Interoperable Application Programming Interfaces for Computer Aided Engineering Applications
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William T Jones↗
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Interoperable Application Programming Interfaces for Computer Aided Engineering Applications
Explore the source record for details and available documents.
William T Jones↗
Survey of ONERA activities on adaptive-wall applications and computation of residual corrections
The research undertaken concerning the computation and/or reduction of wall interference follows two main axes: improvement of wall correction determinations, and use of adaptive flexible walls. The use of wall-measured data to compute interference effects is reliable when the model representation is assessed by signatures with known boundary conditions. When the computed interferences are not easily applicable to correcting the results (especially for gradients in two-dimensional cases), the flexible adaptive walls in operation in T2 are an efficient and assessed means of reducing the boundary effects to a negligible level, if the direction and speed of the flow are accurately measured on the boundary. The extension of the use of adaptive walls to three-dimensional cases may be attempted since the residual corrections are assumed to be small and are computable.
Chevallier, J. P.↗
MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications
Here, this paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source computational platform for parallel finite element and finite volume analyses. In addressing the computational expense and uncertainties inherent in complex multiphysics simulations, this paper integrates Gaussian process (GP) variants, active learning, Bayesian inverse UQ, adaptive forward UQ, Bayesian optimization, evolutionary optimization, and Markov chain Monte Carlo (MCMC) within MOOSE. It also elaborates on the interaction among key MOOSE systems — Sampler, MultiApp, Reporter, and Surrogate — in enabling these capabilities. The modularity offered by these systems enables development of a multitude of probabilistic ML and UQ algorithms in MOOSE. Example code demonstrations include parallel active learning and parallel Bayesian inference via active learning. The impact of these developments is illustrated through five applications relevant to computational energy applications: UQ of nuclear fuel fission product release, using parallel active learning Bayesian inference; very rare events analysis in nuclear microreactors using active learning; advanced manufacturing process modeling using multi-output GPs (MOGPs) and dimensionality reduction; fluid flow using deep GPs (DGPs); and tritium transport model parameter optimization for fusion energy, using batch Bayesian optimization. These capabilities are part of the MOOSE framework.
97 - MATHEMATICS AND COMPUTING↗
Application of computational aerodynamics methods to the design and analysis of transport aircraft
The application and validation of several computational aerodynamic methods in the design and analysis of transport aircraft is established. An assessment is made concerning more recently developed methods that solve three-dimensional transonic flow and boundary layers on wings. Capabilities of subsonic aerodynamic methods are demonstrated by several design and analysis efforts. Among the examples cited are the B747 Space Shuttle Carrier Aircraft analysis, nacelle integration for transport aircraft, and winglet optimization. The accuracy and applicability of a new three-dimensional viscous transonic method is demonstrated by comparison of computed results to experimental data
Da Costa, A. L.↗
A Multiple Filter Based Neural Network Approach to the Extrapolation of Adsorption Energies on Metal Surfaces for Catalysis Applications
Computational catalyst discovery involves the development of microkinetic reactor models based on estimated parameters determined from density functional theory (DFT). For complex surface chemistries, the number of reaction intermediates can be very large, and the cost of calculating the adsorption energies by DFT for all surface intermediates even for one active site model can become prohibitive. In this paper, we have identified appropriate descriptors and machine learning models that can be used to predict a significant part of these adsorption energies given data on the rest of them. Furthermore, our investigations also included the case when the species data used to train the predictive model are of different size relative to the species the model tries to predict—this is an extrapolation in the data space which is typically difficult with regular machine learning models. Due to the relative size of the available data sets, we have attempted to extrapolate from the larger species to the smaller ones in the current work. Here, we have developed a neural network based predictive model that combines an established additive atomic contribution based model with the concepts of a convolutional neural network that, when extrapolating, achieves a statistically significant improvement over the previous models.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Analysis of the economics of photovoltaic-diesel-battery energy systems for remote applications
Computer simulations were conducted to analyze the performance and operating cost of a photovoltaic energy source combined with a diesel generator system and battery storage. The simulations were based on the load demand profiles used for the design of an all photovoltaic energy system installed in the remote Papago Indian Village of Schuchuli, Arizona. Twenty year simulations were run using solar insolation data from Phoenix SOLMET tapes. Total energy produced, energy consumed, operation and maintenance costs were calculated. The life cycle and levelized energy costs were determined for a variety of system configurations (i.e., varying amounts of photovoltaic array and battery storage).
