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Titlebook: Computational Stochastic Mechanics; P. D. Spanos,C. A. Brebbia Book 1991 Computational Mechanics Publications 1991 Finite-Elemente-Methode

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書目名稱Computational Stochastic Mechanics
編輯P. D. Spanos,C. A. Brebbia
視頻videohttp://file.papertrans.cn/234/233148/233148.mp4
圖書封面Titlebook: Computational Stochastic Mechanics;  P. D. Spanos,C. A. Brebbia Book 1991 Computational Mechanics Publications 1991 Finite-Elemente-Methode
描述Over a period of several years the field of probabilistic mechanics and com- putational mechanics have progressed vigorously, but independently. With the advent of powerful computational hardware and the development of novel mechanical techniques, the field of stochastic mechanics has progressed in such a manner that the inherent uncertainty of quite complicated systems can be addressed. The first International Conference on Computational Stochastic Mechanics was convened in Corfu in September 1991 in an ef- fort to provide a forum for the exchanging of ideas on the current status of computational methods as applied to stochastic mechanics and for identi- fying needs for further research. The Conference covered both theoretical techniques and practical applications. The Conference also celebrated the 60th anniversary of the birthday of Dr. Masanobu Shinozuka, the Sollenberger Professor of Civil Engineering at Princeton University, whose work has contributed in such a great measure to the development of Computational Stochastic Mechanics. A brief sum- mary of his career and achievements are given in the Dedication. This book comprises some of the papers presented at the meeting and
出版日期Book 1991
關(guān)鍵詞Finite-Elemente-Methode; development; mechanics; modeling; reliability; simulation; vibration
版次1
doihttps://doi.org/10.1007/978-94-011-3692-1
isbn_ebook978-94-011-3692-1
copyrightComputational Mechanics Publications 1991
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Skewness and Kurtosis of Safety Marginre probability for a specific mode is generally evaluated by the first two moments those are estimated by considering the distributions of constituent basic variables and correlation coefficients between them. They all are settled into a reliability index ..
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A Curve-Fitting Method of Combined Distribution in Probabilistic Modeling of Random Variablestechnique in probabilistic modeling of random variables, especially needed, for example, in the analysis of load combination for structural design. Combined distributions are classified and defined into two types; a jointed type and a mixed type. The basic idea of fitting proposed in this study is t
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The Sensitivity Analysis of Stochastic Hysteretic Dynamic Systems[1]. This approach is applied for a simple nonlinear hysteretic model of practical sliding isolation system discussed by Constantinou and Papageorgiou [2]. The derived analytical solutions are compared with results of Monte Carlo simulations and the degree of accuracy of each solution is established
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Solution of Random Eigenvalue Problem by Crossing Theory and Perturbationmean zero-crossings rate of the characteristic polynomial of this matrix and a perturbation approach. The methods are applied to characterize probabilistically the natural frequencies of an uncertain dynamic system and to find the first two moments of the displacement of a simple oscillator with ran
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SORM Analysis Using Quasi-Newton Optimizationction at the design point. Principal curvatures of the limit-state surface at the design point are required in order to use closed formulas for the probability content of the approximate failure set. After a brief review of current procedures for obtaining the principal curvatures, an alternative al
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