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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Influence of Land‐Surface Conditions on the 2020–2021 Western US Drought

Abstract In summer 2021, 90% of the western United States (WUS) experienced drought, with over half of the region facing extreme or exceptional conditions, leading to water scarcity, crop loss, ecological degradation, and significant socio‐economic consequences. Beyond the established influence of oceanic forcing and internal atmospheric variability, this study highlights the importance of land‐surface conditions in the development of the 2020–2021 WUS drought, using observational data analysis and novel numerical simulations. Our results demonstrate that the soil moisture state preceding a meteorological drought, due to its intrinsic memory, is a critical factor in the development of soil droughts. Specifically, wet soil conditions can delay the transition from meteorological to soil droughts by several months or even nullify the effects of La Niña‐driven meteorological droughts, while drier conditions can exacerbate these impacts, leading to more severe soil droughts. For the same reason, soil droughts can persist well beyond the end of meteorological droughts. Our numerical experiments suggest a relatively weak soil moisture‐precipitation coupling during this drought period, corroborating the primary contributions of the ocean and atmosphere to this meteorological drought. Additionally, drought‐induced vegetation losses can mitigate soil droughts by reducing evapotranspiration and slowing the depletion of soil moisture. This study highlights the importance of soil moisture and vegetation conditions in seasonal‐to‐interannual drought predictions. Findings from this study have implications for regions like the WUS, which are experiencing anthropogenically‐driven soil aridification and vegetation greening, suggesting that future soil droughts in these areas may develop more rapidly, become more severe, and persist longer.

Jiang, Yelin [Lamont‐Doherty Earth Observatory Col↗
DOE OSTI2026

Dynamic strength of iron under pressure-temperature conditions of Earth’s inner core

Iron (Fe) is a primary constituent of terrestrial planetary cores, yet its rheological properties under extreme conditions remain uncertain. Here we present direct measurements of Fe strength at 310-430 GPa pressures and 3700-5800 K temperatures, obtained using Rayleigh-Taylor (RT) instability experiments at the National Ignition Facility. Single-crystal α-Fe samples with [001] and [111] orientations are shock-ramp compressed past the α-ε transition along paths approaching Earth’s inner core conditions. We find that ε-Fe derived from [001] α-Fe is consistently stronger (11-20 GPa) than that from [111] α-Fe (8-18 GPa), contrary to the trend at ambient conditions. Large-scale molecular dynamics simulations reproduce this atypical strength anisotropy and attribute it to microstructural evolution during the phase transition and subsequent ε-phase plasticity. Ripple growth analysis further constrains viscosities of 100-170 Pa·s under the driven conditions. Our results provide experimental benchmarks for Fe rheology at inner-core conditions, with implications for seismic anisotropy and the geodynamo.

Condensed-matter physics↗
DOE OSTI2024

Physical discovery in representation learning via conditioning on prior knowledge

Recent advances in electron, scanning probe, optical, and chemical imaging and spectroscopy yield bespoke data sets containing the information of structure and functionality of complex systems. In many cases, the resulting data sets are underpinned by low-dimensional simple representations encoding the factors of variability within the data. The representation learning methods seek to discover these factors of variability, ideally further connecting them with relevant physical mechanisms. However, generally, the task of identifying the latent variables corresponding to actual physical mechanisms is extremely complex. Here, we present an empirical study of an approach based on conditioning the data on the known (continuous) physical parameters and systematically compare it with the previously introduced approach based on the invariant variational autoencoders. The conditional variational autoencoder (cVAE) approach does not rely on the existence of the invariant transforms and hence allows for much greater flexibility and applicability. Interestingly, cVAE allows for limited extrapolation outside of the original domain of the conditional variable. However, this extrapolation is limited compared to the cases when true physical mechanisms are known, and the physical factor of variability can be disentangled in full. We further show that introducing the known conditioning results in the simplification of the latent distribution if the conditioning vector is correlated with the factor of variability in the data, thus allowing us to separate relevant physical factors. We initially demonstrate this approach using 1D and 2D examples on a synthetic data set and then extend it to the analysis of experimental data on ferroelectric domain dynamics visualized via piezoresponse force microscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

