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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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NASA NTRS1999

Scientific Programming Using Java: A Remote Sensing Example

This paper presents results of a project to port remote sensing code from the C programming language to Java. The advantages and disadvantages of using Java versus C as a scientific programming language in remote sensing applications are discussed. Remote sensing applications deal with voluminous data that require effective memory management, such as buffering operations, when processed. Some of these applications also implement complex computational algorithms, such as Fast Fourier Transformation analysis, that are very performance intensive. Factors considered include performance, precision, complexity, rapidity of development, ease of code reuse, ease of maintenance, memory management, and platform independence. Performance of radiometric calibration code written in Java for the graphical user interface and of using C for the domain model are also presented.

Prados, Don↗

NASA NTRS1992

Neural network training by integration of adjoint systems of equations forward in time

A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically, it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved, but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. The trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.

Toomarian, Nikzad↗

NASA NTRS1999

Neural Network Training by Integration of Adjoint Systems of Equations Forward in Time

A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically. it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved. but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. Tbc trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.

Toomarian, Nikzad↗

NASA NTRS1986

A new VLSI complex integer multiplier which uses a quadratic-polynomial residue system with Fermat numbers

A quadratic-polynomial Fermat residue number system (QFNS) has been used to compute complex integer multiplications. The advantage of such a QFNS is that a complex integer multiplication requires only two integer multiplications. In this article, a new type Fermat number multiplier is developed which eliminates the initialization condition of the previous method. It is shown that the new complex multiplier can be implemented on a single VLSI chip. Such a chip is designed and fabricated in CMOS-pw technology.

Truong, T. K.↗

NASA NTRS1987

A new VLSI complex integer multiplier which uses a quadratic-polynomial residue system with Fermat numbers

Shyu, H. C.↗

NASA NTRS1976

The implementation of fail-operative functions in integrated digital avionics systems

System architectures which incorporate fail operative flight guidance functions within a total integrated avionics complex are described. It is shown that the mixture of flight critical and nonflight critical functions within a common computer complex is an efficient solution to the integration of navigation, guidance, flight control, display, and flight management. Interfacing subsystems retain autonomous capability to avoid vulnerability to total avionics system shutdown as a result of only a few failures.

Osoer, S. S.↗

NASA NTRS1994

Very fast motion planning for highly dexterous-articulated robots

Due to the inherent danger of space exploration, the need for greater use of teleoperated and autonomous robotic systems in space-based applications has long been apparent. Autonomous and semi-autonomous robotic devices have been proposed for carrying out routine functions associated with scientific experiments aboard the shuttle and space station. Finally, research into the use of such devices for planetary exploration continues. To accomplish their assigned tasks, all such autonomous and semi-autonomous devices will require the ability to move themselves through space without hitting themselves or the objects which surround them. In space it is important to execute the necessary motions correctly when they are first attempted because repositioning is expensive in terms of both time and resources (e.g., fuel). Finally, such devices will have to function in a variety of different environments. Given these constraints, a means for fast motion planning to insure the correct movement of robotic devices would be ideal. Unfortunately, motion planning algorithms are rarely used in practice because of their computational complexity. Fast methods have been developed for detecting imminent collisions, but the more general problem of motion planning remains computationally intractable. However, in this paper we show how the use of multicomputers and appropriate parallel algorithms can substantially reduce the time required to synthesize paths for dexterous articulated robots with a large number of joints. We have developed a parallel formulation of the Randomized Path Planner proposed by Barraquand and Latombe. We have shown that our parallel formulation is capable of formulating plans in a few seconds or less on various parallel architectures including: the nCUBE2 multicomputer with up to 1024 processors (nCUBE2 is a registered trademark of the nCUBE corporation), and a network of workstations.

