SEARCH · Engineering Papers

Results for “stochastic models”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33

All sources NASA NTRS DOE OSTI

NASA NTRS1991

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components, part 2

The technical effort and computer code enhancements performed during the sixth year of the Probabilistic Structural Analysis Methods program are summarized. Various capabilities are described to probabilistically combine structural response and structural resistance to compute component reliability. A library of structural resistance models is implemented in the Numerical Evaluations of Stochastic Structures Under Stress (NESSUS) code that included fatigue, fracture, creep, multi-factor interaction, and other important effects. In addition, a user interface was developed for user-defined resistance models. An accurate and efficient reliability method was developed and was successfully implemented in the NESSUS code to compute component reliability based on user-selected response and resistance models. A risk module was developed to compute component risk with respect to cost, performance, or user-defined criteria. The new component risk assessment capabilities were validated and demonstrated using several examples. Various supporting methodologies were also developed in support of component risk assessment.

Source record↗

NASA NTRS2014

Optimizing Integrated Terminal Airspace Operations Under Uncertainty

In the terminal airspace, integrated departures and arrivals have the potential to increase operations efficiency. Recent research has developed geneticalgorithm- based schedulers for integrated arrival and departure operations under uncertainty. This paper presents an alternate method using a machine jobshop scheduling formulation to model the integrated airspace operations. A multistage stochastic programming approach is chosen to formulate the problem and candidate solutions are obtained by solving sample average approximation problems with finite sample size. Because approximate solutions are computed, the proposed algorithm incorporates the computation of statistical bounds to estimate the optimality of the candidate solutions. A proof-ofconcept study is conducted on a baseline implementation of a simple problem considering a fleet mix of 14 aircraft evolving in a model of the Los Angeles terminal airspace. A more thorough statistical analysis is also performed to evaluate the impact of the number of scenarios considered in the sampled problem. To handle extensive sampling computations, a multithreading technique is introduced.

air traffic optimization↗

NASA NTRS1983

Minimum information modelling of structural systems with uncertain parameters

Work is reviewed wherein the design of active structural control is formulated as the mean-square optimal control of a linear mechanical system with stochastic parameters. In practice, a complete probabilistic description of model parameters can never be provided by empirical determinations, and a suitable design approach must accept very limited a priori data on parameter statistics. In consequence, the mean-square optimization problem is formulated using a complete probability assignment which is made to be consistent with available data but maximally unconstrained otherwise through use of a maximum entropy principle. The ramifications of this approach for both robustness and large dimensionality are illustrated by consideration of the full-state feedback regulation problem.

Hyland, D. C.↗

NASA NTRS1995

A simulation to study the feasibility of improving the temporal resolution of LAGEOS geodynamic solutions by using a sequential process noise filter

A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal resolution of solutions obtained from standard sequential filtering methods and process noise sequential filtering methods shows that the accuracy is significantly improved using process noise. The results show that the positional accuracy of the orbit is improved as well. The temporal resolution of the resulting solutions are detailed, and conclusions drawn about the results. Benefits and drawbacks of using process noise filtering in this type of scenario are also identified.

Hartman, Brian Davis↗

NASA NTRS1991

Stochastic availability analysis of operational data systems in the Deep Space Network

Existing availability models of standby redundant systems consider only an operator's performance and its interaction with the hardware performance. In the case of operational data systems in the Deep Space Network (DSN), in addition to an operator system interface, a controller reconfigures the system and links a standby unit into the network data path upon failure of the operating unit. A stochastic (Markovian) process technique is used to model and analyze the availability performance and occurrence of degradation due to partial failures are quantitatively incorporated into the model. Exact expressions of the steady state availability and proportion degraded performance measures are derived for the systems under study. The interaction among the hardware, operator, and controller performance parameters and that interaction's effect on data availability are evaluated and illustrated for an operational data processing system.

