Structural Dynamics And Probabilistic Analysis For Engineers

Probabilistic structural dynamics offers unparalleled tools for analyzing uncertainties in structural design. Once avoided because it is mathematically rigorous, this technique has recently remerged with the aide of computer software. Written by an author/educator with 40 years of experience in structural design, this user friendly manual integrates theories, formulas and mathematical models to produce a guide that will allow professionals to quickly grasp concepts and start solving problems. In this book, the author uses simple examples that provide templates for creating of more robust case studies later in the book. *Problems are presented in an easy to understand form *Practical guide to software programs to solve design problems *Packed with examples and case studies of actual projects *Classical and the new stochastic factors of safety

Probabilistic structural dynamics is a new approach to building calculations that satisfy safety requirements while at the same time driving new efficiencies. This text provides a tutorial to these new methods.

Bayesian methods are a powerful tool in many areas of science and engineering, especially statistical physics, medical sciences, electrical engineering, and information sciences. They are also ideal for civil engineering applications, given the numerous types of modeling and parametric uncertainty in civil engineering problems. For example, earthquake ground motion cannot be predetermined at the structural design stage. Complete wind pressure profiles are difficult to measure under operating conditions. Material properties can be difficult to determine to a very precise level – especially concrete, rock, and soil. For air quality prediction, it is difficult to measure the hourly/daily pollutants generated by cars and factories within the area of concern. It is also difficult to obtain the updated air quality information of the surrounding cities. Furthermore, the meteorological conditions of the day for prediction are also uncertain. These are just some of the civil engineering examples to which Bayesian probabilistic methods are applicable. Familiarizes readers with the latest developments in the field Includes identification problems for both dynamic and static systems Addresses challenging civil engineering problems such as modal/model updating Presents methods applicable to mechanical and aerospace engineering Gives engineers and engineering students a concrete sense of implementation Covers real-world case studies in civil engineering and beyond, such as: structural health monitoring seismic attenuation finite-element model updating hydraulic jump artificial neural network for damage detection air quality prediction Includes other insightful daily-life examples Companion website with MATLAB code downloads for independent practice Written by a leading expert in the use of Bayesian methods for civil engineering problems This book is ideal for researchers and graduate students in civil and mechanical engineering or applied probability and statistics. Practicing engineers interested in the application of statistical methods to solve engineering problems will also find this to be a valuable text. MATLAB code and lecture materials for instructors available at http://www.wiley.com/go/yuen

The increasing necessity to solve complex problems in Structural Dynamics and Earthquake Engineering requires the development of new ideas, innovative methods and numerical tools for providing accurate numerical solutions in affordable computing times. This book presents the latest scientific developments in Computational Dynamics, Stochastic Dynam

This book has been written to provide practising engineers with an easily understandable introduction to the dynamics of civil engineering whilst ensuring that they acquire an understanding of the theories that form the basis of computer packages.

This book contains a series of original contributions in the area of Stochastic Dynamics, which demonstrates the impact of Mike Lin's research and teaching in the area of random vibration and structural dynamics.

Researchers in the engineering industry and academia are making important advances on reliability-based design and modeling of uncertainty when data is limited. Non deterministic approaches have enabled industries to save billions by reducing design and warranty costs and by improving quality. Considering the lack of comprehensive and defini