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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Shoulder fillet effects in strength distributions of microelectromechanical system components

The failure forces and fracture strengths of polysilicon microelectromechanical system (MEMS) components in the form of stepped tensile bars with shoulder fillets were measured using a sequential failure chain methodology. Approximately 150 specimens for each of four fillet geometries with different stress concentration factors were tested. The resulting failure force and strength distributions of the four geometries were related by a common sidewall flaw population existing within different effective stressed lengths. The failure forces, strengths, and flaw population were well described by a weakest-link based analytical framework. Finite element analysis was used to verify body-force based expressions for the stress concentration factors and to provide insight into the variation of specimen effective length with fillet geometry. Monte Carlo simulations of flaw size and location, based on the strength measurements, were also used to provide insight into fillet shape and size effects. The successful description of the shoulder fillet specimen strengths provides further empirical support for application of the strength and flaw framework in MEMS fabrication and design optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Home range and resource selection of Virginia opossums in the rural southeastern United States

The Virginia opossum (Didelphis virginiana) has a rapidly expanding distribution in North America, but many aspects of its ecology remain relatively understudied, particularly in rural areas of its core range. We collected GPS telemetry data from 93 opossums in a rural, non-agricultural landscape in South Carolina, USA (2018–2019) to examine factors influencing space use and resource selection. Estimated male home ranges (99% utilization distributions) were on average 50% larger than those of females (mean home range 115.9 ± 103.7 ha vs 76.7 ± 75.0 ha). The home range size decreased on average by 20% with each 20% increase in deciduous land cover but was not affected by season or other landscape factors. Core area sizes (65% utilization distributions) were not influenced by sex (mean core area size 29.1 ± 23.7 ha and 22.4 ha ± 13.8 for males and females, respectively) or season, but the core area size decreased by 14% with each 400 m increase in distance from a permanent water source. Resource selection by opossums primarily occurred at the landscape level. Both males and females generally selected for wetlands while avoiding pine forests and developed/open areas, likely the result of differences in resource availability and predation risk between habitats. Opossums also tended to select for linear features such as unpaved roads and edge habitat, which may facilitate movement across the landscape. Finally, the home ranges we documented are among the largest recorded for opossums in the USA, likely the result of the relatively low resource abundance throughout our study area due to comparatively minimal anthropogenic influence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Q-Cluster: Quantum Error Mitigation Through Noise-Aware Unsupervised Learning

Quantum error mitigation (QEM) is critical in reducing the impact of noise in the pre-fault-tolerant era, and is expected to complement error correction in fault-tolerant quantum computing (FTQC). In this work, we propose a novel QEM approach, Q-Cluster, that uses unsupervised learning (clustering) to reshape the measured bit-string distribution. Our approach starts with a simplified bit-flip noise model. It first performs clustering on noisy measurement results, i.e., bit-strings, based on the Hamming distance. The centroid of each cluster is calculated using a qubit-wise majority vote. Next, the noisy distribution is adjusted with the clustering outcomes and the bitflip error rates using Bayesian inference. Our simulation results show that Q-Cluster can mitigate high noise rates (up to 40% per qubit) with the simple bit-flip noise model. However, real quantum computers do not fit such a simple noise model. To address the problem, we (a) apply Pauli twirling to tailor the complex noise channels to Pauli errors, and (b) employ a machine learning model, ExtraTrees regressor, to estimate an effective bit-flip error rate using a feature vector consisting of machine calibration data (gate & measurement error rates), circuit features (number of qubits, numbers of different types of gates, etc.) and the shape of the noisy distribution (entropy). Our experimental results show that our proposed Q-Cluster scheme improves the fidelity by a factor of 1.46x, on average, compared to the unmitigated output distribution, for a set of low-entropy benchmarks on five different IBM quantum machines. Our approach outperforms the state-of-art QEM approaches RZNE [28], M3 [24], Hammer [35], and QBEEP [33] by 1.26x,1.29x,1.47x, and 2.65 x, respectively.