Issa, T. N.↗

NASA NTRS2010

Analyzing Non Stationary Processes in Radiometers

The lack of well-developed techniques for modeling changing statistical moments in our observations has stymied the application of stochastic process theory for many scientific and engineering applications. Non linear effects of the observation methodology is one of the most perplexing aspects to modeling non stationary processes. This perplexing problem was encountered when modeling the effect of non stationary receiver fluctuations on the performance of radiometer calibration architectures. Existing modeling approaches were found not applicable; particularly problematic is modeling processes across scales over which they begin to exhibit non stationary behavior within the time interval of the calibration algorithm. Alternatively, the radiometer output is modeled as samples from a sequence random variables; the random variables are treated using a conditional probability distribution function conditioned on the use of the variable in the calibration algorithm. This approach of treating a process as a sequence of random variables with non stationary stochastic moments produce sensible predictions of temporal effects of calibration algorithms. To test these model predictions, an experiment using the Millimeter wave Imaging Radiometer (MIR) was conducted. The MIR with its two black body calibration references was configured in a laboratory setting to observe a third ultra-stable reference (CryoTarget). The MIR was programmed to sequentially sample each of the three references in approximately a 1 second cycle. Data were collected over a six-hour interval. The sequence of reference measurements form an ensemble sample set comprised of a series of three reference measurements. Two references are required to estimate the receiver response. A third reference is used to estimate the uncertainty in the estimate. Typically, calibration algorithms are designed to suppress the non stationary effects of receiver fluctuations. By treating the data sequence as an ensemble collection, it is possible to apply temporal algorithms which exacerbate the non stationary effects. By varying the algorithm, information about the properties of the non stationary receiver fluctuations is obtained. Comparisons of analytical calculations and statistical analysis of data demonstrate impressive agreement.

Racette, Paul↗

NASA NTRS1997

Spectral and Temporal Properties of Galactic Black Hole Systems

Kusunose, Mineshige & Yamada (1996; hereafter KMY) extended the model of Kusunose & Mineshige (1995) to the Galactic black hole candidates by considering nonthermal electron injection with gamma(EQ\0(,\s\up2(less than),\s\do-l(_))) 10. The effects of pair escape and advection on the disk structure and general relativistic effects on the emission spectrum were also examined. They found that the energy spectral index (alpha)(sub x) of the power law X-rays is about-0.8 and-2.0 when 1(sub soft)/1 = 0.2 and 2, respectively, where 1(sub soft)/1 is the ratio of the compactness of the injected soft photons to that of the gravitational energy. The power law index was found to be nearly independent of the mass accretion which is consistent with the observed luminosity independence. The model with small 1(sub soft)/1 (less than 1) shows promise for explaining the low state observed in Galactic black hole candidates. Model fits were provided for GX339-4 and Cyg X- 1 data from COMPTEL and OSSE on the Compton Gamma Ray Observatory. The difference in emission spectra between thermal disks and the model of KMY appears only in the energy range greater than 100 keV. Li, Kusunose and Liang (1996) studied stochastic particle acceleration to produce nonthermal particle distributions which then were used in the model of Kusunose & Mineshige (1995) to model the spectrum above 1 Mev from GBHC's. Under certain conditions, stochastic electron acceleration overcame Coulomb and Compton losses resulting in a suprathermal electron population. Good fits were obtained by COMPTEL and OSSE observations of Cyg X-1 and GRO J0422+23. Kusunose & Mineshige (1996a) examined the role of electron-positron pairs in advection-dominated disks. They found that the results for advection-dominated disks without pairs are not qualitatively changed by including pairs. Summaries of work sponsored by this grant are given in Wheeler, Kim, Moscoso, Kusunose & Mineshige (1996) and Kusunose (1996) Work was also done on developing a model for an e(+-) pair wind from the inner disk region of a black hole. The model consists of three zones: a pair production/annihilation zone at the base of the wind, a pair annihilation zone slightly further out from the disk and a wind zone extending to infinity where no annihilation occurs. The model assumes an input X-ray / gamma-ray power-law spectrum as a function of photon energy and angular distribution. Pairs are created in the pair production/annihilation zone via photon-photon, photonparticle and particle-particle collisions. The bulk velocity of the pairs is obtained from the momentum component perpendicular to the disk taking into account the radiation pressure acceleration of the pairs. Energy balance in the pair production/annihilation zone is calculated by assuming that the momentum component parallel to the disk is thermalized and by taking into account heating/cooling via anisotropic thermal Compton scattering along with the cooling processes of bremsstrahlung and synchrotron radiation. The pair density is also calculated. The outer boundary of the pair production/annihilation zone is where the optical depth for photon-photon pair produciton is unity. Beyond this point only pair annihilation will occur in the pair annihilation zone. When the pair density becomes small, pair annihilation will be negligible and the pairs will flow freely to infinity. In this model we have found that the X-ray power-law spectral index, alpha(sub x) is the primary parameter which determines the density, temperature and velocity of the pair production/annihilation zone (Moscoso, Kusunose & Wheeler 1996).

