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Results for “hybrid computing”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Errors in hybrid computers

Method is described for reduction of error components in numerical integration, sampling with zero hold order, and execution time delay.

Alford, C. O.↗
NASA NTRS1971

Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization

High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.

Drake, R. L.↗
NASA NTRS1972

The study of human venous system dynamics using hybrid computer modeling

A computer-based model of the cardiovascular system was created emphasizing effects on the systemic venous system. Certain physiological aspects were emphasized: effects of heart rate, tilting, changes in respiration, and leg muscular contractions. The results from the model showed close correlation with findings previously reported in the literature.

Snyder, M. F.↗
NASA NTRS1980

Development and validation of a hybrid-computer simulator for a transonic cryogenic wind tunnel

A study was undertaken to model the cryogenic wind tunnel process, to validate the model by the use of experimental data from the Langley 0.3 Meter Transonic Cryogenic Tunnel, and to construct an interactive simulator of the cryogenic tunnel using the validated model. Additionally, this model was used for designing closed loop feedback control laws for regulation of temperature and pressure in the 0.3 meter cryogenic tunnel. The global mathematical model of the cryogenic tunnel that were developed consists of coupled, nonlinear differential governing equations based on an energy state concept of the physical cryogenic phenomena. Process equations and comparisons between actual tunnel responses and computer simulation predictions were examined. Also included are the control laws and simulator responses obtained using the feedback schemes for closed loop control of temperature and pressure were also included.

Thibodeaux, J. J.↗
NASA NTRS2023

Distributed Quantum Processing via Integrated Regional Quantum Networks Using Free-Space Optical Links

The landscape for quantum computing is rapidly evolving with the development of quantum computers and the emergence of future science enabling applications being pursued in many areas, such as distributed quantum computing, hybrid computing scenarios that require cooperatively networked quantum and classical computing assets and more. Quantum networking is also advancing with multiple regional quantum networks and testbeds maturing across the nation. These quantum networking testbeds typically include multiple access points with a heterogeneous mixture of capabilities interconnected by fiber spanning anywhere from tens to hundreds of kilometers; many such networks incorporate a classical networking framework. Alongside these connectivity advancements in the infrastructure, there is quantum sensing device and component technology maturation that is serving to expand the body of quantum networking scenarios that are presently possible and redefining the quantum- enabled future. Bridging the present collective progress in quantum computing and quantum networking will enable the next era of purposeful advancements for national priority use-cases for the benefit of science. One such use-case is enabling future quantum computing applications via integrated regional quantum networking infrastructure in neighboring locations like New York and Maryland, both states are home to robust classical and quantum networking capabilities. To enable near-term distributed quantum computing applications via the practical integration of regional quantum networking infrastructure, free-space optical links via satellite communications will be essential to avoid the exponential loss commonly observed with fiber implementations. There is both an urgent need and a practical justification for pursuing such space-based integration scope now.

Harry Shaw↗
NASA NTRS1978

Plans for wind energy system simulation

A digital computer code and a special purpose hybrid computer, were introduced. The digital computer program, the Root Perturbation Method or RPM, is an implementation of the classic floquet procedure which circumvents numerical problems associated with the extraction of Floquet roots. The hybrid computer, the Wind Energy System Time domain simulator (WEST), yields real time loads and deformation information essential to design and system stability investigations.

