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At least 343 records · Page 19

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Constitutive Model Development for Aging Polymer Encapsulants (ASC P&EM FY2021 L2 Milestone 7836)

This SAND report fulfills the completion requirements for the ASC Physics and Engineering Modeling Level 2 Milestone 7836 during Fiscal Year 2021. The Sandia Simplified potential energy clock (SPEC) non-linear viscoelastic constitutive model was developed to predict a whole host of polymer glass physical behaviors in order to provide a tool to assess the effects of stress on these materials over their lifecycle. Polymer glasses are used extensively in applications such as electronics packaging, where encapsulants and adhesives can be critical to device performance. In this work, the focus is on assessing the performance of the model in predicting material evolution associated with long-term physical aging, an area that the model has not been fully vetted in. These predictions are key to utilizing models to help demonstrate electronics packaging component reliability over decades long service lives, a task that is very costly and time consuming to execute experimentally. The initiating hypothesis for the work was that a model calibration process can be defined that enables confidence in physical aging predictions under ND relevant environments and timescales without sacrificing other predictive capabilities. To test the hypothesis, an extensive suite of calibration and aging data was assembled from a combination of prior work and collaborating projects (Aging and Lifetimes as well as the DoD Joint Munitions Program) for two mission relevant epoxy encapsulants, 828DGEBA/DEA and 828DGEBA/T403. Multiple model calibration processes were developed and evaluated against the entire set of data for each material. A qualitative assessment of each calibration's ability to predict the wide range of aging responses was key to ranking the calibrations against each other. During this evaluation, predictions that were identified as non-physical, i.e., demonstrated something that was qualitatively different than known material behavior, were heavily weighted against the calibration performance. Thus, unphysical predictions for one aspect of aging response could generate a lower overall rating for a calibration process even if that process generated better quantitative predictions for another aspect of aging response. This insurance that all predictions are qualitatively correct is important to the overall aim of utilizing the model to predict residual stress evolution, which will depend on the interplay amongst the different material aging responses. The DSC-focused calibration procedure generated the best all-around aging predictions for both materials, demonstrating material models that can qualitatively predict the whole host of different physical aging responses that have been measured. This step forward in predictive capability comes from an unanticipated source, utilization of calorimetry measurements to specify model parameters. The DSC-focused calibration technique performed better than compression-focused techniques that more heavily weigh measurements more closely related to the structural responses to be predicted. Indeed, the DSC-focused calibration procedure was only possible due to recent incorporation of the enthalpy and heat capacity features into SPEC that was newly verified during this L2 milestone. Fundamentally similar aspects of the two material model calibrations as well as parametric studies to assess sensitives of the aging predictions are discussed within the report. A perspective on the next steps to the overall goal of residual stress evolution predictions under stockpile conditions closes the report.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Kilonovae Across the Nuclear Physics Landscape: The Impact of Nuclear Physics Uncertainties on r-process-powered Emission

Merging neutron stars produce “kilonovae”—electromagnetic transients powered by the decay of unstable nuclei synthesized via rapid neutron capture (the r-process) in material that is gravitationally unbound during inspiral and coalescence. Kilonova emission, if accurately interpreted, can be used to characterize the masses and compositions of merger-driven outflows, helping to resolve a long-standing debate about the origins of r-process material in the Universe. We explore how the uncertain properties of nuclei involved in the r-process complicate the inference of outflow properties from kilonova observations. Using r-process simulations, we show how nuclear physics uncertainties impact predictions of radioactive heating and element synthesis. For a set of models that span a large range in both predicted heating and final abundances, we carry out detailed numerical calculations of decay product thermalization and radiation transport in a kilonova ejecta with a fixed mass and density profile. The light curves associated with our models exhibit great diversity in their luminosities, with peak brightness varying by more than an order of magnitude. We also find variability in the shape of the kilonova light curves and their color, which in some cases runs counter to the expectation that increasing levels of lanthanide and/or actinide enrichment will be correlated with longer, dimmer, redder emission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2001

Osmotic forces and gap junctions in spreading depression: a computational model

In a computational model of spreading depression (SD), ionic movement through a neuronal syncytium of cells connected by gap junctions is described electrodiffusively. Simulations predict that SD will not occur unless cells are allowed to expand in response to osmotic pressure gradients and K+ is allowed to move through gap junctions. SD waves of [K+]out approximately 25 to approximately 60 mM moving at approximately 2 to approximately 18 mm/min are predicted over the range of parametric values reported in gray matter, with extracellular space decreasing up to approximately 50%. Predicted waveform shape is qualitatively similar to laboratory reports. The delayed-rectifier, NMDA, BK, and Na+ currents are predicted to facilitate SD, while SK and A-type K+ currents and glial activity impede SD. These predictions are consonant with recent findings that gap junction poisons block SD and support the theories that cytosolic diffusion via gap junctions and osmotic forces are important mechanisms underlying SD.

