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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Models and techniques for evaluating the effectiveness of aircraft computing systems

Models, measures and techniques were developed for evaluating the effectiveness of aircraft computing systems. The concept of effectiveness involves aspects of system performance, reliability and worth. Specifically done was a detailed development of model hierarchy at mission, functional task, and computational task levels. An appropriate class of stochastic models was investigated which served as bottom level models in the hierarchial scheme. A unified measure of effectiveness called 'performability' was defined and formulated.

Meyer, J. F.↗
NASA NTRS2004

Designing to Mitigate Food Growing Failures in Space

Future space life support systems may use crop plants to grow most of the crew s food. A harvest failure can reduce the food available for future consumption. If the previously stored food is insufficient to reach the next harvest, the crew may go hungry. This paper considers how the overall food supply system should be modified to cope with food production failures. The food supply concept for a mission will use grown food, or stored food, cIr both. The optimum food supply mix depends on the costs and failure probabilities of stored and grown food. A simple food system model assumes that either we obtain the nominal harvest or a failure occurs and no food is harvested. Given the probability that any particular harvest fails, it is easy to compute the expected number of failures and the total food shortfall over a mission. If some food is grown and the probability of harvest failure is high, a non-redundant system has an unacceptable likelihood that the crew will have no food for a full harvest period. Food supply reliability must be increased either by supplying more food initially or by increasing food production capacity. We can obtain a very reliable food supply even when the harvest failure rate is high. If the cost of growing food is much less than the cost of providing stored food, it is better to provide redundant food growing capacity than to increase initial storage. A more realistic biomass production failure model allows the harvest amount or time to vary around the nominal values, using stochastic modeling with repeated Monte Carlo simulation, but such failures have minor impact compared to a complete harvest failure.

Jones, Harry↗
NASA NTRS1993

Narrow band noise as a model of time-dependent accelerations - Study of the stability of a fluid surface in a microgravity environment

We introduce a stochastic model to analyze in quantitative detail the effect of the high frequency components of the residual accelerations onboard spacecraft (often called g-jitter) on fluid motion. The residual acceleration field is modeled as a narrow band noise characterized by three independent parameters: its intensity G squared, a dominant frequency Omega, and a characteristic spectral width tau exp -1. The white noise limit corresponds to Omega tau goes to O, with G squared tau finite, and the limit of a periodic g-jitter (or deterministic limit) can be recovered for Omega tau goes to infinity, G squared finite. The analysis of the response of a fluid surface subjected to a fluctuating gravitational field leads to the stochastic Mathieu equation driven by both additive and multiplicative noise. We discuss the stability of the solutions of this equation in the two limits of white noise and deterministic forcing, and in the general case of narrow band noise. The results are then applied to typical microgravity conditions.

Casademunt, Jaume↗
NASA NTRS1984

Empirical orthogonal functions and normal modes

An attempt to provide physical insight into the empirical orthogonal function (EOF) representation of data fields by the study of fields generated by linear stochastic models is presented in this paper. In a large class of these models, the EOFs at individual Fourier frequencies coincide with the orthogonal mechanical modes of the system - provided they exist. The precise mathematical criteria for this coincidence are derived and a physical interpretation is provided. A scheme possibly useful in forecasting is formally constructed for representing any stochastic field by a linear Hermitian model forced by noise.

North, G. R.↗
NASA NTRS1990

The cost of conservative synchronization in parallel discrete event simulations

The performance of a synchronous conservative parallel discrete-event simulation protocol is analyzed. The class of simulation models considered is oriented around a physical domain and possesses a limited ability to predict future behavior. A stochastic model is used to show that as the volume of simulation activity in the model increases relative to a fixed architecture, the complexity of the average per-event overhead due to synchronization, event list manipulation, lookahead calculations, and processor idle time approach the complexity of the average per-event overhead of a serial simulation. The method is therefore within a constant factor of optimal. The analysis demonstrates that on large problems--those for which parallel processing is ideally suited--there is often enough parallel workload so that processors are not usually idle. The viability of the method is also demonstrated empirically, showing how good performance is achieved on large problems using a thirty-two node Intel iPSC/2 distributed memory multiprocessor.