CFD Simulations of Molten Salts Within Plasma-Facing Components with Twisted Tape Inserts Under One-Sided–Heated Conditions

For liquid immersion blankets (LIBs), the heat removal within different plasma-facing components (PFCs) requires substantial heat removal capabilities that could benefit from the usage of heat transfer enhancements. Of consideration are twisted tape insert heat transfer enhancements that are ribbon-like metal pieces inserted within cooling channels that increase fluid mixing, resulting in higher heat transfer and pressure drop. Unlike traditional applications, PFCs such as divertor coolant tubes experience a significantly higher heat flux on one side versus the other or entirely one-sided heating. These conditions are not well studied for molten salts where the higher Prandtl numbers characteristic of the fluids are significantly higher than water, gases, and liquid metals. As an effort to study this knowledge gap, large eddy simulations were done with Prandtl numbers representative of FLiBe at proposed operating conditions. In this study, the effects of applying a surface heat flux to one side of a tube versus the entire tube with a twisted tape insert were investigated for the heat transfer coefficient and effects on the temperature profile. The findings of the study suggest that for Prandtl number fluids above unity, the Nusselt number was largely unaffected by the change in boundary condition. Both boundary conditions showed good agreement with the Manglik and Bergles Nusselt number correlation for tight-fitting twisted tapes. Finally, the outcomes of this study will be useful for future design studies of LIBs to provide fundamental guidance implementing twisted tape inserts and their performance in one-sided–heated conditions.

molten salts↗
DOE OSTI2024

Evaluation of SPARC divertor conditions in H-mode operation using SOLPS-ITER

The predicted divertor conditions for the SPARC tokamak are calculated using SOLPS-ITER for a range of scrape-off-layer (SOL) heat flux widths λ q , input powers, and particle fueling locations. Under H-mode scenario conditions with an upstream separatrix density of 1 x 10 20 m -3 , the most conservative range of λ q extrapolations ( 0.15 mm) results in extremely high unmitigated particle and energy fluxes to the divertor, both under full field (12.2 T) and power (P SOL = 29 MW) conditions, and 2/3 field with P SOL = 10 MW. Increasing the cross-field SOL diffusivities by 2–10× reduces the magnitude of the mitigation challenge, however strategies such as impurity seeding or strike-point-sweeping will likely still be required. A combination of steady-state and time-dependent SOLPS-ITER simulations are used to map out phase space diagrams of upstream and divertor conditions. The simulations include parallel currents but neglect cross-field drifts. At low upstream density the inner and outer divertor conditions are highly asymmetric, with a large temperature difference and significant heat fluxes driven by parallel currents. The solution has sharp bifurcations with a region of hysteresis, depending on whether the initial state is at a low or high density. This behavior is observed even when the fueling location, cross-field diffusivity, and impurity level is changed, although the density window with asymmetry is reduced with increasing diffusivity. The addition of neon impurity seeding reduces the divertor heat fluxes, but also causes a drop in the upstream electron density with fixed particle throughput. This drop can be counteracted by increased main ion throughput, however too much neon results in a back transition into the asymmetric divertor regimes suggesting a need for control of both main ion and impurity seeding levels to achieve a desired divertor state.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Longitudinal Surveillance for Chronic Health Conditions in Former United States Department of Energy Site Workers

The aim of the study was to determine (1) the rate at which rescreening former Department of Energy site workers identifies noncommunicable chronic diseases and (2) the development of comorbid conditions. Incidence and prevalence of hypertension, diabetes, reduced kidney function, and peripheral neuropathy at both initial and return screenings were calculated. Risk ratio of chronic disease development at return screening based on the presence of other conditions at initial screening were estimated with generalized linear regression. Prevalence of reduced kidney function was 19% at initial examination and 30% at return examination. The screening program was responsible for identifying 81% of reduced kidney function cases. Similar findings were present for the other chronic conditions examined. As a result, former worker health surveillance programs help identify significant health conditions among DOE workers, subcontractors, and visitors. Longitudinal screening of participants detects additional chronic conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Scalar bounded-from-below conditions from Bayesian active learning