Spreading Cortical Depression/physiology↗

NASA NTRS2014

A Morphing Radiator for High-Turndown Thermal Control of Crewed Space Exploration Vehicles

Spacecraft designed for missions beyond low earth orbit (LEO) face a difficult thermal control challenge, particularly in the case of crewed vehicles where the thermal control system (TCS) must maintain a relatively constant internal environment temperature despite a vastly varying external thermal environment and despite heat rejection needs that are contrary to the potential of the environment. A thermal control system may be required to reject a higher heat load to warm environments and a lower heat load to cold environments, necessitating a relatively high turndown ratio. A modern thermal control system is capable of a turndown ratio of on the order of 12:1, but crew safety and environment compatibility have constrained these solutions to massive multi-loop fluid systems. This paper discusses the analysis of a unique radiator design that employs the behavior of shape memory alloys (SMAs) to vary the turndown of, and thus enable, a single-loop vehicle thermal control system for space exploration vehicles. This design, a morphing radiator, varies its shape in response to facesheet temperature to control view of space and primary surface emissivity. Because temperature dependence is inherent to SMA behavior, the design requires no accommodation for control, instrumentation, or power supply in order to operate. Thermal and radiation modeling of the morphing radiator predict a turndown ranging from 11.9:1 to 35:1 independent of TCS configuration. Coupled thermal-stress analyses predict that the desired morphing behavior of the concept is attainable. A system level mass analysis shows that by enabling a single loop architecture this design could reduce the TCS mass by between 139 kg and 225 kg. The concept has been demonstrated in proof-of-concept benchtop tests.

Cognata, Thomas J.↗

NASA NTRS1989

Prediction of the spectrum of atmospheric microburst noise in the range 2-20 Hz - Preliminary results

An engineering estimate of the spectrum of atmospheric microburst noise radiation in the range 2-20 Hz is developed. This prediction is obtained via a marriage of standard aeroacoustic theory with a numerical computation of the relevant fluid dynamics. The 'computational aeroacoustics' technique applied here to the interpretation of atmospheric noise measurements is illustrative of a methodology that can now be employed in a wide class of problems.

Hardin, Jay C.↗

DOE OSTI2023

Synchronizing the consistency relation

We study the N-point function of the density contrast to quadratic order in the squeezed limit during the matter-dominated (MD) and radiation-dominated (RD) eras in synchronous gauge. Since synchronous gauge follows the free-fall frame of observers, the equivalence principle dictates that in the gradient approximation for the long-wavelength mode there is only a single, manifestly time-independent consistency relation for the N-point function. This simple form is dictated by the initial mapping between synchronous and local coordinates, unlike Newtonian gauge and its correspondingly separate dilation and Newtonian consistency relations. Dynamical effects only appear at quadratic order in the squeezed limit and are again characterized by a change in the local background, also known as the separate universe approach. We show that for the 3-point function the compatibility between these squeezed-limit relations and second-order perturbation theory requires both the initial and dynamical contributions to match, as they do in single-field inflation. This clarifies the role of evolution or late-time projection effects in establishing the consistency relation for observable bispectra, which is especially important for radiation acoustic oscillations and for establishing consistency below the matter-radiation equality scale in the MD era. Defining an appropriate angle and time average of these oscillations is also important for making separate universe predictions of spatially varying local observables during the RD era, which can be useful for a wider range of cosmological predictions beyond N-point functions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Coarse-Grained Density Functional Theory Predictions via Deep Kernel Learning

