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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Dynamical eigenfunction decomposition of turbulent channel flow

The results of an analysis of low-Reynolds-number turbulent channel flow based on the Karhunen-Loeve (K-L) expansion are presented. The turbulent flow field is generated by a direct numerical simulation of the Navier-Stokes equations at a Reynolds number Re(tau) = 80 (based on the wall shear velocity and channel half-width). The K-L procedure is then applied to determine the eigenvalues and eigenfunctions for this flow. The random coefficients of the K-L expansion are subsequently found by projecting the numerical flow field onto these eigenfunctions. The resulting expansion captures 90 percent of the turbulent energy with significantly fewer modes than the original trigonometric expansion. The eigenfunctions, which appear either as rolls or shearing motions, possess viscous boundary layers at the walls and are much richer in harmonics than the original basis functions.

Ball, K. S.↗
NASA NTRS2003

Estimating Uncertainty in GPCP and TRMM Multi-Satellite Precipitation Estimates

One of the high-priority problems in satellite precipitation estimation is developing algorithms for estimating the errors in precipitation retrievals by individual sensors and subsequent multi-satellite combinations. Classically, we distinguish between "random" and "bias" errors, which do and do not, respectively average to zero over a "big enough" time/space sample. The current operational GPCP and TRMM multi-satellite algorithms are nearly unique in estimating random error for the monthly precipitation estimates from individual sensor systems (including gauge), following Huffman, and then making multi-sensor combinations. No routinely operational global precipitation produces estimates of bias error. Subsequently, a similar scheme has been followed to provide random error estimates for the Multi-satellite Precipitation Analysis (MPA) being computed in real time and after real time for TRMM. The Huffman algorithm for random error is briefly reviewed, including a discussion of the limitations imposed on the algorithm by standard monthly precipitation data sets. Starting from a very simple theoretical treatment of the histogram of precipitation samples in a month, an equation is developed that depends on the estimated average precipitation rate for the month, the number of samples in the month, and two constants. The constants are set separately for each source of precipitation estimate (such as "raingauge") by calibration at selected ground sites. We discuss recent work validating the random error estimates to highlight the successes and limitations of this first-generation approach. We then consider what information is needed from the individual sensor algorithms to facilitate additional accuracy in the estimation of random errors across the time/space span of climate regimes which a global estimation system must handle. In addition, the thorny issue of estimating bias is raised. Finally, the role of error estimates (and the qualitative errors!) in creating combinations of precipitation estimates from different individual sensors is discussed. This issue is particularly important when fine scales in space and time are being considered, say the 0.25 x 0.25-deg 3-hourly estimates in the MPA.

Huffman, G. J.↗
NASA NTRS1994

The short-term prediction of universal time and length of day using atmospheric angular momentum

The ability to predict short-term variations in the Earth's rotation has gained importance in recent years owing to more precise spacecraft tracking requirements. Universal time (UT1), that component of the Earth's orientation corresponding to the rotation angle, can be measured by number of high-precision space geodetic techniques. A Kalman filter developed at the Jet Propulsion Laboratory (JPL) optimally combines these different data sets and generates a smoothed times series and a set of predictions for UT1, as well as for additional Earth orientation components. These UT1 predictions utilize an empirically derived random walk stochastic model for the length of the day (LOD) and require frequent and up-to-date measurements of either UT1 or LOD to keep errors from quickly accumulating. Recent studies have shown that LOD variations are correlated with changes in the Earth's axial atmospheric angular momentum (AAM) over timescales of several years down to as little as 8 days. AAM estimates and forecasts out to 10 days are routinely available from meteorological analysis centers; these data can supplement geodetic measurements to improve the short-term prediction of LOD and have therefore been incorporated as independent data types in the JPL Kalman filter. We find that AAM and, to a lesser extent, AAM forecast data are extremely helpful in generating accurate near-real-time estimates of UT1 and LOD and in improving short-term predictions of these quantities out to about 10 days.

Freedman, A. P.↗
NASA NTRS1992

On the RNG theory of turbulence

The Yakhot and Orszag (1986) renormalization group (RNG) theory of turbulence has generated a number of scaling law constants in reasonable quantitative agreement with experiments. The theory itself is highly mathematical, and its assumptions and approximations are not easily appreciated. The present paper reviews the RNG theory and recasts it in more conventional terms using a distinctly different viewpoint. A new formulation based on an alternative interpretation of the origin of the random force is presented, showing that the artificially introduced epsilon in the original theory is an adjustable parameter, thus offering a plausible explanation for the remarkable record of quantitative success of the so-called epsilon-expansion procedure.

