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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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NASA NTRS1975

Detection of digital FSK using a phase-locked loop

A theory is presented for the design of a digital FSK receiver which employs a phase-locked loop to set up the desired matched filter as the arriving signal frequency switches. The developed mathematical model makes it possible to establish the error probability performance of systems which employ a class of digital FM modulations. The noise mechanism which accounts for decision errors is modeled on the basis of the Meyr distribution and renewal Markov process theory.

Lindsey, W. C.↗

NASA NTRS1978

Perseveration effects in detection tasks with correlated decision intervals

An investigation of the behavior of the human decisionmaker is described for a task related to the problem of a pilot using a traffic situation display to avoid collisions. This sequential signal detection task is characterized by highly correlated signals with time varying strength. Experimental results are presented and the behavior of the observers is analyzed using the theory of Markov processes and classical signal detection theory. Mathematical models are developed which describe the main result of the experiment: that correlation in sequential signals induced perseveration in the observer response and a strong tendency to repeat their previous decision, even when they were wrong.

Gai, E. G.↗

NASA NTRS1978

FTMP - A highly reliable Fault-Tolerant Multiprocessor for aircraft

The FTMP (Fault-Tolerant Multiprocessor) is a complex multiprocessor computer that employs a form of redundancy related to systems considered by Mathur (1971), in which each major module can substitute for any other module of the same type. Despite the conceptual simplicity of the redundancy form, the implementation has many intricacies owing partly to the low target failure rate, and partly to the difficulty of eliminating single-fault vulnerability. An extensive analysis of the computer through the use of such modeling techniques as Markov processes and combinatorial mathematics shows that for random hard faults the computer can meet its requirements. It is also shown that the maintenance scheduled at intervals of 200 hr or more can be adequate most of the time.

Hopkins, A. L., Jr.↗

NASA NTRS1981

Practical gust load alleviation and flutter suppression control laws based on a LQG methodology

A modified linear quadratic Gaussian (LQG) synthesis procedure has been used to design low-order robust multiloop controllers for a flexible airplane. The introduction of properly constructed fictitious Gauss-Markov processes in the control loops allowed meeting classical frequency-domain stability criteria using the direct synthesis procedures of modern time-domain control theory. Model reduction was used to simplify the control laws to the point where they could be easily implemented on onboard flight computers. These control laws provided excellent gust load and flutter mode control with good stability margins and compared very favorably to other control laws synthesized by the classical root-locus technique.

Gangsaas, D.↗

NASA NTRS1981

Stochastic treatment of electron multiplication without scattering in dielectrics

By treating the emission of optical phonons as a Markov process, a simple analytic method is developed for calculating the electronic ionization rate per unit length for dielectrics. The effects of scattering from acoustic and optical phonons are neglected. The treatment obtains universal functions in recursive form, the theory depending on only two dimensionless energy ratios. A comparison of the present work with other numerical approaches indicates that the effect of scattering becomes important only when the electric potential energy drop in a mean free path for optical-phonon emission is less than about 25% of the ionization potential. A comparison with Monte Carlo results is also given for Teflon.

Lin, D. L.↗

NASA NTRS1984

Data flow modeling techniques

There have been a number of simulation packages developed for the purpose of designing, testing and validating computer systems, digital systems and software systems. Complex analytical tools based on Markov and semi-Markov processes have been designed to estimate the reliability and performance of simulated systems. Petri nets have received wide acceptance for modeling complex and highly parallel computers. In this research data flow models for computer systems are investigated. Data flow models can be used to simulate both software and hardware in a uniform manner. Data flow simulation techniques provide the computer systems designer with a CAD environment which enables highly parallel complex systems to be defined, evaluated at all levels and finally implemented in either hardware or software. Inherent in data flow concept is the hierarchical handling of complex systems. In this paper we will describe how data flow can be used to model computer system.

