SEARCH · Engineering Papers

Results for “component model”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,585 records · Page 88

All sources NASA NTRS DOE OSTI

NASA NTRS2002

Estimating Single-Trial Responses in EEG

Accurate characterization of single-trial field potential responses is critical from a number of perspectives. For example, it allows differentiation of an evoked response from ongoing EEG. We previously developed the multiple component Event Related Potential (mcERP) algorithm to improve resolution of the single-trial evoked response. The mcERP model states that multiple components, each specified by a stereotypic waveform varying in latency and amplitude from trial to trial, comprise the evoked response. Application of the mcERP algorithm to simulated data with three independent, synthetic components has shown that the model is capable of separating these components and estimating their variability. Application of the model to single trial, visual evoked potentials recorded simultaneously from all V1 laminae in an awake, fixating macaque yielded local and far-field components. Certain local components estimated by the model were distributed in both granular and supragranular laminae. This suggests a linear coupling between the responses of thalamo-recipient neuronal ensembles and subsequent responses of supragranular neuronal ensembles, as predicted by the feedforward anatomy of V1. Our results indicate that the mcERP algorithm provides a valid estimation of single-trial responses. This will enable analyses that depend on trial-to-trial variations and those that require separation of the evoked response from background EEG rhythms

Shah, A. S.↗

NASA NTRS1980

X-ray observations of Algol

Observations of Algol using a solid state spectrometer onboard the Einstein Observatory are discussed. Two observations six months apart were made, both during a primary optical eclipse. No corresponding X-ray eclipses were seen. During the second observation the source was flaring and was on average a factor three brighter. The spectrum on both occasions was consistent with a two-component thermal equilibrium model with temperatures of approximately 7.5 and 40 million degrees. Attempts to insert a third component indicate the temperature distribution to be bimodal. Models for the X-ray emission are discussed and it is suggested that the emission most likely originates from an active corona surrounding the K star.

White, N. E.↗

NASA NTRS1980

X-ray observations of Algol

The Solid State Spectrometer on Einstein has been used to study Algol. Two observations six months apart were made, both including a primary optical eclipse. No corresponding X-ray eclipses were seen. During the second observation the source was flaring and was on the average a factor of three brighter. The spectrum on both occasions was consistent with a two-component thermal equilibrium model with temperatures of approximately 7.5 and 40 million degrees. Attempts to insert a third component indicate the temperature distribution to be bimodal. Models for the X-ray emission are discussed and it is suggested that it most likely originates from an active corona surrounding the K star.

White, N. E.↗

DOE OSTI2022

Modeling interconnections of safety and financial performance of nuclear power plants, part 3: Spatiotemporal probabilistic physics-of-failure analysis and its connection to safety and financial performance

Here, this paper is a byproduct of a line of research by the authors to analyze interrelationships of safety and financial performance of nuclear power plants (NPPs). The result of this line of research is summarized in three parts: Part 1 covers a categorical review of relevant literature and the theoretical bases that support the methodological developments in Part 2. Part 2 introduces an Integrated Enterprise Risk Management (I-ERM) methodological framework to quantify the interconnections of safety and financial performance with a focus on operation and maintenance (O&M) of NPPs. Part 2 has also demonstrated the applicability and values of the I-ERM methodology through an NPP case study. This paper is Part 3, where detailed development and implementation of one of the I-ERM modules, i.e., probabilistic physics-of-failure (PPoF) analysis, and its connection with safety and financial performance is reported. In this article, the physical failure modeling for hardware components is advanced by incorporating finite element analysis (FEA) into PPoF analysis and coupling the FEA-based PPoF with the maintenance performance through a renewal process model. This article covers two scientific contributions: (i) first-of-its-kind incorporation of FEA into the PPoF model of thermal fatigue for NPP components; and (ii) advancing the interface between the PPoF analysis and the renewal process model in order to deal with spatiotemporal FEA outputs and to efficiently estimate the physical transition rates even when the PPoF outputs are dominated by success data. Through the incorporation of FEA, the resolution of the PPoF analysis is enhanced as spatiotemporal conditions such as stress and temperature can be considered explicitly instead of relying on simplified assumptions or analytical models with reduced spatiotemporal dimensions. To demonstrate an application of the FEA-based PPoF analysis and its coupling with maintenance through the renewal process model, a case study is conducted using excess letdown elbow piping in the chemical and volume control system of a Pressurized Water Reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Ab initio property predictions of quinary solid solutions using small binary cells

