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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Forward sensitivity approach for estimating eddy viscosity closures in nonlinear model reduction

In this paper, we propose a variational approach to estimate eddy viscosity using forward sensitivity method (FSM) for closure modeling in nonlinear reduced order models. FSM is a data assimilation technique that blends model's predictions with noisy observations to correct initial state and/or model parameters. We apply this approach on a projection based reduced order model (ROM) of the one-dimensional viscous Burgers equation with a square wave defining a moving shock, and the two-dimensional vorticity transport equation formulating a decay of Kraichnan turbulence. We investigate the capability of the approach to approximate an optimal value for eddy viscosity with different measurement configurations. Specifically, we show that our approach can sufficiently assimilate information either through full field or sparse noisy measurements to estimate eddy viscosity closure to cure standard Galerkin reduced order model (GROM) predictions. Therefore, our approach provides a modular framework to correct forecasting error from a sparse observational network on a latent space. We highlight that the proposed GROM-FSM framework is promising for emerging digital twin applications, where real-time sensor measurements can be used to update and optimize surrogate model's parameters.

42 ENGINEERING↗
DOE OSTI2022

A phase transition for finding needles in nonlinear haystacks with LASSO artificial neural networks

To fit sparse linear associations, a LASSO sparsity inducing penalty with a single hyperparameter provably allows to recover the important features (needles) with high probability in certain regimes even if the sample size is smaller than the dimension of the input vector (haystack). More recently learners known as artificial neural networks (ANN) have shown great successes in many machine learning tasks, in particular fitting nonlinear associations. Small learning rate, stochastic gradient descent algorithm and large training set help to cope with the explosion in the number of parameters present in deep neural networks. Yet few ANN learners have been developed and studied to find needles in nonlinear haystacks. Driven by a single hyperparameter, our ANN learner, like for sparse linear associations, exhibits a phase transition in the probability of retrieving the needles, which we do not observe with other ANN learners. To select our penalty parameter, we generalize the universal threshold of Donoho and Johnstone (Biometrika 81(3):425–455, 1994) which is a better rule than the conservative (too many false detections) and expensive cross-validation. In the spirit of simulated annealing, we propose a warm-start sparsity inducing algorithm to solve the high-dimensional, non-convex and non-differentiable optimization problem. We perform simulated and real data Monte Carlo experiments to quantify the effectiveness of our approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

TOI-908: a planet at the edge of the Neptune desert transiting a G-type star

ABSTRACT We present the discovery of an exoplanet transiting TOI-908 (TIC-350153977) using data from TESS sectors 1, 12, 13, 27, 28, and 39. TOI-908 is a T = 10.7 mag G-dwarf (Teff = 5626 ± 61 K) solar-like star with a mass of 0.950 ± 0.010 M⊙ and a radius of 1.028 ± 0.030 R⊙. The planet, TOI-908 b, is a 3.18 ± 0.16 R⊕ planet in a 3.18 d orbit. Radial velocity measurements from HARPS reveal TOI-908 b has a mass of approximately 16.1 ± 4.1 M⊕, resulting in a bulk planetary density of $2.7^{+0.2}_{-0.4}$ g cm−3. TOI-908 b lies in a sparsely populated region of parameter space known as the Neptune desert. The planet likely began its life as a sub-Saturn planet before it experienced significant photoevaporation due to X-rays and extreme ultraviolet radiation from its host star, and is likely to continue evaporating, losing a significant fraction of its residual envelope mass.

Hawthorn, Faith (ORCID:000000028675182X)↗
DOE OSTI2026

AmeriFlux FLUXNET-1F CA-LU2 Lutose

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-LU2 Lutose. This is the FLUXNET version of the carbon flux data for the site CA-LU2 Lutose produced by applying the standard ONEFlux (1F) software. Site Description - Lutose is a peat plateau that burned from a moderate forest fire in June 2007. Prior to the fire the site was likley an open canopy of stunted black spruce and a ground layer of Labrador tea shurbs and lichen or sphagnum. No black spruce survived the fire and lichens were still completely absent during this study. By 2019, most charred tree boles has fallen over and vegetation recovery was dominated by dense Labrador tea shrubs and sparse regenerating black spruce with around >150cm of peat.

