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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 1,225 records · Page 68

Unsteady turbomachinery flow simulations on massively parallel architectures

The accurate numerical simulation of unsteady, three-dimensional viscous flow in turbomachines is computationally very intensive, requiring prohibitively large amounts of computer time on current vector supercomputers. In recent years, computer systems based on massively parallel architectures have been developed that offer the promise of meeting the computational power requirements of such large-scale simulations. However, a rethinking of existing algorithms and methodology is required in order to fully harness the computational power of such architectures. In this paper the capabilities of the Connection Machine (CM-2) in predicting unsteady flows in turbomachines are evaluated. The implementation on the CM-2 of an implicit, time-accurate, zonal algorithm for the Navier-Stokes equations in two dimensions is described. Programming issues and modifications made to the original algorithm (developed for vector, pipelined supercomputers) in order to improve performance on the CM-2 are outlined. Algorithm performance is evaluated and compared with a functionally equivalent code for the CRAY-YMP.

Madavan, N. K.↗

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Madavan, Nateri K.↗

High-speed computerized tomography

The development of a high-speed reconstruction processor and a channelized architecture to use with a high-resolution tomographic unit is discussed with attention to the convolution reconstruction algorithm. By means of this algorithm, input data and intermediate result precision required throughout the algorithm execution have been studied with computer simulation using profile data derived from mathematically simulated test objects and experimental animal data. A prototype section for a highly parallel all-digital system executes 60 million arithmetic operations per second, and the full-scale version is expected to reconstruct 500 to 1000 cross sections per second.

Swartzlander, E. E., Jr.↗

Cumulative reports and publications through 31 December 1983

All reports for the calendar years 1975 through December 1983 are listed by author. Since ICASE reports are intended to be preprints of articles for journals and conference proceedings, the published reference is included when available. Thirteen older journal and conference proceedings references are included as well as five additional reports by ICASE personnel. Major categories of research covered include: (1) numerical methods, with particular emphasis on the development and analysis of basic algorithms; (2) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, structural analysis, and chemistry; and (3) computer systems and software, especially vector and parallel computers, microcomputers, and data management.

Source record↗

Efficiency of group implicit concurrent algorithms for transient finite element analysis

The performance of group implicit algorithms is assessed on actual concurrent computers. It is shown that, as the number of subdomains is increased, performance enhancements are derived from two sources: the increased parallelism in the computations; and a reduction in equation solving effort. Moreover, these two performance enhancements are synergistic, in the sense that the corresponding speed-ups are multiplied, rather than merely added. Simulations on a 32-node hypercube are presented for which the interprocessor communications efficiencies obtained are consistently in excess of 90 percent.

Ortiz, M.↗

Design of optimal correlation filters for hybrid vision systems

Research is underway at the NASA Johnson Space Center on the development of vision systems that recognize objects and estimate their position by processing their images. This is a crucial task in many space applications such as autonomous landing on Mars sites, satellite inspection and repair, and docking of space shuttle and space station. Currently available algorithms and hardware are too slow to be suitable for these tasks. Electronic digital hardware exhibits superior performance in computing and control; however, they take too much time to carry out important signal processing operations such as Fourier transformation of image data and calculation of correlation between two images. Fortunately, because of the inherent parallelism, optical devices can carry out these operations very fast, although they are not quite suitable for computation and control type operations. Hence, investigations are currently being conducted on the development of hybrid vision systems that utilize both optical techniques and digital processing jointly to carry out the object recognition tasks in real time. Algorithms for the design of optimal filters for use in hybrid vision systems were developed. Specifically, an algorithm was developed for the design of real-valued frequency plane correlation filters. Furthermore, research was also conducted on designing correlation filters optimal in the sense of providing maximum signal-to-nose ratio when noise is present in the detectors in the correlation plane. Algorithms were developed for the design of different types of optimal filters: complex filters, real-value filters, phase-only filters, ternary-valued filters, coupled filters. This report presents some of these algorithms in detail along with their derivations.