Dreier, M. E.↗
NASA NTRS2009

Hybrid NN/SVM Computational System for Optimizing Designs

A computational method and system based on a hybrid of an artificial neural network (NN) and a support vector machine (SVM) (see figure) has been conceived as a means of maximizing or minimizing an objective function, optionally subject to one or more constraints. Such maximization or minimization could be performed, for example, to optimize solve a data-regression or data-classification problem or to optimize a design associated with a response function. A response function can be considered as a subset of a response surface, which is a surface in a vector space of design and performance parameters. A typical example of a design problem that the method and system can be used to solve is that of an airfoil, for which a response function could be the spatial distribution of pressure over the airfoil. In this example, the response surface would describe the pressure distribution as a function of the operating conditions and the geometric parameters of the airfoil. The use of NNs to analyze physical objects in order to optimize their responses under specified physical conditions is well known. NN analysis is suitable for multidimensional interpolation of data that lack structure and enables the representation and optimization of a succession of numerical solutions of increasing complexity or increasing fidelity to the real world. NN analysis is especially useful in helping to satisfy multiple design objectives. Feedforward NNs can be used to make estimates based on nonlinear mathematical models. One difficulty associated with use of a feedforward NN arises from the need for nonlinear optimization to determine connection weights among input, intermediate, and output variables. It can be very expensive to train an NN in cases in which it is necessary to model large amounts of information. Less widely known (in comparison with NNs) are support vector machines (SVMs), which were originally applied in statistical learning theory. In terms that are necessarily oversimplified to fit the scope of this article, an SVM can be characterized as an algorithm that (1) effects a nonlinear mapping of input vectors into a higher-dimensional feature space and (2) involves a dual formulation of governing equations and constraints. One advantageous feature of the SVM approach is that an objective function (which one seeks to minimize to obtain coefficients that define an SVM mathematical model) is convex, so that unlike in the cases of many NN models, any local minimum of an SVM model is also a global minimum.

Rai, Man Mohan↗
DOE OSTI2026

A lumped particle direct simulation Monte-Carlo method combined with the collisional-radiative model for simulations of non-equilibrium laser-induced plasma plumes

Collisional plasma plumes induced by laser irradiation of material targets exhibit large variations in local density as well as ionization and excitation states, making purely hydrodynamic or kinetic simulations inaccurate or infeasible. To address this challenge and capture non-equilibrium effects in laser-induced plasma plumes at arbitrary degrees of ionization, we develop a hybrid computational approach that combines the kinetic direct simulation Monte Carlo (DSMC) method with a collisional-radiative model (CRM). This ℓDSMC-CRM approach utilizes a lumped particle method to represent minor fractions of excited ions in particle-based simulations and a special coarse-graining technique for atomic spectra and photoionization rates, ensuring numerical convergence at reduced computational cost. The hybrid approach is applied to simulate spatially homogeneous relaxation as well as one- and two-dimensional expansions of plasma plumes induced by irradiation of a copper target by a nanosecond laser pulse in a vacuum or background gas. The comparison with an equilibrium model, where local Saha-Boltzmann equilibrium is enforced, shows that the non-equilibrium effects play a dominant role. The equilibrium model can fail to predict the flow structure and strongly underestimate the degree of absorption of laser radiation by the plume. The ℓDSMC-CRM approach is validated against experimental data demonstrating reasonable agreement with the experimental electron density and temperature, while the equilibrium model is found to dramatically underestimate electron density and temperature. The flexibility of the ℓDSMC-CRM approach allows for its seamless integration into existing DSMC frameworks, making it a valuable tool for high-fidelity plasma modeling in laser-material interactions, laser-based manufacturing, and beyond.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

A New Formulation for Hybrid LES-RANS Computations

Ideally, a hybrid LES-RANS computation would employ LES only where necessary to make up for the failure of the RANS model to provide sufficient accuracy or to provide time-dependent information. Current approaches are fairly restrictive in the placement of LES and RANS regions; an LES-RANS transition in a boundary layer, for example, yields an unphysical log-layer shift. A hybrid computation is formulated here to allow greater control over the placement of LES and RANS regions and the transitions between them. The concept of model invariance is introduced, which provides a basis for interpreting hybrid results within an LES-RANS transition zone. Consequences of imposing model invariance include the addition of terms to the governing equations that compensate for unphysical gradients created as the model changes between RANS and LES. Computational results illustrate the increased accuracy of the approach and its insensitivity to the location of the transition and to the blending function employed.

Woodruff, Stephen L.↗