Kavi, K. M.↗

NASA NTRS1985

An error-dependent model of instrument-scanning behavior in commercial airline pilots

A new flexible model of pilot instrument scanning behavior is presented which assumes that the pilot uses a set of deterministic scanning patterns on the pilot's perception of error in the state of the aircraft, and the pilot's knowledge of the interactive nature of the aircraft's systems. Statistical analyses revealed that a three stage Markov process composed of the pilot's three predicted lookpoints (LP), occurring 1/30, 2/30, and 3/30 of a second prior to each LP, accurately modelled the scanning behavior of 14 commercial airline pilots while flying steep turn maneuvers in a Boeing 737 flight simulator. The modelled scanning data for each pilot were not statistically different from the observed scanning data in comparisons of mean dwell time, entropy, and entropy rate. These findings represent the first direct evidence that pilots are using deterministic scanning patterns during instrument flight. The results are interpreted as direct support for the error dependent model and suggestions are made for further research that could allow for identification of the specific scanning patterns suggested by the model.

Jones, D. H.↗

NASA NTRS1984

Optimal maintenance center inventories for fault-tolerant repairable systems

A probabilistic approach is taken to determine the optimal repairable parts inventory for a maintenance center, servicing machines which contain several m-out-of-n systems of different parts, with a constraint on the total inventory investment. A model, based on the discrete Markov process, accounts for a typical ultrareliable avionics system, such as one presently being developed by NASA. The dynamic programming algorithm for minimizing the stockout and holding costs is applied to an exemplary maintenance center, and solutions for single-item and multi-item cases are given. The computational burden is noted to be reasonable and a computer program is used to generate optimal solutions.

Lawrence, S. H.↗

NASA NTRS1986

Discrete-time Markovian-jump linear quadratic optimal control

This paper is concerned with the optimal control of discrete-time linear systems that possess randomly jumping parameters described by finite-state Markov processes. For problems having quadratic costs and perfect observations, the optimal control laws and expected costs-to-go can be precomputed from a set of coupled Riccati-like matrix difference equations. Necessary and sufficient conditions are derived for the existence of optimal constant control laws which stabilize the controlled system as the time horizon becomes infinite, with finite optimal expected cost.

Chizeck, H. J.↗

NASA NTRS1987

Performability modeling based on real data: A casestudy

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different types of errors.

Hsueh, M. C.↗

NASA NTRS1988

Performability modeling based on real data: A case study

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of apparent types of errors.

Hsueh, M. C.↗

NASA NTRS1988

Performance evaluation of fault-tolerant systems with application to the IUS

A new method for quantitatively evaluating the performance of fault-tolerant systems is developed and applied to an example. The method assumes that the random failure and diagnostic decision behavior of the system can be modeled by a finite state Markov process. A performance value must be assigned to each of the states of the model. The method then generates the moments of the probability mass function of the cumulative performance and uses these to generate a maximum entropy approximation to the performance PMF. Some computational considerations are discussed. The method is applied to a typical mission for the Inertial Upper Stage to examine the attitude accuracy performance of the inertial system.

Missana, J.-O.↗

NASA NTRS1988

Sampling error study for rainfall estimate by satellite using a stochastic model

In a parameter study of satellite orbits, sampling errors of area-time averaged rain rate due to temporal sampling by satellites were estimated. The sampling characteristics were studied by accounting for the varying visiting intervals and varying fractions of averaging area on each visit as a function of the latitude of the grid box for a range of satellite orbital parameters. The sampling errors were estimated by a simple model based on the first-order Markov process of the time series of area averaged rain rates. For a satellite of nominal Tropical Rainfall Measuring Mission (Thiele, 1987) carrying an ideal scanning microwave radiometer for precipitation measurements, it is found that sampling error would be about 8 to 12 pct of estimated monthly mean rates over a grid box of 5 X 5 degrees. It is suggested that an observation system based on a low inclination satellite combined with a sunsynchronous satellite simultaneously might be the best candidate for making precipitation measurements from space.