Rajan, Periasamy K.↗

Execution time support for scientific programs on distributed memory machines

Optimizations are considered that are required for efficient execution of code segments that consists of loops over distributed data structures. The PARTI (Parallel Automated Runtime Toolkit at ICASE) execution time primitives are designed to carry out these optimizations and can be used to implement a wide range of scientific algorithms on distributed memory machines. These primitives allow the user to control array mappings in a way that gives an appearance of shared memory. Computations can be based on a global index set. Primitives are used to carry out gather and scatter operations on distributed arrays. Communications patterns are derived at runtime, and the appropriate send and receive messages are automatically generated.

Berryman, Harry↗

Ionospheric refraction effects on TOPEX orbit determination accuracy using the Tracking and Data Relay Satellite System (TDRSS)

This investigation concerns the effects on Ocean Topography Experiment (TOPEX) spacecraft operational orbit determination of ionospheric refraction error affecting tracking measurements from the Tracking and Data Relay Satellite System (TDRSS). Although tracking error from this source is mitigated by the high frequencies (K-band) used for the space-to-ground links and by the high altitudes for the space-to-space links, these effects are of concern for the relatively high-altitude (1334 kilometers) TOPEX mission. This concern is due to the accuracy required for operational orbit-determination by the Goddard Space Flight Center (GSFC) and to the expectation that solar activity will still be relatively high at TOPEX launch in mid-1992. The ionospheric refraction error on S-band space-to-space links was calculated by a prototype observation-correction algorithm using the Bent model of ionosphere electron densities implemented in the context of the Goddard Trajectory Determination System (GTDS). Orbit determination error was evaluated by comparing parallel TOPEX orbit solutions, applying and omitting the correction, using the same simulated TDRSS tracking observations. The tracking scenarios simulated those planned for the observation phase of the TOPEX mission, with a preponderance of one-way return-link Doppler measurements. The results of the analysis showed most TOPEX operational accuracy requirements to be little affected by space-to-space ionospheric error. The determination of along-track velocity changes after ground-track adjustment maneuvers, however, is significantly affected when compared with the stringent 0.1-millimeter-per-second accuracy requirements, assuming uncoupled premaneuver and postmaneuver orbit determination. Space-to-space ionospheric refraction on the 24-hour postmaneuver arc alone causes 0.2 millimeter-per-second errors in along-track delta-v determination using uncoupled solutions. Coupling the premaneuver and postmaneuver solutions, however, appears likely to reduce this figure substantially. Plans and recommendations for response to these findings are presented.

Radomski, M. S.↗

An Efficient GPU-Accelerated Multi-Source Global Fit Pipeline for LISA Data Analysis

The large-scale analysis task of deciphering gravitational wave signals in the LISA data stream will be difficult, requiring a large amount of computational resources and extensive development of computational methods. Its high dimensionality, multiple model types, and complicated noise profile require a global fit to all parameters and input models simultaneously. In this work, we detail our global fit algorithm, called “Erebor,” designed to accomplish this challenging task. It is capable of analysing current state-of-the-art datasets and then growing into the future as more pieces of the pipeline are completed and added. We describe our pipeline strategy, the algorithmic setup, and the results from our analysis of the LDC2A Sangria dataset, which contains Massive Black Hole Binaries, compact Galactic Binaries, and a parameterized noise spectrum whose parameters are unknown to the user. The Erebor algorithm includes three unique and very useful contributions: GPU acceleration for enhanced computational efficiency; ensemble MCMC sampling with multiple MCMC walkers per temperature for better mixing and parallelized sample creation; and special online updates to reversible-jump (or trans-dimensional) sampling distributions to ensure sampler mixing and accurate initial estimates for detectable sources in the data. We recover posterior distributions for all 15 (6) of the injected MBHBs in the LDC2A training (hidden) dataset. We catalog ∼12000 Galactic Binaries (∼8000 as high confidence detections) for both the training and hidden datasets. All of the sources and their posterior distributions are provided in publicly available catalogs.

