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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 901 records · Page 50

Radiative Heat Transfer Capability Implemented in OpenNCC for Conjugate Heat Transfer Applications

Thermal efficiency of gas turbine engine increases as the temperature and pressure at the combustor increases. Consequently, the materials used inside a combustor must survive an increasingly challenging environment. For this reason, accurate assessment of heat transfer is crucial for combustor design. While all three modes of heat transfer are present inside a combustor, the focus of this paper is the thermal radiation. Radiative heat transfer in a gas turbine combustors are particularly interesting from three reasons. Firstly, the radiative heat loss from the combustion region may affect the emission performance. Secondly, the cooling air will protect the liner from convection but not necessary from radiation. Finally, it is less frequently incorporated in CFD analysis than other forms of heat transfer. In this work, radiative heat transfer using discrete ordinate method has been incorporated in OpenNCC (a publicly releasable version of the National Combustion Code) developed at NASA Glenn Research Center. Aside from massively parallel computation capability using MPI and the ability to utilize unstructured mesh, the current implementation includes two types of spectral models, namely, the weighted some of gray gas model and the full spectrum correlated k-distribution model. After presenting the theory and the strategy of implementation, results of validation cases for gray gas and spectral models will be presented. While the implementation of the radiation solver is intended for gas turbine application, the radiation solver can run independently from the convection/combustion solver and the same theory can be applied to other application.

OpenNCC↗

Radiative Heat Transfer Capability Implemented in OpenNCC for Conjugate Heat Transfer Applications

Thermal efficiency of gas turbine engine increases as the temperature and pressure at the combustor increases. Consequently, the materials used inside a combustor must survive an increasingly challenging environment. For this reason, accurate assessment of heat transfer is crucial for combustor design. While all three modes of heat transfer are present inside a combustor, the focus of this paper is the thermal radiation. Radiative heat transfer in a gas turbine combustors are particularly interesting from three reasons. Firstly, the radiative heat loss from the combustion region may affect the emission performance. Secondly, the cooling air will protect the liner from convection but not necessary from radiation. Finally, it is less frequently incorporated in CFD analysis than other forms of heat transfer. In this work, radiative heat transfer using discrete ordinate method has been incorporated in OpenNCC (a publicly releasable version of the National Combustion Code) developed at NASA Glenn Research Center. Aside from massively parallel computation capability using MPI and the ability to utilize unstructured mesh, the current implementation includes two types of spectral models, namely, the weighted some of gray gas model and the full spectrum correlated k-distribution model. After presenting the theory and the strategy of implementation, results of validation cases for gray gas and spectral models will be presented. While the implementation of the radiation solver is intended for gas turbine application, the radiation solver can run independently from the convection/combustion solver and the same theory can be applied to other application.

OpenNCC↗

Parallel and pipeline computation of fast unitary transforms

The letter discusses the parallel and pipeline organization of fast-unitary-transform algorithms such as the fast Fourier transform, and points out the efficiency of a combined parallel-pipeline processor of a transform such as the Haar transform, in which (2 to the n-th power) -1 hardware 'butterflies' generate a transform of order 2 to the n-th power every computation cycle.

Fino, B. J.↗

A parallel simulated annealing algorithm for standard cell placement on a hypercube computer

A parallel version of a simulated annealing algorithm is presented which is targeted to run on a hypercube computer. A strategy for mapping the cells in a two dimensional area of a chip onto processors in an n-dimensional hypercube is proposed such that both small and large distance moves can be applied. Two types of moves are allowed: cell exchanges and cell displacements. The computation of the cost function in parallel among all the processors in the hypercube is described along with a distributed data structure that needs to be stored in the hypercube to support parallel cost evaluation. A novel tree broadcasting strategy is used extensively in the algorithm for updating cell locations in the parallel environment. Studies on the performance of the algorithm on example industrial circuits show that it is faster and gives better final placement results than the uniprocessor simulated annealing algorithms. An improved uniprocessor algorithm is proposed which is based on the improved results obtained from parallelization of the simulated annealing algorithm.

Jones, Mark Howard↗

Parallel and vector computation for stochastic optimal control applications

A general method for parallel and vector numerical solutions of stochastic dynamic programming problems is described for optimal control of general nonlinear, continuous time, multibody dynamical systems, perturbed by Poisson as well as Gaussian random white noise. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random atmospheric fluctuations. The numerical formulation is highly suitable for a vector multiprocessor or vectorizing supercomputer, and results exhibit high processor efficiency and numerical stability. Advanced computing techniques, data structures, and hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations.