Nicol, David M.↗
NASA NTRS2011

Martian Atmospheric Modeling of Scale Factors for MarsGRAM 2005 and the MAVEN Project

For spacecraft missions to Mars, especially the navigation of Martian orbiters and landers, an extensive knowledge of the Martian atmosphere is extremely important. The generally-accepted NASA standard for modeling (MarsGRAM), which was developed at Marshall Space Flight Center. MarsGRAM is useful for task such as aerobraking, performance analysis and operations planning for aerobraking, entry descent and landing, and aerocapture. Unfortunately, the densities for the Martian atmosphere in MarsGRAM are based on table look-up and not on an analytical algorithm. Also, these values can vary drastically from the densities actually experienced by the spacecraft. This does not have much of an impact on simple integrations but drastically affects its usefulness in other applications, especially those in navigation. For example, the navigation team for the Mars Atmosphere Volatile Environment (MAVEN) Project uses MarsGRAM to target the desired atmospheric density for the orbiter's pariapse passage, its closet approach to the planet. After the satellite's passage through pariapsis the computed density is compared to the MarsGRAM model and a scale factor is assigned to the model to account for the difference. Therefore, large variations in the atmosphere from the model can cause unexpected deviations from the spacecraft's planned trajectory. In order to account for this, an analytic stochastic model of the scale factor's behavior is desired. The development of this model will allow for the MAVEN navigation team to determine the probability of various Martian atmospheric variations and their effects on the spacecraft.

Martian atmosphere↗
NASA NTRS1999

Physical Model of Immune Inspired Computing

Artificial Immune System is a rapidly growing field of information processing and computing based upon immune inspired paradigns of nonlinear dynamics. This paper introduces stochastic models which mimic the phenomenology of basic functions of immune systems such as self-nonself discrimination, self-repair, predator-prey pursuit, and reproduction.

Immune↗
NASA NTRS1993

Developing interpretable models with optimized set reduction for identifying high risk software components

Applying equal testing and verification effort to all parts of a software system is not very efficient, especially when resources are limited and scheduling is tight. Therefore, one needs to be able to differentiate low/high fault frequency components so that testing/verification effort can be concentrated where needed. Such a strategy is expected to detect more faults and thus improve the resulting reliability of the overall system. This paper presents the Optimized Set Reduction approach for constructing such models, intended to fulfill specific software engineering needs. Our approach to classification is to measure the software system and build multivariate stochastic models for predicting high risk system components. We present experimental results obtained by classifying Ada components into two classes: is or is not likely to generate faults during system and acceptance test. Also, we evaluate the accuracy of the model and the insights it provides into the error making process.

Briand, Lionel C.↗
NASA NTRS1994

Micromechanics of fatigue in woven and stitched composites

The goals of this research program were to: (1) determine how microstructural factors, especially the architecture of reinforcing fibers, control stiffness, strength, and fatigue life in 3D woven composites; (2) identify mechanisms of failure; (3) model composite stiffness; (4) model notched and unnotched strength; and (5) model fatigue life. We have examined a total of eleven different angle and orthogonal interlock woven composites. Extensive testing has revealed that these 3D woven composites possess an extraordinary combination of strength, damage tolerance, and notch insensitivity in compression and tension and in monotonic and cyclic loading. In many important regards, 3D woven composites far outstrip conventional 2D laminates or stitched laminates. Detailed microscopic analysis of damage has led to a comprehensive picture of the essential mechanisms of failure and how they are related to the reinforcement geometry. The critical characteristics of the weave architecture that promote favorable properties have been identified. Key parameters are tow size and the distributions in space and strength of geometrical flaws. The geometrical flaws should be regarded as controllable characteristics of the weave in design and manufacture. In addressing our goals, the simplest possible models of properties were always sought, in a blend of old and new modeling concepts. Nevertheless, certain properties, especially regarding damage tolerance, ultimate failure, and the detailed effects of weave architecture, require computationally intensive stochastic modeling. We have developed a new model, the 'binary model,' to carry out such tasks in the most efficient manner and with faithful representation of crucial mechanisms. This is the final report for contract NAS1-18840. It covers all work from April 1989 up to the conclusion of the program in January 1993.