42 ENGINEERING↗
DOE OSTI2024

Size Up or Size Down? National Analysis of Heat Pump Sizing and Impacts

Electrification of on-site fossil fuel combustion in buildings is recognized as a key component of achieving global greenhouse gas emissions targets. Air-source heat pumps are an efficient approach for space heating electrification. However, a major barrier to heat pump adoption is the high installation cost relative to furnaces and air conditioners. Because the installation cost of heat pumps - especially cold climate models - is dependent on their size, it is important to understand the distribution of heat pump sizes using different sizing methods and factors that impact heat pump sizing. In this study, we use sub-hourly physics simulations of 550,000 statistically representative dwelling units to analyze the distribution of heat pump size in the U.S. for three different efficiency levels of heat pumps, with and without building insulation and air sealing upgrades. We will present results from the national analysis of different factors affecting heat pump sizing along with the impact of sizing decisions on upgrade costs and operating costs.

electrification↗
NASA NTRS2008

Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

Platnick, Steven↗
NASA NTRSDate not supplied

Learjet 25D Jet Noise Flyover Measurements: Comparisons with Scale-Model Data

Continued interest in commercial supersonic flight has highlighted the need for accurate jet-noise predictions as jet noise is expected to be a dominant noise source for aircraft takeoff conditions. The current study compares the acoustic spectra obtained from a scale-model investigation to that from a Learjet 25D flyover test. Reasonable agreement was achieved between the scale-model and flight data in both peak level and frequency when the physical scale factor for the scale-model was increased by roughly 6%. The peak perceived noise levels (PNL) for the flight data were between 1.29 dB and 1.65 dB higher than those for the scale model. The roll-off of PNL with time for large emission angles was greater for the flight data than for the scale-model data. Using a distributed source model for shear-layer-refraction corrections to the scale-model data slightly improved comparisons to flight data at low frequencies for emission angles near 70° and between 110° and 130°. Distributed source models had no impact on the scale-model spectra near the peak jet-noise angle. Applying a stretching factor to the distributed source models to capture the effects of a flight stream had a very limited impact on the computed spectra.

Acoustics↗
DOE OSTI2024

Evidence of short chains in liquid sulfur

High energy x-ray pair distribution function measurements show the average coordination number of the first shell in liquid sulfur is 1.86 ± 0.04 across the λ-transition, not precisely 2.0 as widely accepted. This indicates that upon melting, liquid sulfur does not comprise solely of S 8 rings but also possesses a significant number of short chains. Intensities of the pre-peak and first diffraction peak of the x-ray structure factor and third peak height of the pair distribution function all show deviations at the λ-transition temperature T λ , associated with the break-up of S 8 rings and the start of oligomer polymerization. A significant number of non-bonded or loosely bonded “interstitial atoms,” with an average coordination number of 0.20 ± 0.005, are also observed in the so-called “forbidden zone” between the first and second shells upon melting. The number of interstitial atoms is found to decrease to a minimum at the λ-transition, but the majority persist into the high temperature polymerized liquid. Furthermore, the existence of short chains and nearby interstitial atoms represent the two main factors required to initiate the S 8 -ring to chain transition, as proposed by recent molecular dynamics simulations.

Chemical bonding↗
DOE OSTI2020

Time-resolved in situ visualization of the structural response of zeolites during catalysis

Zeolites form an important class of materials that are widely used in various fields. Their unique properties come primarily from their size, shape, and connectivity of their sub-nm crystalline voids, the Si/Al ratio of the anionic framework, and the number and the nature of charge-balancing cations.The inhomogeneous distribution of the Si/Al ratio within crystals, and hence the cation density, the presence of organic residues, and their inhomogeneous distribution within crystals sensitively affect their performances because these factors influencethe intra-crystalline diffusion rates of the reactants and products. However, the information regarding these inhomogeneities in zeolite crystals cannot be obtained by conventional analytical tools because they only provide information regardingthe average properties of zeolite crystals. Here we employin situX-ray free electron laser-based time-resolved coherent X-ray diffraction imaging to investigate the internal deformations originating from the inhomogeneous Cu ion distributions in Cu-exchanged ZSM-5 zeolite crystals during the deoxygenation of nitrogen oxides with propene. We show that the interactions between the reactants and the active sites lead to an unusual strain distribution,which is confirmed by density functional theory simulations. Moreover, this elucidates the factors responsible for distinct active regions,which are essential to maximizing some applications with enhanced performances. These observations provide insights into the role of structural inhomogeneity in zeolites during a catalytic processand will assist the future design of zeolites for their applications.