LISA global fit↗

Exploiting Modern C++ for Portable Parallel Programming in Lattice QCD Applications

The evolution of ISO C++ standards increasingly serves the needs of scientific computing, offering potential benefits for developing portable applications. The recent revisions of C++ programming language, for instance, introduces a suite of algorithms capable of being executed on accelerators. Although this approach may not yield best performance, it can present a viable balance between code productivity and computational efficiency. In this report, we discuss the implementation of the HISQ operator utilizing a range of features from the C++17/20/23 standards and include an assessment of their performance.

Strelchenko, Alexei↗

Some Experiences with Nonoverlapping Schur Complement Parallel Preconditioning for CFD Calculations

In this work we consider solving matrices which arise from the discretization of advection-diffusion field equations on arbitrary triangulated domains using stabilized numerical methods. The talk will discuss several candidate matrix preconditioning algorithms based on the 2 x 2 block factorization induced by an apriori partitioning of the triangulated domain. Application of the 2 x 2 block preconditioner requires the formation and inversion of the Schur complement submatrix. We consider several strategies for simplifying this task: incomplete Schur complement factorizations, drop tolerance element filling, Schur complement probing, and localized Schur complement inversion. Numerical results will be shown comparing performance and efficiency of these approximations. The matrix preconditioner has also been embedded into a Newton algorithm for solving the nonlinear Euler and Navier-Stokes equations governing compressible flow. The remainder of the talk will show numerous examples in CFD to demonstrate the efficiency and robustness of the techniques.

Barth, Timothy J.↗

Fast Particle Methods for Multiscale Phenomena Simulations

We are developing particle methods oriented at improving computational modeling capabilities of multiscale physical phenomena in : (i) high Reynolds number unsteady vortical flows, (ii) particle laden and interfacial flows, (iii)molecular dynamics studies of nanoscale droplets and studies of the structure, functions, and evolution of the earliest living cell. The unifying computational approach involves particle methods implemented in parallel computer architectures. The inherent adaptivity, robustness and efficiency of particle methods makes them a multidisciplinary computational tool capable of bridging the gap of micro-scale and continuum flow simulations. Using efficient tree data structures, multipole expansion algorithms, and improved particle-grid interpolation, particle methods allow for simulations using millions of computational elements, making possible the resolution of a wide range of length and time scales of these important physical phenomena.The current challenges in these simulations are in : [i] the proper formulation of particle methods in the molecular and continuous level for the discretization of the governing equations [ii] the resolution of the wide range of time and length scales governing the phenomena under investigation. [iii] the minimization of numerical artifacts that may interfere with the physics of the systems under consideration. [iv] the parallelization of processes such as tree traversal and grid-particle interpolations We are conducting simulations using vortex methods, molecular dynamics and smooth particle hydrodynamics, exploiting their unifying concepts such as : the solution of the N-body problem in parallel computers, highly accurate particle-particle and grid-particle interpolations, parallel FFT's and the formulation of processes such as diffusion in the context of particle methods. This approach enables us to transcend among seemingly unrelated areas of research.

Koumoutsakos, P.↗

Efficient Mosaicking of Spitzer Space Telescope Images

A parallel version of the MOPEX software, which generates mosaics of infrared astronomical images acquired by the Spitzer Space Telescope, extends the capabilities of the prior serial version. In the parallel version, both the input image space and the output mosaic space are divided among the available parallel processors. This is the only software that performs the point-source detection and the rejection of spurious imaging effects of cosmic rays required by Spitzer scientists. This software includes components that implement outlier-detection algorithms that can be fine-tuned for a particular set of image data by use of a number of adjustable parameters. This software has been used to construct a mosaic of the Spitzer Infrared Array Camera Shallow Survey, which comprises more than 17,000 exposures in four wavelength bands from 3.6 to 8 m and spans a solid angle of about 9 square degrees. When this software was executed on 32 nodes of the 1,024-processor Cosmos cluster computer at NASA s Jet Propulsion Laboratory, a speedup of 8.3 was achieved over the serial version of MOPEX. The performance is expected to improve dramatically once a true parallel file system is installed on Cosmos.