Lam, S. H.↗
NASA NTRS2018

Randomizer for High Data Rates

NASA as well as a number of other space agencies now recognize that the current recommended CCSDS randomizer used for telemetry (TM) is too short. When multiple applications of the PN8 Maximal Length Sequence (MLS) are required in order to fully cover a channel access data unit (CADU), spectral problems in the form of elevated spurious discretes (spurs) appear. Originally the randomizer was called a bit transition generator (BTG) precisely because it was thought that its primary value was to insure sufficient bit transitions to allow the bit/symbol synchronizer to lock and remain locked. We, NASA, have shown that the old BTG concept is a limited view of the real value of the randomizer sequence and that the randomizer also aids in signal acquisition as well as minimizing the potential for false decoder lock. Under the guidelines we considered here there are multiple maximal length sequences under GF(2) which appear attractive in this application. Although there may be mitigating reasons why another MLS sequence could be selected, one sequence in particular possesses a combination of desired properties which offsets it from the others.

randomizer↗
NASA NTRS2018

Randomizer for High Data Rates

NASA as well as a number of other space agencies now recognize that the current recommended CCSDS randomizer used for telemetry (TM) is too short. When multiple applications of the PN8 Maximal Length Sequence (MLS) are required in order to fully cover a channel access data unit (CADU), spectral problems in the form of elevated spurious discretes (spurs) appear. Originally the randomizer was called a bit transition generator (BTG) precisely because it was thought that its primary value was to insure sufficient bit transitions to allow the bit/symbol synchronizer to lock and remain locked. We, NASA, have shown that the old BTG concept is a limited view of the real value of the randomizer sequence and that the randomizer also aids in signal acquisition as well as minimizing the potential for false decoder lock. Under the guidelines we considered here there are multiple maximal length sequences under GF(2) which appear attractive in this application. Although there may be mitigating reasons why another MLS sequence could be selected, one sequence in particular possesses a combination of desired properties which offsets it from the others.

primitive polynomials↗
NASA NTRS1971

Reward and uncertainty in exploration programs

A set of variables which are crucial to the economic outcome of petroleum exploration are discussed. These are treated as random variables; the values they assume indicate the number of successes that occur in a drilling program and determine, for a particular discovery, the unit production cost and net economic return if that reservoir is developed. In specifying the joint probability law for those variables, extreme and probably unrealistic assumptions are made. In particular, the different random variables are assumed to be independently distributed. Using postulated probability functions and specified parameters, values are generated for selected random variables, such as reservoir size. From this set of values the economic magnitudes of interest, net return and unit production cost are computed. This constitutes a single trial, and the procedure is repeated many times. The resulting histograms approximate the probability density functions of the variables which describe the economic outcomes of an exploratory drilling program.

Kaufman, G. M.↗
NASA NTRS1994

The decay of axisymmetric homogeneous turbulence

The decay of a homogeneous turbulence generated by an axisymmetric distribution of random impulsive forces acting at the initial instant is considered. The impulsive forces may be either parallel or perpendicular to the symmetry axis. For impulsive forces which result in a kappa(exp 4) low wavenumber energy spectrum of the turbulence, it is determined that the flow approaches isotropy on all scales of motion at long-times provided the Reynolds number is large. However, for the type of impulsive forces originally proposed by Saffman in which a sq kappa low wavenumber energy spectrum is produced, the turbulence approaches isotropy only at the smallest scales and remains significantly anisotropic at the largest and energy-containing scales. Nevertheless, a similarity state of the flow field establishes itself asymptotically, in which the kinetic energy per unit mass of the turbulence decays as t(exp -6/5).

