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At least 703 records · Page 39

Factors which Limit the Value of Additional Redundancy in Human Rated Launch Vehicle Systems

The National Aeronautics and Space Administration (NASA) has embarked on an ambitious program to return humans to the moon and beyond. As NASA moves forward in the development and design of new launch vehicles for future space exploration, it must fully consider the implications that rule-based requirements of redundancy or fault tolerance have on system reliability/risk. These considerations include common cause failure, increased system complexity, combined serial and parallel configurations, and the impact of design features implemented to control premature activation. These factors and others must be considered in trade studies to support design decisions that balance safety, reliability, performance and system complexity to achieve a relatively simple, operable system that provides the safest and most reliable system within the specified performance requirements. This paper describes conditions under which additional functional redundancy can impede improved system reliability. Examples from current NASA programs including the Ares I Upper Stage will be shown.

Anderson, Joel M.↗

Fully-Implicit Navier-Stokes (FIN-S)

FIN-S is a SUPG finite element code for flow problems under active development at NASA Lyndon B. Johnson Space Center and within PECOS: a) The code is built on top of the libMesh parallel, adaptive finite element library. b) The initial implementation of the code targeted supersonic/hypersonic laminar calorically perfect gas flows & conjugate heat transfer. c) Initial extension to thermochemical nonequilibrium about 9 months ago. d) The technologies in FIN-S have been enhanced through a strongly collaborative research effort with Sandia National Labs.

Kirk, Benjamin S.↗

CALIPSO Lidar Calibration at 532 nm: Version 4 Nighttime Algorithm

Data products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were recently updated following the implementation of new (version 4) calibration algorithms for all of the level 1 attenuated backscatter measurements. In this work we present the motivation for and the implementation of the version 4 nighttime 532 nm parallel channel calibration. The nighttime 532 nm calibration is the most fundamental calibration of CALIOP data, since all of CALIOP’s other radiometric calibration procedures – i.e., the 532 nm daytime calibration and the 1064 nm calibrations during both nighttime and daytime – depend either directly or indirectly on the 532 nm nighttime calibration. The accuracy of the 532 nm nighttime calibration has been significantly improved by raising the molecular normalization altitude from 30-34 km to 36-39 km to substantially reduce stratospheric aerosol contamination. Due to the greatly reduced molecular number density and consequently reduced signal-to-noise ratio (SNR) at these higher altitudes, the signal is now averaged over a larger number of samples using data from multiple adjacent granules. As well, an enhanced strategy for filtering the radiation-induced noise from high energy particles was adopted. Further, the meteorological model used in the earlier versions has been replaced by the improved MERRA-2 model. An aerosol scattering ratio of 1.01 ± 0.01 is now explicitly used for the calibration altitude. These modifications lead to globally revised calibration coefficients which are, on average, 2-3% lower than in previous data releases. Further, the new calibration procedure is shown to eliminate biases at high altitudes that were present in earlier versions and consequently leads to an improved representation of stratospheric aerosols. Validation results using airborne lidar measurements are also presented. Biases relative to collocated measurements acquired by the Langley Research Center (LaRC) airborne high spectral resolution lidar (HSRL) are reduced from 3.6% ± 2.2% in the version 3 data set to 1.6% ± 2.4 % in the version 4 release.

Jayanta Kar↗

The New (Version 4) Calibration of the Nighttime 532nm Channel of the CALIPSO Lidar

The data products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were recently updated following the implementation of a new (version 4.1) calibration algorithm for all the level 1 products. We present the motivation for and the implementation of the version 4.1 nighttime 532 nm parallel channel measurements. This is the most fundamental calibration of CALIOP data since all other measurements, i.e the 532 nm nighttime perpendicular, daytime 532 nm as well as 1064 nm are tied to this calibration. The new calibration is shown to resolve the discrepancies in the earlier version and also leads to an improved representation of the stratospheric aerosols. Initial validation results using ground based and airborne lidar measurements are also presented.

Kar, J.↗

Numerical Investigation of Multi-Rotor Configurations

The development of a conservative, parallel blade-element rotor model and its implementation into an adaptive Cartesian method is briefly reviewed. The model is first validated and then applied in edgewise forward flight for a variety of configurations. Validation studies comparing torque required for an isolated rotor match XV-15 wind tunnel trends well. Simulations of a simple quadrotor in “×” and “+” configurations are performed, demonstrating how the trailing rotor(s) lose thrust because of unfavorable aerodynamic interactions with the forward rotor(s), while power required remains near constant. A modified “+1” configuration is also examined, where the lateral rotors are brought inboard by 25%. This configuration showed a further 2% performance improvement over the “+” arrangement. The final paper will also include validation of a tandem rotor configuration with wind tunnel data as well as results and analysis of unsteady quadcopter simulations. In addition, a 4th configuration (× will be analyzed.

