System Survival Probability Research Articles

A new stress–strength model for systems subject to stochastic shocks

A new general approach for obtaining system survival probability under the Poisson shock process is suggested. It takes into account the explicitly defined distribution of shock magnitude (stress) and system strength deterioration caused by the previous shocks. The approach can be used for any form of stress distribution, strength deterioration function and stress–strength interplay model. Specifically, we use the contest success function to model the stress–strength interplay and a cumulative stress ratio form function to represent strength deterioration. Numerical examples illustrating the obtained results are presented.

Nonlinear MDOF system Survival Probability Determination Subject to Evolutionary Stochastic Excitation

An approximate technique for assessing the reliability of nonlinear multi-degree-of-freedom (MDOF) systems subject to a non-stationary stochastic excitation vector is developed. The proposed technique can be construed as a two-stage approach. First, relying on statistical linearization and utilizing a dimension reduction approach the nonlinear n-degree-of-freedom system is decoupled and cast into (n) effective single-degree-of-freedom (SDOF) linear time-variant (LTV) oscillators. Second, utilizing the effective SDOF LTV oscillator time-varying stiffness and damping elements in conjunction with a stochastic averaging treatment of the problem, the MDOF system survival probability and first-passage PDF are determined. Overall, the developed technique appears to be efficient and versatile since it can handle readily, at a low computational cost, a wide range of nonlinear/hysteretic behaviors as well as various stochastic excitation forms, even of the fully non-stationary in time and frequency kind. A 3-DOF system exhibiting hysteresis following the Bouc-Wen model is included in the numerical examples section. Comparisons with pertinent Monte Carlo simulations demonstrate the accuracy of the technique.

Performance deterioration modeling and optimal preventive maintenance strategy under scheduled servicing subject to mission time

Servicing is applied periodically in practice with the aim of restoring the system state and prolonging the lifetime. It is generally seen as an imperfect maintenance action which has a chief influence on the maintenance strategy. In order to model the maintenance effect of servicing, this study analyzes the deterioration characteristics of system under scheduled servicing. And then the deterioration model is established from the failure mechanism by compound Poisson process. On the basis of the system damage value and failure mechanism, the failure rate refresh factor is proposed to describe the maintenance effect of servicing. A maintenance strategy is developed which combines the benefits of scheduled servicing and preventive maintenance. Then the optimization model is given to determine the optimal servicing period and preventive maintenance time, with an objective to minimize the system expected life-cycle cost per unit time and a constraint on system survival probability for the duration of mission time. Subject to mission time, it can control the ability of accomplishing the mission at any time so as to ensure the high dependability. An example of water pump rotor relating to scheduled servicing is introduced to illustrate the failure rate refresh factor and the proposed maintenance strategy. Compared with traditional methods, the numerical results show that the failure rate refresh factor can describe the maintenance effect of servicing more intuitively and objectively. It also demonstrates that this maintenance strategy can prolong the lifetime, reduce the total lifetime maintenance cost and guarantee the dependability of system.

A defect- and fault-tolerant architecture for nanocomputers

Both von Neumann’s NAND multiplexing, based on a massive duplication ofimperfect devices and randomized imperfect interconnects, and reconfigurablearchitectures have been investigated to come up with solutions for integrations ofhighly unreliable nanometre-scale devices. In this paper, we review these twotechniques, and present a defect- and fault-tolerant architecture in which vonNeumann’s NAND multiplexing is combined with a massively reconfigurablearchitecture. The system performance of this architecture is evaluated by studyingits reliability, i.e. the probability of system survival. Our evaluation showsthat the suggested architecture can tolerate a device error rate of up to10−2,with multiple redundant components; the structure is efficiently robust againstboth permanent and transient faults for an ultra-large integration of highlyunreliable nanometre-scale devices.

Optimization Techniques for Parametric Synthesis of Stochastic Systems

The paper discusses the problem of choosing parameter ratings of engineering devices and systems for which the system survival probability or the performance assurance probability for the predetermined time period is maximized. Special attention is paid to algorithms that reduce the labour content of optimization problems. The fundamental concepts underlined consist in replacing the original stochastic criterion with a certain deterministic one, allowing to find a solution that is nearby an optimum. Several techniques to reduce labour requirements of Monte Carlo modeling are discussed. The main conception of them consist in splitting the region of admissible parameters variations into a set of subregions and creating a database for operating system state in each of them. It is assumed that the operating state is not affected by any system parameter variations in subregion. The optimal solution is sought using the idea of dependent trials and “correlated samples method”.

