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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

cWINNOWER Algorithm for Finding Fuzzy DNA Motifs

The cWINNOWER algorithm detects fuzzy motifs in DNA sequences rich in protein-binding signals. A signal is defined as any short nucleotide pattern having up to d mutations differing from a motif of length l. The algorithm finds such motifs if multiple mutated copies of the motif (i.e., the signals) are present in the DNA sequence in sufficient abundance. The cWINNOWER algorithm substantially improves the sensitivity of the winnower method of Pevzner and Sze by imposing a consensus constraint, enabling it to detect much weaker signals. We studied the minimum number of detectable motifs qc as a function of sequence length N for random sequences. We found that qc increases linearly with N for a fast version of the algorithm based on counting three-member sub-cliques. Imposing consensus constraints reduces qc, by a factor of three in this case, which makes the algorithm dramatically more sensitive. Our most sensitive algorithm, which counts four-member sub-cliques, needs a minimum of only 13 signals to detect motifs in a sequence of length N = 12000 for (l,d) = (15,4).

Liang, Shoudan↗
NASA NTRS2004

Preparations for Global Precipitation Measurement(GPM)Ground Validation

The Global Precipitation Measurement (GPM) program is an international partnership led by the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA). GPM will improve climate, weather, and hydro-meterorological forecasts through more frequent and more accurate measurement of precipitation across the globe. This paper describes the concept and the preparations for Ground Validation within the GPM program. Ground Validation (GV) plays a critical role in the program by investigating and quantitatively assessing the errors within the satellite retrievals. These quantitative estimates of retrieval errors will assist the scientific community by bounding the errors within their research products. The two fundamental requirements of the GPM Ground Validation program are: (1) error characterization of the precipitation retrievals and (2) continual improvement of the satellite retrieval algorithms. These two driving requirements determine the measurements, instrumentation, and location for ground observations. This paper describes GV plans for estimating the systematic and random components of retrieval error and for characterizing the spatial and temporal structure of the error. This paper describes the GPM program for algorithm improvement in which error models are developed and experimentally explored to uncover the physical causes of errors within the retrievals. GPM will ensure that information gained through Ground Validation is applied to future improvements in the spaceborne retrieval algorithms. This paper discusses the potential locations for validation measurement and research, the anticipated contributions of GPM's international partners, and the interaction of Ground Validation with other GPM program elements.

Bidwell, S. W.↗
NASA NTRS1984

Studies of coastal mesoscale winds using SIR-B

The variability of the mesoscale wind fields near coastlines which can be caused by mountains that shadow offshore wind and by valleys that enhance them. These wind, provide relatively fixed patterns that must be considered in the development of algorithms for future spaceborne scatterometer systems; mesoscale variability over the offshore regions is random and must be averaged out for forecasting yet nearshore fixed patterns are treated differently. Before the patterns of interest can be defined quantitatively, the scattering response of the ocean to winds at the L-band frequency and SIR-B angles of incidence must be developed from the SIR-B data. Patterns can be analyzed on the images both in regions selected for high probability of the occurrence of suitable patterns, and in other regions where the patterns are observed. The patterns are analyzed for topographic effects and the distance to sea over which these effects cause variations in the oceanic wind patterns. The results are interpreted in terms of quantitative description of the processes involved and in for need of modifications of future scatterometer algorithms.

Moore, R. K.↗
NASA NTRS1992

A sweep algorithm for massively parallel simulation of circuit-switched networks

A new massively parallel algorithm is presented for simulating large asymmetric circuit-switched networks, controlled by a randomized-routing policy that includes trunk-reservation. A single instruction multiple data (SIMD) implementation is described, and corresponding experiments on a 16384 processor MasPar parallel computer are reported. A multiple instruction multiple data (MIMD) implementation is also described, and corresponding experiments on an Intel IPSC/860 parallel computer, using 16 processors, are reported. By exploiting parallelism, our algorithm increases the possible execution rate of such complex simulations by as much as an order of magnitude.

Gaujal, Bruno↗
NASA NTRS1988

Kanerva's sparse distributed memory: An associative memory algorithm well-suited to the Connection Machine

The advent of the Connection Machine profoundly changes the world of supercomputers. The highly nontraditional architecture makes possible the exploration of algorithms that were impractical for standard Von Neumann architectures. Sparse distributed memory (SDM) is an example of such an algorithm. Sparse distributed memory is a particularly simple and elegant formulation for an associative memory. The foundations for sparse distributed memory are described, and some simple examples of using the memory are presented. The relationship of sparse distributed memory to three important computational systems is shown: random-access memory, neural networks, and the cerebellum of the brain. Finally, the implementation of the algorithm for sparse distributed memory on the Connection Machine is discussed.