Schulze, Christopher [University of Alberta]↗
DOE OSTI2025

Novel CHI3L1 ‐Associated Angiogenic Phenotypes Define Glioma Microenvironments: Insights From Multi‐Omics Integration

ABSTRACT The CHI3L1 signaling pathway significantly influences glioma angiogenesis, but its role in the tumor microenvironment (TME) remains elusive. We propose a novelCHI3L1‐associated vascular phenotype classification for glioma through integrative analyses of multiple datasets with bulk and single‐cell transcriptome, genomics, digital pathology, and clinical data. We investigated the biological characteristics, genomic alterations, therapeutic vulnerabilities, and immune profiles within these phenotypes through a comprehensive multi‐omics approach. We constructed the vascular‐related risk (VR) score based onCHI3L1‐associated vascular signatures (CAVS) identified by machine learning algorithms. Utilizing unsupervised consensus clustering, gliomas were stratified into three distinct vascular phenotypes: Cluster A, marked by high vascularization and stromal activation with a relatively low levels of tumor‐infiltrating lymphocytes (TILs); Cluster B, characterized by moderate vascularization and stromal activity, coupled with a high density of TILs; and Cluster C, defined by low vascularization and sparse immune cell infiltration. We observed that the CAVS effectively indicated glioma‐associated angiogenesis and immune suppression by single‐cell RNA‐seq analysis. Moreover, the high‐VR‐score group exhibited enhanced angiogenic activity, reduced immune response, resistance to immunotherapy, and poorer clinical outcomes. The VR score independently predicted glioma prognosis and, combined with a nomogram, provided a robust clinical decision‐making tool. Potential drug prediction based on transcription factors for high‐risk patients was also performed. Our study reveals thatCHI3L1‐associated vascular phenotypes shape distinct immune landscapes in gliomas, offering insights for optimizing therapeutic strategies to improve patient outcomes.

Oncology↗
DOE OSTI2022

Scaled Vecchia Approximation for Fast Computer-Model Emulation

Many scientific phenomena are studied using computer experiments consisting of multiple runs of a computer model while varying the input settings. Gaussian processes (GPs) are a popular tool for the analysis of computer experiments, enabling interpolation between input settings, but direct GP inference is computationally infeasible for large datasets. We adapt and extend a powerful class of GP methods from spatial statistics to enable the scalable analysis and emulation of large computer experiments. Specifically, we apply Vecchia’s ordered conditional approximation in a transformed input space, with each input scaled according to how strongly it relates to the computer-model response. The scaling is learned from the data by estimating parameters in the GP covariance function using Fisher scoring. Our methods are highly scalable, enabling estimation, joint prediction, and simulation in near-linear time in the number of model runs. In several numerical examples, our approach substantially outperformed existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Validation of Fault Displacements from Dynamic Rupture Simulations against the Observations from the 1992 Landers Earthquake

ABSTRACT Coseismic fault displacements in large earthquakes have caused significant damage to structures and lifelines on and near fault lines. Coseismic displacements represent a real threat, especially to distributed infrastructure systems. For infrastructure systems that can not avoid active faults, engineering displacement demands are defined using probabilistic fault-displacement hazard analyses (PFDHA). However, PFDHA models are sparse and poorly constrained partly due to the scarcity of detailed fault-displacement observations. Advancements in dynamic rupture simulation methods make them an attractive approach to address this important issue. Because fault displacements can be simulated for various geologic conditions as constrained by current knowledge about earthquake processes, they can be used to supplement the observation datasets. In addition to providing on-fault displacements, when used with appropriate constitutive models for the bulk medium, they can capture off-fault distributed inelastic deformations as well. For viable extrapolation, simulations must first be validated against data. In this article, we summarize the calibration and validation of the dynamic rupture model against the observations of the well-documented 1992 Landers earthquake. We defined a preferred model that reproduces several first-order fault-displacement metrics such as the on-fault partition of the total displacement, the mean fault-zone width, and the location of the peak displacement. Simulated ground motions consistent with the observations ensure that all physics important to modeling have been properly parameterized. For the extrapolation, we generated a suite of dynamic rupture models to quantify expected fault-displacement metrics, their intercorrelations, and magnitude dependencies, which are in part supported by the Landers and other recent earthquakes. Our validation and extrapolation exercise paves the way for using dynamic rupture modeling to quantitatively address fault-displacement hazard on a broader scale. The results are promising and are expected to be useful to inform PFDHA model development.

