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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Sensitivity Analysis of Neutron Multiplicity Counting Statistics Using First-Order Perturbation Theory and Application to a Subcritical Plutonium Metal Benchmark

It is frequently important to estimate the uncertainty and sensitivity of measured and computed detector responses in subcritical experiments and simulations. These uncertainties arise from the physical construction of the experiment, uncertainties in the transport parameters, and counting uncertainties. Perturbation theory enables sensitivity analysis (SA) and uncertainty quantification on integral quantities like detector responses. Here the aim of our work is to apply SA to the statistics of subcritical neutron multiplicity counting distributions. Current SA methods have only been applied to mean detector responses and the keff eigenvalue. For multiplicity counting experiments, knowledge of the higher-order counting moments and their uncertainties are essential for a complete SA. We apply perturbation theory to compute the sensitivity of neutron multiplicity counting moments to arbitrarily high order. Each moment is determined by solving an adjoint transport equation with a source term that is a function of the adjoint solutions for lower-order moments. This enables moments of arbitrarily high order to be sequentially determined, and it shows that each moment is sensitive to the uncertainties of all lower-order moments. To close our SA of the moments, we derive forward transport equations that are functions of the forward flux and lower-order moment adjoint fluxes. We verify our calculations for the first three moments by comparison with multiplicity counting measurements of a subcritical plutonium metal sphere. For the first three moments, the most influential parameters are ranked, and the validity of first-order perturbation theory is demonstrated by examining the series truncation error. This enables a detailed SA of subcritical multiplicity counting measurements of fissionable material based on transport theory.

42 ENGINEERING↗
NASA NTRS1982

Computation of incompressible, three-dimensional turbulent boundary layers and comparison with experiment

Incompressible three dimensional, turbulent boundary layer (3DTBL) experiments were simulated numerically by integrating the boundary layer equations together with an algebraic eddy viscosity turbulence model. For the flow treated, the downstream portion, where the crossflow was large, was not predicted with the present computational method; the flow was significantly influenced by elliptic flow field effects. Departures from the boundary layer concept are indicated. Calculations agreed reasonably well with the mean flow development up to separation. In one experiment the normal pressure gradients were found to be neligible in regions with large skewing and allowed testing turbulence models using the boundary layer equations. The simulation of this flow compared favorably with the experimental data throughout the flow field and suggested the applicability of algebraic eddy viscosity models for 3DTBLs.

Mueller, U. R.↗
NASA NTRS2012

Large Eddy/Reynolds-Averaged Navier-Stokes Simulations of CUBRC Base Heating Experiments

ven with great advances in computational techniques and computing power during recent decades, the modeling of unsteady separated flows, such as those encountered in the wake of a re-entry vehicle, continues to be one of the most challenging problems in CFD. Of most interest to the aerothermodynamics community is accurately predicting transient heating loads on the base of a blunt body, which would result in reduced uncertainties and safety margins when designing a re-entry vehicle. However, the prediction of heat transfer can vary widely depending on the turbulence model employed. Therefore, selecting a turbulence model which realistically captures as much of the flow physics as possible will result in improved results. Reynolds Averaged Navier Stokes (RANS) models have become increasingly popular due to their good performance with attached flows, and the relatively quick turnaround time to obtain results. However, RANS methods cannot accurately simulate unsteady separated wake flows, and running direct numerical simulation (DNS) on such complex flows is currently too computationally expensive. Large Eddy Simulation (LES) techniques allow for the computation of the large eddies, which contain most of the Reynolds stress, while modeling the smaller (subgrid) eddies. This results in models which are more computationally expensive than RANS methods, but not as prohibitive as DNS. By complimenting an LES approach with a RANS model, a hybrid LES/RANS method resolves the larger turbulent scales away from surfaces with LES, and switches to a RANS model inside boundary layers. As pointed out by Bertin et al., this type of hybrid approach has shown a lot of promise for predicting turbulent flows, but work is needed to verify that these models work well in hypersonic flows. The very limited amounts of flight and experimental data available presents an additional challenge for researchers. Recently, a joint study by NASA and CUBRC has focused on collecting heat transfer data on the backshell of a scaled model of the Orion Multi-Purpose Crew Vehicle (MPCV). Heat augmentation effects due to the presence of cavities and RCS jet firings were also investigated. The high quality data produced by this effort presents a new set of data which can be used to assess the performance of CFD methods. In this work, a hybrid LES/RANS model developed at North Carolina State University (NCSU) is used to simulate several runs from these experiments, and evaluate the performance of high fidelity methods as compared to more typical RANS models. .