Chasnov, J. R.↗
NASA NTRS2011

Step-by-Step Simulation of Radiation Chemistry Using Green Functions for Diffusion-Influenced Reactions

Radiolytic species are formed approximately 1 ps after the passage of ionizing radiation through matter. After their formation, they diffuse and chemically react with other radiolytic species and neighboring biological molecules, leading to various oxidative damage. Therefore, the simulation of radiation chemistry is of considerable importance to understand how radiolytic species damage biological molecules [1]. The step-by-step simulation of chemical reactions is difficult, because the radiolytic species are distributed non-homogeneously in the medium. Consequently, computational approaches based on Green functions for diffusion-influenced reactions should be used [2]. Recently, Green functions for more complex type of reactions have been published [3-4]. We have developed exact random variate generators of these Green functions [5], which will allow us to use them in radiation chemistry codes. Moreover, simulating chemistry using the Green functions is which is computationally very demanding, because the probabilities of reactions between each pair of particles should be evaluated at each timestep [2]. This kind of problem is well adapted for General Purpose Graphic Processing Units (GPGPU), which can handle a large number of similar calculations simultaneously. These new developments will allow us to include more complex reactions in chemistry codes, and to improve the calculation time. This code should be of importance to link radiation track structure simulations and DNA damage models.

Plante, Ianik↗
NASA NTRS2003

Predicting protein functions from redundancies in large-scale protein interaction networks

Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (approximately 89%) of the original associations.

Proteins/chemistry/metabolism↗
NASA NTRS2021

A Ground-Delay-Based Approach to Reduce Impedance-Based Airspace Complexity

This paper introduces a ground-delay-based traffic management approach to reduce the impedance-based airspace complexity for a given scenario. This work extends our prior research on developing an impedance-based complexity metric for unmanned aircraft system traffic scenario classification. Impedance-based metric was evaluated for 1045 randomly generated scenarios. Scenarios with overall impedance above a certain threshold were declared as not feasible. A ground-delay-based approach was developed to be applied to the rest of the scenarios so as to remediate any scenarios with small areas of high impedance on their impedance maps. A sample application is shown for a scenario with sixty flights. The detailed trade-offs between overall accrued system delay, the number of delayed flights, the total number of conflicts and the highest impedance observed as a function of the delay tolerance for each aircraft are provided. Potential applications to Urban Air Mobility traffic scenarios are also discussed.

ground-delay based traffic management↗
NASA NTRS1972

Fault tolerant data management system

Described in detail are: (1) results obtained in modifying the onboard data management system software to a multiprocessor fault tolerant system; (2) a functional description of the prototype buffer I/O units; (3) description of modification to the ACADC and stimuli generating unit of the DTS; and (4) summaries and conclusions on techniques implemented in the rack and prototype buffers. Also documented is the work done in investigating techniques of high speed (5 Mbps) digital data transmission in the data bus environment. The application considered is a multiport data bus operating with the following constraints: no preferred stations; random bus access by all stations; all stations equally likely to source or sink data; no limit to the number of stations along the bus; no branching of the bus; and no restriction on station placement along the bus.

Gustin, W. M.↗
NASA NTRS1989

A connectionist model for diagnostic problem solving

A competition-based connectionist model for solving diagnostic problems is described. The problems considered are computationally difficult in that (1) multiple disorders may occur simultaneously and (2) a global optimum in the space exponential to the total number of possible disorders is sought as a solution. The diagnostic problem is treated as a nonlinear optimization problem, and global optimization criteria are decomposed into local criteria governing node activation updating in the connectionist model. Nodes representing disorders compete with each other to account for each individual manifestation, yet complement each other to account for all manifestations through parallel node interactions. When equilibrium is reached, the network settles into a locally optimal state. Three randomly generated examples of diagnostic problems, each of which has 1024 cases, were tested, and the decomposition plus competition plus resettling approach yielded very high accuracy.

Peng, Yun↗
NASA NTRS2010

High-Intensity Radiated Field Fault-Injection Experiment for a Fault-Tolerant Distributed Communication System

Safety-critical distributed flight control systems require robustness in the presence of faults. In general, these systems consist of a number of input/output (I/O) and computation nodes interacting through a fault-tolerant data communication system. The communication system transfers sensor data and control commands and can handle most faults under typical operating conditions. However, the performance of the closed-loop system can be adversely affected as a result of operating in harsh environments. In particular, High-Intensity Radiated Field (HIRF) environments have the potential to cause random fault manifestations in individual avionic components and to generate simultaneous system-wide communication faults that overwhelm existing fault management mechanisms. This paper presents the design of an experiment conducted at the NASA Langley Research Center's HIRF Laboratory to statistically characterize the faults that a HIRF environment can trigger on a single node of a distributed flight control system.

