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Title:On-Line Monitoring, Control, and Reliability of Structural Dynamical Systems
Author(s):Johnson, Erik Arthur
Doctoral Committee Chair(s):Bergman, Lawrence A.; Voulgaris, Petros G.
Department / Program:Aerospace Engineering
Discipline:Aerospace Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Applied Mechanics
Abstract:Ideas for improving the efficiency of Monte Carlo simulation (MCS) is the subject of the final section. Determining the low failure probabilities of typical engineering systems is quite difficult without using millions of MCS realizations to characterize the probability distribution. Several links between some MCS variance reduction techniques and Genetic Algorithms are discussed. A simple example, incorporating Genetic Algorithm operators into MCS, is shown to estimate probabilities a couple orders of magnitude smaller than standard MCS. Several concepts for characterizing the sense of a realization's "importance", such as discrepancy sensitivity and phase space velocity, are examined and found to successfully quantify realization importance.
Issue Date:1997
Description:368 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.
Other Identifier(s):(MiAaPQ)AAI9812643
Date Available in IDEALS:2015-09-25
Date Deposited:1997

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