Multirotor↗

Efficiently modeling neural networks on massively parallel computers

Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.

Farber, Robert M.↗

Hypercube matrix computation task

A major objective of the Hypercube Matrix Computation effort at the Jet Propulsion Laboratory (JPL) is to investigate the applicability of a parallel computing architecture to the solution of large-scale electromagnetic scattering problems. Three scattering analysis codes are being implemented and assessed on a JPL/California Institute of Technology (Caltech) Mark 3 Hypercube. The codes, which utilize different underlying algorithms, give a means of evaluating the general applicability of this parallel architecture. The three analysis codes being implemented are a frequency domain method of moments code, a time domain finite difference code, and a frequency domain finite elements code. These analysis capabilities are being integrated into an electromagnetics interactive analysis workstation which can serve as a design tool for the construction of antennas and other radiating or scattering structures. The first two years of work on the Hypercube Matrix Computation effort is summarized. It includes both new developments and results as well as work previously reported in the Hypercube Matrix Computation Task: Final Report for 1986 to 1987 (JPL Publication 87-18).

Calalo, Ruel H.↗

An architecture for real-time vision processing

To study the feasibility of developing an architecture for real time vision processing, a task queue server and parallel algorithms for two vision operations were designed and implemented on an i860-based Mercury Computing System 860VS array processor. The proposed architecture treats each vision function as a task or set of tasks which may be recursively divided into subtasks and processed by multiple processors coordinated by a task queue server accessible by all processors. Each idle processor subsequently fetches a task and associated data from the task queue server for processing and posts the result to shared memory for later use. Load balancing can be carried out within the processing system without the requirement for a centralized controller. The author concludes that real time vision processing cannot be achieved without both sequential and parallel vision algorithms and a good parallel vision architecture.

Chien, Chiun-Hong↗

Distributed parallel processing applied to an implicit multigrid Euler/Navier-Stokes algorithm

An implicit multigrid algorithm for the solution of the Euler and Navier-Stokes equations has been implemented within the framework of multiple block-structured grids in which the physical domain is spatially decomposed into several blocks and the solution is advanced in parallel on each block. Utilities have been developed to implement such a scheme in a distributed computing environment. The multi-block algorithm is designed so that the explicit residual calculation is identical to that of single-block scheme, and therefore converged solutions for both schemes must be the same. To accelerate convergence, synchronous and asynchronous multigrid strategies are implemented. Significant speedups have been achieved in a multiple processor environment, while convergence rates similar to those of the single-block scheme are observed.

Tysinger, T. L.↗

CDMA with interference cancellation for multiprobe missions

Code division multiple-access spread spectrum has been proposed for use in future multiprobe/multispacecraft missions. This article considers a general parallel interference-cancellation scheme that significantly reduces the degradation effect of probe (user) interference but with a lesser implementation complexity than the maximum-likelihood technique. The scheme operates on the fact that parallel processing simultaneously removes from each probe (user) the total interference produced by the remaining most reliably received probes (users) accessing the channel. The parallel processing can be done in multiple stages. The proposed scheme uses tentative decision devices with different optimum thresholds at the multiple stages to produce the most reliably received data for generation and cancellation of probe/spacecraft interference. The one-stage interference cancellation was analyzed for two types of tentative decision devices, namely, hard and null zone decisions. Simulation results are given for one- and two-stage interference cancellation for equal as well as unequal received power probes.

Divsalar, D.↗

Contextual classification on the massively parallel processor

Classifiers are often used to produce land cover maps from multispectral Earth observation imagery. Conventionally, these classifiers have been designed to exploit the spectral information contained in the imagery. Very few classifiers exploit the spatial information content of the imagery, and the few that do rarely exploit spatial information content in conjunction with spectral and/or temporal information. A contextual classifier that exploits spatial and spectral information in combination through a general statistical approach was studied. Early test results obtained from an implementation of the classifier on a VAX-11/780 minicomputer were encouraging, but they are of limited meaning because they were produced from small data sets. An implementation of the contextual classifier is presented on the Massively Parallel Processor (MPP) at Goddard that for the first time makes feasible the testing of the classifier on large data sets.

Tilton, James C.↗

Efficient, massively parallel eigenvalue computation

In numerical simulations of disordered electronic systems, one of the most common approaches is to diagonalize random Hamiltonian matrices and to study the eigenvalues and eigenfunctions of a single electron in the presence of a random potential. An effort to implement a matrix diagonalization routine for real symmetric dense matrices on massively parallel SIMD computers, the Maspar MP-1 and MP-2 systems, is described. Results of numerical tests and timings are also presented.