The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density functional theory calculations relative to other well-known techniques such as cluster expansions and special quasirandom structures for modelling solid solutions. Here in this work, we demonstrate that SSOS’s can be constructed using cells with only a subset of elements while still accurately modelling multi-component systems. Specifically, we show that small binary cells can effectively model two quinary high entropy alloys – NbTaTiHfZr and MoNbTaVW – accurately capturing properties such as formation energy, lattice parameters, elastic constants, and root-mean-square atomic displacements. Overall, this insight is useful for those looking to construct databases of such small structures for predicting the properties of multi-component solid solutions, as it greatly decreases the number of structures that needs to be considered.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Evaluating model accuracy for model-based reasoning

Described here is an approach to automatically assessing the accuracy of various components of a model. In this approach, actual data from the operation of a target system is used to drive statistical measures to evaluate the prediction accuracy of various portions of the model. We describe how these statistical measures of model accuracy can be used in model-based reasoning for monitoring and design. We then describe the application of these techniques to the monitoring and design of the water recovery system of the Environmental Control and Life Support System (ECLSS) of Space Station Freedom.

Chien, Steve↗

NASA NTRS1992

Modeling of membrane processes for air revitalization and water recovery

Gas-separation and reverse-osmosis membrane models are being developed in conjunction with membrane testing at NASA JSC. The completed gas-separation membrane model extracts effective component permeabilities from multicomponent test data, and predicts the effects of flow configuration, operating conditions, and membrane dimensions on module performance. Variable feed- and permeate-side pressures are considered. The model has been applied to test data for hollow-fiber membrane modules with simulated cabin-air feeds. Results are presented for a membrane designed for air drying applications. Extracted permeabilities are used to predict the effect of operating conditions on water enrichment in the permeate. A first-order reverse-osmosis model has been applied to test data for spiral wound membrane modules with a simulated hygiene water feed. The model estimates an effective local component rejection coefficient under pseudosteady-state conditions. Results are used to define requirements for a detailed reverse-osmosis model.

Lange, Kevin E.↗

DOE OSTI2024

Seismic Signal Detection on International Monitoring System 3-Component Stations using PhaseNet

In this report we discuss training a deep learning seismic signal detection model on 3-component stations from the International Monitoring System (IMS) using the PhaseNet architecture. Using 14 years of associated signals from the International Data Centre’s (IDC) Late Event Bulletin (LEB), we auto-curated training data consisting of signal windows containing associated arrivals, and noise windows that contain no LEB-associated signals. We trained several models using different waveform window durations (30 seconds and 100 seconds), with and without bandpass filtering. We evaluated the effectiveness of our models using associated signals from the Unconstrained Global Event Bulletin (UGEB) and found that several of our models outperformed the signal detections from the IDC’s Selected Event List 3 (SEL3) arrival table. The SEL3 bulletin evaluated on the UGEB dataset with 100-second waveform windows registered a precision and recall of .15 and .48, respectively, versus .19 and .59 for our filtered-data model. For the 30-second waveform window dataset, the SEL3 bulletin achieved a precision and recall of .31 and .47, respectively, versus .32 and .60 for our filtered-data model. Finally, our models detected signals from all source-to-receiver distances, suggesting it is feasible to use a single PhaseNet model for the IMS network.