Satellite Survivability Estimates

In this paper we discuss how information on system safety margins, whether provided by a model or by test-to-failure data, can be combined into simple analytical survivability estimates expressed in terms of damage functions, i.e. probability of system survival as a function of the strength of the environment. The statistical procedures developed here are applicable to the situation where statements about survivability are based on safety margins. Examples of nuclear weapons effects where the concept of safety margins can be easily applied are: DEMP, SGEMP and TREE burnout, neutron and total dose degradation.

The effect of alpha-particle-induced soft errors on memory systems with error correction

Using Poisson statistics, a model for the survival probability of integrated memory circuits having both hard and soft error bit failure mechanisms is developed. Calculations are made over a range of soft error generation rates and erasure intervals for both single and double error correction. It is shown that even if the soft errors are erased effectively instantaneously, there is still an impact on the probability of system survival which is a function of soft error generation rate, and that in the case of instantaneous erasure of soft errors, a system with N bit error correction will have a probability of survival at least as good as the same system with N-1 bit error correction, no matter how high the soft error generation rate.

Approximately optimum confidence bounds on series system reliability for exponential time to failure data

SUMMARY For a series system with exponentially distributed survival times for independent subsystems, there exist optimum uniformly most accurate unbiased exact confidence bounds on the probability of system survival until a specified time; see Lentner & Buehler (1963) and the doctoral dissertation of A. H. El Mawaziny. Calculation of these optimum exact confidence bounds, however, must be performed iteratively by means of a high-speed computer. Moreover, their calculation can be extremely expensive in terms of computer time, and in certain cases there are serious problems of loss of precision as the number of subsystems increases. An approximation is derived which can, if necessary, be evaluated by hand and which agrees with the optimum lower confidence bound on the probability of system survival to within about a unit in the second decimal place in the many and varied cases examined. Numerical examples are given and comparisons made with other approximate confidence bounds.

Approximately Optimum Confidence Bounds on Series System Reliability for Exponential Time to Failure Data

For a series system with exponentially distributed survival times for independent subsystems, there exist optimum uniformly most accurate unbiased exact confidence bounds on the probability of system survival until a specified time; see Lentner & Buehler (1963) and the doctoral dissertation of A. H. El Mawaziny. Calculation of these optimum exact confidence bounds, however, must be performed iteratively by means of a high-speed computer. Moreover, their calculation can be extremely expensive in terms of computer time, and in certain cases there are serious problems of loss of precision as the number of subsystems increases. An approximation is derived which can, if necessary, be evaluated by hand and which agrees with the optimum lower confidence bound on the probability of system survival to within about a unit in the second decimal place in the many and varied cases examined. Numerical examples are given and comparisons made with other approximate confidence bounds.

Satellite system survival probability

Short expressions for the survival probability of a large fraction of a multiple satellite system are developed. This probability is expressed as a function of launch probability, time, and number of satellites available.

Some Weapon System Survival Probability Models—I. Fixed Time Between Firings

The various survival probability models considered in this series of two papers can be reduced to basically two types depending on whether the time between firings is fixed or random. In Part I several deterministic models for estimating weapon system survival probability are considered. These are introduced by way of problems of increasing complexity, the first being concerned with the simple problem of determining the probability that a weapon system engaged in a duel with another will survive a specified length of time. The time between firings is assumed to be the same for both sides and the friendly force is assumed to have fired first. In the second problem, the former assumption is removed. Problem 3 introduces the concept of evacuation and illustrates the effect evacuation capability has on probability of survival. Problem 4 is a natural extension of Problem 3 and uses results from the previously derived models. In the very last model the deterministric nature of which side fires first is removed. All told, the models serve to highlight the effects of kill probability, vulnerability, guidance errors, kill radius, mobility, and rate of fire on the probability of survival.