Cox, B. N.↗
NASA NTRS1992

Computational technology for high-temperature aerospace structures

The status and some recent developments of computational technology for high-temperature aerospace structures are summarized. Discussion focuses on a number of aspects including: goals of computational technology for high-temperature structures; computational material modeling; life prediction methodology; computational modeling of high-temperature composites; error estimation and adaptive improvement strategies; strategies for solution of fluid flow/thermal/structural problems; and probabilistic methods and stochastic modeling approaches, integrated analysis and design. Recent trends in high-performance computing environment are described and the research areas which have high potential for meeting future technological needs are identified.

Noor, A. K.↗
NASA NTRS1999

External Sources of Water for Mercury's Putative Ice Deposits

Radar images have revealed the possible presence of ice deposits in Mercury's polar regions. Although thermal models indicate that water ice can be stable in permanently shaded regions near Mercury's poles, the ultimate source of the water remains unclear. We use stochastic models and other theoretical methods to investigate the role of external sources in supplying Mercury with the requisite amount of water. By extrapolating the current terrestrial influx of interplanetary dust particles to that at Mercury, we find that continual micrometeoritic bombardment of Mercury over the last 3.5 byr could have resulted in the delivery of (3-60) x 10(exp 16) grams of water ice to the permanently shaded regions at Mercury's poles (equivalent to an average ice thickness of 0.8-20 m). Erosion by micrometeoritic impact on exposed ice deposits could reduce the above value by about a half. For comparison, the current ice deposits on Mercury are believed to be somewhere between approx. 2 and 20 m thick. Using a Monte Carlo model to simulate the impact history of Mercury, we find that asteroids and comets can also deliver an amount of water consistent with the observations. Impacts from Jupiter-family comets over the last 3.5 billion years can supply (0.1-200) x 10(exp 16) grams of water to Mercury's polar regions (corresponding to ice deposits 0.05-60 m thick), Halley-type comets can supply (0.2-20) x 10(exp 16) grams of water to the poles (0.07-7 m of ice), and asteroids can provide (0.4-20) x 10(exp 16) grams of water to the poles (0.1-8 m of ice). Although all these external sources are nominally sufficient to explain the estimated amount of ice currently at Mercury's poles, impacts by a few large comets and/or asteroids seem to provide the best explanation for both the amount and cleanliness of the ice deposits on Mercury. Despite their low population estimates in the inner solar system, Jupiter-family comets are particularly promising candidates for delivering water to Mercury because they have a larger volatile content than asteroids and more favorable orbital and impact characteristics than Halley-type comets.

Moses, Julianne I.↗
NASA NTRS1992

Providing an empirical basis for optimizing the verification and testing phases of software development

Applying equal testing and verification effort to all parts of a software system is not very efficient, especially when resources are limited and scheduling is tight. Therefore, one needs to be able to differentiate low/high fault density components so that the testing/verification effort can be concentrated where needed. Such a strategy is expected to detect more faults and thus improve the resulting reliability of the overall system. This paper presents an alternative approach for constructing such models that is intended to fulfill specific software engineering needs (i.e. dealing with partial/incomplete information and creating models that are easy to interpret). Our approach to classification is as follows: (1) to measure the software system to be considered; and (2) to build multivariate stochastic models for prediction. We present experimental results obtained by classifying FORTRAN components developed at the NASA/GSFC into two fault density classes: low and high. Also we evaluate the accuracy of the model and the insights it provides into the software process.

Briand, Lionel C.↗
NASA NTRS2004

Direct Numerical Simulation of Turbulent Condensation in Clouds

In this brief, we investigate the turbulent condensation of a population of droplets by means of a direct numerical simulation. To that end, a coupled Navier-Stokes/Lagrangian solver is used where each particle is tracked and its growth by water vapor condensation is monitored exactly. The main goals of the study are to find out whether turbulence broadens the droplet size distribution, as observed in in situ measurements. The second issue is to understand if and for how long a correlation between the droplet radius and the local supersaturation exists for the purpose of modeling sub-grid scale microphysics in cloud-resolving codes. This brief is organized as follows. In Section 2 the governing equations are presented, including the droplet condensation model. The implementation of the forcing procedure is described in Section 3. The simulation results are presented in Section 4 together with a sketch of a simple stochastic model for turbulent condensation. Conclusions and the main outcomes of the study are given in Section 5.