Wheeler, J. Craig↗

NASA NTRS1981

Model degradation effects on sensor failure detection

This paper discusses the effects of imperfect modeling on the detection and isolation of sensor failures. For systems with non-zero set points, deterministic inputs or non-zero noise biases, the model mismatch appears as a bias on the stochastic innovation process. This bias, if left unaccounted for, would be sufficient to declare a false alarm failure in one or more sensors. A practical design procedure based upon the Generalized Likelihood Ratio (GLR) form uses a finite data window sequential t-test to detect and isolate model mismatch effects and soft sensor failures. Application to an eighth order model of the QCSEE turbofan engine is discussed.

Leininger, G. G.↗

NASA NTRS1991

Measuring earth orientation with the Global Positioning System

A globally distributed network of high-precision receivers which obtain data from the full Global Positioning System (GPS) configuration of 18 or more satellites may soon become an efficient and economical method for the rapid determination of short-term variations in earth orientation. A covariance analysis has been performed to evaluate the errors associated with GPS monitoring of earth orientation. Earth orientation parameters were modeled either as constants over observing windows of various lengths, or as stochastic process-noise variables. The sensitivity of earth orientation estimates to systematic errors in selected model parameters was also examined. GPS measurements appear to be highly competitive with those from other techniques, and have the potential to generate nearly continuous centimeter-level earth orientation information to aid both spacecraft navigation and the study of high-frequency earth orientation-related processes.

Freedman, Adam P.↗

NASA NTRS1999

The NASA/MSFC Global Reference Atmospheric Model: 1999 Version (GRAM-99)

The latest version of Global Reference Atmospheric Model (GRAM-99) is presented and discussed. GRAM-99 uses either (binary) Global Upper Air Climatic Atlas (GUACA) or (ASCII) Global Gridded Upper Air Statistics (GGUAS) CD-ROM data sets, for 0-27 km altitudes. As with earlier versions, GRAM-99 provides complete geographical and altitude coverage for each month of the year. GRAM-99 uses a specially-developed data set, based on Middle Atmosphere Program (MAP) data, for 20-120 km altitudes, and NASA's 1999 version Marshall Engineering Thermosphere (MET-99) model for heights above 90 km. Fairing techniques assure smooth transition in overlap height ranges (20-27 km and 90-120 km). GRAM-99 includes water vapor and 11 other atmospheric constituents (O3, N2O, CO, CH4, CO2, N2, O2, O, A, He and H). A variable-scale perturbation model provides both large-scale (wave) and small-scale (stochastic) deviations from mean values for thermodynamic variables and horizontal and vertical wind components. The small-scale perturbation model includes improvements in representing intermittency ("patchiness"). A major new feature is an option to substitute Range Reference Atmosphere (RRA) data for conventional GRAM climatology when a trajectory passes sufficiently near any RRA site. A complete user's guide for running the program, plus sample input and output, is provided. An example is provided for how to incorporate GRAM-99 as subroutines in other programs (e.g., trajectory codes).

Justus, C. G.↗

NASA NTRS1973

A suboptimal stochastic controller for an N-body spacecraft

Considerable attention, in the open literature, is being focused on the problem of developing a suitable set of deterministic dynamical equations for a complex spacecraft. This paper considers the problem of determining a stochastic optimal controller for an n-body spacecraft. The approach used in obtaining the stochastic controller involves the application, interpretation, and combination of advanced dynamical principles and the theoretical aspects of modern control theory. The stochastic controller obtained herein for a complicated model of a spacecraft uses sensor angular measurements associated with the base body to obtain smoothed estimates of the entire state vector. It can be easily implemented, and it enables system performance to be significantly improved.

Larson, V.↗

NASA NTRS1974

On the robustness of a Bayes estimate

This paper examines the robustness of a Bayes estimator with respect to the assigned prior distribution. A Bayesian analysis for a stochastic scale parameter of a Weibull failure model is summarized in which the natural conjugate is assigned as the prior distribution of the random parameter. The sensitivity analysis is carried out by the Monte Carlo method in which, although an inverted gamma is the assigned prior, realizations are generated using distribution functions of varying shape. For several distributional forms and even for some fixed values of the parameter, simulated mean squared errors of Bayes and minimum variance unbiased estimators are determined and compared. Results indicate that the Bayes estimator remains squared-error superior and appears to be largely robust to the form of the assigned prior distribution.

