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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Contribution of Proton-Donor pKa on Reactivity Profiles of [FeFe]-hydrogenases

The [FeFe]-hydrogenases are enzymes that catalyze the reversible activation of H 2 coupled to the reduction–oxidation of electron carriers. Members of the different taxonomic groups of [FeFe]-hydrogenases display a wide range of preference, or bias, for H 2 oxidation or H 2 production reactions, despite sharing a common catalytic cofactor, or H-cluster. Identifying the properties that control reactivity remains an active area of investigation, and models have emerged that include diversity in the catalytic site coordination environments and compositions of electron transfer chains. The kinetics of proton-coupled electron transfer at the H-cluster might be expected to be a point of control of reactivity. To test this hypothesis, systematic changes were made to the conserved cysteine residue that functions in proton exchange with the H-cluster in the three model enzymes: CaI, CpII, and CrHydA1. CaI and CpII both employ electron transfer accessory clusters but differ in bias, whereas CrHydA1 lacks accessory clusters having only the H-cluster. Changing from cysteine to either serine (more basic) or aspartate (more acidic) modifies the sidechain pKa and thus the barrier for the proton exchange step. The reaction rates for H 2 oxidation or H 2 evolution were surveyed and measured for model [FeFe]-hydrogenases, and the results show that the initial proton-transfer step in [FeFe]-hydrogenase is tightly coupled to the control of reactivity; a change from cysteine to more basic serine favored H 2 oxidation in all enzymes, whereas a change to more acidic aspartate caused a shift in preference toward H 2 evolution. Overall, the changes in reactivity profiles were profound, spanning 10 5 in ratio of the H 2 oxidation-to-H 2 evolution rates. The fact that the change in reactivity follows a common trend implies that the effect of changing the proton-transfer residue pKa may also be framed as an effect on the scaling relationship between the H-cluster di(thiolmethyl)amine (DTMA) ligand pKa and E m values of the H-cluster. Experimental observations that support this relationship, and how it relates to catalytic function in [FeFe]-hydrogenases, are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hutchinson Trace Estimation for high-dimensional and high-order Physics-Informed Neural Networks

Physics-Informed Neural Networks (PINNs) have proven effective in solving partial differential equations (PDEs), especially when some data are available by seamlessly blending data and physics. However, extending PINNs to high-dimensional and even high-order PDEs encounters significant challenges due to the computational cost associated with automatic differentiation in the residual loss function calculation. Herein, we address the limitations of PINNs in handling high-dimensional and high-order PDEs by introducing the Hutchinson Trace Estimation (HTE) method. Starting with the second-order high-dimensional PDEs, which are ubiquitous in scientific computing, HTE is applied to transform the calculation of the entire Hessian matrix into a Hessian vector product (HVP). This approach not only alleviates the computational bottleneck via Taylor-mode automatic differentiation but also significantly reduces memory consumption from the Hessian matrix to an HVP’s scalar output. We further showcase HTE’s convergence to the original PINN loss and its unbiased behavior under specific conditions. Comparisons with the Stochastic Dimension Gradient Descent (SDGD) highlight the distinct advantages of HTE, particularly in scenarios with significant variability and variance among dimensions. We further extend the application of HTE to higher-order and higher-dimensional PDEs, specifically addressing the biharmonic equation. By employing tensor-vector products (TVP), HTE efficiently computes the colossal tensor associated with the fourth-order high-dimensional biharmonic equation, saving memory and enabling rapid computation. The effectiveness of HTE is illustrated through experimental setups, demonstrating comparable convergence rates with SDGD under memory and speed constraints. Additionally, HTE proves valuable in accelerating the Gradient-Enhanced PINN (gPINN) version as well as the Biharmonic equation. Overall, HTE opens up a new capability in scientific machine learning for tackling high-order and high-dimensional PDEs.