Hanson, F. B.↗

Application Portable Parallel Library

Application Portable Parallel Library (APPL) computer program is subroutine-based message-passing software library intended to provide consistent interface to variety of multiprocessor computers on market today. Minimizes effort needed to move application program from one computer to another. User develops application program once and then easily moves application program from parallel computer on which created to another parallel computer. ("Parallel computer" also include heterogeneous collection of networked computers). Written in C language with one FORTRAN 77 subroutine for UNIX-based computers and callable from application programs written in C language or FORTRAN 77.

Cole, Gary L.↗

The question of the possibility of using Associative Computer Devices (ACD) for parallel adaptive discretization of multichannel telemetry information

The method of parallel adaptive discretization of data is considered the most promising and allows the effective compression algorithms to be used for high information-capacity radio telemetry systems. An associative computer device (ACD), i.e., parallel computers based on associative memory units (AMU), are recommended for realization of this method. A detailed discussion of the problems of application of AMU is followed by description of a particular ACD and its recommended use.

Kantor, A. V.↗

Parallel algorithms for computation of the manipulator inertia matrix

The development of an O(log2N) parallel algorithm for the manipulator inertia matrix is presented. It is based on the most efficient serial algorithm which uses the composite rigid body method. Recursive doubling is used to reformulate the linear recurrence equations which are required to compute the diagonal elements of the matrix. It results in O(log2N) levels of computation. Computation of the off-diagonal elements involves N linear recurrences of varying-size and a new method, which avoids redundant computation of position and orientation transforms for the manipulator, is developed. The O(log2N) algorithm is presented in both equation and graphic forms which clearly show the parallelism inherent in the algorithm.

Amin-Javaheri, Masoud↗

Parallel adaptive mesh refinement techniques for plasticity problems

The accurate modeling of the nonlinear properties of materials can be computationally expensive. Parallel computing offers an attractive way for solving such problems; however, the efficient use of these systems requires the vertical integration of a number of very different software components, we explore the solution of two- and three-dimensional, small-strain plasticity problems. We consider a finite-element formulation of the problem with adaptive refinement of an unstructured mesh to accurately model plastic transition zones. We present a framework for the parallel implementation of such complex algorithms. This framework, using libraries from the SUMAA3d project, allows a user to build a parallel finite-element application without writing any parallel code. To demonstrate the effectiveness of this approach on widely varying parallel architectures, we present experimental results from an IBM SP parallel computer and an ATM-connected network of Sun UltraSparc workstations. The results detail the parallel performance of the computational phases of the application during the process while the material is incrementally loaded.

Barry, W. J.↗

Parallel Proximity Detection for Computer Simulation

The present invention discloses a system for performing proximity detection in computer simulations on parallel processing architectures utilizing a distribution list which includes movers and sensor coverages which check in and out of grids. Each mover maintains a list of sensors that detect the mover's motion as the mover and sensor coverages check in and out of the grids. Fuzzy grids are includes by fuzzy resolution parameters to allow movers and sensor coverages to check in and out of grids without computing exact grid crossings. The movers check in and out of grids while moving sensors periodically inform the grids of their coverage. In addition, a lookahead function is also included for providing a generalized capability without making any limiting assumptions about the particular application to which it is applied. The lookahead function is initiated so that risk-free synchronization strategies never roll back grid events. The lookahead function adds fixed delays as events are scheduled for objects on other nodes.

Steinman, Jeffrey S.↗

Parallel Proximity Detection for Computer Simulations

The present invention discloses a system for performing proximity detection in computer simulations on parallel processing architectures utilizing a distribution list which includes movers and sensor coverages which check in and out of grids. Each mover maintains a list of sensors that detect the mover's motion as the mover and sensor coverages check in and out of the grids. Fuzzy grids are included by fuzzy resolution parameters to allow movers and sensor coverages to check in and out of grids without computing exact grid crossings. The movers check in and out of grids while moving sensors periodically inform the grids of their coverage. In addition, a lookahead function is also included for providing a generalized capability without making any limiting assumptions about the particular application to which it is applied. The lookahead function is initiated so that risk-free synchronization strategies never roll back grid events. The lookahead function adds fixed delays as events are scheduled for objects on other nodes.

Steinman, Jeffrey S.↗

Concurrent extensions to the FORTRAN language for parallel programming of computational fluid dynamics algorithms

Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.

