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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
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 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.↗
NASA NTRS1991

A research program in empirical computer science

During the grant reporting period our primary activities have been to begin preparation for the establishment of a research program in experimental computer science. The focus of research in this program will be safety-critical systems. Many questions that arise in the effort to improve software dependability can only be addressed empirically. For example, there is no way to predict the performance of the various proposed approaches to building fault-tolerant software. Performance models, though valuable, are parameterized and cannot be used to make quantitative predictions without experimental determination of underlying distributions. In the past, experimentation has been able to shed some light on the practical benefits and limitations of software fault tolerance. It is common, also, for experimentation to reveal new questions or new aspects of problems that were previously unknown. A good example is the Consistent Comparison Problem that was revealed by experimentation and subsequently studied in depth. The result was a clear understanding of a previously unknown problem with software fault tolerance. The purpose of a research program in empirical computer science is to perform controlled experiments in the area of real-time, embedded control systems. The goal of the various experiments will be to determine better approaches to the construction of the software for computing systems that have to be relied upon. As such it will validate research concepts from other sources, provide new research results, and facilitate the transition of research results from concepts to practical procedures that can be applied with low risk to NASA flight projects. The target of experimentation will be the production software development activities undertaken by any organization prepared to contribute to the research program. Experimental goals, procedures, data analysis and result reporting will be performed for the most part by the University of Virginia.

Knight, J. C.↗
NASA NTRS1992

Database computing in HEP

The major SSC experiments are expected to produce up to 1 Petabyte of data per year each. Once the primary reconstruction is completed by farms of inexpensive processors, I/O becomes a major factor in further analysis of the data. We believe that the application of database techniques can significantly reduce the I/O performed in these analyses. We present examples of such I/O reductions in prototypes based on relational and object-oriented databases of CDF data samples.

Day, C. T.↗
DOE OSTI2020

Photoproduction of Cascade Baryons Using the GlueX Detector at Jefferson Laboratory

Multi-strange baryons have played an important role in understanding the strong interaction. Despite their importance to advancing quantum chromodynamics (QCD), little is known about such hyperons due to the lack of a strange probe. Almost all knowledge of Cascade baryons today stems from kaon-nucleon interactions in bubble chamber experiments performed in the 1960s and 1970s. The 1980s saw advancement in electronics and computational resources allowing for higher statistic experiments such as the MultiParticle Spectrometer (MPS) at Brookhaven National Laboratory. From these previous experiments, the octet and decuplet ground states, Xi(1320) and Xi(1530) respectively, were well established with known properties and four excited states were well established. This research uses the GlueX experiment at Jefferson Laboratory to extend photoproduction cross section measurements for Xi(1320)- to higher beam energies to further understand the production mechanism, as well as to search for the first excited Cascade resonance observation in photoproduction through the decay Xi-* -> K-Lambda. The GlueX Spectrometer is a nearly hermetic detector used to study exclusive photoproduction reactions with photon beam energies up to 12 GeV. The first phase of GlueX running has recently been completed. Preliminary results for the total cross section and differential cross sections in terms of momentum transfer -t are shown within. Additionally, the first observation of an excited Cascade baryon, in particular Xi(1820)-, is shown.

Ernst, Ashley↗
DOE OSTI2025

Track reconstruction as a service for collider physics

Optimizing charged-particle track reconstruction algorithms is crucial for efficient event reconstruction in Large Hadron Collider (LHC) experiments due to their significant computational demands. Existing track reconstruction algorithms have been adapted to run on massively parallel coprocessors, such as graphics processing units (GPUs), to reduce processing time. Nevertheless, challenges remain in fully harnessing the computational capacity of coprocessors in a scalable and non-disruptive manner. This paper proposes an inference-as-a-service approach for particle tracking in high energy physics experiments. To evaluate the efficacy of this approach, two distinct tracking algorithms are tested: Patatrack, a rule-based algorithm, and Exa.TrkX, a machine learning-based algorithm. The as-a-service implementations show enhanced GPU utilization and can process requests from multiple CPU cores concurrently without increasing per-request latency. The impact of data transfer is minimal and insignificant compared to running on local coprocessors. This approach greatly improves the computational efficiency of charged particle tracking, providing a solution to the computing challenges anticipated in the High-Luminosity LHC era.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1991

On the quasi-conical flowfield structure of the swept shock wave-turbulent boundary layer interaction