We present a procedure leveraging Bayesian deep active learning to rapidly produce highly accurate approximate bounded-from-below conditions for arbitrary renormalizable scalar potentials, in the form of a neural network which may be saved and exported for use in arbitrary parameter space scans. We explore the performance of our procedure on three different scalar potentials with either highly nontrivial or unknown symbolic bounded-from-below conditions (the most general two-Higgs doublet model, the three-Higgs doublet model, and a version of the Georgi-Machacek model without custodial symmetry). We find that we can produce fast and highly accurate binary classifiers for all three potentials. Furthermore, for the potentials for which no known symbolic necessary and sufficient conditions on boundedness-from-below exist, our classifiers substantially outperform some common approximate analytical methods, such as producing tractable sufficient but not necessary conditions or evaluating boundedness-from-below conditions for scenarios in which only a subset of the theory’s fields achieve vacuum expectation values. Our methodology can be readily adapted to any renormalizable scalar field theory. For the community’s use, we have developed a package, BFBrain, which allows for the rapid implementation of our analysis procedure on user-specified scalar potentials with a high degree of customizability. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2025

The Study of Microbial Physiology Under Microoxic Conditions Is Critical but Neglected

ABSTRACT During the early evolution of life on Earth, the environment was largely free of molecular oxygen, and only anaerobic life existed. With the subsequent oxidation of oceans and the atmosphere, a wide range of environmental niches, ranging from anoxic to microoxic/hypoxic and oxic, developed. Despite this broad range of natural environments, microbiology as a field has focused on the physiology, metabolism, and genetics of aerobic microorganisms, with less attention paid to anaerobes and much less attention paid to microaerophiles. The disparity in studies between aerobic and anaerobic conditions is rampant in host‐associated systems, particularly in human health, and studies of microorganisms in intermediate oxygen conditions between fully aerobic and fully anoxic conditions are exceedingly rare. Studies on the physiological behaviour, metabolism, growth response, and drug susceptibility patterns of commensal and pathogenic organisms are almost totally neglected in microoxic conditions. Furthermore, microorganisms from microaerobic and microoxic ecosystems have been less robustly explored in terms of physiology, growth, and metabolism. In this work, we highlight the importance of understanding the physiological and metabolic behaviours of microorganisms under hypoxic or microoxic conditions.

Environmental Sciences & Ecology↗
DOE OSTI2025

Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference

In this work, we present two neural network approaches that approximate the solutions of static and dynamic conditional optimal transport (COT) problems. Both approaches enable conditional sampling and conditional density estimation, which are core tasks in Bayesian inference—particularly in the simulation-based (“likelihood-free”) setting. Our methods represent the target conditional distribution as a transformation of a tractable reference distribution. Obtaining such a transformation, chosen here to be an approximation of the COT map, is computationally challenging even in moderate dimensions. To improve scalability, our numerical algorithms use neural networks to parameterize candidate maps and further exploit the structure of the COT problem. Our static approach approximates the map as the gradient of a partially input convex neural network. It uses a novel numerical implementation to increase computational efficiency compared to state-of-the-art alternatives. Our dynamic approach approximates the conditional optimal transport via the flow map of a regularized neural ODE; compared to the static approach, it is slower to train but offers more modeling choices and can lead to faster sampling. We demonstrate both algorithms numerically, comparing them with competing state-of-the-art approaches, using benchmark datasets and simulation-based Bayesian inverse problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Environmental Conditions Affecting Global Mesoscale Convective System Occurrence

