£109.51

Springer Structural Reliability: Statistical Learning Perspectives

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Description

Explore advanced methodologies in structural reliability with this academic volume from Springer. Part of the Lecture Notes in Applied and Computational Mechanics series, this book addresses the complex challenge of determining the probability of failure in structural systems. As structural reliability problems have evolved through global research efforts, new methods have emerged to handle systems where the limit state function is only implicitly known. This text focuses on the development of solutions for these specific engineering problems. It provides a detailed look at methods based on the Taylor expansion of the performance function g(x) around the most likely failure point, also known as the design point. This resource is designed for researchers and professionals working within the fields of computational mechanics and statistical learning. It offers a technical deep dive into the mathematical processes required to solve reliability problems in modern engineering contexts, making it a valuable addition to your technical library.

Key Features

Covers essential methods for solving structural reliability problems developed by global researchers.

Provides analysis of systems where the limit state function g(x) = 0 is only implicitly known.

Explains methods based on Taylor expansion of the performance function about the design point.

Part of the professional Lecture Notes in Applied and Computational Mechanics series.

Focuses on determining the probability of failure in complex structural systems.

Product Specifications

Format
paperback
Domain
Amazon UK
Publication Date
20 July 2012
Listed Since
17 July 2013

Barcode

No barcode data available

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