogate modeling, including node-level AC-OPF solution prediction, graph-level prediction, feasibility classification, operating-condition generalization, and contingency-response tasks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Final Report: Development of a Chemical Model to Predict the Interactions between Supercritical CO2, Fluid and Rock in EGS Reservoirs

This report summarizes development of a coupled-process reservoir model for simulating enhanced geothermal systems (EGS) that utilize supercritical carbon dioxide as a working fluid. Specifically, the project team developed an advanced chemical kinetic model for evaluating important processes in EGS reservoirs, such as mineral precipitation and dissolution at elevated temperature and pressure, and for evaluating potential impacts on EGS surface facilities by related chemical processes. We assembled a new database for better-calibrated simulation of water/brine/ rock/CO2 interactions in EGS reservoirs. This database utilizes existing kinetic and other chemical data, and we updated those data to reflect corrections for elevated temperature and pressure conditions of EGS reservoirs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Quantifying Temperature Dependence of Pu(IV) Absorbance Spectra for Advanced Online Monitoring of Nuclear Processes

This article presents a systematic study of Pu(IV) absorbance spectral features as a function of temperature to develop an understanding of this parameter’s effect on chemometric models that can be used as online monitoring tools to support nuclear processing. The descriptive and predictive models that provide real-time feedback of these processes are usually constructed with data collected in conditions typical of a laboratory environment, which can differ drastically from a processing environment. To assess the impact of temperature on Pu(IV) absorbance spectra, 11 samples of Pu(IV) were synthesized with varying HNO 3 concentrations ranging from 0.6 to 9.5 M and heated between 15 and 45 °C. Ultraviolet (UV)–visible (vis)–near-infrared (NIR) absorption spectra collected at different HNO 3 concentrations and temperatures revealed that features associated with Pu(IV) are sensitive to temperature at all HNO 3 concentrations and that changes in features depend on HNO 3 concentration. The contributions of temperature and HNO 3 concentration to variation in Pu(IV) spectral features were evaluated using the principal component analysis of spectra that were baseline-corrected with an asymmetric least-squares method. Furthermore, predictive modeling for HNO 3 concentration with partial least-squares regression of UV–vis–NIR spectra highlighted the importance of accounting for temperature in the calibration set to optimize model performance. This methodology constitutes a new, systematic approach to account for the effect of temperature on the absorption spectra of metal ions and is useful for process monitoring applications in many industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Module Level Exposure and Evaluation Test (MLEET) for Real- world and Laboratory-based PV Modules: Common Data and Analytics for Quantitative Cross-correlation and Validation

Our objective is to develop a set of lifetime performance prediction models for PV modules. Models were developed based on common I-V, P mp datastreams from modules under outdoor (real-world) exposure and indoor (laboratory-based) accelerated exposures and temporal analytics. These common datastreams that span both indoor and outdoor exposures were supplemented with additional information such as meteorology data, climate and PV module make/model and module specifications. The predictive models were developed using a stressor/mechanism/response framework in which all data are categorized as stressor, mechanism or performance variables and are represented as time-series datastreams. We develop and validate these accelerated indoor exposures and evaluation tests and models and cross-correlate the temporal signatures of PV module degradation mechanisms in the I-V, P mp time-series between outdoor and accelerated indoor tests. The predictive test and model specify indoor and outdoor exposure and data acquisition criteria, variable selection, and temporal duration and variance.

14 SOLAR ENERGY↗
DOE OSTI2018

Fixed switching frequency predictive control of an asymmetric source dual inverter system with a floating bridge for multilevel operation

In this study, we propose a modified modulated model predictive control (MMPC) scheme to control an open-end winding induction motor drive using an asymmetric source dual inverter with one floating bridge. The control algorithm uses a modulation algorithm within the cost function optimisation scheme to avoid variable switching frequency. The voltage of the floating capacitor is regulated utilising predefined redundant switching sequences as well as the voltage vector location is identified to improve calculation time. Lastly, the proposed MMPC scheme enhances the output performance with comparison to the model predictive control scheme. Experimental results are presented to verify theory and simulation results.

42 ENGINEERING↗
DOE OSTI2025

A search for dark matter produced in association with a dark Higgs boson decaying into a Higgs boson pair in 3b or 4b final states using pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

A search is performed for dark matter particles produced in association with a resonant pair of Higgs bosons using 140 fb −1 of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. This signature is expected in some extensions of the Standard Model predicting the production of dark matter particles, and is interpreted in terms of a dark Higgs model containing a Z′ mediator in which the dark Higgs boson s decays into a pair of Higgs bosons. The dark Higgs boson is reconstructed through final states with at least three b-tagged jets, produced by the pair of Higgs boson decays, in events with significant missing transverse momentum consistent with the presence of dark matter. The observed data are found to be in good agreement with Standard Model predictions, constraining scenarios with dark Higgs boson masses within the range of 250 to 400 GeV and Z′ mediators up to 2.3 TeV.

Dark Energy and Dark Matter↗
DOE OSTI2017

Fluorescent H{sub 2} Emission Lines from the Reflection Nebula NGC 7023 Observed with IGRINS

We have analyzed the temperature, velocity, and density of H{sub 2} gas in NGC 7023 with a high-resolution near-infrared spectrum of the northwestern filament of the reflection nebula. By observing NGC 7023 in the H and K bands at R ≃ 45,000 with the Immersion GRating INfrared Spectrograph, we detected 68 H{sub 2} emission lines within the 1″ × 15″ slit. The diagnostic ratio of 2-1 S(1)/1-0 S(1) is 0.41−0.56. In addition, the estimated ortho-to-para ratio (OPR) is 1.63−1.82, indicating that the H{sub 2} emission transitions in the observed region arise mostly from gas excited by UV fluorescence. Gradients in the temperature, velocity, and OPR within the observed area imply motion of the photodissociation region (PDR) relative to the molecular cloud. In addition, we derive the column density of H{sub 2} from the observed emission lines and compare these results with PDR models in the literature covering a range of densities and incident UV field intensities. The notable difference between PDR model predictions and the observed data, in high rotational J levels of ν = 1, is that the predicted formation temperature for newly formed H{sub 2} should be lower than that of the model predictions. To investigate the density distribution, we combine pixels in 1″ × 1″ areas and derive the density distribution at the 0.002 pc scale. The derived gradient of density suggests that NGC 7023 has a clumpy structure, including a high clump density of ∼10{sup 5} cm{sup −3} with a size smaller than ∼5 × 10{sup −3} pc embedded in lower-density regions of 10{sup 3}–10{sup 4} cm{sup −3}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