Scalable electronic predictions are critical for soft materials design. Recently, the Electronic Coarse-Graining (ECG) method was introduced to renormalize all-atom quantum chemical (QC) predictions to coarse-grained (CG) resolutions using deep neural networks (DNNs). While DNNs can learn complex representations that prove challenging for kernel-based methods, they are susceptible to overfitting and the overconfidence of uncertainty estimations. Here, we develop ECG within a GPU-accelerated Deep Kernel Learning (DKL) framework to enable CG QC predictions using range-separated hybrid density functional theory (DFT), obtaining a 107 speedup relative to naive all-atom QC. By treating the predicted electronic properties as random Gaussian Processes, DKL incorporates CG mapping degeneracy by learning the distribution of electronic energies as a function of CG configuration. DKL-ECG accurately reproduces molecular orbital energies from range-separated DFT while facilitating efficient training via active learning using the uncertainties provided by DKL. Further, we show that while active learning algorithms enable efficient sampling of a more diverse configurational space relative to random sampling, all explored query methods exhibit comparable performance for the examined system. We attribute this result to the significant overlap of the feature space and output property distributions across multiple temperatures.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1995

Effects of target fragmentation on evaluation of LET spectra from space radiation in low-earth orbit (LEO) environment: impact on SEU predictions

Recent improvements in the radiation transport code HZETRN/BRYNTRN and galactic cosmic ray environmental model have provided an opportunity to investigate the effects of target fragmentation on estimates of single event upset (SEU) rates for spacecraft memory devices. Since target fragments are mostly of very low energy, an SEU prediction model has been derived in terms of particle energy rather than linear energy transfer (LET) to account for nonlinear relationship between range and energy. Predictions are made for SEU rates observed on two Shuttle flights, each at low and high inclination orbit. Corrections due to track structure effects are made for both high energy ions with track structure larger than device sensitive volume and for low energy ions with dense track where charge recombination is important. Results indicate contributions from target fragments are relatively important at large shield depths (or any thick structure material) and at low inclination orbit. Consequently, a more consistent set of predictions for upset rates observed in these two flights is reached when compared to an earlier analysis with CREME model. It is also observed that the errors produced by assuming linear relationship in range and energy in the earlier analysis have fortuitously canceled out the errors for not considering target fragmentation and track structure effects.

STS-51 Shuttle Project↗

NASA NTRS1995

Effects of Target Fragmentation on Evaluation of LET Spectra From Space Radiation in Low-Earth Orbit (LEO) Environment: Impact on SEU Predictions

Shinn, J. L.↗

NASA NTRS1992

Redox effects in ordinary chondrites and implications for asteroid spectrophotometry

The sensitivity of reflectance spectra to mean ferrous iron content and olivine and pyroxene proportion enhancements in the course of metamorphic oxidation is presently used to examine whether metamorphically-induced ranges in mineralogy, and corresponding spectral parameters, may explain the observed variations in S-asteroid rotational spectra. The predicted spectral variations within any one chondrite class are, however, insufficient to account for S-asteroid rotational spectra, and predicted spectral-range slopes have a sign opposite to the rotational measurements. Metamorphic oxidation is found unable to account for S-asteroid rotational spectra.

Mcsween, Harry Y., Jr.↗

NASA NTRS2000

Double-Plate Penetration Equations

This report compares seven double-plate penetration predictor equations for accuracy and effectiveness of a shield design. Three of the seven are the Johnson Space Center original, modified, and new Cour-Palais equations. The other four are the Nysmith, Lundeberg-Stern-Bristow, Burch, and Wilkinson equations. These equations, except the Wilkinson equation, were derived from test results, with the velocities ranging up to 8 km/sec. Spreadsheet software calculated the projectile diameters for various velocities for the different equations. The results were plotted on projectile diameter versus velocity graphs for the expected orbital debris impact velocities ranging from 2 to 15 km/sec. The new Cour-Palais double-plate penetration equation was compared to the modified Cour-Palais single-plate penetration equation. Then the predictions from each of the seven double-plate penetration equations were compared to each other for a chosen shield design. Finally, these results from the equations were compared with test results performed at the NASA Marshall Space Flight Center. Because the different equations predict a wide range of projectile diameters at any given velocity, it is very difficult to choose the "right" prediction equation for shield configurations other than those exactly used in the equations' development. Although developed for various materials, the penetration equations alone cannot be relied upon to accurately predict the effectiveness of a shield without using hypervelocity impact tests to verify the design.