Challou, Daniel J.↗

NASA NTRSDate not supplied

Optimization of a Solver for Computational Materials and Structures Problems on NVIDIA Volta and AMD Instinct GPUs

The Scalable Implementation of Finite Elements by NASA (ScIFEN) is a software package developed to solve complex computational materials and structures problems using the finite element method (FEM). In this paper, we describe optimization techniques to speed up the linear solver computation that occurs within the ScIFEN application. We consider GPUs from two different vendors, NVIDIA and AMD as our target platforms for optimization and highlight differences in performance and optimization techniques. The NVIDIA GPU Volta V100 is used in the Summit system deployed at Oak Ridge National Laboratory, and the new exascale system, Frontier, will be using AMD Radeon Instinct GPU. We evaluated the performance of various optimization techniques on test matrices, ranging in size from100K to 4M, that are representative of ScIFEN applications. The linear solver computation is memory-bound on both GPUs. Our experiments show that on the NVIDIA GPU we obtained up to79%of the theoretical peak bandwidth, while the AMD GPU achieved 59%. Overall, the NVIDIA V100 GPU outperforms the AMD MI 25 GPU1. We observed an overall speedup of up to37X on an NVIDIA V100 compared to an Intel Skylake 12-coremachine. The solver for a 4M degree of freedom system took under 2.5 seconds.

Mohammad Zubair↗

NASA NTRS1980

Real-time data reduction capabilities at the Langley 7 by 10 foot high speed tunnel

The 7 by 10 foot high speed tunnel performs a wide range of tests employing a variety of model installation methods. To support the reduction of static data from this facility, a generalized wind tunnel data reduction program had been developed for use on the Langley central computer complex. The capabilities of a version of this generalized program adapted for real time use on a dedicated on-site computer are discussed. The input specifications, instructions for the console operator, and full descriptions of the algorithms are included.

Fox, C. H., Jr.↗

NASA NTRSDate not supplied

Dude Where's My Stars: A Novel Topologically Justified Approach to Star Tracking

In this paper, we consider two novel approaches to celestial navigation for spacecraft. Determining attitude without any prior knowledge using star tracking is known to be a difficult task, particularly given the computational complexity and the many potential sources of misinformation. We consider localization by optimizing matching parameters without explicit star identification in a computationally tractable manner. This is achieved using the mathematical tools of topological data analysis (TDA) and cellular sheaves to study the geometry and distribution of cataloged stars. A framework is gained that enhances the statistical approach to noise handling and false star detection, and heterogeneous sensor fusion. Finally, we discuss confidence bounds and minimum information requirements for successful operation.

Sheaf theory↗

NASA NTRS1991

Monte-Carlo methods make Dempster-Shafer formalism feasible

One of the main obstacles to the applications of Dempster-Shafer formalism is its computational complexity. If we combine m different pieces of knowledge, then in general case we have to perform up to 2(sup m) computational steps, which for large m is infeasible. For several important cases algorithms with smaller running time were proposed. We prove, however, that if we want to compute the belief bel(Q) in any given query Q, then exponential time is inevitable. It is still inevitable, if we want to compute bel(Q) with given precision epsilon. This restriction corresponds to the natural idea that since initial masses are known only approximately, there is no sense in trying to compute bel(Q) precisely. A further idea is that there is always some doubt in the whole knowledge, so there is always a probability p(sub o) that the expert's knowledge is wrong. In view of that it is sufficient to have an algorithm that gives a correct answer a probability greater than 1-p(sub o). If we use the original Dempster's combination rule, this possibility diminishes the running time, but still leaves the problem infeasible in the general case. We show that for the alternative combination rules proposed by Smets and Yager feasible methods exist. We also show how these methods can be parallelized, and what parallelization model fits this problem best.

Kreinovich, Vladik YA.↗

NASA NTRS2009

Physical Principle for Generation of Randomness

A physical principle (more precisely, a principle that incorporates mathematical models used in physics) has been conceived as the basis of a method of generating randomness in Monte Carlo simulations. The principle eliminates the need for conventional random-number generators. The Monte Carlo simulation method is among the most powerful computational methods for solving high-dimensional problems in physics, chemistry, economics, and information processing. The Monte Carlo simulation method is especially effective for solving problems in which computational complexity increases exponentially with dimensionality. The main advantage of the Monte Carlo simulation method over other methods is that the demand on computational resources becomes independent of dimensionality. As augmented by the present principle, the Monte Carlo simulation method becomes an even more powerful computational method that is especially useful for solving problems associated with dynamics of fluids, planning, scheduling, and combinatorial optimization. The present principle is based on coupling of dynamical equations with the corresponding Liouville equation. The randomness is generated by non-Lipschitz instability of dynamics triggered and controlled by feedback from the Liouville equation. (In non-Lipschitz dynamics, the derivatives of solutions of the dynamical equations are not required to be bounded.)