Huo, Yan↗

Parallel processors and nonlinear structural dynamics algorithms and software

Techniques are discussed for the implementation and improvement of vectorization and concurrency in nonlinear explicit structural finite element codes. In explicit integration methods, the computation of the element internal force vector consumes the bulk of the computer time. The program can be efficiently vectorized by subdividing the elements into blocks and executing all computations in vector mode. The structuring of elements into blocks also provides a convenient way to implement concurrency by creating tasks which can be assigned to available processors for evaluation. The techniques were implemented in a 3-D nonlinear program with one-point quadrature shell elements. Concurrency and vectorization were first implemented in a single time step version of the program. Techniques were developed to minimize processor idle time and to select the optimal vector length. A comparison of run times between the program executed in scalar, serial mode and the fully vectorized code executed concurrently using eight processors shows speed-ups of over 25. Conjugate gradient methods for solving nonlinear algebraic equations are also readily adapted to a parallel environment. A new technique for improving convergence properties of conjugate gradients in nonlinear problems is developed in conjunction with other techniques such as diagonal scaling. A significant reduction in the number of iterations required for convergence is shown for a statically loaded rigid bar suspended by three equally spaced springs.

Belytschko, Ted↗

Programming model for distributed intelligent systems

A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.

Sztipanovits, J.↗

User's guide to the Fault Inferring Nonlinear Detection System (FINDS) computer program

Described are the operation and internal structure of the computer program FINDS (Fault Inferring Nonlinear Detection System). The FINDS algorithm is designed to provide reliable estimates for aircraft position, velocity, attitude, and horizontal winds to be used for guidance and control laws in the presence of possible failures in the avionics sensors. The FINDS algorithm was developed with the use of a digital simulation of a commercial transport aircraft and tested with flight recorded data. The algorithm was then modified to meet the size constraints and real-time execution requirements on a flight computer. For the real-time operation, a multi-rate implementation of the FINDS algorithm has been partitioned to execute on a dual parallel processor configuration: one based on the translational dynamics and the other on the rotational kinematics. The report presents an overview of the FINDS algorithm, the implemented equations, the flow charts for the key subprograms, the input and output files, program variable indexing convention, subprogram descriptions, and the common block descriptions used in the program.

Caglayan, A. K.↗

Dynamic Load Balancing for Computational Plasticity on Parallel Computers

The simulation of the computational plasticity on a complex structure remains a formidable computational task, especially when a highly nonlinear, complex material model was used. It appears that the computational requirements for a such problem can only be satisfied by massively parallel architectures. In order to effectively harness the tremendous computational power provided by such architectures, it is imperative to investigate and to study the algorithmic and implementation issues pertaining to dynamic load balancing for computational plasticity on a highly parallel, distributed-memory, multiple-instruction, multiple-data computers. This paper will measure the effectiveness of the algorithms developed in handling the dynamic load balancing.

Pramono, Eddy↗

Electromagnetic Design of a Magnetically-Coupled Spatial Power Combiner

The design of a two-dimensional beam-combining network employing a parallel-plate superconducting waveguide with a mono-crystalline silicon dielectric is presented. This novel beam-combining network structure employs an array of magnetically coupled antenna elements to achieve high coupling efficiency and full sampling of the intensity distribution while avoiding diffractive losses in the multi-mode region defined by the parallel-plate waveguide. These attributes enable the structures use in realizing compact far-infrared spectrometers for astrophysical and instrumentation applications. When configured with a suitable corporate-feed power-combiner, this fully sampled array can be used to realize a low-sidelobe apodized response without incurring a reduction in coupling efficiency. To control undesired reflections over a wide range of angles in the finite-sized parallel-plate waveguide region, a wideband meta-material electromagnetic absorber structure is implemented. This adiabatic structure absorbs greater than 99 of the power over the 1.7:1 operational band at angles ranging from normal (0 degree) to near parallel (180 degree) incidence. Design, simulations, and application of the device will be presented.

Bulcha, B.↗

Parallel Finite Element Solution of 3D Rayleigh-Benard-Marangoni Flows

A domain decomposition strategy and parallel gradient-type iterative solution scheme have been developed and implemented for computation of complex 3D viscous flow problems involving heat transfer and surface tension effects. Details of the implementation issues are described together with associated performance and scalability studies. Representative Rayleigh-Benard and microgravity Marangoni flow calculations and performance results on the Cray T3D and T3E are presented. The work is currently being extended to tightly-coupled parallel "Beowulf-type" PC clusters and we present some preliminary performance results on this platform. We also describe progress on related work on hierarchic data extraction for visualization.

Carey, G. F.↗