Hayashida, K. B.↗

NASA NTRS1993

Multiple-camera/motion stereoscopy for range estimation in helicopter flight

Aiding the pilot to improve safety and reduce pilot workload by detecting obstacles and planning obstacle-free flight paths during low-altitude helicopter flight is desirable. Computer vision techniques provide an attractive method of obstacle detection and range estimation for objects within a large field of view ahead of the helicopter. Previous research has had considerable success by using an image sequence from a single moving camera to solving this problem. The major limitations of single camera approaches are that no range information can be obtained near the instantaneous direction of motion or in the absence of motion. These limitations can be overcome through the use of multiple cameras. This paper presents a hybrid motion/stereo algorithm which allows range refinement through recursive range estimation while avoiding loss of range information in the direction of travel. A feature-based approach is used to track objects between image frames. An extended Kalman filter combines knowledge of the camera motion and measurements of a feature's image location to recursively estimate the feature's range and to predict its location in future images. Performance of the algorithm will be illustrated using an image sequence, motion information, and independent range measurements from a low-altitude helicopter flight experiment.

Smith, Phillip N.↗

NASA NTRS1996

Studies of Large-Area Inversion-Layer Metal-Insulator-Semiconductor (IL/MIS) Solar Cells and Arrays

Many inversion-layer metal-insulator-semiconductor (IL/MIS) solar cells have been fabricated. There are around eighteen 1 cm(exp 2) IL/MIS solar cells which have efficiencies greater than 7%. There are only about three 19 cm(exp 2) IL/MIS cells which have efficiencies greater than 4%. The more accurate control of the thickness of the thin layer of oxide between aluminum and silicon of the MIS contacts has been achieved. A lot of effort and progress have been made in this area. A comprehensive model for MIS contacts under dark conditions has been developed that covers a wide range of parameters. It has been applied to MIS solar cells. One of the main advantages of these models is the prediction of the range of the thin oxide thickness versus the maximum efficiencies of the MIS solar cells. This is particularly important when the thickness is increased to 25 A. This study is very useful for our investigation of the IL/MIS solar cells. The two-dimensional numerical model for the IL/MIS solar cells has been tried to develop and the results are presented in this report.

Ho, Fat Duen↗

DOE OSTI2026

Sparse non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations

The influence of noise on quantum dynamics is one of the main factors preventing current quantum processors from performing accurate quantum computations. Sufficient noise characterization and modeling can provide key insights into the effect of noise on quantum algorithms and inform the design of targeted error protection protocols. However, constructing effective noise models that are sparse in model parameters, yet predictive can be challenging. In this work, we present an approach for effective noise modeling of multi-qubit operations on transmon-based devices. Through a comprehensive characterization of seven devices offered by the IBM Quantum Platform, we show that the model can capture and predict a wide range of single- and two-qubit behaviors, including non-Markovian effects resulting from spatiotemporally correlated noise sources. The model’s predictive power is further highlighted through multi-qubit dynamical decoupling demonstrations and an implementation of the variational quantum eigensolver. As a training proxy for the hardware, we show that the model can predict expectation values within a relative error of 0.5%; this is a sevenfold improvement over default hardware noise models. Through these demonstrations, we highlight key error sources in superconducting qubits and illustrate the utility of reduced noise models for predicting hardware dynamics.

open quantum systems & decoherence↗

NASA NTRS1988

Some implications of colloid stability theory for protein crystallization

Colloid stability theory has been applied to protein crystallization and predicts a narrow range of conditions under which crystals can be grown without the agglomeration of protein molecules (colloids) in the bulk solution. It also predicts a critical electrolyte concentration above which agglomeration will always occur. Using this theory, the rapid protein agglomeration occurring during Schlieren experiments as well as a terminal crystal size effect in a fixed container were explained. Following this concept, the supposed 'terminal' crystal size has been at least doubled.