Brainard, W. A.↗
TM digital image products for applications
Computer compatible tapes (CCTs) of LANDSAT 4 thematic mapper (TM) digital image products are compared and reviewed. The following tape formats are discussed: (1) raw band-sequential data (CCT-BT); (2) calibrated data (CCT-AT); and (3) geometrically resampled data (CCT-PT). Each format represents different steps in the process of producing fully corrected TM data. The CCT-BT images are uncorrected radiometrically or geometrically, CCT-AT data are radiometrically calibrated, and CCT-PT images are both radiometrically and geometrically corrected.
Barker, J. L.↗
Evolution and status of CFD techniques for scramjet applications
Computational Fluid Dynamics (CFD) methods are presently applied to the design and analysis of scramjet propulsion systems for missiles and aircraft operating at speeds in excess of Mach 5, in forms ranging from simple inviscid codes for parametric studies of inlet geometries to Navier-Stokes codes incorporating chemistry models which address complex scramjet combustion phenomena. Attention is given to the development history of CFD for the hypersonic regime, as well as to scramjet flowfield modeling in inlets, combustors and nozzles, and prospective development trends.
White, M. E.↗
Supercomputer applications in computational fluid dynamics
The field of computational fluid dynamics (CFD) using large-scale supercomputer applications is discussed. Formulational and computational requirements for the various governing equations, including the Euler and Navier-tokes approaches, are examined for typical problems including the viscous flow field solution about a complete aerospace vehicle. Recent computed results and experimental comparisons are given to highlight the presentation. The future of CFD associated with three-dimensional applications is found to be rapidly expanding across a broad front, including internal and external flows and flows across the entire speed regime.
Holst, Terry L.↗
Potential applications of computational fluid dynamics to biofluid analysis
Computational fluid dynamics was developed to the stage where it has become an indispensable part of aerospace research and design. In view of advances made in aerospace applications, the computational approach can be used for biofluid mechanics research. Several flow simulation methods developed for aerospace problems are briefly discussed for potential applications to biofluids, especially to blood flow analysis.
Kwak, D.↗
Application of Computational Stability and Control Techniques Including Unsteady Aerodynamics and Aeroelastic Effects
The motivation behind the inclusion of unsteady aerodynamics and aeroelastic effects in the computation of stability and control (S&C) derivatives will be discussed as they pertain to aeroelastic and aeroservoelastic analysis. This topic will be addressed in the context of two applications, the first being the estimation of S&C derivatives for a cable-mounted aeroservoelastic wind tunnel model tested in the NASA Langley Research Center (LaRC) Transonic Dynamics Tunnel (TDT). The second application will be the prediction of the nonlinear aeroservoelastic phenomenon known as Residual Pitch Oscillation (RPO) on the B-2 Bomber. Techniques and strategies used in these applications to compute S&C derivatives and perform flight simulations will be reviewed, and computational results will be presented.
Schuster, David M.↗
Evaluation and optimization of the performance of frame geometries for lithium-ion battery application by computer simulation
Tailoring battery geometries is essential for many applications, as geometry influences the delivered capacity value. Two geometries, frame and conventional, have been studied and, for a given scan rate of 330C, the square frame shows a capacity value of 305,52 Ahm{sup −2}, which is 527 times higher than the one for the conventional geometry for a constant the area of all components.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
A survey of parametrized variational principles and applications to computational mechanics
This survey paper describes recent developments in the area of parametrized variational principles (PVP's) and selected applications to finite-element computational mechanics. A PVP is a variational principle containing free parameters that have no effect on the Euler-Lagrange equations. The theory of single-field PVP's based on gauge functions (also known as null Lagrangians) is a subset of the inverse problem of variational calculus that has limited value. On the other hand, multifield PVP's are more interesting from theoretical and practical standpoints. Following a tutorial introduction, the paper describes the recent construction of multifield PVP's in several areas of elasticity and electromagnetics. It then discusses three applications to finite-element computational mechanics: the derivation of high-performance finite elements, the development of element-level error indicators, and the constructions of finite element templates. The paper concludes with an overview of open research areas.