Geochemistry & Geophysics↗
DOE OSTI2022

Year-round trace gas measurements in the central Arctic during the MOSAiC expedition

Despite the key role of the Arctic in the global Earth system, year-round in-situ atmospheric composition observations within the Arctic are sparse and mostly rely on measurements at ground-based coastal stations. Measurements of a suite of in-situ trace gases were performed in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. These observations give a comprehensive picture of year-round near-surface atmospheric abundances of key greenhouse and trace gases, i.e., carbon dioxide, methane, nitrous oxide, ozone, carbon monoxide, dimethylsulfide, sulfur dioxide, elemental mercury, and selected volatile organic compounds (VOCs). Redundancy in certain measurements supported continuity and permitted cross-evaluation and validation of the data. This paper gives an overview of the trace gas measurements conducted during MOSAiC and highlights the high quality of the monitoring activities. In addition, in the case of redundant measurements, merged datasets are provided and recommended for further use by the scientific community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Atomic structures determined from digitally defined nanocrystalline regions

Nanocrystallography has transformed our ability to interrogate the atomic structures of proteins, peptides, organic molecules and materials. By probing atomic level details in ordered sub-10 nm regions of nanocrystals, scanning nanobeam electron diffraction extends the reach of nanocrystallography and in principle obviates the need for diffraction from large portions of one or more crystals. Scanning nanobeam electron diffraction is now applied to determine atomic structures from digitally defined regions of beam-sensitive peptide nanocrystals. Using a direct electron detector, thousands of sparse diffraction patterns over multiple orientations of a given crystal are recorded. Each pattern is assigned to a specific location on a single nanocrystal with axial, lateral and angular coordinates. This approach yields a collection of patterns that represent a tilt series across an angular wedge of reciprocal space: a scanning nanobeam diffraction tomogram. Using this diffraction tomogram, intensities can be digitally extracted from any desired region of a scan in real or diffraction space, exclusive of all other scanned points. Intensities from multiple regions of a crystal or from multiple crystals can be merged to increase data completeness and mitigate missing wedges. It is demonstrated that merged intensities from digitally defined regions of two crystals of a segment from the OsPYL/RCAR5 protein produce fragment-based ab initio solutions that can be refined to atomic resolution, analogous to structures determined by selected-area electron diffraction. In allowing atomic structures to now be determined from digitally outlined regions of a nanocrystal, scanning nanobeam diffraction tomography breaks new ground in nanocrystallography.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data-Driven Surrogate Modeling with Microstructure-Sensitivity of Viscoplastic Creep in Grade 91 Steel

Abstract To support the development of advanced steel alloys tailored to withstand extreme conditions, it is imperative to account for the mechanical performance of components, while considering the influence of local microstructure on the macroscopic response. To this end, this study focuses on the development of microstructure-sensitive constitutive models for the mechanical response of Grade 91 steel exposed to extreme thermo-mechanical environments. Polynomial chaos expansion (PCE) surrogates are used to emulate high-fidelity polycrystal simulations of the viscoplastic response of Grade 91 steel as a function of the microstructure fingerprint (e.g., dislocations and precipitates). To cover a wide temperature–stress domain, two separate PCE surrogates—one that captures softening and the other that captures hardening behavior—are combined using another (sparse) Gaussian process regression model. The resulting constitutive creep surrogate model is integrated within the MOOSE finite element framework to simulate the intricate effects of microstructure, in particular MX-phase precipitates, on a component with a graded microstructure. Surrogate sensitivity analysis is applied to quantify the relevant impact of spatially varying microstructure on the creep response in a test-case involving a Grade 91 alloy with a prototypical weld.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Modeling the Impacts of Material Properties on Oscillatory Neuron Behavior

In this study, neuromorphic computing, which mimics the functions of biological brains, offers improvements in both latency and energy efficiency over typical von Neumann computing architectures. Spiking neural networks can be especially power-efficient because they encode information temporally and can use more sparse electrical inputs. Here, we study the design of volatile memristors (variable resistors with memory) for neuronal devices, with particular consideration toward the feasibility of all-on-chip oscillation using built-in capacitance. We use circuit simulations to model the behavior of oscillator neurons with a range of realistic material properties. We find that energy inputs increase with insulating-phase resistivity, thermal conductivity, and device aspect ratio. However, we also find that the minimum capacitance needed for oscillation decreases with increasing insulating-phase resistivity, which opposes the constraints for power efficiency. Based on published data on NbO 2 , VO 2 , and EuNiO 3 , we find that existing materials can be engineered for all-on-chip spiking using their parasitic capacitance.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Proteome-wide analysis of protein stability in Escherichia coli under acid stress

