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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

An investigation of wing buffeting response at subsonic and transonic speeds. Phase 2: F-111A flight data analysis. Volume 1: Summary of technical approach, results and conclusions

A detailed investigation of the flight buffeting response of the F-111A was performed in two phases. In Phase 1 stochastic analysis techniques were applied to wing and fuselage responses for maneuvers flown at subsonic speeds and wing leading edge sweep of 26 degrees. Power spectra and rms values were obtained. This report gives results of Phase 2 where the analyses were extended to include maneuvers flown at wing leading edge sweep values of 50 and 75.5 degrees at subsonic and supersonic speeds and the responses examined were expanded to include vertical shear, bending moment, and hingeline torque of the left and right horizontal tails. Power spectra, response time histories, variations of rms response with angle of attack and effects of wing sweep and Mach number are presented and discussed. Some Phase 1 results are given for comparison purposes.

Benepe, D. B.↗
NASA NTRS1989

Stochastic Petri net analysis of a replicated file system

A stochastic Petri-net model of a replicated file system is presented for a distributed environment where replicated files reside on different hosts and a voting algorithm is used to maintain consistency. Witnesses, which simply record the status of the file but contain no data, can be used in addition to or in place of files to reduce overhead. A model sufficiently detailed to include file status (current or out-of-date), as well as failure and repair of hosts where copies or witnesses reside, is presented. The number of copies and witnesses is a parameter of the model. Two different majority protocols are examined, one where a majority of all copies and witnesses is necessary to form a quorum, and the other where only a majority of the copies and witnesses on operational hosts is needed. The latter, known as adaptive voting, is shown to increase file availability in most cases.

Bechta Dugan, Joanne↗
NASA NTRS1985

Drop-turbulence interactions in a diffusion flame

A monodisperse stream of methanol drops injected along the axis of a turbulent, methane-fueled diffusion flame burning in still air is studied experimentally and theoretically, in order to determine mean and fluctuating phase velocities, mean drop number flux, drop size distributions, and mean gas phase temperature. Measured values were compared with the predictions of two separated flow analyses, namely deterministic separated flow and stochastic separated flow. The stochastic analysis yielded the best agreement with measurements, due to its providing for the turbulent dispersion of drops.

Shuen, J.-S.↗
NASA NTRS1989

Turbulent multiphase flows

Measurements and predictions of the structure of several multiphase flows are considered. The properties of dense sprays near the exits of pressure-atomizing injectors and of noncombusting and combusting dilute dispersed flows in round-jet configurations are addressed. It is found that the properties of dense sprays exhibit structure and mixing properties similar to variable-density single-phase flows at high Reynolds numbers within the atomization regime. The degree of development and turbulence levels at the injector exit have a surprisingly large effect on the structure and mixing properties of pressure-atomized sprays, particularly when the phase densities are large. Contemporary stochastic analysis of dilute multiphase flows provides encouraging predictions of turbulent dispersion for a wide variety of jetlike flows, particle-laden jets in gases and liquids, noncondensing and condensing bubbly jets, and nonevaporating, evaporating, and combusting sprays.

Faeth, G. M.↗
NASA NTRS1991

Chaotic appearance of the AE index

Results are reported from a stochastic analysis of a 5-day time series of the geomagnetic AE index during an active period. The original data, the power spectrum, and the autocorrelation function are shown, and the steps in the analysis are described in detail. It is found that the autocorrelation time scale is about 50 min, giving a correlation dimension (for the construction of a time series of m-dimensional vectors) of 2.4. This result is consistent with either colored-noise or deterministic-chaos magnetosphere models, indicating the need for further investigation.

Shan, L.-H.↗
NASA NTRS1993

Turbulence modeling for non-equilibrium flows

Two projects are reported. The first is the development and testing of an eddy viscosity transport model. This project also is a starting point for our work on developing computational tools for solving turbulence models in complex geometries. The second project is a stochastic analysis of the realizability of Reynolds stress transport models.

Durbin, Paul A.↗
NASA NTRS1991

A Scheduling Algorithm for Replicated Real-Time Tasks

We present an algorithm for scheduling real-time periodic tasks on a multiprocessor system under fault-tolerant requirement. Our approach incorporates both the redundancy and masking technique and the imprecise computation model. Since the tasks in hard real-time systems have stringent timing constraints, the redundancy and masking technique are more appropriate than the rollback techniques which usually require extra time for error recovery. The imprecise computation model provides flexible functionality by trading off the quality of the result produced by a task with the amount of processing time required to produce it. It therefore permits the performance of a real-time system to degrade gracefully. We evaluate the algorithm by stochastic analysis and Monte Carlo simulations. The results show that the algorithm is resilient under hardware failures.

Yu, Albert C.↗
NASA NTRS2006

A Framework for Performing Multiscale Stochastic Progressive Failure Analysis of Composite Structures

A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis - Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.

Bednarcyk, Brett A.↗
NASA NTRS2007

A Framework for Performing Multiscale Stochastic Progressive Failure Analysis of Composite Structures

A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis-Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.

Bednarcyk, Brett A.↗
NASA NTRS1975

Estimation and Analysis of Nonlinear Stochastic Systems

The algebraic and geometric structures of certain classes of nonlinear stochastic systems were exploited in order to obtain useful stability and estimation results. The class of bilinear stochastic systems (or linear systems with multiplicative noise) was discussed. The stochastic stability of bilinear systems driven by colored noise was considered. Approximate methods for obtaining sufficient conditions for the stochastic stability of bilinear systems evolving on general Lie groups were discussed. Two classes of estimation problems involving bilinear systems were considered. It was proved that, for systems described by certain types of Volterra series expansions or by certain bilinear equations evolving on nilpotent or solvable Lie groups, the optimal conditional mean estimator consists of a finite dimensional nonlinear set of equations. The theory of harmonic analysis was used to derive suboptimal estimators for bilinear systems driven by white noise which evolve on compact Lie groups or homogeneous spaces.

