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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 253 records · Page 14

Structural Model for the Flip-Flop Action in Thiamin Pyrophosphate-Dependent Human Pyruvate Dehydrogenase

The derivative of vitamin B1 thiamin pyrophosphate (TPP) is a cofactor of enzymes performing catalysis in pathways of energy production, including (i) decarboxylation of alpha-keto acids followed by (ii) transketolation. These enzymes have shown a common mechanism of TPP activation by imposing an active V-conformation of this coenzyme that brings the N4 atom of the aminopyrimidine ring to the distance required for the intramolecular C-H N hydrogen-bonding with the C2- atom of the thiazolium ring. The reactive C2 atom of TPP is the nucleophile that attacks the carbonyl carbon of different substrates used by the TPP-dependent enzymes. The structure of the heterotetrameric human pyruvate dehydrogenase (Elp) recently determined in our laboratory (1) revealed the association pattern of the subunits and the specifics of two chemically equivalent cofactor binding sites. Dynamic nonequivalence of these two cofactor sites directs the flip-flop action of this enzyme, depending upon which two active sites effect each other (2). The crystal structure derived from the holo-form of Elp provided the basis for the model of the flip-flop action of Elp in which different steps of the catalytic reaction are performed in each of the two cofactor sites at any given moment, where these steps are governed by the concerted shuttle-like motion of the subunits. It is further proposed that balancing a hydrogen-bond network and related cofactor geometry determine the continuity of catalytic events.

Ciszak, Ewa↗

Modeling structural damping for solids having distinct shear and dilatational loss factors

For steady state time harmonic problems (rigid format 8), the NASTRAN program as currently configured treats internal structural damping through the introduction of a single structural element damping coefficient that typically is viewed as the ratio of the complex to real modulus of elasticity. For problems dealing with two or three dimensional dynamic linear viscoelasticity (e.g. a Kelvin-Voigt viscoelastic model), the present NASTRAN capability cannot directly handle this situation wherein two independent damping coefficients are required to properly model the dissipation phenomenon. A technique is presented whereby the user can adapt the standard versions of NASTRAN (without resorting to either DMAP and/or FORTRAN coding changes) for the purpose of treating this class of problem.

Kalinowski, A. J.↗

Electronic structure modeling of InAs/GaSb superlattices with hybrid density functional theory

The application of first-principles calculations holds promise for greatly improving our understanding of semiconductor superlattices. By developing a procedure to accurately predict band gaps using hybrid density functional theory, it lays the groundwork for future studies investigating more nuanced properties of these structures. Our approach allows a priori prediction of the properties of SLS structures using only the band gaps of the constituent materials. Furthermore, it should enable direct investigation of the effects of interface structure, e.g., intermixing or ordering at the interface, on SLS properties. In this paper, we present band gap data for various InAs/GaSb type-II superlattice structures calculated using the generalized Kohn-Sham formulation of density functional theory. A PBE0-type hybrid functional was used, and the portion of the exact exchange was tuned to fit the band gaps of the binary compounds InAs and GaSb with the best agreement to bulk experimental values obtained with 18% of the exact exchange. The heterostructures considered in this study are 6 monolayer (ML) InAs/6 ML GaSb, 8 ML InAs/8 ML GaSb and 10 ML InAs/10 ML GaSb with deviations from the experimental band gaps ranging from 3% to 11%.

36 MATERIALS SCIENCE↗

Reference Controls Methodologies for Large Structural Models at Kennedy Space Center

This presentation will discuss the methodology behind Model Class Definition--the use of separate model assemblies of the same product, at different fidelities, driven by the same skeleton files. These fidelities can be used to convey only the detail that the end user needs, by allowing the end user to pick and choose between model classes for assembly creation. The usefulness of MPA for the Windchill Release Process will be demonstrated, along with its usefulness in minimizing CPU resources during design. The presentation will include an overview the ML product, how to structure complex products in a flexible modular architecture, and how to maximize system resources.

Jones, Corey↗

Reusable Solid Rocket Motor - V(RSRMV)Nozzle Forward Nose Ring Thermo-Structural Modeling

During the developmental static fire program for NASAs Reusable Solid Rocket Motor-V (RSRMV), an anomalous erosion condition appeared on the nozzle Carbon Cloth Phenolic nose ring that had not been observed in the space shuttle RSRM program. There were regions of augmented erosion located on the bottom of the forward nose ring (FNR) that measured nine tenths of an inch deeper than the surrounding material. Estimates of heating conditions for the RSRMV nozzle based on limited char and erosion data indicate that the total heat loading into the FNR, for the new five segment motor, is about 40-50% higher than the baseline shuttle RSRM nozzle FNR. Fault tree analysis of the augmented erosion condition has lead to a focus on a thermomechanical response of the material that is outside the existing experience base of shuttle CCP materials for this application. This paper provides a sensitivity study of the CCP material thermo-structural response subject to the design constraints and heating conditions unique to the RSRMV Forward Nose Ring application. Modeling techniques are based on 1-D thermal and porous media calculations where in-depth interlaminar loading conditions are calculated and compared to known capabilities at elevated temperatures. Parameters such as heat rate, in-depth pressures and temperature, degree of char, associated with initiation of the mechanical removal process are quantified and compared to a baseline thermo-chemical material removal mode. Conclusions regarding postulated material loss mechanisms are offered.