Salazar, Giovanni↗
DOE OSTI2025

Survey-wide asteroid discovery with a high-performance computing enabled non-linear digital tracking framework

Modern astronomical surveys detect asteroids by linking together their appearances across multiple images taken over time. This approach faces limitations in detecting faint asteroids and handling the computational complexity of trajectory linking. Here, we present a novel method that adapts “digital tracking” – traditionally used for short-term linear asteroid motion across images – to work with large-scale synoptic surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time (Rubin/LSST). Our approach combines hundreds of sparse observations of individual asteroids across their non-linear orbital paths to enhance detection sensitivity by several magnitudes. To address the computational challenges of processing massive data sets and dense orbital phase spaces, we developed a specialized high-performance computing architecture. We demonstrate the effectiveness of our method through experiments that take advantage of the extensive computational resources at Lawrence Livermore National Laboratory. This work enables the detection of significantly fainter asteroids in existing and future survey data, potentially increasing the observable asteroid population by orders of magnitude across different orbital families, from near-Earth objects (NEOs) to Kuiper belt objects (KBOs).

Asteroid discovery↗
DOE OSTI2025

Efficient Streaming Dynamic Mode Decomposition

We propose a reformulation of the streaming dynamic mode decomposition method that requires maintaining a single orthonormal basis, thereby reducing computational redundancy. The proposed efficient streaming dynamic mode decomposition method results in a constant-factor reduction in computational complexity and memory storage requirements. Numerical experiments on representative canonical dynamical systems show that the enhanced computational efficiency does not compromise the accuracy of the proposed method.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Computational fluid dynamics application to hypersonic flow over a Martian entry vehicle (MEV) - A correlation with experiment

A class of vehicles for a mission to Mars are analyzed for aerodynamic characteristics using advanced Computational Fluid Dynamics (CFD). The general configuration is a modified cone-conical-frustum geometry where the nose radius has a large influence on the flowfield. Inviscid-compressible flow using the Euler equations and viscous-compressible flow using the thin-layer Navier-Stokes equations is applied to the configuration. The surface modeling, grid generation and application of state-of-the-art CFD software are described. The effects of nose radius, angle of attack, and hypersonic velocity on the flight characteristics of the vehicle are discussed. The numerical simulations demonstrate the merits of the inviscid and viscous software. Results are compared with wind tunnel experiments.

Stewart, John E.↗
DOE OSTI2024

A linear response framework for quantum simulation of bosonic and fermionic correlation functions

Response functions are a fundamental aspect of physics; they represent the link between experimental observations and the underlying quantum many-body state. However, this link is often under-appreciated, as the Lehmann formalism for obtaining response functions in linear response has no direct link to experiment. Within the context of quantum computing, and via a linear response framework, we restore this link by making the experiment an inextricable part of the quantum simulation. This method can be frequency- and momentum-selective, avoids limitations on operators that can be directly measured, and can be more efficient than competing methods. As prototypical examples of response functions, we demonstrate that both bosonic and fermionic Green’s functions can be obtained, and apply these ideas to the study of a charge-density-wave material on the ibm_auckland superconducting quantum computer. The linear response method provides a robust framework for using quantum computers to study systems in physics and chemistry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Good Practices for High-Quality Scientific Computing

Experimental and observational sciences have developed robust practices for conducting experiments, maintaining their instruments, and record keeping for provenance. Computational science has only recently begun to confront the issue of quality of their instrument, the software, and the credibility of their scientific output. Most of the available literature in software engineering relates to enterprise software. While it can inform practices in scientific software, adjustments are usually needed. From time to time quality conscious practitioners have published collections of best practices for scientific software. Here, this article provides one more such list but with updated suggestions, motivated by the need to keep up with the rapid changes in the computing industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The emerging role of 4D synchrotron X-ray micro-tomography for climate and fossil energy studies: five experiments showing the present capabilities at beamline 8.3.2 at the Advanced Light Source

Here, continuous improvements at X-ray imaging beamlines at synchrotron light sources have made dynamic synchrotron X-ray micro-computed tomography (SXR-µCT) experiments more routinely available to users, with a rapid increase in demand given its tremendous potential in very diverse areas. In this work a survey of five different four-dimensional SXR-µCT experiments is presented, examining five different parameters linked to the evolution of the investigated system, and tackling problems in different areas in earth sciences. SXR-µCT is used to monitor the microstructural evolution of the investigated sample with the following variables: (i) high temperature, observing in situ oil shale pyrolysis; (ii) low temperature, replicating the generation of permafrost; (iii) high pressure, to study the invasion of supercritical CO 2 in deep aquifers; (iv) uniaxial stress, to monitor the closure of a fracture filled with proppant, in shale; (v) reactive flow, to observe the evolution of the hydraulic properties in a porous rock subject to dissolution. For each of these examples, it is shown how dynamic SXR-µCT was able to provide new answers to questions related to climate and energy studies, highlighting the significant opportunities opened recently by the technique.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations

Here, this work proposes a machine-learning framework for constructing statistical models of errors incurred by approximate solutions to parameterized systems of nonlinear equations. These approximate solutions may arise from early termination of an iterative method, a lower-fidelity model, or a projection-based reduced-order model, for example. The proposed statistical model comprises the sum of a deterministic regression-function model and a stochastic noise model. The method constructs the regression-function model by applying regression techniques from machine learning (e.g., support vector regression, artificial neural networks) to map features (i.e., error indicators such as sampled elements of the residual) to a prediction of the approximate-solution error. The method constructs the noise model as a mean-zero Gaussian random variable whose variance is computed as the sample variance of the approximate-solution error on a test set; this variance can be interpreted as the epistemic uncertainty introduced by the approximate solution. This work considers a wide range of feature-engineering methods, data-set-construction techniques, and regression techniques that aim to ensure that (1) the features are cheaply computable, (2) the noise model exhibits low variance (i.e., low epistemic uncertainty introduced), and (3) the regression model generalizes to independent test data. Finally, numerical experiments performed on several computational-mechanics problems and types of approximate solutions demonstrate the ability of the method to generate statistical models of the error that satisfy these criteria and significantly outperform more commonly adopted approaches for error modeling.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

An optical study of grain formation: Casting and solidification technology (2-IML-1)

By studying the unidirectional growth of a metal-model material in microgravity, an attempt is made to characterize alloy solidification. Using holograms and supporting temperature measurements obtained during processing in the Fluids Experiment System (FES), the solute and thermal fields associated with the dendrite growth front and extraneous nucleation will be measured and compared to a theoretical (computational) model. Ground based supporting experiments include particle tracking to measure the velocity fields, and optical phase shift techniques (confocal optical signal processing, interferometry, and Schlieren) to study thermal and solutal fields.

Mccay, Mary H.↗
NASA NTRS1993

Numerical study of shock-induced combustion in methane-air mixtures

The shock-induced combustion of methane-air mixtures in hypersonic flows is investigated using a new reaction mechanism consisting of 19 reacting species and 52 elementary reactions. This reduced model is derived from a full kinetic mechanism via the Detailed Reduction technique. Zero-dimensional computations of several shock-tube experiments are presented first. The reaction mechanism is then combined with a fully implicit Navier-Stokes computational fluid dynamics (CFD) code to conduct numerical simulations of two-dimensional and axisymmetric shock-induced combustion experiments of stoichiometric methane-air mixtures at a Mach number of M = 6.61. Applications to the ram accelerator concept are also presented.

Yungster, Shaye↗
DOE OSTI2015

Li{sub 2}Ca{sub 2}Si{sub 2}O{sub 7}: Structural, spectroscopic and computational studies on a sorosilicate

