Bayesian Methods for Structura
PAYBACK Punkte
80 °P sammeln!
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 conc...
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
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
Andere Kunden interessierten sich für