Curse of dimensionality↗
DOE OSTI2020

Tailoring poplar lignin without yield penalty by combining a null and haploinsufficient CINNAMOYL-CoA REDUCTASE2 allele

Lignin causes lignocellulosic biomass recalcitrance to enzymatic hydrolysis. Engineered low-lignin plants have reduced recalcitrance but often exhibit yield penalties, offsetting their gains in fermentable sugar yield. Here, CRISPR/Cas9-generated CCR2(–/*) line 12 poplars have one knockout CCR2 allele while the other contains a 3-bp deletion, resulting in a 114I115A-to-114T conversion in the corresponding protein. Despite having 10% less lignin, CCR2(–/*) line 12 grows normally. On a plant basis, the saccharification efficiency of CCR2(–/*) line 12 is increased by 25–41%, depending on the pretreatment. Analysis of monoallelic CCR2 knockout lines shows that the reduced lignin amount in CCR2(–/*) line 12 is due to the combination of a null and the specific haploinsufficient CCR2 allele. Analysis of another CCR2(–/*) line shows that depending on the specific CCR2 amino-acid change, lignin amount and growth can be affected to different extents. Furthermore, our findings open up new possibilities for stably fine-tuning residual gene function in planta.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

In this paper, we describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Decoding Resilience by Modeling Outage and Restoration Processes in Distribution Grids: A Pittsburgh Case Study

Climate-induced extreme weather events, such as floods and heatwaves, pose significant challenges to the resilience of urban power distribution grids. This paper examines the outage and restoration dynamics of Pittsburgh's power grid during the flood event in April 2024 and three heatwaves in June, July, and August 2024. We introduce a comprehensive modeling framework that integrates outage and restoration processes, enabling the quantification of resilience metrics, including total customer-hours of power outage, maximum residual values, and restoration durations across various ZIP codes. Our analysis highlights spatial disparities in outage impacts and restoration efficiencies, with ZIP Code 15222 experiencing the highest cumulative disruptions, while ZIP Code 15217 shows lower susceptibility. By linking statistical trends with weather events, this study underscores the critical need for targeted infrastructure upgrades and advanced restoration strategies. Furthermore, the proposed framework offers valuable insights for planning and managing resilient power systems in the face of increasing climate stress.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Optimization-based algorithms for nonlinear mechanics and frictional contact

An optimization-based strategy for solving nonlinear mechanics problems is proposed. In contrast to typical nonlinear equation solver algorithms that aim to find zeros in the residual force function, we minimize an energy (or energy-like) function to encourage solutions which are locally stable equilibria. These smooth and potentially non-convex objective functions are minimized using a preconditioned conjugate-gradient trust-region algorithm. Contact is formulated as an inequality constrained minimization problem, and is solved with an augmented Lagrangian algorithm. Friction is included in the approach via a regularized quasi-potential energy, and other dissipative behavior is included through the use of variational constitutive updates. Finally, to accelerate convergence rates for the Lagrange multipliers, we propose a novel multiplier update algorithm utilizing the Fischer-Burmeister function, and demonstrate super-linear solver convergence for some applications.

42 ENGINEERING↗
NASA NTRS2000

Autoinhibition of a calmodulin-dependent calcium pump involves a structure in the stalk that connects the transmembrane domain to the ATPase catalytic domain

The regulation of Ca(2+)-pumps is important for controlling [Ca(2+)] in the cytosol and organelles of all eukaryotes. Here, we report a genetic strategy to identify residues that function in autoinhibition of a novel calmodulin-activated Ca(2+)-pump with an N-terminal regulatory domain (isoform ACA2 from Arabidopsis). Mutant pumps with constitutive activity were identified by complementation of a yeast (K616) deficient in two Ca(2+)-pumps. Fifteen mutations were found that disrupted a segment of the N-terminal autoinhibitor located between Lys(23) and Arg(54). Three mutations (E167K, D219N, and E341K) were found associated with the stalk that connects the ATPase catalytic domain (head) and with the transmembrane domain. Enzyme assays indicated that the stalk mutations resulted in calmodulin-independent activity, with V(max), K(mATP), and K(mCa(2+)) similar to that of a pump in which the N-terminal autoinhibitor had been deleted. A highly conservative substitution at Asp(219) (D219E) still produced a deregulated pump, indicating that the autoinhibitory structure in the stalk is highly sensitive to perturbation. In plasma membrane H(+)-ATPases from yeast and plants, similarly positioned mutations resulted in hyperactive pumps. Together, these results suggest that a structural feature of the stalk is of general importance in regulating diverse P-type ATPases.