Jacob, Joseph↗

Deep Reinforcement Learning Based Control of Wind Turbines for Fast Frequency Response

In order to fulfill vital auxiliary grid services, such as load regulation, spin and non-spin reserve provision, and frequency support during emergencies, there is often a requirement for certain wind farms to operate in de-loaded modes. Leveraging the swift response capabilities of wind farms, this study demonstrates that reserving power in de-loaded modes can significantly enhance power grid stability and reliability during system contingencies. Controlling wind farms optimally for frequency support is intricate due to the nonlinearity of models and controllers and the complexity of wind farm interactions with power systems. Here, to address this challenge, this paper introduces a novel approach that integrates wind turbines into reinforcement learning-based solutions for frequency response. This innovative methodology utilizes the state-of-the-art reinforcement learning algorithm known as the surrogate-gradient-based evolutionary strategy. The proposed learning-based algorithm provides continuous control of wind farm output to rapidly stabilize system frequency and prevent unnecessary trips of under-frequency load shedding relays. To facilitate efficient training, parallel computing techniques are employed. The proposed methodology is evaluated on a modified IEEE-39 bus system, and simulation results reveal its efficacy in reliably supporting power system frequency and preventing the need for unnecessary load shedding.

Gao, Wei [Argonne National Laboratory (ANL), Argon↗

Designing a Framework for Solving Multiobjective Simulation Optimization Problems

Multiobjective simulation optimization (MOSO) problems are optimization problems with multiple conflicting objectives, where evaluation of at least one of the objectives depends on a black-box numerical code or real-world experiment, which we refer to as a simulation. Whereas an extensive body of research is dedicated to developing new algorithms and methods for solving these and related problems, it is challenging and time-consuming to integrate these techniques into real-world production-ready solvers. This is partly because of the diversity and complexity of modern state-of-the-art MOSO algorithms and methods and partly because of the complexity and specificity of many real-world problems and their corresponding computing environments. The complexity of this problem is only compounded when introducing potentially complex and/or domain-specific surrogate-modeling techniques, problem formulations, design spaces, and data acquisition functions. Here, this paper carefully surveys the current state of the art in MOSO algorithms, techniques, and solvers, as well as problem types and computational environments where MOSO is commonly applied. We then present several key challenges in the design of a parallel multiobjective simulation optimization framework (ParMOO) and how they have been addressed. Finally, we provide two case studies demonstrating how customized ParMOO solvers can be quickly built and deployed to solve real-world MOSO problems.

engineering design optimization↗

Multiprocessor architecture: Synthesis and evaluation

Multiprocessor computed architecture evaluation for structural computations is the focus of the research effort described. Results obtained are expected to lead to more efficient use of existing architectures and to suggest designs for new, application specific, architectures. The brief descriptions given outline a number of related efforts directed toward this purpose. The difficulty is analyzing an existing architecture or in designing a new computer architecture lies in the fact that the performance of a particular architecture, within the context of a given application, is determined by a number of factors. These include, but are not limited to, the efficiency of the computation algorithm, the programming language and support environment, the quality of the program written in the programming language, the multiplicity of the processing elements, the characteristics of the individual processing elements, the interconnection network connecting processors and non-local memories, and the shared memory organization covering the spectrum from no shared memory (all local memory) to one global access memory. These performance determiners may be loosely classified as being software or hardware related. This distinction is not clear or even appropriate in many cases. The effect of the choice of algorithm is ignored by assuming that the algorithm is specified as given. Effort directed toward the removal of the effect of the programming language and program resulted in the design of a high-level parallel programming language. Two characteristics of the fundamental structure of the architecture (memory organization and interconnection network) are examined.

Standley, Hilda M.↗

Local parallel models for integration of stereo matching constraints and intrinsic image combination

Parallel relaxation computations such as those of connectionist networks offer a useful model for constraint integration and intrinsic image combination in developing a general-purpose stereo matching algorithm. This paper describes such a stereo algorithm that incorporates hierarchical, surface-structure, and edge-appearance constraints that are redefined and integrated at the level of individual candidate matches. The algorithm produces a high percentage of correct decisions on a wide variety of stereo pairs. Its few errors arise when the correlation measures defined by the constraints are either weakened or ambiguous, as in the case of periodic patterns in the images. Two additional mechanisms are discussed for overcoming the remaining errors.

Stewart, Charles V.↗