58 GEOSCIENCES↗

DOE OSTI2025

A Computational Tool Compatible with NEAMS Code Packages for Optimizing the Shape of Nuclear Reactor Components and of Whole Core Performance

We designed and implemented a shape optimization tool that functions with NEAMS codes, and that nuclear scientists and engineers can employ to optimize the shape of individual components and the whole core under the applicable single- or multi-physics model comprising the employed code(s). The shape-optimization tool enables varying the geometric shape itself as well as its dimensions to yield, potentially, new component designs that are not limited by the designer’s intuition and previous experience. In cases where the optimal-shape object is an individual component, we provide the capability for additional verification that the whole-core performance using the optimized component performs better, under the prescribed optimization criteria, than the initial design. Our shape-optimization tool couples to NEAMS codes via a flexible input- composer interface and enables the user to constrain the shape’s evolution to ensure the component’s manufacturability. Finally, we demonstrate our shape-optimization tool with single- and multi-physics NEAMS codes. This objective is motivated by the recent advances in manufacturing technology that, combined with rising interest in novel reactor concepts, are creating new opportunities for innovation in the design of individual components that affect the performance of the full reactor system. In particular, Additive Manufacturing (AM) enables mass production of highly precise, intricate and complex component shapes that are not feasible with traditional manufacturing techniques. To accomplish this goal we developed and implemented in MOOSE: (1) discrete shape optimization capability based on a state-space search that uses Artificial Intelligence strategies to find the optimal state/shape; (2) smooth shape optimization tool that employs PETSc’s toolkit for advanced optimization (TAO) to optimize node-displacement of the components’ model sidesets; (3) hierarchical core optimization workflow that recognizes the repeating patterns typical in a nuclear reactor and performs the optimization one level at a time with increasing length scale. Each of these tools is equipped with user-specified constraints to avoid optimal shapes that are not manufacturable. The developed shape optimization tool is verified and demonstrated on various nuclear reactor core components and models. The optimization process accounts for tightly coupled physics that govern the behavior of these target reactors, and exercises several NEAMS codes in a coupled multiphysics fashion. The impact of the delivered shape optimization tool will materialize in the optimal design, from the outset, of advanced reactors currently contemplated to regain the US’s leadership in nuclear energy R&D. Novel reactor concepts, e.g. Molten Salt Reactors, and sizes/capacities, e.g. micro- reactors, provide a unique opportunity to optimize performance from the early stages of development, before the investment in components’ production lines, validation experiments, and licensing regimes make future improvements in performance prohibitively expensive and force sub-optimal performance on the affected reactor concept in perpetuity. This benefit will be realized by the delivered shape optimization tool regardless of the applicable manufacturing process whether traditional or AM, thereby broadening the impact of this project on current and future reactor concepts and technologies

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2013

Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS

The Mars Exploration Rovers (MERs), Spirit and Opportunity, far exceeded their original drive distance expectations and have traveled, at the time of this reporting, a combined 29 kilometers across the surface of Mars. The Rover Sequencing and Visualization Program (RSVP), the current program used to plan drives for MERs, is only a kinematic simulator of rover movement. Therefore, rover response to various terrains and soil types cannot be modeled. Although sandbox experiments attempt to model rover-terrain interaction, these experiments are time-intensive and costly, and they cannot be used within the tactical timeline of rover driving. Imaging techniques and hazard avoidance features on MER help to prevent the rover from traveling over dangerous terrains, but mobility issues have shown that these methods are not always sufficient. ARTEMIS, a dynamic modeling tool for MER, allows planned drives to be simulated before commands are sent to the rover. The deformable soils component of this model allows rover-terrain interactions to be simulated to determine if a particular drive path would take the rover over terrain that would induce hazardous levels of slip or sink. When used in the rover drive planning process, dynamic modeling reduces the likelihood of future mobility issues because high-risk areas could be identified before drive commands are sent to the rover, and drives planned over these areas could be rerouted. The ARTEMIS software consists of several components. These include a preprocessor, Digital Elevation Models (DEMs), Adams rover model, wheel and soil parameter files, MSC Adams GUI (commercial), MSC Adams dynamics solver (commercial), terramechanics subroutines (FORTRAN), a contact detection engine, a soil modification engine, and output DEMs of deformed soil. The preprocessor is used to define the terrain (from a DEM) and define the soil parameters for the terrain file. The Adams rover model is placed in this terrain. Wheel and soil parameter files can be altered in the respective text files. The rover model and terrain are viewed in Adams View, the GUI for ARTEMIS. The Adams dynamics solver calls terramechanics subroutines in FORTRAN containing the Bekker-Wong equations.