Synthesis experiments in the system Li{sub 2}O–CaO–SiO{sub 2} resulted in the formation of single-crystals of Li{sub 2}Ca{sub 2}Si{sub 2}O{sub 7}. Structural investigations were based on single-crystal diffraction. At ambient conditions the compound has the following basic crystallographic data: hexagonal symmetry, space group P6{sub 1}22, a=5.0961(2) Å, c=41.264(2) Å, V=928.07(6) Å{sup 3}, Z=6. Structure solution was performed using direct methods. The final least-squares refinement calculations converged at a residual of R(|F|)=0.0260. From a structural point the lithium calcium silicate belongs to the group of pyrosilicates containing [Si{sub 2}O{sub 7}]-groups. Additional lithium and calcium cations are incorporated between the silicate dimers and are coordinated by four and six nearest oxygen neighbours, respectively. Each [LiO{sub 4}]-tetrahedron shares two common corners with directly neighboring tetrahedra forming zweier single-chains which are running parallel to 〈1 0 0〉 in z-levels defined by the presence of the 6{sub 1}{sup [0} {sup 0} {sup 1]}-screw axes. From the corner-sharing [LiO{sub 4}]- and [SiO{sub 4}]-moieties a three dimensional framework can be constructed. An interesting feature of this framework is the presence of an O{sup [3]}-type bridging oxygen linking three tetrahedra (one [LiO{sub 4}]- and two [SiO{sub 4}]-units). Structural similarities with other silicates are discussed in detail. The high-temperature behavior of the Si–O, Ca–O and Li–O bond distances in Li{sub 2}Ca{sub 2}Si{sub 2}O{sub 7} was investigated by in{sub -}situ single-crystal X-ray diffraction in the range between 65 and 700 °C. From the evolution of the lattice parameters, the thermal expansion tensor α{sub ij} has been determined. The structural characterization has been supplemented by micro-Raman spectroscopy. Interpretation of the spectroscopic data including the allocation of the bands to certain vibrational species has been aided by DFT-calculations. - Graphical abstract: Framework of [SiO{sub 4}]- and [LiO{sub 4}]-tetrahedra in the crystal structure of Li{sub 2}Ca{sub 2}Si{sub 2}O{sub 7}. - Highlights: • We report the crystal structure of the sorosilicate Li{sub 2}Ca{sub 2}Si{sub 2}O{sub 7} at ambient conditions. • The thermal expansion tensor as well as the evolution of the structure between 25 and 700 °C was studied. • A topological analysis of the tetrahedral framework based on [SiO{sub 4}]- and [LiO{sub 4}]-units is presented. • The crystal structure of Li{sub 2}Ca{sub 2}Si{sub 2}O{sub 7} is discussed with respect to related compounds. • Interpretation of the Raman spectra of the crystals has been aided by DFT-calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Antiviral discovery using sparse datasets by integrating experiments, molecular simulations, and machine learning

Computational methods have demonstrated success in identifying virucidal agents, effectively contributing to the discovery of novel virucidal molecules. In this study, we developed a machine learning (ML) model, trained on a small dataset, to predict inhibitors of human enterovirus 71 (EV71), a pathological agent that causes severe disease in children and immunocompromised adults. Despite the dataset’s limitation, comprising of only 36 compounds tested, our ML framework demonstrated significant predictive capability. Notably, experimental validation revealed that five out of the eight compounds predicted by our model from the Chinese cosmetic material list exhibited virucidal activity. The inhibitor effects displayed by the main active compounds were further confirmed by molecular dynamics simulation. This underscores the potential of our AI-driven approach to bypass data constraints in identifying active molecules against viral pathogens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

First principles modeling of polymer encapsulant degradation in Si photovoltaic modules

An outstanding issue in the longevity of photovoltaic (PV) modules is the accelerated degradation caused by the presence of moisture. Moisture leads to interfacial instability, de-adhesion, encapsulant decomposition, and contact corrosion. However, experimental characterization of moisture in PV modules is not trivial and its impacts can take years or decades to establish in the field, presenting a major obstacle to designing high-reliability modules. First principles calculations provide an alternative way to study the ingress of water and its detrimental effect on the structure and decomposition of the polymer encapsulant and interfaces between the encapsulant and the semiconductor, the metal contacts, or the dielectric layer. Here, we use density functional theory (DFT) computations to model single chain, crystalline and cross-linked structures, infrared (IR) signatures, and degradation mechanisms of ethylene vinyl acetate (EVA), the most common polymer encapsulant used in Si PV modules. IR-active modes computed for low energy EVA structures and possible decomposition products match well with reported experiments. The EVA decomposition energy barriers computed using the Nudged Elastic Band (NEB) method show a preference for acetic acid formation as compared to acetaldehyde, are lowered in the presence of a water solvent or hydroxyl ion catalyst, and match well with reported experimental activation energies. This systematic study leads to a clear picture of the hydrolysis-driven decomposition of EVA in terms of energetically favorable mechanisms, possible intermediate structures, and IR signatures of reactants and products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1971

Numerical experiments with a disk of stars

Computer model for dynamical evolution of isolated disks of stars with initial velocity dispersions corresponding to Toomre criterion, noting instability relative to large scale modes

Hohl, F.↗
NASA NTRS1981

Investigation of models for large-scale meteorological prediction experiments

An attempt is made to compute the contributions of various surface boundary conditions to the monthly mean states generated by the 7 layer, 8 x 10 GISS climate model (Hansen et al., 1980), and also to examine the influence of initial conditions on the model climate simulations. Obvious climatic controls as the shape and rotation of the Earth, the solar radiation, and the dry composition of the atmosphere are fixed, and only the surface boundary conditions are altered in the various climate simulations.

Spar, J.↗