Young, C. C.↗

NASA NTRS1990

The effect of latent heat release on synoptic-to-planetary scale wave interactions and implications for satellite observations: Observational study

Researchers have been exploring methods to facilitate the prediction of rapidly intensifying surface cyclones. Recognizing that synoptic-scale systems, such as these cyclones, are less predictable at medium range and beyond than are planetary-scale circulations, researchers propose that the planetary-scale environment for explosive cyclogenesis could be better predicted than the cyclones themselves. Researchers have therefore constructed a planetary-scale climatology of explosive cyclogenesis by compositing together filtered 500 mb height fields (retaining planetary waves only) corresponding to a large sample of rapidly intensifying surface cyclones, stratified geographically and according to the direction of 500 mb geostrophic flow (southwesterly, northwesterly or westerly) over the cyclone center. The composites are calculated from five days preceding to five days following each rapid cyclogenesis event, and have climatology subtracted so that the evolution of planetary-scale anomalies before and after cyclogenesis can be followed. Whether the anomalies are distinct from background variability and thus provide predictive value is now being evaluated. Following explosive cyclogenesis over which the filtered 500 mb flow is southwesterly, there appear in the composites large positive 500 mb height anomalies downstream. In some cases, these anomalies are associated with blocking patterns. Whether the objectively-defined blocking patterns in the data set are preceded by upstream intense surface cyclone activity is being investigated. Finally, the contribution of synoptic-scale processes, notably warm air advection, to planetary-scale height rises during a block formation following an explosive cyclogenesis event is being diagnosed. Researchers hope to eventually evaluate the impact of satellite derived latent heat release upon the warm air advection in this case.

Colucci, Stephen J.↗

NASA NTRS2021

Cutting out the Middleman: Calibrating and Validating a Dynamic Vegetation Model (ED2-PROSPECT5) Using Remotely Sensed Surface Reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types. Using a single common set of parameters across all sites, the calibrated model was able to accurately reproduce surface reflectance for sites with highly varied forest composition and structure. However, the calibrated model's predictions of leaf area index (LAI) were less robust, capturing only 46 % of the variability in the observations. Comparing the ED2 radiative transfer model with another two-stream soil–leaf–canopy radiative transfer model commonly used in remote sensing studies (PRO4SAIL) illustrated structural errors in the ED2 representation of direct radiation backscatter that resulted in systematic underestimation of reflectance. In addition, we also highlight that, to directly compare with a two-stream radiative transfer model like EDR, we had to perform an additional processing step to convert the directional reflectance estimates of AVIRIS to hemispherical reflectance (also known as “albedo”). In future work, we recommend that vegetation models add the capability to predict directional reflectance, to allow them to more directly assimilate a wide range of airborne and satellite reflectance products. We ultimately conclude that despite these challenges, using dynamic vegetation models to predict surface reflectance is a promising avenue for model calibration and validation using remote sensing data.

Alexey N Shiklomanov↗

DOE OSTI2025

Data-Driven Recommendation of Optimal Tuning Scheme for Range-Separated Hybrid Functionals in Solution-Phase UV/Vis Absorption Energy Prediction

Time-dependent density functional theory (TDDFT) combined with range-separated hybrid (RSH) functionals and a tuned range-separation parameter γ offers a computationally economical approach for high-throughput excited- state property predictions. The γ-tuning procedure in the gas phase is well established. However, no agreement on the best γ- tuning procedure has been made when considering the solvent effect with implicit solvent models like the polarizable continuum model (PCM). To answer that question, this study created a diverse dataset with 937 molecules with experimental solutionphase UV/vis absorption spectra. Three γ-tuning methods, the gasphase γ-tuning (GPγT), the partial vertical γ-tuning (PVγT), and the strict vertical γ-tuning (SVγT), were evaluated for the ωPBEh functional over the entire dataset. Additional benchmarks are done for the optimally tuned screened range-separated hybrid combined with the PCM approach (SRSH-PCM) and the solvation-mediated tuning procedure (sol-med-OT). Our findings revealed that the optimal γ-values obtained by the PVγT and the SVγT are significantly smaller than the GPγT. This trend holds consistently across all molecules in our dataset, and we explained the origin of this phenomenon. TDDFT calculations with PVγTand SVγT-tuned γ-values and default global Fock exchange fraction achieve superior performance compared to those using GPγTtuned or default γ and slightly outperform SRSH-PCM and sol-med-OT with similar or lesser computational cost. Furthermore, we found that the smaller γ-values from SVγT captured the expected 1/(εR) asymptotic behavior in the solution phase, resulting in accurate prediction of solution-phase CT excitations, consistent with the screened asymptote behavior encoded in SRSH-PCM. These results show that SVγT is the best scheme for high-throughput UV/vis absorption spectrum calculations using the ωPBEh functional from a data-driven perspective.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