36 MATERIALS SCIENCE↗
NASA NTRS1976

The effect of several intact or broken stringers of the stress intensity factor in a cracked sheet

The stringers which are continuously attached to the plate and placed perpendicular to the crack may be partially debonded due to high stress concentrations. Since the stringers may even break under excessive loading conditions, both intact and broken stringers are considered to investigate the effect of rupture. The continuity of displacements along the bond lines leads to an integral equation which is solved to give the shear stress distribution in the adhesive and the stress intensity factors at the crack tips.

Arin, K.↗
NASA NTRS1992

Simulation of space measurements of vegetation canopy bidirectional reflectance factors

A vegetation canopy receives both monodirectional and scattered radiation which is then reflected back into the atmosphere according to its bidirectional reflectance distribution function (BRDF). Remote measurements are typically the angular and spectral distributions of radiations exiting the atmosphere. The evaluation of vegetation canopy bidirectional reflectance factors requires a numerical solution of the canopy radiative transfer equation. A horizontally homogeneous vegetation canopy, of finite physical depth, filled densely with small leaves and bounded by a flat Lambertian ground surface is considered. The canopy is illuminated spatially uniformly by monodirectional radiation. The scattered intensity distribution emerging at the top of the canopy in all directions in the upper hemisphere is evaluated. The magnitude, sign and angular distribution of atmospheric effects are wavelength specific and depend on the composition of the atmosphere. The net atmospheric effect is positive (negative) at the red (near-infrared) wavelength due to strong scattering (absorption) in the atmosphere. The angular distribution of these effects is bowl-shaped. Thus, off-nadir remote observations, especially at shorter wavelengths, are most affected by atmospheric perturbations.

Myneni, R. B.↗
NASA NTRS1984

Opening of an interface flaw in a layered elastic half-plane under compressive loading

A static analysis is given of the problem of an elastic layer perfectly bonded, except for a frictionless interface crack, to a dissimilar elastic half-plane. The free surface of the layer is loaded by a finite pressure distribution directly over the crack. The problem is formulated using the two dimensional linear elasticity equations. Using Fourier transforms, the governing equations are converted to a pair of coupled singular integral equations. The integral equations are reduced to a set of simultaneous algebraic equations by expanding the unknown functions in a series of Jacobi polynomials and then evaluating the singular Cauchy-type integrals. The resulting equations are found to be ill-conditioned and, consequently, are solved in the least-squares sense. Results from the analysis show that, under a normal pressure distribution on the free surface of the layer and depending on the combination of geometric and material parameters, the ends of the crack can open. The resulting stresses at the crack-tips are singular, implying that crack growth is possible. The extent of the opening and the crack-top stress intensity factors depend on the width of the pressure distribution zone, the layer thickness, and the relative material properties of the layer and half-plane.