Abstract The ERA5 environments of mesoscale convective systems (MCSs), tracked from satellite observations, are assessed over a 20-yr period. The use of a large set of MCS tracks allows us to robustly test the sensitivity of the results to factors such as region, latitude, and diurnal cycle. We aim to provide novel information on environments of observed MCSs for assessments of global atmospheric models and to improve their ability to simulate MCSs. Statistical analysis of all tracked MCSs is performed in two complementary ways. First, we investigate the environments when an MCS has occurred at different spatial scales before and after MCS formation. Several environmental variables are found to show marked changes before MCS initiation, particularly over land. The vertically integrated moisture flux convergence shows a robust signal across different regions and when considering MCS initiation diurnal cycle. We also found spatial scale dependence of the environments between 200 and 500 km, providing new evidence of a natural length scale for use with MCS parameterization. In the second analysis, the likelihood of MCS occurrence for given environmental conditions is evaluated, by considering all environments and determining the probability of being in an MCS core or shield region. These are compared to analogous non-MCS environments, allowing discrimination between conditions suitable for MCS and non-MCS occurrence. Three environmental variables are found to be useful predictors of MCS occurrence: total column water vapor, midlevel relative humidity, and total column moisture flux convergence. Such relations could be used as trigger conditions for the parameterization of MCSs, thereby strengthening the dependence of the MCS scheme on the environment. Significance Statement Large storm systems called mesoscale convective systems form across Earth. These are collections of thunderstorms, with associated high-level clouds that produce substantial, lighter rainfall and modulate Earth’s energy balance. They produce hazardous weather conditions, such as floods and high winds, and are responsible for a high percentage of rainfall in many regions globally. We investigate the environmental conditions under which they form, so that we can understand the spatial extent of the environment which is important for their formation, and also where and when the effects of these storms might be felt. The novel information generated here should help improve the representation of these storms in weather and climate models, improving the prediction of rainfall, thunderclouds, and high-level clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Progress Towards RF Conditioning of Low-Loss Couplers for a Conduction-Cooled Cryomodule

This work presents current progress on the conditioning of two new 25 kW couplers optimized for use in a compact, conduction-cooled SRF cryomodule. A connecting waveguide, previously used for conditioning the 805 MHz SNS couplers, was altered for use at 915 MHz. The necessary modifications were determined via RF modeling, while thermal analysis results identified additional cooling requirements during RF conditioning and provided insight about potential higher-power operation. Initial low-power conditioning will be performed with a 2.5 kW solid-state amplifier, with plans to use an industrial magnetron for RF conditioning at 25 kW in the near future.

Stilin, N. [Thomas Jefferson National Accelerator ↗
DOE OSTI2025

Theoretical Modeling of Reactor Relevant Conditions for Plasma Jet Driven Magneto-Inertial Fusion

The Charger Advanced Power and Propulsion Laboratory (CAPP), a laboratory within the Propulsion Research Center (PRC) at the University of Alabama in Huntsville (UAH) is working with Los Alamos National Laboratory (LANL). to develop models and inform on promising paths for high gain magneto-inertial fusion (MIF) conditions. This report provides a framework for identifying promising conditions for achieving ignition in plasma-jet-driven magneto-inertial fusion (PJMIF)[1]. As proposed, for the first part of the contract, UAH proposes to develop a gain over unity set of stagnation conditions to provide a state of plasma conditions to achieve to set long terms goals for the PJMIF program. Specifically, UAH will model PJMIF stagnation conditions to include radiation, heat transfer, two temperature energy equations, fusion reactivity and nonlocal fusion product deposition, but no hydrodynamics for these purposes. These calculations will use a stationary plasma model to reduce simulation complexity—focusing on a DT target at 10 keV. Subsequent work will include a DD plasma layer acting as an afterburner. UAH will assume an initial magnetic field without any consideration of the topology, just assume a field strength, most likely scaled with consideration of the local hall parameter. This effort will inform the team on the tradeoff between mass, peak target field, etc and the achievable gain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Testing horizontal momentum boundary conditions in MPAS-Ocean

A rising concern within E3SM’s MPAS-Ocean is the implementation of boundary conditions. Currently, MPAS-Ocean utilizes a no-slip boundary condition, meaning that the velocity of fluid at the boundaries is zero; however, the model should should satisfy both no-slip and free-slip boundary conditions given the correct parameters. This study focuses on testing these boundary conditions in depth, determining the accuracy of the current implementation. To accomplish this, we focus on two test cases: the barotropic gyre and barotropic channel. By manipulating parameters and comparing the numerical to corresponding analytical solutions (when available), we show that MPAS-Ocean’s ability to satisfy both boundary conditions is promising.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