NASA Discipline Plant Biology↗
NASA NTRS2005

Attitude-Independent Magnetometer Calibration for Spin-Stabilized Spacecraft

The paper describes a three-step estimator to calibrate a Three-Axis Magnetometer (TAM) using TAM and slit Sun or star sensor measurements. In the first step, the Calibration Utility forms a loss function from the residuals of the magnitude of the geomagnetic field. This loss function is minimized with respect to biases, scale factors, and nonorthogonality corrections. The second step minimizes residuals of the projection of the geomagnetic field onto the spin axis under the assumption that spacecraft nutation has been suppressed by a nutation damper. Minimization is done with respect to various directions of the body spin axis in the TAM frame. The direction of the spin axis in the inertial coordinate system required for the residual computation is assumed to be unchanged with time. It is either determined independently using other sensors or included in the estimation parameters. In both cases all estimation parameters can be found using simple analytical formulas derived in the paper. The last step is to minimize a third loss function formed by residuals of the dot product between the geomagnetic field and Sun or star vector with respect to the misalignment angle about the body spin axis. The method is illustrated by calibrating TAM for the Fast Auroral Snapshot Explorer (FAST) using in-flight TAM and Sun sensor data. The estimated parameters include magnetic biases, scale factors, and misalignment angles of the spin axis in the TAM frame. Estimation of the misalignment angle about the spin axis was inconclusive since (at least for the selected time interval) the Sun vector was about 15 degrees from the direction of the spin axis; as a result residuals of the dot product between the geomagnetic field and Sun vectors were to a large extent minimized as a by-product of the second step.

Natanson, Gregory↗
NASA NTRS1977

Application of Kalman filtering to spacecraft range residual prediction

One function of the Deep Space Network is validation of the range data that they receive. In this paper we present an automated online sequential range predictor which shows promise of significantly reducing computational and manpower expenditures. The proposed algorithm, a U-D covariance factored Kalman filter, is demonstrated by processing a four-month record of Viking spacecraft data taken enroute to Mars.

Madrid, G. A.↗
DOE OSTI2021

Distribution of Bound and Free Water in Anatomical Fractions of Pine Residues and Corn Stover as a Function of Biological Degradation

Biomass quality is influenced by water’s abundance, distribution, and status in relation to other chemical species within the polymer matrix. Water interacts with polymers that make up the cell walls, and these interactions govern the physical and chemical changes that occur during the storage and preprocessing of biomass feedstocks. Time-domain nuclear magnetic resonance (TD-NMR) was employed to explore variations in the physical constraints of water within the lignocellulosic microstructure in distinct anatomical fractions of biomass and as a function of biological degradation. The Carr–Purcell–Meiboom–Gill sequence, when combined with knowledge of the chemical composition and physical structure of pine residues and corn stover anatomical fractions, gives an accurate measurement of the bound and free water. In this work, the impacts of storage and biological degradation were investigated to elucidate changes in the status and distribution of water within distinct plant tissues. We also investigate how degradation during storage affects water interactions in different pine residues (e.g., bark, branch, and needle) and corn stover (e.g., cob, leaf, and stalk) anatomical fractions using transverse relaxation times (T2). As demonstrated herein, TD-NMR provides quantitative data on lignocellulosic biomass–water interactions within anatomical fractions, which can further aid in the investigation of preprocessing effects on feedstock quality. Our findings suggest that biological heating enhances biomass–water interactions at the cellular and macromolecular scale. In addition, analysis of three-dimensional scanning electron microscopy reconstructions indicates that surface roughness wavelengths align with microscale roughness, suggesting that pine forestry residue and corn stover particles have primarily hydrophobic exterior surfaces. Furthermore, this study offers multiscale insights into understanding the microstructure, wettability, and chemical environment that dictate diffusion, enzyme access, and recalcitrance of lignocellulosic biomass.