Marcus, S. I.↗
NASA NTRS1974

Sequential decision analysis for nonstationary stochastic processes

A formulation of the problem of making decisions concerning the state of nonstationary stochastic processes is given. An optimal decision rule, for the case in which the stochastic process is independent of the decisions made, is derived. It is shown that this rule is a generalization of the Bayesian likelihood ratio test; and an analog to Wald's sequential likelihood ratio test is given, in which the optimal thresholds may vary with time.

Schaefer, B.↗
NASA NTRS1987

Stochastic and fractal analysis of fracture trajectories

Analyses of fracture trajectories are used to investigate structures that fall between 'micro' and 'macro' scales. It was shown that fracture trajectories belong to the class of nonstationary processes. It was also found that correlation distance, which may be related to a characteristic size of a fracture process, increases with crack length. An assemblage of crack trajectory processes may be considered as a diffusive process. Chudnovsky (1981-1985) introduced a 'crack diffusion coefficient' d which reflects the ability of the material to deviate the crack trajectory from the most energetically efficient path and thus links the material toughness to its structure. For the set of fracture trajectories in AISI 304 steel, d was found to be equal to 1.04 microns. The fractal dimension D for the same set of trajectories was found to be 1.133.

Bessendorf, Michael H.↗
NASA NTRSDate not supplied

Stochastic Verification by Analysis for Autonomous Systems Management Architecture (ASMA)

The Gateway Vehicle Systems Manager (VSM) is the top-level of a distributed, hierarchical software control system. VSM is data-driven and will make decisions related to mission, fault, resource management and vehicle control. These attributes combined with a high degree of autonomy make it susceptible to emergent behavior. In order to achieve the high level of confidence needed in this critical system, the VSM team has developed a multifaceted verification strategy employing traditional verification techniques, simulation, model checking, and runtime verification. Individual algorithms are verified using conventional testing and model checking using assume-guarantee contracts. A discrete event-based simulation approach is being developed to verify timelines. This presentation describes an enhancement to the verification approach using analysis to enhance system robustness by detecting and resolving the potential for emergent behavior. The verification by analysis employs a Software in the Loop (SITL) environment with real flight software executing on emulated processors, simulations of vehicle subsystems, flight dynamics, and human inputs. Since the possible input space and configuration data set are too large for exhaustive testing, a Monte Carlo approach is used to cover feasible scenarios, augmented with corner cases and known higher-risk scenarios. A key problem in using Monte Carlo-based system verification is evaluating test results to ensure that system behavior is correct. The presentation describes the approach the VSM team uses to monitor behavior for compliance with predetermined boundaries and to identify anomalous behavior for further analysis. This presentation describes the multi-level systems approach to verification, and the simulation-based layer that covers the feasible state space: 1. Overview of the Gateway VSM 2. Special challenges due to heterogeneous, hierarchical architecture 3. Modeling and simulation environment using flight software and system simulations 4. Developing input sets to ensure state-space coverage 5. Developing model and data configuration sets to ensure model coverage 6. Interpreting results without predetermined outcomes 7. Lessons learned and future work

Verification and Validation↗
NASA NTRS1986

A structural-stochastic model for the analysis and synthesis of cloud images

A structural-stochastic image model is developed for the analysis and synthesis of cloud images. The ability of the model to characterize the visual appearance of cloud fields observed by satellite with a limited number of parameters is demonstrated. The model merges structural and stochastic information, the stochastic model acting as a local statistical operator applied to the output of the structural model. The structural or large-scale organization of the scene is retrieved from the two-dimensional Fourier representation of the digital image. The pattern generated by the major Fourier components provides a first guess of the scene. The stochastic aspect is described by a Markov model of texture that assumes a binomial probability distribution for the local grey-level variability. This Markov model provides four parameters that represent the clustering strength in the horizontal, vertical and diagonal directions. These parameters are estimated by a standard maximum-likelihood technique. The image can be reproduced with a fair degree of verisimilitude from these parameters. The data compression factor is of the order of one hundred to several hundreds.

Garand, L.↗
NASA NTRS2003

A Stochastic Collocation Algorithm for Uncertainty Analysis

This report describes a stochastic collocation method to adequately handle a physically intrinsic uncertainty in the variables of a numerical simulation. For instance, while the standard Galerkin approach to Polynomial Chaos requires multi-dimensional summations over the stochastic basis functions, the stochastic collocation method enables to collapse those summations to a one-dimensional summation only. This report furnishes the essential algorithmic details of the new stochastic collocation method and provides as a numerical example the solution of the Riemann problem with the stochastic collocation method used for the discretization of the stochastic parameters.

Mathelin, Lionel↗
NASA NTRS1990

Computer-aided-analysis of linear control system robustness

Stochastic robustness is a simple technique used to estimate the stability and performance robustness of linear, time-invariant systems. The use of high-speed graphics workstations and control system design software in stochastic robustness analysis is discussed and demonstrated. It is shown that stochastic robustness makes good use of modern computational and graphic tools, and it is easily implemented using commercial control system design and analysis software.

Stengel, Robert F.↗