Knowledge of protein acid sensitivity remains sparse and is largely derived from low-throughput, enzyme-specific assays. We used a scalable framework to map acid stability across the Escherichia coli proteome to assess the acid stability of 1,675 unique proteins, estimating pH 50 values for over 90% of them. The parameter pH50 was defined as the pH value at which only 50% of the initial protein remains in solution following acid treatment. Proteome-wide pH 50 values ranged from 2.28 to 6.33 (median 5.11). Approximately 9% of detected proteins remained stable across all tested pH conditions. Our results align with published data and the assay of citrate synthase (GltA) performed here. Protein acid stability differed significantly by subcellular localization: periplasmic proteins were relatively more abundant in the acid-stable group, cytoplasmic proteins were abundant at pH 50 values 4.5–5.5, and inner membrane proteins at higher pH 50 between 5.5 and 6.0. Outer membrane proteins were too few to draw strong conclusions regarding enrichment within specific pH 50 groups. Notably, the periplasmic binding protein of the molybdate ABC transporter (ModA), was enriched after incubation at low pH. Estimated pH 50 values showed no correlation with protein isoelectric point and molecular weight. Together, this work provides the first proteome-wide map of protein acid stability and establishes a general framework for studying different chemical stressors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Sawtooth lattice multiferroic BeCr 2 O 4 : Noncollinear magnetic structure and multiple magnetic transitions

Noncollinear magnetic structures and multiple magnetic phase transitions in a sawtooth lattice antiferromagnet consisting of Cr 3+ are experimentally identified in this work, thereby proposing the scenario of magnetism-driven ferroelectricity in a sawtooth lattice. The title compound, BeCr 2 O 4 , displays three magnetic phase transitions at low temperatures—at T N1 ≈ 7.5 K, at T N2 ≈ 25 K, and at T N3 ≈ 26 K—revealed through magnetic susceptibility, specific heat, and neutron diffraction in this work. These magnetic phase transitions are found to be influenced by externally applied magnetic fields. Isothermal magnetization curves at low temperatures below the magnetic transitions indicate the antiferromagnetic nature of BeCr 2 O 4 with two spin-flop-like transitions occurring at H c1 ≈ 29 kOe and H c2 ≈ 47 kOe. Our high-resolution x-ray and neutron diffraction studies, performed on single crystal and powder samples, unambiguously determined the crystal structure as orthorhombic Pbnm. By performing the magnetic superspace group analysis of the neutron diffraction data at low temperatures, the magnetic structure in the temperature range T N3,N2 < T < T N1 is determined to be the polar magnetic space group P21nm. 1' (00g) 0s0s with a cycloidal magnetic propagation vector k 1 = (0, 0, 0.090 (1)) . The magnetic structure in the newly identified phase below T N1 is determined as P21/b.1' [b] (00 g) 00s with the magnetic propagation vector k 2 = (0, 0, 0.908 (1)). Finally, the cycloidal spin structure determined in our work is usually associated with electric polarization, thereby making BeCr 2 O 4 a promising multiferroic belonging to the sparsely populated family of sawtooth lattice antiferromagnets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The High Latitude Spectroscopic Survey on the Nancy Grace Roman Space Telescope

The Nancy Grace Roman Space Telescope will conduct a High Latitude Spectroscopic Survey (HLSS) over a large volume at high redshift, using the near-IR grism (1.0–1.93 μm, R = 435–865) and the 0.28 deg 2 wide-field camera. We present a reference HLSS that maps 2000 deg 2 and achieves an emission-line flux limit of 10 -16 erg s -1 cm -2 at 6.5σ, requiring ~0.6 yr of observing time. We summarize the flowdown of the Roman science objectives to the science and technical requirements of the HLSS. We construct a mock redshift survey over the full HLSS volume by applying a semianalytic galaxy formation model to a cosmological N-body simulation and use this mock survey to create pixel-level simulations of 4 deg 2 of HLSS grism spectroscopy. We find that the reference HLSS would measure ~10 million H α galaxy redshifts that densely map large-scale structure at z = 1–2 and 2 million [O III] galaxy redshifts that sparsely map structures at z = 2–3. We forecast the performance of this survey for measurements of the cosmic expansion history with baryon acoustic oscillations and the growth of large-scale structure with redshift-space distortions. We also study possible deviations from the reference design and find that a deep HLSS at f line > 7 × 10 -17 erg s -1 cm -2 over 4000 deg 2 (requiring ~1.5 yr of observing time) provides the most compelling stand-alone constraints on dark energy from Roman alone. This provides a useful reference for future optimizations. The reference survey, simulated data sets, and forecasts presented here will inform community decisions on the final scope and design of the Roman HLSS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Non-asymptotic analysis of ensemble Kalman updates: effective dimension and localization