09 BIOMASS FUELS↗
NASA NTRS1992

Incorporation of spatial information in Bayesian image reconstruction - The maximum residual likelihood criterion

We have developed a new figure of merit, a 'maximum-residual-likelihood' (MRL) statistic, for the goodness of fit for Bayesian image restoration which explicitly incorporates spatial information. The MRL constraint provides a natural means of incorporating the prior knowledge that the residuals contain no spatial structure through the autocorrelation function of the residuals. We demonstrate that this statistic follows a Chi-square distribution and that forcing this statistic to have its most probable value leads to a restored image whose residuals are consistent with the noise model. Our numerical experiments suggest that image restoration using the MRL statistic alone is numerically robust and produces results which are independent of the initial guess for the restored image. However, we caution that using the MRL statistic without an image prior can result in overresolution in low SNR portions of the image.

Pina, R. K.↗
DOE OSTI2021

Protein conformational switch discerned via network centrality properties

Network analysis has emerged as a powerful tool for examining structural biology systems. The spatial organization of the components of a biomolecular structure has been rendered as a graph representation and analyses have been performed to deduce the biophysical and mechanistic properties of these components. For proteins, the analysis of protein structure networks (PSNs), especially via network centrality measurements and cluster coefficients, has led to identifying amino acid residues that play key functional roles and classifying amino acid residues in general. Whether these network properties examined in various studies are sensitive to subtle (yet biologically significant) conformational changes remained to be addressed. Here, we focused on four types of network centrality properties (betweenness, closeness, degree, and eigenvector centralities) for conformational changes upon ligand binding of a sensor protein (constitutive androstane receptor) and an allosteric enzyme (ribonucleotide reductase). We found that eigenvector centrality is sensitive and can distinguish salient structural features between protein conformational states while other centrality measures, especially closeness centrality, are less sensitive and rather generic with respect to the structural specificity. We also demonstrated that an ensembleinformed, modified PSN with static edges removed (which we term PSN*) has enhanced sensitivity at discerning structural changes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2011

Comparison of Four Mixed Layer Mesoscale Parameterizations and the Equation for an Arbitrary Tracer

In this paper we discuss two issues, the inter-comparison of four mixed layer mesoscale parameterizations and the search for the eddy induced velocity for an arbitrary tracer. It must be stressed that our analysis is limited to mixed layer mesoscales since we do not treat sub-mesoscales and small turbulent mixing. As for the first item, since three of the four parameterizations are expressed in terms of a stream function and a residual flux of the RMT formalism (residual mean theory), while the fourth is expressed in terms of vertical and horizontal fluxes, we needed a formalism to connect the two formulations. The standard RMT representation developed for the deep ocean cannot be extended to the mixed layer since its stream function does not vanish at the ocean's surface. We develop a new RMT representation that satisfies the surface boundary condition. As for the general form of the eddy induced velocity for an arbitrary tracer, thus far, it has been assumed that there is only the one that originates from the curl of the stream function. This is because it was assumed that the tracer residual flux is purely diffusive. On the other hand, we show that in the case of an arbitrary tracer, the residual flux has also a skew component that gives rise to an additional bolus velocity. Therefore, instead of only one bolus velocity, there are now two, one coming from the curl of the stream function and other from the skew part of the residual flux. In the buoyancy case, only one bolus velocity contributes to the mean buoyancy equation since the residual flux is indeed only diffusive.