Trease, Brian P.↗

NASA NTRS1992

Modeling the stellar contribution to the Galactic component of the diffuse soft X-ray background. I - Background fluxes and number counts

A combination of a stellar Galaxy model based on optical data, stellar X-ray luminosity functions derived from the full Einstein base, and a model for X-ray absorption derived from hydrogen column densities are used to estimate the contribution to the diffuse soft X-ray background flux from the main-sequence A, F, G, K, and M stars, and RS CVn stars, at various energies ranging from 0.1 to about 5 keV. Previous discrepancies between earlier estimates of the stellar contribution to the diffuse soft X-ray background are resolved; this stellar contribution to the diffuse soft X-ray background is found to be under 3 percent for photon energies less than energy I and J bands (about 0.8-2 keV), at a threshold sensitivity for point source detection about 10 exp -10 ergs/s sq cm. At low latitudes, stellar contribution estimates are less than 3 percent below 0.3 keV, 7-40 percent in the medium-energy bands, and 27-70 percent in the I and J bands. It is shown that while dM stars are the major contributors to the diffuse stellar flux, other stellar types contribute as much as 40 percent of this flux at the higher energies in the passband studied.

Kashyap, V.↗

DOE OSTI2023

A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks

Hyperbolic neural networks have recently gained significant attention due to their promising results on several graph problems including node classification and link prediction. The primary reason for this success is the effectiveness of hyperbolic space in capturing the inherent hierarchy of graph datasets. However, they are limited in terms of generalization, scalability, and have inferior performance when applied to non-hierarchical datasets. In this paper, we take a completely different perspective for modeling hyperbolic networks and answer the following question: is an Euclidean model able to approximate a function or behavior in the hyperbolic space? Extending the universal approximation theory developed for Euclidean models, We draw an analogy from the hyperbolic components to the Euclidean counterparts and conclude that, in order to capture hierarchical features, it is possible to generalize hyperbolic models to be a special case of Euclidean models with the proposed Pseudo-Poincaré technique. We applied our non-linear hyperbolic normalization to the current state-of-the-art homogeneous and multi-relational graph networks and demonstrate significant improvements in performance compared to both Euclidean and hyperbolic counterparts. The primary impact of this work lies in its ability to capture hierarchical features in the Euclidean space, and thus, can replace hyperbolic networks without any loss in performance metrics while simultaneously leveraging the power of Euclidean networks such as interpretability and efficient execution of various model components.

Khatir, Mehrdad↗

NASA NTRS1995

Nonlinear structure formation in flat cosmological models

This paper describes the formation of nonlinear structure in flat (zero curvature) Friedmann cosmological models. We consider models with two components: the usual nonrelativistic component that evolves under gravity and eventually forms the large-scale structure of the universe, and a uniform dark matter component that does not clump under gravity, and whose energy density varies with the scale factor a(t) like a(t)(sup -n), where n is a free parameter. Each model is characterized by two parameters: the exponent n and the present density parameter Omega(sub 0) of the nonrelativistic component. The linear perturbation equations are derived and solved for these models, for the three different cases n = 3, n is greater than 3, and n is less than 3. The case n = 3 is relevant to model with massive neutrinos. The presence of the uniform component strongly reduces the growth of the perturbation compared with the Einstein-de Sitter model. We show that the Meszaros effect (suppression of growth at high redshift) holds not only for n = 4, radiation-dominated models, but for all models with n is greater than 3. This essentially rules out any such model. For the case n is less than 3, we numerically integrate the perturbation equations from the big bang to the present, for 620 different models with various values of Omega(sub 0) and n. Using these solutions, we show that the function f(Omega(sub 0), n) = (a/delta(sub +))d(delta)(sub +)/da, which enters in the relationship between the present density contrast delta(sub 0) and peculiar velocity field u(sub 0) is essentially independent of n. We derive approximate solutions for the second-order perturbation equations. These second-order solutions are tested against the exact solutions and the Zel'dovich approximation for spherically symmetric perturbations in the marginally nonlinear regime (the absolute value of delta is less than or approximately 1). The second-order and Zel'dovich solutions have comparable accuracy, significantly higher than the accuracy of the linear solutions. We then investigate the dependence of the delta(sub 0) - u(sub 0) relationship upon the value of n in the nonlinear regime using the second-order solutions for marginally nonlinear, general perturbations, and the exact solutions for strongly nonlinear, spherically symmetric perturbations. In both cases, we find that the delta(sub 0) - u(sub 0) relationship remains independent of n. We speculate that this result extends to strongly nonlinear, general perturbations as well. This eliminates any hope to determine the presence of the uniform component or the value of n using dynamical methods. Finally, we compute the nonlinear evolution of the skewness of the distribution of values of delta, assuming Gaussian initial conditions. We find that the skewness is not only independent of n, but also of Omega(sub 0). Thus the skewness cannot be used to discriminate among various models with Gaussian initial conditions. However, it can be used for testing the Gaussianity of the initial conditions themselves. We conclude that the uniform component leaves no observable signature in the present large-scale structure of the universe. To determine its presence and nature, we must investigate the relationship between the past and present universe, using redshift-dependent tests.