Rogers, David↗
NASA NTRS1984

Development and preliminary tests of a new long-wave radiation parameterization

An efficient broad band longwave radiation code for CO2 and H2O and for O3 was developed. There are two bands each in the CO2 and H2O absorption regions, one for the band center and one for the band wings. One band covers O3 absorption and the overlapping H2O continuum. Overlap is also considered in the CO2 region, and there is H2O continuum absorption where applicable. Clouds are considered nonreflecting in the longwave. Therefore partial cover or partial transmission can be allowed for, by considering a cloud fraction at each atmospheric level. A special subroutine was written to allow for maximum or random overlap of clouds that may be used in the future. All algorithms were written with vectorization in mind with identical operations made for all horizontal grid points in a latitude circle. Where possible, operations are carried out covering the vertical grid points as well, yielding long vectors for efficient computations.

HARSHVARDHAN↗
NASA NTRS1985

Numerical synthesis of tri-variate velocity realizations of turbulence

An approach for synthesizing trivariate turbulence velocity field spatial realizations is presented. Some of the spatial frequency characteristics of the random velocity field are described by the von Karman spectrum. The simulation algorithm is based on an efficient autoregressive-moving average (ARMA) scheme involving coefficient square matrices of order three. The determination of the efficient low order ARMA algorithm is preceded by the determination of a suitable high order autoregressive (AR) simulation algorithm. The numerical results are presented in a dimensionless form. Thus, they are applicable for any scale of turbulence.

Spanos, P.-T. D.↗
NASA NTRS1999

Investigation of Near Shannon Limit Coding Schemes

Turbo codes can deliver performance that is very close to the Shannon limit. This report investigates algorithms for convolutional turbo codes and block turbo codes. Both coding schemes can achieve performance near Shannon limit. The performance of the schemes is obtained using computer simulations. There are three sections in this report. First section is the introduction. The fundamental knowledge about coding, block coding and convolutional coding is discussed. In the second section, the basic concepts of convolutional turbo codes are introduced and the performance of turbo codes, especially high rate turbo codes, is provided from the simulation results. After introducing all the parameters that help turbo codes achieve such a good performance, it is concluded that output weight distribution should be the main consideration in designing turbo codes. Based on the output weight distribution, the performance bounds for turbo codes are given. Then, the relationships between the output weight distribution and the factors like generator polynomial, interleaver and puncturing pattern are examined. The criterion for the best selection of system components is provided. The puncturing pattern algorithm is discussed in detail. Different puncturing patterns are compared for each high rate. For most of the high rate codes, the puncturing pattern does not show any significant effect on the code performance if pseudo - random interleaver is used in the system. For some special rate codes with poor performance, an alternative puncturing algorithm is designed which restores their performance close to the Shannon limit. Finally, in section three, for iterative decoding of block codes, the method of building trellis for block codes, the structure of the iterative decoding system and the calculation of extrinsic values are discussed.

Kwatra, S. C.↗
NASA NTRS2003

Engineering-Level Model Atmospheres for Titan and Neptune

Engineering-level atmospheric models for Titan and Neptune have been developed for use in NASA s systems analysis studies of aerocapture applications in missions to the outer planets. Analogous to highly successful Global Reference Atmospheric Models for Earth (GRAM, Justus et al., 2000) and Mars (Mars-GRAM, Justus and Johnson, 2001, Justus et al., 2002) the new models are called Titan-GRAM and Neptune-GRAM. Like GRAM and Mars-GRAM, an important feature of Titan-GRAM and Neptune-GRAM is their ability to simulate quasi-random perturbations for Monte- Carlo analyses in developing guidance, navigation and control algorithms, and for thermal systems design.

Justus, C. G.↗
NASA NTRS2004

Atmospheric Models for Aeroentry and Aeroassist

Eight destinations in the Solar System have sufficient atmosphere for aeroentry, aeroassist, or aerobraking/aerocapture: Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune, plus Saturn's moon Titan. Engineering-level atmospheric models for Earth, Mars, Titan, and Neptune have been developed for use in NASA s systems analysis studies of aerocapture applications. Development has begun on a similar atmospheric model for Venus. An important capability of these models is simulation of quasi-random perturbations for Monte Carlo analyses in developing guidance, navigation and control algorithms, and for thermal systems design. Characteristics of these atmospheric models are compared, and example applications for aerocapture are presented. Recent Titan atmospheric model updates are discussed, in anticipation of applications for trajectory and atmospheric reconstruct of Huygens Probe entry at Titan. Recent and planned updates to the Mars atmospheric model, in support of future Mars aerocapture systems analysis studies, are also presented.

Justus, C. G.↗
NASA NTRS2005

GRAM Series of Atmospheric Models for Aeroentry and Aeroassist

The eight destinations in the Solar System with sufficient atmosphere for either aeroentry or aeroassist, including aerocapture, are: Venus, Earth, Mars, Jupiter, Saturn; Uranus. and Neptune, and Saturn's moon Titan. Engineering-level atmospheric models for four of these (Earth, Mars, Titan, and Neptune) have been developed for use in NASA's systems analysis studies of aerocapture applications in potential future missions. Work has recently commenced on development of a similar atmospheric model for Venus. This series of MSFC-sponsored models is identified as the Global Reference Atmosphere Model (GRAM) series. An important capability of all of the models in the GRAM series is their ability to simulate quasi-random perturbations for Monte Carlo analyses in developing guidance, navigation and control algorithms, and for thermal systems design. Example applications for Earth aeroentry and Mars aerocapture systems analysis studies are presented and illustrated. Current and planned updates to the Earth and Mars atmospheric models, in support of NASA's new exploration vision, are also presented.

