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Applied Civil Engineering Risk Analysis [electronic resource] / by Robb Eric S. Moss.

By: Moss, Robb Eric S [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: 2nd ed. 2020.Description: XI, 180 p. 110 illus., 56 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030226800.Subject(s): Security systems | Fire prevention | Buildings—Protection | Buildings—Design and construction | Engineering mathematics | Engineering—Data processing | Security Science and Technology | Fire Science, Hazard Control, Building Safety | Building Construction and Design | Mathematical and Computational Engineering ApplicationsAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621 Online resources: Click here to access online
Contents:
Introduction -- Data Analysis/Sample Statistics -- Elementary Probability and Set Theory -- Random Variables and Probability Distributions -- Functions of Random Variables: Error Propagation -- Component Reliability Analysis -- System Reliability Analysis -- Introduction to Decision Analysis -- Reliability-Based Codes (LRFD) -- Spatial Variability -- Bayesian Updating -- References -- Appendix A -- Appendix B -- Appendix C.
In: Springer Nature eBookSummary: This updated edition retains its introduction to applied fundamental statistics, probability, reliability, and decision theory as these pertain to problems in Civil Engineering. The new edition adds an expanded treatment of systems reliability, Bayesian methods, and spatial variabililty, along with additional example problems throughout. The book provides readers with the tools needed to determine the probability of failure, and when multiplied by the consequences of failure, illustrates how to assess the risk of civil engineering problems. Presenting methods for quantifying uncertainty that exists in engineering analysis and design, with an emphasis on fostering more accurate analysis and design, the text is ideal for students and practitioners of a range of civil engineering disciplines. Expands on the class-tested pedagogy from the first edition with more material and more examples; Broadens understanding with simulations coded both in Matlab and in R; Features new chapters on spatial variability and Bayesian methods; Emphasizes techniques for estimating the influence of uncertainty on the probability of failure.
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Introduction -- Data Analysis/Sample Statistics -- Elementary Probability and Set Theory -- Random Variables and Probability Distributions -- Functions of Random Variables: Error Propagation -- Component Reliability Analysis -- System Reliability Analysis -- Introduction to Decision Analysis -- Reliability-Based Codes (LRFD) -- Spatial Variability -- Bayesian Updating -- References -- Appendix A -- Appendix B -- Appendix C.

This updated edition retains its introduction to applied fundamental statistics, probability, reliability, and decision theory as these pertain to problems in Civil Engineering. The new edition adds an expanded treatment of systems reliability, Bayesian methods, and spatial variabililty, along with additional example problems throughout. The book provides readers with the tools needed to determine the probability of failure, and when multiplied by the consequences of failure, illustrates how to assess the risk of civil engineering problems. Presenting methods for quantifying uncertainty that exists in engineering analysis and design, with an emphasis on fostering more accurate analysis and design, the text is ideal for students and practitioners of a range of civil engineering disciplines. Expands on the class-tested pedagogy from the first edition with more material and more examples; Broadens understanding with simulations coded both in Matlab and in R; Features new chapters on spatial variability and Bayesian methods; Emphasizes techniques for estimating the influence of uncertainty on the probability of failure.

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