Shin, Kyung-Sup↗

NASA NTRS1990

Closed-form solution of decomposable stochastic models

Markov and semi-Markov processes are increasingly being used in the modeling of complex reconfigurable systems (fault tolerant computers). The estimation of the reliability (or some measure of performance) of the system reduces to solving the process for its state probabilities. Such a model may exhibit numerous states and complicated transition distributions, contributing to an expensive and numerically delicate solution procedure. Thus, when a system exhibits a decomposition property, either structurally (autonomous subsystems), or behaviorally (component failure versus reconfiguration), it is desirable to exploit this decomposition in the reliability calculation. In interesting cases there can be failure states which arise from non-failure states of the subsystems. Equations are presented which allow the computation of failure probabilities of the total (combined) model without requiring a complete solution of the combined model. This material is presented within the context of closed-form functional representation of probabilities as utilized in the Symbolic Hierarchical Automated Reliability and Performance Evaluator (SHARPE) tool. The techniques adopted enable one to compute such probability functions for a much wider class of systems at a reduced computational cost. Several examples show how the method is used, especially in enhancing the versatility of the SHARPE tool.

Sjogren, Jon A.↗

NASA NTRS1991

Model reduction by trimming for a class of semi-Markov reliability models and the corresponding error bound

Semi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. A model reduction technique called trimming is presented that can be applied to a popular class of systems. Automatic model generation programs were written to help the reliability analyst produce models of complex systems. This method, trimming, is easy to implement and the error bound easy to compute. Hence, the method lends itself to inclusion in an automatic model generator.

White, Allan L.↗

NASA NTRS1990

State reduction for semi-Markov reliability models

Semi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model construction and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. Automatic model generation programs have been written to help the reliability analyst produce models of complex systems. Because of the importance of these programs, the model reduction technique needs to be precise and easily implemented. This paper presents a model reduction technique called trimming that can be applied to a popular class of systems. An error bound for the trimming procedure is derived that uses readily available system parameters. The trimming procedure is precisely described and appears easy to implement in a model generation program.

Reduced order systems↗

NASA NTRS1992

Availability analysis of the traveling-wave maser amplifiers in the deep space network. Part 1: The 70-meter antennas

The results of the reliability and availability analyses of the individual S- and X-band traveling-wave maser (TWM) assemblies and their operational configurations in the 70-meter antennas of NASA's Deep Space Network (DSN) are described. For the period 1990 through 1991, the TWM availability parameters for the Telemetry Data System are: mean time between failures (MTBF), 930 hr; mean time to restore services (MTTRS), 1.4 hr; and the average availability, 99.85 percent. In previously published articles, the performance analysis of the TWM assemblies was confined to the determination of the parameters specified above. However, as the mean down time (MDT) for the repair of TWM's increases, the levels of the TWM operational availabilities and MTTRS are adversely affected. A more comprehensive TWM availability analysis is presented to permit evaluation of both MTBF and MDT effects. Performance analysis of the TWM assemblies, based on their station monthly failure reports, indicates that the TWM's required MTBF and MDT levels of 3000 hr and 36 to 48 hr, respectively, have been achieved by the TWM's only at the Canberra Deep Space Station (DSS 43). The Markov Process technique is employed to develop suitable availability measures for the S- and X-band TWM configurations when each is operated in a two-assembly standby mode. The derived stochastic expressions allow for the evaluation of those configurations' simultaneous availability for the Antenna Microwave Subsystem. The application of these expressions to demonstrate the impact of various levels of TWM maintainability (or MDT) on their configurations' operational availabilities is presented for each of the 70-m antenna stations.

Issa, T. N.↗

NASA NTRS1987

A measurement-based performability model for a multiprocessor system

A measurement-based performability model based on real error-data collected on a multiprocessor system is described. Model development from the raw errror-data to the estimation of cumulative reward is described. Both normal and failure behavior of the system are characterized. The measured data show that the holding times in key operational and failure states are not simple exponential and that semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different failure types and recovery procedures.

Ilsueh, M. C.↗