Kennedy, J. M.↗
DOE OSTI2023

Updating and Evaluating Anthropogenic Emissions for NOAA’s Global Ensemble Forecast Systems for Aerosols (GEFS-Aerosols): Application of an SO 2 Bias-Scaling Method

We updated the anthropogenic emissions inventory in NOAA’s operational Global Ensemble Forecast for Aerosols (GEFS-Aerosols) to improve the model’s prediction of aerosol optical depth (AOD). We used a methodology to quickly update the pivotal global anthropogenic sulfur dioxide (SO 2 ) emissions using a speciated AOD bias-scaling method. The AOD bias-scaling method is based on the latest model predictions compared to NASA’s Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2). The model bias was subsequently applied to the CEDS 2019 SO 2 emissions for adjustment. The monthly mean GEFS-Aerosols AOD predictions were evaluated against a suite of satellite observations (e.g., MISR, VIIRS, and MODIS), ground-based AERONET observations, and the International Cooperative for Aerosol Prediction (ICAP) ensemble results. The results show that transitioning from CEDS 2014 to CEDS 2019 emissions data led to a significant improvement in the operational GEFS-Aerosols model performance, and applying the bias-scaled SO 2 emissions could further improve global AOD distributions. The biases of the simulated AODs against the observed AODs varied with observation type and seasons by a factor of 3~13 and 2~10, respectively. The global AOD distributions showed that the differences in the simulations against ICAP, MISR, VIIRS, and MODIS were the largest in March–May (MAM) and the smallest in December–February (DJF). When evaluating against the ground-truth AERONET data, the bias-scaling methods improved the global seasonal correlation (r), Index of Agreement (IOA), and mean biases, except for the MAM season, when the negative regional biases were exacerbated compared to the positive regional biases. The effect of bias-scaling had the most beneficial impact on model performance in the regions dominated by anthropogenic emissions, such as East Asia. However, it showed less improvement in other areas impacted by the greater relative transport of natural emissions sources, such as India. The accuracies of the reference observation or assimilation data for the adjusted inputs and the model physics for outputs, and the selection of regions with less seasonal emissions of natural aerosols determine the success of the bias-scaling methods. A companion study on emission scaling of anthropogenic absorbing aerosols needs further improved aerosol prediction.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Several intact or broken stringers attached to an orthotropic sheet with a crack

Several intact or broken stringers which are continuously attached to a cracked orthotropic sheet through an adhesive are considered. The effect of orthotropy on the stress intensity factors is investigated. The stringers are assumed to be partially debonded due to high stress concentrations. The shear stress distribution between the stringers and the plate and the stress intensity factors are obtained from an integral equation which represents the continuity of displacements along the bond lines.

Arin, K.↗
DOE OSTI2026

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Effects of threshold resummation for large-x PDF in large momentum effective theory

Parton distribution functions (PDFs) at large x are challenging to extract from experimental data, yet they are essential for understanding hadron structure and searching for new physics beyond the Standard Model. Within the framework of the large momentum P z expansion of lattice quasi-PDFs, we investigate large x PDFs, where the matching coefficient is factorized into the hard kernel, related to the active quark momentum xP z , and the threshold soft function, associated with the spectator momentum (1 − x)P z . The renormalization group equation of the soft function enables the resummation of the threshold double logarithms α k ln 2k (1 − x), which is crucial for a reliable and controllable calculation of large x PDFs. Our analysis with pion valence PDFs indicates that perturbative matching breaks down when the spectator momentum (1 − x)P z approaches Λ QCD , but remains valid when both xP z and (1 − x)P z are much larger than Λ QCD . Additionally, we incorporate leading renormalon resummation within the threshold framework, demonstrating good perturbative convergence in the region where both spectator and active quark momenta are perturbative scales.

factorization↗
DOE OSTI2025

Impact of Grazing Duration and Environment on Soil Carbon in Reclaimed Uranium Mines Tailings: A Region Specific Study