The swept oblique shock-wave/turbulent-boundary-layer interaction generated by a 20-deg sharp fin at Mach 4 and Reynolds number 21,000 is investigated via a series of computations using both conical and three-dimensional Reynolds-averaged Navier-Stokes equations with turbulence incorporated through the algebraic turbulent eddy viscosity model of Baldwin-Lomax. Results are compared with known experimental data, and it is concluded that the computed three-dimensional flowfield is quasi-conical (in agreement with the experimental data), the computed three-dimensional and conical surface pressure and surface flow direction are in good agreement with the experiment, and the three-dimensional and conical flows significantly underpredict the peak experimental skin friction. It is pointed out that most of the features of the conical flowfield model in the experiment are observed in the conical computation which also describes the complete conical streamline pattern not included in the model of the experiment.

Knight, Doyle D.↗
NASA NTRS1977

MCSCF + Cl wavefunctions and properties of the X2-Pi and A2-Pi states of ClO

A multiconfiguration, self-consistent field plus configuration-interaction calculation has been performed on the X2-Pi and A2-Pi electronic states of ClO. The values of certain molecular properties computed from the wavefunctions agree well with those from experiment. The sum of the squares of the computed electronic transition moments between the X2-Pi and A2-Pi states at 3.07 bohr is 1.75 a.u., which corresponds to the experimental result of 1.58 plus or minus 0.20 a.u. The computed ground state dipole moment at the experimental equilibrium separation is 1.232 D, which compares well with two experimental results of 1.18 plus or minus 0.12 and 1.239 plus or minus 0.010 D. The value of the computed dissociation energy is 2.75 eV, which agrees well with the experimental value of 2.803 plus or minus 0.001 eV.

Arnold, J. O.↗
DOE OSTI2020

Application of an Embedded Fracture and Borehole Modeling Approach to the Understanding of EGS Collab Experiment 1

EGS Collab is a series of meso-scale experiments and associated numerical simulation activities being funded by the United States Department of Energy, Geothermal Technologies Office (GTO) to investigate enhanced geothermal system processes under in-situ stress and slightly elevated temperature conditions. This project is designed to provide scientists and engineers with immediate access to impermeable rock at scales larger than possible in the laboratory, but generally smaller than those for commercial production. Immediate access to rock is provided via the existing drifts of the former Homestake Gold Mine, now operated as the Sanford Underground Research Facility in Lead, South Dakota. The objectives of the EGS Collab project are to develop well controlled fracture networks between injector and producer boreholes using normal and shear stimulation for permeability enhancement. The first experimental site was located off the West Access drift on the 4850 Level (4850 feet below ground surface) in phyllite of the Precambrian Poorman formation, and involved the creation of a fracture network comprising a combination of hydraulic and natural fractures. A second experimental site is now being considered near the battery alcove on the 4100 Level in amphibolite and rhyolite of the Yates Unit. Data generated during these experiments will be compared against predictions of a suite of computer codes specifically designed to solve problems involving coupled thermal, hydrological, geomechanical, and geochemical processes. Comparisons between experimental and numerical simulation results will provide code developers with direction for improvements and verification of process models, build confidence in the suite of available numerical tools, and ultimately identify critical future development needs for the geothermal modeling community. Moreover, conducting thorough comparisons of models, modelling approaches, measurement approaches and measured data, via the EGS Collab project, will serve to identify techniques that are most likely to succeed at the Frontier Observatory for Research in Geothermal Energy (FORGE), the GTO’s flagship EGS research effort. Experiment 1 has comprised a series of successful tests, including a long-term chilled-water circulation test, but the testbed has two atypical EGS elements. Active ventilation in the adjacent drift over a 50-year period cooled the testbed rock mass and hydraulic fracturing intersected monitoring boreholes making them conduits for fluid flow. Numerical simulations executed in support of the design of the EGS Collab Experiment 1, computed a radial temperature distribution and stress gradient orthogonal to the drift axis, resulting in the forecast of an oblong hydraulic fracture geometry, extended in the direction of the drift from the stimulation borehole. This paper describes the numerical simulation of long-term chilled-water circulation test with an embedded fracture and borehole modeling approach. The principal objective of the simulation work is show agreement between experimental observations in terms of production fluid temperatures, monitoring borehole temperatures, injection and production pressures, and tracer recoveries using a single conceptual model for the fracture network, using characterization and monitoring data generally available for EGS. A secondary objective is to improve the numerical simulation result comparisons with additional data available from the broader monitoring equipment within the testbed versus deeper, hotter, and more remote EGS. One complicating factor for comparisons between the numerical simulation results and experimental observations, is the Joule-Thomson heating associated with large pressure drops across the fracture network.