Zak, Michail↗

NASA NTRS1973

Shuttle mission simulator baseline definition report, volume 2

The baseline definition report for the space shuttle mission simulator is presented. The subjects discussed are: (1) the general configurations, (2) motion base crew station, (3) instructor operator station complex, (4) display devices, (5) electromagnetic compatibility, (6) external interface equipment, (7) data conversion equipment, (8) fixed base crew station equipment, and (9) computer complex. Block diagrams of the supporting subsystems are provided.

Dahlberg, A. W.↗

NASA NTRS1987

Navier-Stokes simulation of real gas flows in nozzles

Air flow in a hypersonic nozzle causes real gas effects due to reaction among the species constituting air. Such reactions may be in chemical equilibrium or in chemical nonequilibrium. Here using the CSCM upwind scheme for the compressible Navier-Stokes equations, the real gas flowfield in an arcjet nozzle is computed for both the equilibrium case and the nonequilibrium case. A hypersonic nozzle flow arising from a pebble bed heated plenum is also computed for the equilibrium situation. Between the equilibrium cases, the chemistry is treated by two different schemes and comments are made as to computational complexity. For the nonequilibrium case, a full set of seventeen reactions and full implicit coupling of five species with gasdynamics is employed to compute the flowfield. For all cases considered here the gas is assumed to be a calorically imperfect mixture of ideal gases in thermal equilibrium.

Nagaraj, N.↗

NASA NTRS1990

Constructing an advanced software tool for planetary atmospheric modeling

Scientific model building can be an intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot be easily distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientist/programmer to understand. We believe that advanced software techniques can facilitate both the model building and model sharing process. In this paper, we describe a prototype for a scientific modeling software tool that serves as an aid to the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities. Our prototype has been developed in the domain of planetary atmospheric modeling, and is being used to construct models of Titan's atmosphere.

Keller, Richard M.↗

NASA NTRS1990

Proposal for constructing an advanced software tool for planetary atmospheric modeling

Scientific model building can be a time intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientist/programmer to understand. We believe that advanced software techniques can facilitate both the model building and model sharing process. We propose to construct a scientific modeling software tool that serves as an aid to the scientist in developing and using models. The proposed tool will include an interactive intelligent graphical interface and a high level, domain specific, modeling language. As a testbed for this research, we propose development of a software prototype in the domain of planetary atmospheric modeling.

Keller, Richard M.↗

NASA NTRS1992

Artificial intelligence support for scientific model-building

Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

Keller, Richard M.↗

NASA NTRS2007

Scope of Gradient and Genetic Algorithms in Multivariable Function Optimization

Global optimization of a multivariable function - constrained by bounds specified on each variable and also unconstrained - is an important problem with several real world applications. Deterministic methods such as the gradient algorithms as well as the randomized methods such as the genetic algorithms may be employed to solve these problems. In fact, there are optimization problems where a genetic algorithm/an evolutionary approach is preferable at least from the quality (accuracy) of the results point of view. From cost (complexity) point of view, both gradient and genetic approaches are usually polynomial-time; there are no serious differences in this regard, i.e., the computational complexity point of view. However, for certain types of problems, such as those with unacceptably erroneous numerical partial derivatives and those with physically amplified analytical partial derivatives whose numerical evaluation involves undesirable errors and/or is messy, a genetic (stochastic) approach should be a better choice. We have presented here the pros and cons of both the approaches so that the concerned reader/user can decide which approach is most suited for the problem at hand. Also for the function which is known in a tabular form, instead of an analytical form, as is often the case in an experimental environment, we attempt to provide an insight into the approaches focusing our attention toward accuracy. Such an insight will help one to decide which method, out of several available methods, should be employed to obtain the best (least error) output. *

Shaykhian, Gholam Ali↗