Canavos, G. C.↗

NASA NTRS1986

Temperature fluctuations and infrared emission from dust particles in a hot gas

In this paper, the effect of temperature fluctuations in very small dust particles caused by electronic collisions with an ambient hot gas, is calculated. The dust-temperature distribution differs strongly from that derived on the basis of equilibrium heating models, peaking at lower temperatures in the stochastically heated case. The resulting infrared spectrum is broadened at short wavelengths, giving much more emission than expected from equilibrium calculations, and at long wavelengths exhibits a lower color temperature. Dust-temperature fluctuations are thus expected to play an important role in determining the infrared spectrum of dusty, X-ray-emitting plasmas. A power-law distribution of grain radii extended to very small grain sizes will have a distinct infrared spectrum characterized by an infrared excess at the Wien side of the spectrum. This excess emission represents a high-temperature component in the spectrum, resulting from the stochastic heating of very small dust particles. Its magnitude depends on the grain-size distribution and the temperature and density of the ambient hot gas. This excess emission may be observed by IRAS in supernova remnants and rich clusters of galaxies.

Dwek, E.↗

NASA NTRS1986

On magnetic field stochasticity and nonthermal line broadening in solar flares

Observations of nonthermal line broadening seen in solar flares by the Solar Maximum Mission satellite are discussed in light of recent results on the generation of magnetic field stochasticity. It is shown that a consistent model for the data can be constructed by assuming that the observations signal the destruction of an ambient magnetohydrodynamic equilibrium.

Antonucci, E.↗

NASA NTRS1988

A few parts in 10 to the 8th geodetic baseline repeatablity in the Gulf of California using the Global Positioning System

GPS geodetic measurements of 350-650 km baselines across the Pacific-North America plate boundary in the Gulf of California are presented. The analysis employs a four-station U.S. fiducial network and combined carrier phase and pseudorange data. Water vapor radiometer data at the Gulf sites are used to calibrate the GPS signal for wet tropospheric path delays. Residual tropospheric delays are modeled as first-order exponentially correlated stochastic processes. The measurement precision for horizontal components is a few parts in 10 to the 8th or better.

Tralli, David M.↗

NASA NTRS1997

Spectral Density of Laser Beam Scintillation in Wind Turbulence: Theory - Part 1

The temporal spectral density of the log-amplitude scintillation of a laser beam wave due to a spatially dependent vector-valued crosswind (deterministic as well as random) is evaluated. The path weighting functions for normalized spectral moments are derived, and offer a potential new technique for estimating the wind velocity profile. The Tatarskii-Klyatskin stochastic propagation equation for the Markov turbulence model is used with the solution approximated by the Rytov method. The Taylor 'frozen-in' hypothesis is assumed for the dependence of the refractive index on the wind velocity, and the Kolmogorov spectral density is used for the refractive index field.

Balakrishnan, A. V.↗

NASA NTRS2010

Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks

For hard computational problems, stochastic local search has proven to be a competitive approach to finding optimal or approximately optimal problem solutions. Two key research questions for stochastic local search algorithms are: Which algorithms are effective for initialization? When should the search process be restarted? In the present work we investigate these research questions in the context of approximate computation of most probable explanations (MPEs) in Bayesian networks (BNs). We introduce a novel approach, based on the Viterbi algorithm, to explanation initialization in BNs. While the Viterbi algorithm works on sequences and trees, our approach works on BNs with arbitrary topologies. We also give a novel formalization of stochastic local search, with focus on initialization and restart, using probability theory and mixture models. Experimentally, we apply our methods to the problem of MPE computation, using a stochastic local search algorithm known as Stochastic Greedy Search. By carefully optimizing both initialization and restart, we reduce the MPE search time for application BNs by several orders of magnitude compared to using uniform at random initialization without restart. On several BNs from applications, the performance of Stochastic Greedy Search is competitive with clique tree clustering, a state-of-the-art exact algorithm used for MPE computation in BNs.

Mengshoel, Ole J.↗

NASA NTRS2012

A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

Celaya, Jose R.↗