Weeks, Cindy Lou↗

Large-Scale Parallel Viscous Flow Computations using an Unstructured Multigrid Algorithm

The development and testing of a parallel unstructured agglomeration multigrid algorithm for steady-state aerodynamic flows is discussed. The agglomeration multigrid strategy uses a graph algorithm to construct the coarse multigrid levels from the given fine grid, similar to an algebraic multigrid approach, but operates directly on the non-linear system using the FAS (Full Approximation Scheme) approach. The scalability and convergence rate of the multigrid algorithm are examined on the SGI Origin 2000 and the Cray T3E. An argument is given which indicates that the asymptotic scalability of the multigrid algorithm should be similar to that of its underlying single grid smoothing scheme. For medium size problems involving several million grid points, near perfect scalability is obtained for the single grid algorithm, while only a slight drop-off in parallel efficiency is observed for the multigrid V- and W-cycles, using up to 128 processors on the SGI Origin 2000, and up to 512 processors on the Cray T3E. For a large problem using 25 million grid points, good scalability is observed for the multigrid algorithm using up to 1450 processors on a Cray T3E, even when the coarsest grid level contains fewer points than the total number of processors.

Mavriplis, Dimitri J.↗

Evaluating Performance of Components

Parallel Component Performance Benchmarks is a computer program developed to aid the evaluation of the Common Component Architecture (CCA) - a software architecture, based on a component model, that was conceived to foster high-performance computing, including parallel computing. More specifically, this program compares the performances (principally by measuring computing times) of componentized versus conventional versions of the Parallel Pyramid 2D Adaptive Mesh Refinement library - a software library that is used to generate computational meshes for solving physical problems and that is typical of software libraries in use at NASA s Jet Propulsion Laboratory.

Katz, Daniel↗

HPCC Methodologies for Structural Design and Analysis on Parallel and Distributed Computing Platforms

In this grant, we have proposed a three-year research effort focused on developing High Performance Computation and Communication (HPCC) methodologies for structural analysis on parallel processors and clusters of workstations, with emphasis on reducing the structural design cycle time. Besides consolidating and further improving the FETI solver technology to address plate and shell structures, we have proposed to tackle the following design related issues: (a) parallel coupling and assembly of independently designed and analyzed three-dimensional substructures with non-matching interfaces, (b) fast and smart parallel re-analysis of a given structure after it has undergone design modifications, (c) parallel evaluation of sensitivity operators (derivatives) for design optimization, and (d) fast parallel analysis of mildly nonlinear structures. While our proposal was accepted, support was provided only for one year.

Farhat, Charbel↗

Parallel Object-Oriented Computation Applied to a Finite Element Problem

The conventional wisdom in the scientific computing community is that the best way to solve large-scale numerically intensive scientific problems on today's parallel MIMD computers is to use Fortran or C programmed in a data-parallel style using low-level message-passing primitives. This approach inevitably leads to nonportable codes, extensive development time, and restricts parallel programming to the domain of the expert programmer. We believe that these problems are not inherent to parallel computing but are the result of the tools used. We will show that comparable performance can be achieved with little effort if better tools that present higher level abstractions are used.

parallel object-oriented computation scientific pr↗

Efficient use of high performance computers for integrated controls and structures design

Simply transporting design codes from sequential-scalar computers to parallel-vector computers does not fully utilize the computational benefits offered by high performance computers. By performing integrated controls and structures design on an experimental truss platform with both sequential-scalar and parallel-vector design codes, conclusive results are presented to substantiate this claim. The efficiency of a Cholesky factorization scheme in conjunction with a variable-band row data structure is presented. In addition, the Lanczos eigensolution algorithm has been incorporated in the design code for both parallel and vector computations. Comparisons of computational efficiency between the initial design code and the parallel-vector design code are presented. It is shown that the Lanczos algorithm with the Cholesky factorization scheme is far superior to the sub-space iteration method of eigensolution when substantial numbers of eigenvectors are required for control design and/or performance optimization. Integrated design results show the need for continued efficiency studies in the area of element computations and matrix assembly.

Belvin, W. K.↗

Computational mechanics analysis tools for parallel-vector supercomputers

Computational algorithms for structural analysis on parallel-vector supercomputers are reviewed. These parallel algorithms, developed by the authors, are for the assembly of structural equations, 'out-of-core' strategies for linear equation solution, massively distributed-memory equation solution, unsymmetric equation solution, general eigensolution, geometrically nonlinear finite element analysis, design sensitivity analysis for structural dynamics, optimization search analysis and domain decomposition. The source code for many of these algorithms is available.

Storaasli, Olaf O.↗