Clayton, J. Louie↗

SPAR Model Structural Efficiencies

The Nuclear Regulatory Commission (NRC) and the Electric Power Research Institute (EPRI) are supporting initiatives aimed at improving the quality of probabilistic risk assessments (PRAs). Included in these initiatives are the resolution of key technical issues that are have been judged to have the most significant influence on the baseline core damage frequency of the NRC’s Standardized Plant Analysis Risk (SPAR) models and licensee PRA models. Previous work addressed issues associated with support system initiating event analysis and loss of off-site power/station blackout analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An Integrative Model for Soil Biogeochemistry and Methane Processes: I. Model Structure and Sensitivity Analysis

Abstract Environmental changes are anticipated to generate substantial impacts on carbon cycling in peatlands, affecting terrestrial‐climate feedbacks. Understanding how peatland methane (CH 4 ) fluxes respond to these changing environments is critical for predicting the magnitude of feedbacks from peatlands to global climate change. To improve predictions of CH 4 fluxes in response to changes such as elevated atmospheric CO 2 concentrations and warming, it is essential for Earth system models to include increased realism to simulate CH 4 processes in a more mechanistic way. To address this need, we incorporated a new microbial‐functional group‐based CH 4 module into the Energy Exascale Earth System land model (ELM) and tested it with multiple observational data sets at an ombrotrophic peatland bog in northern Minnesota. The model is able to simulate observed land surface CH 4 fluxes and fundamental mechanisms contributing to these throughout the soil profile. The model reproduced the observed vertical distributions of dissolved organic carbon and acetate concentrations. The seasonality of acetoclastic and hydrogenotrophic methanogenesis—two key processes for CH 4 production—and CH 4 concentration along the soil profile were accurately simulated. Meanwhile, the model estimated that plant‐mediated transport, diffusion, and ebullition contributed to ∼23.5%, 15.0%, and 61.5% of CH 4 transport, respectively. A parameter sensitivity analysis showed that CH 4 substrate and CH 4 production were the most critical mechanisms regulating temporal patterns of surface CH 4 fluxes both under ambient conditions and warming treatments. This knowledge will be used to improve Earth system model predictions of these high‐carbon ecosystems from plot to regional scales.

58 GEOSCIENCES↗

Modeling Structured Electrodes and Graded Porosity for Improving Discharge Rate Capability in Ultra-Thick Graphite|LiNi 0.6 Mn 0.2 Co 0.2 O 2 Batteries

Long-range electric vehicles (EVs) require high-energy-density batteries that also meet the power demands of high current charge and discharge. Ultra-thick (>100 μm) Lithium-ion battery electrodes are critical to enable this need, but slow ion transport in conventional uniform electrodes (UEs) reduces battery capacity at increasing charge/discharge rates. We present a 3D computational analysis on the impact of structured electrode (SE) and graded electrode (GE) geometries on the discharge rate capability of ultra-thick graphite|LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC-622) battery cells based on the footprint of a commercial EV pouch cell. SE cathodes with either a “grid” or “line” geometry and GEs with two layers of porosity were modeled. Based on the results of 230 models, we found that the electrolyte volume fraction is a key parameter that impacts capacity improvements in UEs, GEs, and SEs at 2 C–6 C discharge rates. SEs have the greatest discharge rate capability, outperforming GEs and UEs due to reduced Lithium-ion concentration gradients across the electrode thickness, which mitigates electrolyte depletion at high rates. The best SE model has a “grid” geometry with gravimetric and volumetric energy density improvements of 0.9%–4% at C/2–2 C and 18%–24% at 4 C–6 C relative to UEs.

25 ENERGY STORAGE↗

Structural model of an mRNA in complex with the bacterial chaperone Hfq

The Sm-like protein Hfq (host factor Q-beta phage) facilitates regulation by bacterial small noncoding RNAs (sRNAs) in response to stress and other environmental signals. In this paper, we present a low-resolution model of Escherichia coli Hfq bound to the rpoS mRNA, a bacterial stress response gene that is targeted by three different sRNAs. Selective 2'-hydroxyl acylation and primer extension, small-angle X-ray scattering, and Monte Carlo molecular dynamics simulations show that the distal face and lateral rim of Hfq interact with three sites in the rpoS leader, folding the RNA into a compact tertiary structure. These interactions are needed for sRNA regulation of rpoS translation and position the sRNA target adjacent to an sRNA binding region on the proximal face of Hfq. Finally, our results show how Hfq specifically distorts the structure of the rpoS mRNA to enable sRNA base pairing and translational control.

