Showing 3 results for Stochastic Model
A. Nicknam, S. Yaghmaei Sabegh, A. Yazdani,
Volume 19, Issue 3 (7-2008)
Abstract
Abstract : The main objective of this study is estimating the strong motion for the Bam region using the stochastically based seismological models. The two widely used synthetic techniques namely point-source and finite-fault were utilized incorporating the source-path and site parameters into simple function. The decay factor kappa was estimated based on the data obtained from recorded strong motions to be used as an appropriate factor for the region. The results were validated against those of the recorded data during the destructive 26 December 2003 Bam earthquake in south east of Iran. The efficiency of these methods and estimating the appropriate regional model parameters are the main objectives of this study. The results of the synthesized ground motion, such as acceleration time history, PGA and elastic response spectra were compared /assessed with those of observed data. The Bias model (MB) is used to assess the validation of the simulated earthquakes against recorded horizontal acceleration time histories. The %90 confidence interval of the means averaged over the whole stations using t-student distribution was evaluated and it was shown to be in an acceptable range. The elastic response spectra of the simulated strong motion are showed to be in a good agreement between the recorded waveforms confirming the acceptability of the selected/evaluated source-path-site model parameters. The sensitivity of the simulated PGA and response spectra against kappa factor as well as the path-averaged frequency-dependent quality factor Q, is studied and discussed.
S. G. Jalali Naini , M. B. Aryanezhad, A. Jabbarzadeh , H. Babaei ,
Volume 20, Issue 3 (9-2009)
Abstract
This paper studies a maintenance policy for a system composed of two components, which are subject to continuous deterioration and consequently stochastic failure. The failure of each component results in the failure of the system. The components are inspected periodically and their deterioration degrees are monitored. The components can be maintained using different maintenance actions (repair or replacement) with different costs. Using stochastic regenerative properties of the system, a stochastic model is developed in order to analyze the deterioration process and a novel approach is presented that simultaneously determines the time between two successive inspection periods and the appropriate maintenance action for each of the components based on the observed degrees of deterioration. This approach considers different criteria like reliability and long-run expected cost of the system. A numerical example is provided in order to illustrate the implementation of the proposed approach.
Kamyar Sabri Laghaie, Mohammad Saidi Mehrabad, Arash Motaghedi Larijani,
Volume 22, Issue 4 (12-2011)
Abstract
In this paper a single server queuing production system is considered which is subject to gradual deterioration. The system is discussed under two different deteriorating conditions. A planning horizon is considered and server which is a D/M/1 queuing system is gradually deteriorates through time periods. A maintenance policy is taken into account whereby the server is restored to its initial condition before some distinct periods. This system is modeled to obtain optimal values of arrival rates and also optimal maintenance policy which minimizes production, holding and maintenance costs and tries to satisfy demands through time periods. The model is also considered to control customers’ sojourn times. For each deteriorating condition a model is developed. Models are solved by GA based algorithms and results for a sample are represented .