PROGRESS TOWARDS RF CONDITIONING OF LOW-LOSS COUPLERS FOR A CONDUCTION-COOLED CRYOMODULE

This work presents current progress on the conditioning of two new 25 kW couplers optimized for use in a compact, conduction-cooled SRF cryomodule. A connecting waveguide, previously used for conditioning the 805 MHz SNS couplers, was altered for use at 915 MHz. The necessary modifications were determined via RF modeling, while thermal analysis results identified additional cooling requirements during RF conditioning and provided insight about potential higher-power operation. Initial low-power conditioning will be performed with a 2.5 kW solid-state amplifier, with plans to use an industrial magnetron for RF conditioning at 25 kW in the near future.

Wilson, Christiana [Thomas Jefferson National Acce↗
DOE OSTI2024

Inverse prediction of PuO2 processing conditions using Bayesian seemingly unrelated regression with functional data

Over the past decade, a variety of innovative methodologies have been developed to better characterize the relationships between processing conditions and the physical, morphological, and chemical features of special nuclear material (SNM). Different processing conditions generate SNM products with different features, which are known as “signatures” because they are indicative of the processing conditions used to produce the material. These signatures can potentially allow a forensic analyst to determine which processes were used to produce the SNM and make inferences about where the material originated. This article investigates a statistical technique for relating processing conditions to the morphological features of PuO 2 particles. We develop a Bayesian implementation of seemingly unrelated regression (SUR) to inverse-predict unknown PuO 2 processing conditions from known PuO 2 features. Model results from simulated data demonstrate the usefulness of the technique. Applied to empirical data from a bench-scale experiment specifically designed with inverse prediction in mind, our model successfully predicts nitric acid concentration, while results for Pu concentration and precipitation temperature were equivalent to a simple mean model. Our technique compliments other recent methodologies developed for forensic analysis of nuclear material and can be generalized across the field of chemometrics for application to other materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1975

Velocity and extraneous boundary conditions of viscous flow problems

A novel method for treating certain troublesome boundary conditions in the numerical solution of time-dependent incompressible viscous flow problems is presented. This new method is developed on the basis of an integral representation for the velocity vector which contains the entire kinematics of the problem, including the boundary conditions of concern. It is shown that for the exterior flow problem the free-stream condition is satisfied at infinity exactly and the need to treat a far-field condition is removed by the use of the integral representation. The distribution of a nonvelocity variable on the solid boundary - i.e., the 'extraneous' boundary condition needed for both the exterior and the interior flows - is shown to be governed by the kinematics of the problem.

Wu, J. C.↗
NASA NTRS1980

Boundary conditions for the numerical solution of elliptic equations in exterior regions

Elliptic equations in exterior regions frequently require a boundary condition at infinity to ensure the well-posedness of the problem. Examples of practical applications include the Helmholtz equation and Laplace's equation. Computational procedures based on a direct discretization of the elliptic problem require the replacement of the condition on a finite artificial surface. Direct imposition of the condition at infinity along the finite boundary results in large errors. A sequence of boundary conditions is developed which provides increasingly accurate approximations to the problem in the infinite domain. Estimates of the error due to the finite boundary are obtained for several cases. Computations are presented which demonstrate the increased accuracy that can be obtained by the use of the higher order boundary conditions. The examples are based on a finite element formulation but finite difference methods can also be used.

Bayliss, A.↗
NASA NTRS1980

Apparatus for supplying conditioned air at a substantially constant temperature and humidity

The apparatus includes a supply duct coupled to a source of supply air for carrying the supply air therethrough. A return duct is coupled to the supply duct for carrying return conditioned air therethrough. A temperature reducing device is coupled to the supply duct for decreasing the temperature of the supply and return conditioned air. A by-pass duct is coupled to the supply duct for selectively directing portions of the supply and return conditioned air around the temperature reducing device. Another by-pass duct is coupled to the return duct for selectively directing portions of the return conditioned air around the supply duct and the temperature reduction device. Controller devices selectively control the flow and amount of mixing of the supply and return conditioned air.

Obler, H. D.↗