Felippa, Carlos A.↗
Applications of Computational Methods for Dynamic Stability and Control Derivatives
Initial steps in the application o f a low-order panel method computational fluid dynamic (CFD) code to the calculation of aircraft dynamic stability and control (S&C) derivatives are documented. Several capabilities, unique to CFD but not unique to this particular demonstration, are identified and demonstrated in this paper. These unique capabilities complement conventional S&C techniques and they include the ability to: 1) perform maneuvers without the flow-kinematic restrictions and support interference commonly associated with experimental S&C facilities, 2) easily simulate advanced S&C testing techniques, 3) compute exact S&C derivatives with uncertainty propagation bounds, and 4) alter the flow physics associated with a particular testing technique from those observed in a wind or water tunnel test in order to isolate effects. Also presented are discussions about some computational issues associated with the simulation of S&C tests and selected results from numerous surface grid resolution studies performed during the course of the study.
Green, Lawrence L.↗
Convergence acceleration for vector sequences and applications to computational fluid dynamics
Some recent developments in acceleration of convergence methods for vector sequences are reviewed. The methods considered are the minimal polynomial extrapolation, the reduced rank extrapolation, and the modified minimal polynomial extrapolation. The vector sequences to be accelerated are those that are obtained from the iterative solution of linear or nonlinear systems of equations. The convergence and stability properties of these methods as well as different ways of numerical implementation are discussed in detail. Based on the convergence and stability results, strategies that are useful in practical applications are suggested. Two applications to computational fluid mechanics involving the three dimensional Euler equations for ducted and external flows are considered. The numerical results demonstrate the usefulness of the methods in accelerating the convergence of the time marching techniques in the solution of steady state problems.
Sidi, Avram↗
Convergence acceleration for vector sequences and applications to computational fluid dynamics
Some recent developments in acceleration of convergence methods for vector sequences are reviewed. The methods considered are the minimal polynomial extrapolation, the reduced rank extrapolation, and the modified minimal polynomial extrapolation. The vector sequences to be accelerated are those that are obtained from the iterative solution of linear or nonlinear systems of equations. The convergence and stability properties of these methods as well as different ways of numerical implementation are discussed in detail. Based on the convergence and stability results, strategies that are useful in practical applications are suggested. Two applications to computational fluid mechanics involving the three dimensional Euler equations for ducted and external flows are considered. The numerical results demonstrate the usefulness of the methods in accelerating the convergence of the time marching techniques in the solution of steady state problems.
Sidi, Avram↗
A Framework for Error-Bounded Approximate Computing, with an Application to Dot Products
Approximate computing techniques, which trade off the computation accuracy of an algorithm for better performance and energy efficiency, have been successful in reducing computation and power costs in several domains. However, error sensitive applications in high-performance computing are unable to benefit from existing approximate computing strategies that are not developed with guaranteed error bounds. While approximate computing techniques can be developed for individual high-performance computing applications by domain specialists, this often requires additional theoretical analysis and potentially extensive software modification. Hence, the development of low-level error-bounded approximate computing strategies that can be introduced into any high-performance computing application without requiring additional analysis or significant software alterations is desirable. In this paper, we provide a contribution in this direction by proposing a general framework for designing error-bounded approximate computing strategies and apply it to the dot product kernel to develop \bf qdot---an error-bounded approximate dot product kernel. Following the introduction of qdot, here we perform a theoretical analysis that yields a deterministic bound on the relative approximation error introduced by qdot. Empirical tests are performed to illustrate the tightness of the derived error bound and to demonstrate the effectiveness of qdot on a synthetic dataset, as well as two scientific benchmarks---the conjugate gradient (CG) and power methods. In some instances, using qdot for the dot products in CG can result in many components being quantized to half precision without increasing the iteration count required for convergence to the same solution as CG using a double precision dot product.
97 MATHEMATICS AND COMPUTING↗