Duvall, Aleta↗
NASA NTRS2005

GLOBAL REFERENCE ATMOSPHERIC MODELS FOR AEROASSIST APPLICATIONS

Aeroassist is a broad category of advanced transportation technology encompassing aerocapture, aerobraking, aeroentry, precision landing, hazard detection and avoidance, and aerogravity assist. The eight destinations in the Solar System with sufficient atmosphere to enable aeroassist technology are Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Saturn's moon Titan. Engineering-level atmospheric models for five of these targets - Earth, Mars, Titan, Neptune, and Venus - have been developed at NASA's Marshall Space Flight Center. These models are useful as tools in mission planning and systems analysis studies associated with aeroassist applications. The series of models is collectively named the Global Reference Atmospheric Model or GRAM series. An important capability of all the models in the GRAM series is their ability to simulate quasi-random perturbations for Monte Carlo analysis in developing guidance, navigation and control algorithms, for aerothermal design, and for other applications sensitive to atmospheric variability. Recent example applications are discussed.

Duvall, Aleta↗
NASA NTRS2005

Atmospheric Models for Aeroentry and Aeroassist

Eight destinations in the Solar System have sufficient atmosphere for aeroentry, aeroassist, or aerobraking/aerocapture: Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune, plus Saturn's moon Titan. Engineering-level atmospheric models for Earth, Mars, Titan, and Neptune have been developed for use in NASA's systems analysis studies of aerocapture applications. Development has begun on a similar atmospheric model for Venus. An important capability of these models is simulation of quasi-random perturbations for Monte Carlo analyses in developing guidance, navigation and control algorithms, and for thermal systems design. Characteristics of these atmospheric models are compared, and example applications for aerocapture are presented. Recent Titan atmospheric model updates are discussed, in anticipation of applications for trajectory and atmospheric reconstruct of Huygens Probe entry at Titan. Recent and planned updates to the Mars atmospheric model, in support of future Mars aerocapture systems analysis studies, are also presented.

Justus, C. G.↗
NASA NTRS2017

A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications

Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort.

Grauer, Jared A.↗
NASA NTRS1991

Probabilistic structural analysis algorithm development for computational efficiency

The PSAM (Probabilistic Structural Analysis Methods) program is developing a probabilistic structural risk assessment capability for the SSME components. An advanced probabilistic structural analysis software system, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress), is being developed as part of the PSAM effort to accurately simulate stochastic structures operating under severe random loading conditions. One of the challenges in developing the NESSUS system is the development of the probabilistic algorithms that provide both efficiency and accuracy. The main probability algorithms developed and implemented in the NESSUS system are efficient, but approximate in nature. In the last six years, the algorithms have improved very significantly.

Wu, Y.-T.↗
NASA NTRS2008

Implementation of Complex Signal Processing Algorithms for Position-Sensitive Microcalorimeters

We have recently reported on a theoretical digital signal-processing algorithm for improved energy and position resolution in position-sensitive, transition-edge sensor (POST) X-ray detectors [Smith et al., Nucl, lnstr and Meth. A 556 (2006) 2371. PoST's consists of one or more transition-edge sensors (TES's) on a large continuous or pixellated X-ray absorber and are under development as an alternative to arrays of single pixel TES's. PoST's provide a means to increase the field-of-view for the fewest number of read-out channels. In this contribution we extend the theoretical correlated energy position optimal filter (CEPOF) algorithm (originally developed for 2-TES continuous absorber PoST's) to investigate the practical implementation on multi-pixel single TES PoST's or Hydras. We use numerically simulated data for a nine absorber device, which includes realistic detector noise, to demonstrate an iterative scheme that enables convergence on the correct photon absorption position and energy without any a priori assumptions. The position sensitivity of the CEPOF implemented on simulated data agrees very well with the theoretically predicted resolution. We discuss practical issues such as the impact of random arrival phase of the measured data on the performance of the CEPOF. The CEPOF algorithm demonstrates that full-width-at- half-maximum energy resolution of < 8 eV coupled with position-sensitivity down to a few 100 eV should be achievable for a fully optimized device.

Smith, Stephen J.↗
NASA NTRS1986

A pattern-matching algorithm for two-dimensional coordinate lists

A pattern-matching algorithm for two-dimensional coordinate lists is described. The algorithm matches pairs of coordinates in two lists based on the triangles that can be formed from triplets of points in each list. The algorithm is insensitive to coordinate translation, rotation, magnification, or inversion and can tolerate random errors or distortions.

Groth, E. J.↗