Canuto, V. M.↗
NASA NTRS1994

Craters in aluminum 1100 targets using glass projectiles at 1-7 km/s

We report on impact experiments using soda-lime glass spheres of 3.2 mm diameter and aluminum targets (1100 series). The purpose is to assist in the interpretation of LDEF instruments and in the development of future cosmic-dust collectors in low-Earth orbit. Because such instruments demand understanding of both the cratering and penetration process, we typically employ targets with thicknesses that range from massive, infinite half-space targets, to ultrathin films. This report addresses a subset of cratering experiments that were conducted to fine-tune our understanding of crater morphology as a function of impact velocity. Also, little empirical insight exists about the physical distribution and shock-metamorphism of the impactor residues as a function of encounter speed, despite their recognized significance in the analysis of space-exposed surfaces. Soda-lime glass spheres were chosen as a reasonable analog to extraterrestrial silicates, and aluminum 1100 was chosen for targets, which among the common Al-alloys, best represents the physical properties of high-purity aluminum. These materials complement existing impact studies that typically employed metallic impactors and less ductile Al-alloys. We have completed dimensional analyses of the resulting craters and are in the process of investigating the detailed distribution of the unmelted and melted impactor residues via SEM methods, as well as potential compositional modifications of the projectile melts via electron microprobe.

Bernhard, R. P.↗
NASA NTRS2011

XANES Analysis of Organic Residues Produced from the UV Irradiation of Astrophysical Ice Analogs

Organic residues formed in the laboratory from the ultraviolet (UV) photo-irradiation or ion bombardment of astrophysical ice analogs have been extensively studied for the last 15 years with a broad suite of techniques, including infrared (IR) and UV spectroscopies, as well as mass spectrometry. Analyses of these materials show that they consist of complex mixtures of organic compounds stable at room temperature, mostly soluble, that have not been fully characterized. However, the hydrolysis products of these residues have been partly identified using chromatography techniques, which indicate that they contain molecular precursors of prebiotic interest such as amino acids, nitrile-bearing compounds, and amphiphilic compounds. In this study, we present the first X-ray absorption near-edge structure (XANES) spectroscopy measurements of three organic residues made from the UV irradiation of ices having different starting compositions. XANES spectra confirm the presence of different chemical functions in these residues, and indicate that they are rich in nitrogenand oxygen-bearing species. These data can be compared with XANES measurements of extraterrestrial materials. Finally, this study also shows how soft X rays can alter the chemical composition of samples.

XANES(X-RAY ABSORPTION NEAR-EDGE STRUCTURE)↗
DOE OSTI2022

The Local Topological Free Energy of the SARS-CoV-2 Spike Protein

The novel coronavirus SARS-CoV-2 infects human cells using a mechanism that involves binding and structural rearrangement of its Spike protein. Understanding protein rearrangement and identifying specific amino acids where mutations affect protein rearrangement has attracted much attention for drug development. In this manuscript, we use a mathematical method to characterize the local topology/geometry of the SARS-CoV-2 Spike protein backbone. Our results show that local conformational changes in the FP, HR1, and CH domains are associated with global conformational changes in the RBD domain. The SARS-CoV-2 variants analyzed in this manuscript (alpha, beta, gamma, delta Mink, G614, N501) show differences in the local conformations of the FP, HR1, and CH domains as well. Finally, most mutations of concern are either in or in the vicinity of high local topological free energy conformations, suggesting that high local topological free energy conformations could be targets for mutations with significant impact of protein function. Namely, the residues 484, 570, 614, 796, and 969, which are present in variants of concern and are targeted as important in protein function, are predicted as such from our model.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1990

New correction procedures for the fast field program which extend its range

A fast field program (FFP) algorithm was developed based on the method of Lee et al., for the prediction of sound pressure level from low frequency, high intensity sources. In order to permit accurate predictions at distances greater than 2 km, new correction procedures have had to be included in the algorithm. Certain functions, whose Hankel transforms can be determined analytically, are subtracted from the depth dependent Green's function. The distance response is then obtained as the sum of these transforms and the Fast Fourier Transformation (FFT) of the residual k dependent function. One procedure, which permits the elimination of most complex exponentials, has allowed significant changes in the structure of the FFP algorithm, which has resulted in a substantial reduction in computation time.

West, M.↗