Martel, Hugo↗

NASA NTRS1984

Bearing tester fit analysis

A NASTRAN model of the Bearing Tester was developed to determine the fit of its components while in use. The model was executed for three loading conditions involving appropriate thermal and pressure loading throughout: rotation (30,000 rpm), rotation with 5000 lb axial shaft loading, and rotation with 2000 lb lateral shaft loading. A 30 deg slice of the Bearing Tester was modeled with solid isoparametric elements (CIHEX). Five more slices were generated to form a 180 deg symmetrical half. Each component was modeled separately for two reasons: (1) in the heat transfer version each component required covering with appropriate heat transfer coefficient elements, and (2) for the displacement version each component required independent radial expansion with respect to adjacent components. The components are connected at fastener and bearing locations axially and/or tangentially. Differences in radial displacements of adjacent cylindrical surfaces were calculated and added to those differences calculated for 180 deg opposite locations to determine the diametric change.

Source record↗

DOE OSTI2022

High-precision measurement of the W boson mass with the CDF II detector

The mass of the W boson, a mediator of the weak force between elementary particles, is tightly constrained by the symmetries of the standard model of particle physics. The Higgs boson was the last missing component of the model. After observation of the Higgs boson, a measurement of the W boson mass provides a stringent test of the model. We measure the W boson mass, M W , using data corresponding to 8.8 inverse femtobarns of integrated luminosity collected in proton-antiproton collisions at a 1.96 tera–electron volt center-of-mass energy with the CDF II detector at the Fermilab Tevatron collider. A sample of approximately 4 million W boson candidates is used to obtain M W = 80,433.5 ± 6.4 stat ± 6.9 syst = 80,433.5 ± 9.4 MeV/c 2 , the precision of which exceeds that of all previous measurements combined (stat, statistical uncertainty; syst, systematic uncertainty; MeV, mega–electron volts; c, speed of light in a vacuum). This measurement is in significant tension with the standard model expectation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Selective consolidation of learning and memory via recall-gated plasticity

Lindsey, Jack W. (ORCID:0000000309307327)↗

NASA NTRS1980

A low-cost forward fairing for the Bell Long Ranger Helicopter

A description is presented of work concerned with determining the effects of long-term flight service on advanced composite helicopter airframe components. The helicopter chosen for the program is the Long Ranger Model 206L. The components to be evaluated include the baggage door, litter door, vertical fin, and forward fairing. Only the vertical fin is classified as primary structure. Loss of any of the other components will not compromise safety of the aircraft. Attention is given to the program objectives, the design of the forward fairing, the fabrication procedures, the exterior surface, the cocure procedure, material tests, and initial cost-tracking. The considered program demonstrates the ability to produce an acceptable fairing by the 'one-shot' cocured process and, based on learning curve experience, production costs will be low. The low-temperature 200 F cure does not affect the structural properties to an unacceptable degree. A method for obtaining a smooth, exterior painted surface for Kevlar/epoxy fabric has been developed.

Zinberg, H.↗