Computational Analysis of Randomness in Structural Mechanics: Structures and I..

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Item specifics

Condition
Good
A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages. See all condition definitionsopens in a new window or tab
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“Good condition. Text looks free of highlighting and underlining. Wear to the exterior. Small bit of ...
ISBN
9780415403542
Category

About this product

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
0415403545
ISBN-13
9780415403542
eBay Product ID (ePID)
70944989

Product Key Features

Number of Pages
248 Pages
Language
English
Publication Name
Computational Analysis of Randomness in Structural Mechanics : Structures and Infrastructures Book Series, Vol. 3
Publication Year
2009
Subject
Probability & Statistics / Stochastic Processes, Structural, Mechanical, General, Civil / General
Type
Textbook
Author
Christian Bucher
Subject Area
Mathematics, Technology & Engineering
Series
Structures and Infrastructures Ser.
Format
Hardcover

Dimensions

Item Height
0.7 in
Item Weight
22.4 Oz
Item Length
10 in
Item Width
6.8 in

Additional Product Features

Intended Audience
College Audience
LCCN
2009-007681
Dewey Edition
22
Series Volume Number
3
Volume Number
Vol. 3
Illustrated
Yes
Dewey Decimal
624.1710285
Table Of Content
1 Introduction 1.1 Outline 1.2 Introductory examples 1.2.1 Outline of analysis 1.2.2 Static analysis 1.2.3 Buckling analysis 1.2.4 Dynamic analysis 2 Preliminaries in Probability Theory and Statistics 2.1 Definitions 2.2 Probabilistic models 2.2.1 Random variables 2.2.2 Some types of distributions 2.2.3 Conditional distribution 2.2.4 Functions of random variables 2.2.5 Random vectors 2.2.6 Joint probability density function models 2.2.7 Marginal and conditional distribution 2.3 Estimation 2.3.1 Basic properties 2.3.2 Confidence intervals 2.3.3 Chi-square test 2.3.4 Correlation statistics 2.3.5 Bayesian updating 2.3.6 Entropy concepts 2.4 Simulation techniques 2.4.1 General remarks 2.4.2 Crude Monte Carlo simulation 2.4.3 Latin Hypercube sampling 2.4.4 Quasirandom sequences 2.4.5 Transformation of random samples 2.4.6 Simulation of correlated variables 3 Regression and Response Surfaces 3.1 Regression 3.2 Ranking of variables 3.3 Response surface models 3.3.1 Basic formulation 3.3.2 Linear models and regression 3.3.3 First- and second-order polynomials 3.3.4 Weighted interpolation 3.3.5 Moving Least Squares Regression 3.3.6 Radial basis functions 3.4 Design of experiments 3.4.1 Transformations 3.4.2 Saturated designs 3.4.3 Redundant designs 4 Mechanical vibrations due to random excitations 4.1 Basic definitions 4.2 Markov processes 4.2.1 Upcrossing rates 4.3 Single-degree-of-freedom system response 4.3.1 Mean and variance of response 4.3.2 White noise approximation 4.4 Multi-degree-of-freedom response 4.4.1 Equations of motion 4.4.2 Covariance analysis 4.4.3 First passage probability 4.5 Monte-Carlo simulation 4.5.1 General remarks 4.5.2 Central difference method 4.5.3 Euler method 4.5.4 Newmark method 4.5.5 Digital simulation of white noise 4.6 Fokker-Planck equation 4.7 Statistical linearization 4.7.1 General concept 4.8 Dynamic stability analysis 4.8.1 Basics 4.8.2 Nonlinear stability analysis 4.8.3 Linear stability analysis 5 Response analysis of spatially random structures 5.1 Representation of Random Fields 5.1.1 Basic Definitions 5.1.2 Properties of the auto-covariance function 5.1.3 Spectral Decomposition 5.1.4 Conditional Random Fields 5.1.5 Local Averages of Random Fields 5.2 Geometrical Imperfections 5.3 Stochastic Finite Element Formulation 5.3.1 Elasticity (Plane Stress) 5.3.2 Principle of Virtual Work 5.4 Finite Element Method 5.4.1 Element Formulation 5.4.2 Structural response 5.4.3 Stochastic Stiffness Matrix 5.4.4 Integration Point Method 5.4.5 Static Response - Perturbation Method 5.4.6 Monte Carlo Simulation 5.4.7 Natural Frequencies of a Structure with Randomly Distributed Elastic Modulus 6 Computation of failure probabilities 6.1 Structural Reliability 6.1.1 Definitions 6.1.2 First Order - Second Moment Concept 6.1.3 FORM - First Order Reliability Method 6.2 Monte-Carlo-Simulation 6.2.1 Definitions and Basics 6.2.2 Importance Sampling (Weighted Simulation) 6.2.3 Directional Sampling 6.2.4 Asymptotic Sampling 6.3 Application of RSM 6.3.1 Basic concept 6.3.2 Structural examples 6.4 First Passage Failure 6.4.1 Problem formulation 6.4.2 Extension to Non-Linear Problems
Synopsis
Proper treatment of structural behavior under severe loading - such as the performance of a high-rise building during an earthquake - relies heavily on the use of probability-based analysis and decision-making tools. Proper application of these tools is significantly enhanced by a thorough understanding of the underlying theoretical and computational concepts as provided by this book. Detailing the computational aspects of stochastic analysis within the field of structural mechanics, this book first presents a few motivating examples that demonstrate the various random effects within the context of simple structural analysis models. It moreover briefly reviews the fundamental concepts from continuum mechanics and puts them in the perspective of modern numerical tools, such as the finite element method. More advanced topics are developed step by step while gradually increasing the complexity of the structural and probabilistic analyses. This volume is intended for structural analysts and advanced students who wish to explore the benefits of stochastic analysis. It will provide researchers and decision makers working on structural and infrastructural systems with the necessary probabilistic information needed for strategic developments in construction, inspection and maintenance., This volume details the computational aspects of stochastic analysis within the field of structural mechanics. The material is suitable for graduate students and for structural analysts wishing to explore the potential benefits of stochastic analysis.
LC Classification Number
TA647.B93 2009

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