ABSTRACT Grassland ecosystems, which cover over one‐third of the Earth's land area, store 10%–30% of global soil carbon (C). However, these ecosystems face substantial impacts from human activities, including mining. This study investigates the spatial distribution of soil C and related environmental factors in reclaimed grasslands on former uranium mine sites in Wyoming. We hypothesized that grazing duration and environmental factors would influence soil C levels. Interactions between topography, vegetation diversity, soil properties, and soil C in the context of grazing management in both natural and reclaimed grasslands from a wide range of periods from 1 year to 100 years were analyzed using geographically weighted regression models. Data collected from 2022 to 2023 showed that total carbon was consistently higher in natural grasslands (1.2%–4.9%) than in reclaimed grasslands (0.8%–1.3%). Additionally, soil C was significantly higher in natural grasslands grazed for 1 year compared to those grazed for 100 years. In contrast, reclaimed grasslands had lower soil C in areas grazed for 1 year compared to those grazed for 7 or 14 years. The absolute values of coefficients from environmental covariates indicated that areas grazed for a shorter duration (~1 year) were more influenced by biotic and abiotic factors than areas grazed for longer periods (> 7 years). Our findings show moderate grazing increases the resiliency of grassland ecosystems when grazed 7 years or longer and acknowledge the roles of topographic, soil, and vegetative factors in enhancing soil C concentration and developing sustainable land management practices in rangeland conditions.

Shilpakar, Chandan [Department of Plant Sciences U↗
DOE OSTI2022

Two-step neutronics calculations with Shift and Griffin for advanced reactor systems

This research develops the initial coupling of the Shift Monte Carlo (MC) code and the Griffin reactor physics code for reactor analysis of non–light-water reactor systems. The novelty of this work is twofold. It is the first application of Shift to produce the multigroup cross sections needed for Griffin as applied to a non–light-water reactor system; and, the first investigation and analysis of characteristics of the Empire microreactor benchmark that should be considered for steady state and transient reactor physics calculations. This application uses the previously developed two-step neutronics analysis workflow to demonstrate this initial coupling. Here, we outline the two-step neutronics analysis workflow in which the Shift MC code is used to generate the multigroup cross sections and fluxes needed by the Griffin deterministic solver. Details on how these multigroup cross sections are generated using MC tallies are given, as well as the practicalities and limitations of the two-step neutronics workflow. The Empire microreactor benchmark was used to investigate and validate this coupling. Results using this benchmark show good agreement between Griffin calculations using Serpent-generated cross sections and Shift-generated cross sections. Analysis of the characteristics of this Empire benchmark show larger eigenvalue differences between heterogeneous and pin–homogenized solutions compared to those of traditional light-water reactor (LWR) designs, thus requiring super homogenization factor corrections for accurate eigenvalue and power distribution predictions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Typological representation of the offshore oceanographic environment along the Alaskan North Slope

Erosion and flooding impacts to Arctic coastal environments are intensifying with nearshore oceanographic conditions acting as a key environmental driver. Robust and comprehensive assessment of the nearshore oceanographic conditions require knowledge of the following boundary conditions: incident wave energy, water level, incident wind energy, ocean temperature and salinity, bathymetry, and shoreline orientation. The number of offshore oceanographic boundary conditions can be large, requiring a significant computational investment to reproduce nearshore conditions. This present study develops location-independent typologies to reduce the number of boundary conditions needed to assess nearshore oceanographic environments in both a Historical (2007–2019) and Future (2020–2040) timespan along the Alaskan North Slope. We used WAVEWATCH III® and Delft3D Flexible Mesh model output from six oceanographic sites located along a constant ~50 m bathymetric line spanning the Chukchi to Beaufort Seas. K-means clustering was applied to the energy-weighted joint-probability distribution of significant wave height (H s ) and peak period (T p ). Distributions of wave and wind direction, wind speed, and water level associated with location-independent centroids were assigned single values to describe a reduced order, typological rendition of offshore oceanographic conditions. Reanalysis data (e.g., ASRv2, ERA5, and GOFS) grounded the historical simulations while projected conditions were obtained from downscaled GFDL-CM3 forced under RCP8.5 conditions. Location-dependence for each site is established through the occurrence joint-probability distribution in the form of unique scaling factors representing the fraction of time that the typology would occupy over a representative year. As anticipated, these typologies show increasingly energetic ocean conditions in the future. They also enable computationally efficient simulation of the nearshore oceanographic environment along the North Slope of Alaska for better characterization of coastal processes (e.g., erosion, flooding, or sediment transport).

54 ENVIRONMENTAL SCIENCES↗