Yates, Amy M.↗
NASA NTRS1990

A fractal transition in the two dimensional shear layer

The dependence of product generation with the Peclet and Reynolds number in a numerically simulated, reacting, two dimensional, temporally growing mixing layer is used to compute the fractal dimension of passive scalar interfaces. A transition from a low dimension of 4/3 to a higher one of 5/3 is identified and shown to be associated to the kinematic distortion on the flow field during the first pairing interaction. It is suggested that the structures responsible for this transition are non-deterministic, non-random, inhomogeneous fractals. Only the large scales are involved. No further transition is found for Reynolds numbers up to 20,000.

Jimenez, Javier↗
NASA NTRS1992

Antipodal hotspot pairs on the earth

The results of statistical analyses performed on three published hotspot distributions suggest that significantly more hotspots occur as nearly antipodal pairs than is anticipated from a random distribution, or from their association with geoid highs and divergent plate margins. The observed number of antipodal hotspot pairs depends on the maximum allowable deviation from exact antipodality. At a maximum deviation of not greater than 700 km, 26 to 37 percent of hotspots form antipodal pairs in the published lists examined here, significantly more than would be expected from the general hotspot distribution. Two possible mechanisms that might create such a distribution include: (1) symmetry in the generation of mantle plumes, and (2) melting related to antipodal focusing of seismic energy from large-body impacts.

Rampino, Michael R.↗
NASA NTRS1996

Dynamics of vegetative cytoplasm during generative cell formation and pollen maturation in Arabidopsis thaliana

Ultrastructural changes of pollen cytoplasm during generative cell formation and pollen maturation in Arabidopsis thaliana were studied. The pollen cytoplasm develops a complicated ultrastructure and changes dramatically during these stages. Lipid droplets increase after generative cell formation and their organization and distribution change with the developmental stage. Starch grains in amyloplasts increase in number and size during generative and sperm cell formation and decrease at pollen maturity. The shape and membrane system of mitochondria change only slightly. Dictyosomes become very prominent, and numerous associated vesicles are observed during and after sperm cell formation. Endoplasmic reticulum appears extensively as stacks during sperm cell formation. Free and polyribosomes are abundant in the cytoplasm at all developmental stages although they appear denser at certain stages and in some areas. In mature pollen, all organelles are randomly distributed throughout the vegetative cytoplasm and numerous small particles appear. Organization and distribution of storage substances and appearance of these small particles during generative and sperm cell formation and pollen maturation are discussed.

Non-NASA Center↗
NASA NTRSDate not supplied

Uncovering Hazards Using a Multi-Objective Optimization to Explore the Faulty State-Space

Considering resilience when designing complex engineered systems is crucial to ensure the system is safe under unexpected hazardous scenarios. Traditional risk-based approaches, such as Failure Modes and Effects Analysis (FMEA) are useful for designing the system to mitigate hazardous scenarios that can be identified by the designer, but often require experience or prior knowledge of system failures to generate. More recently, researchers have developed simulation tools that enable the designer to model large sets of hazardous scenarios (driven by both internal faults and external factors) through simulation. While these tools enable a wider scope of fault modes to be evaluated (e.g., by injecting combined set of fault modes or injecting modes at different times), the resulting assessments (like FMEA) still require knowledge of the specific modes to be evaluated. However, failure to analyze a wide variety of fault scenarios can lead to an incomplete picture of the system resilience, especially to "surprise events'' which may be difficult for the designer to identify and predict beforehand. To overcome this challenge, previous work developed a fault sampling approach for resilience simulations which would procedurally-generate a wide variety of potential faults by systematically perturbing the health states of the system. While the resulting fault modes generated covered a much larger space hazards than would be otherwise considered (and identified many unique failure trajectories which would not have otherwise been identified), it also significantly increased the computational cost of the analysis and resulted in the simulation and analysis of a large set of essentially duplicate scenarios. Additionally, as the number of dimensions in the faulty state-space increases, the full elaboration of possible modes becomes computationally infeasible, justifying the use of a more targeted search. To resolve this limitation, this work proposes the use of a multiobjective optimization algorithm to search the health state space for potential fault modes that are both (1) hazardous and (2) unique. To solve this type of problem, this work proposes the use of a cooperative co-evolutionary algorithm. To demonstrate this approach, it will be applied to a model of an autonomous rover which uses line markings to navigate, focusing on potential hazards in the drive system which could cause the rover to crash. To determine the merit of the approach, it will further be compared with the previously-presented range elaboration approach and a random mode generation approach on the basis of computational efficiency and found modes.

Resilience↗