Shariff, K.↗
NASA NTRS1994

Multivariate space - time analysis of PRE-STORM precipitation

This paper presents the methodologies and results of the multivariate modeling and two-dimensional spectral and correlation analysis of PRE-STORM rainfall gauge data. Estimated parameters of the models for the specific spatial averages clearly indicate the eastward and southeastward wave propagation of rainfall fluctuations. A relationship between the coefficients of the diffusion equation and the parameters of the stochastic model of rainfall fluctuations is derived that leads directly to the exclusive use of rainfall data to estimate advection speed (about 12 m/s) as well as other coefficients of the diffusion equation of the corresponding fields. The statistical methodology developed here can be used for confirmation of physical models by comparison of the corresponding second-moment statistics of the observed and simulated data, for generating multiple samples of any size, for solving the inverse problem of the hydrodynamic equations, and for application in some other areas of meteorological and climatological data analysis and modeling.

Polyak, Ilya↗
NASA NTRS2014

Improving FermiI Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecrafts ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45 improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

orbit prediction↗
NASA NTRS2014

Improving Fermi Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecraft's ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45% improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

orbit prediction↗
NASA NTRS2015

Orbit Determination for the Lunar Reconnaissance Orbiter Using an Extended Kalman Filter

Orbit determination (OD) analysis results are presented for the Lunar Reconnaissance Orbiter (LRO) using a commercially available Extended Kalman Filter, Analytical Graphics' Orbit Determination Tool Kit (ODTK). Process noise models for lunar gravity and solar radiation pressure (SRP) are described and OD results employing the models are presented. Definitive accuracy using ODTK meets mission requirements and is better than that achieved using the operational LRO OD tool, the Goddard Trajectory Determination System (GTDS). Results demonstrate that a Vasicek stochastic model produces better estimates of the coefficient of solar radiation pressure than a Gauss-Markov model, and prediction accuracy using a Vasicek model meets mission requirements over the analysis span. Modeling the effect of antenna motion on range-rate tracking considerably improves residuals and filter-smoother consistency. Inclusion of off-axis SRP process noise and generalized process noise improves filter performance for both definitive and predicted accuracy. Definitive accuracy from the smoother is better than achieved using GTDS and is close to that achieved by precision OD methods used to generate definitive science orbits. Use of a multi-plate dynamic spacecraft area model with ODTK's force model plugin capability provides additional improvements in predicted accuracy.

Orbit Determination↗
NASA NTRS2018

Structural Certification of Human-Rated Inflatable Space Structures

This paper details the results of an initial study to develop a certification plan for human-rated inflatable space structures, including guidelines for qualification testing. Habitable softgoods inflatables are multi-layered shell structures that use high-strength webbing, cordage and broadcloth fabric to carry the skin loads of a variety of volumetric shapes and structural architectures. The primary objectives of this study are to define the key parameters that affect these structures and propose a statistically robust approach to defining safety and knockdown factors based on test and analysis. Current NASA standards for habitable inflatable space structures use a factor of safety of 4, which was inherited from airship design criteria. An updated approach to defining a design factor, taking into account material strength variability, load variability in the article, number of test samples, and damage and degradation effects is specified. Accurate analytical modeling of these structures is hindered by the difficulty of obtaining accurate and consistent material data due to load-history- dependent, nonlinear load versus strain behavior. A building block approach to certification is detailed that uses stochastic modeling and statistical test design and analysis to address the unique challenges these high-strength softgoods structures present. Human-rated inflatable modules are a transformative capability for launching much larger habitable volumes into space than is possible with rigid shell structures. This research aims to provide the framework for certifying these structures for future human space exploration missions.

Jones, Thomas C.↗