Many modern algorithms for inverse problems and data assimilation rely on ensemble Kalman updates to blend prior predictions with observed data. Ensemble Kalman methods often perform well with a small ensemble size, which is essential in applications where generating each particle is costly. This paper develops a non-asymptotic analysis of ensemble Kalman updates, which rigorously explains why a small ensemble size suffices if the prior covariance has moderate effective dimension due to fast spectrum decay or approximate sparsity. Here, we present our theory in a unified framework, comparing everal implementations of ensemble Kalman updates that use perturbed observations, square root filtering and localization. As part of our analysis, we develop new dimension-free covariance estimation bounds for approximately sparse matrices that may be of independent interest.

Mathematics↗
DOE OSTI2022

A QUBO formulation for top-τ eigencentrality nodes

The efficient calculation of the centrality or “hierarchy” of nodes in a network has gained great relevance in recent years due to the generation of large amounts of data. The eigenvector centrality (aka eigencentrality) is quickly becoming a good metric for centrality due to both its simplicity and fidelity. In this work we lay the foundations for solving the eigencentrality problem of ranking the importance of the nodes of a network with scores from the eigenvector of the network, using quantum computational paradigms such as quantum annealing and gate-based quantum computing. The problem is reformulated as a quadratic unconstrained binary optimization (QUBO) that can be solved on both quantum architectures. The results focus on correctly identifying a given number of the most important nodes in numerous networks given by the sparse vector solution of our QUBO formulation of the problem of identifying the top- τ highest eigencentrality nodes in a network on both the D-Wave and IBM quantum computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Tucana B: A Potentially Isolated and Quenched Ultra-faint Dwarf Galaxy at $D$ ≈ 1.4 Mpc*

We report the discovery of Tucana B, an isolated ultra-faint dwarf galaxy at a distance of $D$ = 1.4 Mpc. Tucana B was found during a search for ultra-faint satellite companions to the known dwarfs in the outskirts of the Local Group, although its sky position and distance indicate the nearest galaxy to be ~500 kpc distant. Deep ground-based imaging resolves Tucana B into stars, and it displays a sparse red giant branch consistent with an old, metal-poor stellar population analogous to that seen in the ultra-faint dwarf galaxies of the Milky Way, albeit at fainter apparent magnitudes. Tucana B has a half-light radius of 80 ± 40 pc and an absolute magnitude of ${M}_{V}=-{6.9}_{-0.6}^{+0.5}$ mag (${L}_{V}=({5}_{-2}^{+4})\times {10}^{4}$ L⊙), which is again comparable to the Milky Way's ultra-faint satellites. There is no evidence for a population of young stars, either in the optical color–magnitude diagram or in GALEX archival ultraviolet imaging, with the GALEX data indicating $\mathrm{log}({\mathrm{SFR}}_{\mathrm{NUV}}/{M}_{\odot }\,{\mathrm{yr}}^{-1})\lt -5.4$ for star formation on ≲100 Myr timescales. Given its isolation and physical properties, Tucana B may be a definitive example of an ultra-faint dwarf that has been quenched by reionization, providing strong confirmation of a key driver of galaxy formation and evolution at the lowest mass scales. It also signals a new era of ultra-faint dwarf galaxy discovery at the extreme edges of the Local Group.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Variance Preserving Spectral Subsampling

Generating statistically faithful short-duration gamma-ray spectra from a single long measurement is essential in nuclear safeguards, supporting tasks such as algorithm development and machine-learning applications, especially when list-mode data are unavailable. Existing subsampling methods often distort the statistical characteristics of genuine short-duration measurements, leading to biased or unreliable analytical outcomes and thereby undermining downstream tasks. In this work, we compare five subsampling approaches using a benchmark set of 156 genuine replicate spectra collected with a high-purity germanium detector. We evaluate each method with respect to run-to-run variance, channel-to-channel variance, and preservation of total counts (losslessness). Across a wide range of subsampling ratios, only binomial subsampling without replacement consistently reproduces the statistical properties of genuine short-duration spectra, maintaining proper dispersion even in sparse spectral regions and perfectly preserving total counts. These results provide a mathematically principled and practically validated framework for generating synthetically shortened spectra when true short-duration measurements are unavailable.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