numerical simulation, embedded fractures and boreh↗
NASA NTRS2002

The NASA Integrated Vehicle Health Management Technology Experiment for X-37

The NASA Integrated Vehicle Health Management (IVHM) Technology Experiment for X-37 was intended to run IVHM software on-board the X-37 spacecraft. The X-37 is intended to be an unpiloted vehicle that would orbit the Earth for up to 21 days before landing on a runway. The objectives of the experiment were to demonstrate the benefits of in-flight IVHM to the operation of a Reusable Launch Vehicle, to advance the Technology Readiness Level of this IVHM technology within a flight environment, and to demonstrate that the IVHM software could operate on the Vehicle Management Computer. The scope of the experiment was to perform real-time fault detection and isolation for X-37's electrical power system and electro-mechanical actuators. The experiment used Livingstone, a software system that performs diagnosis using a qualitative, model-based reasoning approach that searches system-wide interactions to detect and isolate failures. Two of the challenges we faced were to make this research software more efficient so that it would fit within the limited computational resources that were available to us on the X-37 spacecraft, and to modify it so that it satisfied the X-37's software safety requirements. Although the experiment is currently unfunded, the development effort had value in that it resulted in major improvements in Livingstone's efficiency and safety. This paper reviews some of the details of the modeling and integration efforts, and some of the lessons that were learned.

Schwabacher, Mark↗
NASA NTRS1993

Designers' models of the human-computer interface

Understanding design models of the human-computer interface (HCI) may produce two types of benefits. First, interface development often requires input from two different types of experts: human factors specialists and software developers. Given the differences in their backgrounds and roles, human factors specialists and software developers may have different cognitive models of the HCI. Yet, they have to communicate about the interface as part of the design process. If they have different models, their interactions are likely to involve a certain amount of miscommunication. Second, the design process in general is likely to be guided by designers' cognitive models of the HCI, as well as by their knowledge of the user, tasks, and system. Designers do not start with a blank slate; rather they begin with a general model of the object they are designing. The author's approach to a design model of the HCI was to have three groups make judgments of categorical similarity about the components of an interface: human factors specialists with HCI design experience, software developers with HCI design experience, and a baseline group of computer users with no experience in HCI design. The components of the user interface included both display components such as windows, text, and graphics, and user interaction concepts, such as command language, editing, and help. The judgments of the three groups were analyzed using hierarchical cluster analysis and Pathfinder. These methods indicated, respectively, how the groups categorized the concepts, and network representations of the concepts for each group. The Pathfinder analysis provides greater information about local, pairwise relations among concepts, whereas the cluster analysis shows global, categorical relations to a greater extent.

Gillan, Douglas J.↗
DOE OSTI2024

Transfer learning for probabilistic localization of hidden cracks in concrete structures

Abstract The utility of discriminative supervised learning models built using multiple training-data sources is investigated for hidden crack localization in concrete. Feed-forward neural network (FFNN) is chosen as the model architecture, and transfer learning is used to assimilate the information obtained from different sources (computational physics simulations and laboratory experiments). The labeled training data consists of values of a damage index and the known locations of hidden cracks. The classification models need to learn how the presence of damage (hidden cracks) affects the damage index at different sensors for different test conditions. To this end, diagnostic FFNN models are built by sequentially adding and training new hidden layers to assimilate labeled information from computer models (different model geometries, test conditions, crack lengths, crack locations) and laboratory experiments on a plain cement slab. These transfer learning-based models are then used to localize damage in concrete specimens that reflect real-world conditions (i.e., specimens with steel reinforcement and randomly distributed aggregate). The actual damage state in these specimens is determined by extracting cores and performing petrographic studies on the extracted cores. The damage probability estimated by transfer learning-based models is compared with the petrographic damage rating index (DRI) to identify the most suitable approach to train the diagnostic models. The transfer learning-based diagnostic methodology shows promise and could be used in various structural health monitoring applications, where sufficient labeled data are typically not available from a single data source.

Miele, S.↗