59 BASIC BIOLOGICAL SCIENCES↗

Improved Axisymmetric and High Temperature Material Structural Modeling in MOOSE and NEML

This report describes improvements made to the solid mechanics formulation in the MOOSE open source finite element simulation environment and the open source Nuclear Engineering Material model Library (NEML) for mechanical constitutive models. The focus of these improvements is to improve the usability and performance of simulations involving one or both pieces of software. Specifically, this work completes a new system for solid mechanics simulations in the MOOSE ecosystem providing exact linearizations and optimal (quadratic) convergence, for a variety of coordinate systems and material types, including large deformation simulations. This work then provides users a framework to build highly efficient mechanical simulations of structures or materials or to couple in additional MOOSE physics modules to build complex, scalable multiphysics simulations.

36 MATERIALS SCIENCE↗

Vibrational behavior of adaptive aircraft wing structures modelled as composite thin-walled beams

The vibrational behavior of cantilevered aircraft wings modeled as thin-walled beams and incorporating piezoelectric effects is studied. Based on the converse piezoelectric effect, the system of piezoelectric actuators conveniently located on the wing yield the control of its associated vertical and lateral bending eigenfrequencies. The possibility revealed by this study enabling one to increase adaptively the eigenfrequencies of thin-walled cantilevered beams could play a significant role in the control of the dynamic response and flutter of wing and rotor blade structures.

Song, O.↗

Learning Model Structural Uncertainty with Gaussian Processes

The advent of commercially available quantum computers has marked the beginning of quantum computing as a reality. Both quantum gate and annealing computers have been released by major computer hardware companies. In this work, the D-Wave 2XTM quantum annealing computer housed at the NASA Advanced Systems computational facility is investigated to accelerate Machine Learning (ML) for image registration. NASA collects large amounts of images over the globe remotely using space-based monitoring. Images of a fixed areas of the land surface are taken over time. Due to the orbit of the sensors, the viewing angles deviate slightly, and it is necessary to align or register the images precisely to create image time series over the land surface. Unaligned images can lead to substantial analysis errors. These time-series are then used in modeling Earth Systems models such as hydrological, weather, and carbon monitoring models. In this work, we consider the Moderate Resolution Image Spectrometer (MODIS) data collected by the NASA's terra satellite. Artificial Neural Networks (ANNs) is a natural fit for ML modelling of images. Several successes have been reported using machine learning related to image processing. We investigate the use of ML to register MODIS images. ANNs are investigated in combination with a Restricted Boltzmann Machines (RBM) as an auto-encoder. We will present results showing the accuracy and efficiency of this approach.The D-Wave 2XTM quantum annealer samples the ground-state wave-function of a spin-Ising systems with quadratic interactions between qubits and a Chimera connectivity. The system sits in a ~15 mK thermal bath. One can think of the system as being placed in the ground state initially and subject to thermal excitations governed by Boltzmann statistics. If this is assumed true, one can use the statistics from the D-Wave 2XTM to train RBMs. Generating statistics for training Boltzmann machines is an NP-hard problem and constitutes the largest compute cost. We investigate the use of the D-Wave 2XTM to accelerate the training of the RBMs in our ANNs and report on the results.

Kouatchou, Jules↗

Evaluating the accuracy of common γ-Al 2 O 3 structure models by selected area electron diffraction from high-quality crystalline γ-Al 2 O 3

Single crystal and textured polycrystalline γ-Al 2 O 3 thin films were synthesized by oxidation of NiAl(110) in air at 850 °C for 1 and 2 hours, respectively, and used to evaluate the accuracy of two spinel-based and two nonspinel models by comparison of selected-area electron diffraction (SAED). The lattice interplanar distances derived from the polycrystalline SAED pattern most closely matched the cubic spinel γ-Al 2 O 3 model. The single-crystal SAED spot pattern reflected symmetry consistent with both the cubic spinel and tetragonal nonspinel models, yet, the Al cation distribution better matched the cubic spinel model based on the relative intensities of diffraction spots. Our work indicates that the traditional cubic spinel model is a more accurate model of γ-Al 2 O 3 than the other models considered. Furthermore, the spinel-based monoclinic model is more accurate than the monoclinic nonspinel model. The understanding of the relative accuracy of the different models is key for simulating γ-Al 2 O 3 containing systems and is of general interest for the metal oxide and ceramic communities.

77 NANOSCIENCE AND NANOTECHNOLOGY↗