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Author: Yu-Kweng Lin
Publisher: McGraw Hill Professional
ISBN: 9780071438001
Category : Technology & Engineering
Languages : en
Pages : 564
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Book Description
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.
Author: Yu-Kweng Lin
Publisher: McGraw Hill Professional
ISBN: 9780071438001
Category : Technology & Engineering
Languages : en
Pages : 564
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Book Description
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.
Author: Yu-Kweng Lin
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 392
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Book Description
Author: Ka-Veng Yuen
Publisher: John Wiley & Sons
ISBN: 9780470824559
Category : Mathematics
Languages : en
Pages : 320
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Book Description
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
Author: C.R. Sundararajan
Publisher: Springer Science & Business Media
ISBN: 1461517710
Category : Technology & Engineering
Languages : en
Pages : 756
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Book Description
The need for a comprehensive book on probabilistic structural mechanics that brings together the many analytical and computational methods developed over the years and their applications in a wide spectrum of industries-from residential buildings to nuclear power plants, from bridges to pressure vessels, from steel structures to ceramic structures-became evident from the many discussions the editor had with practising engineers, researchers and professors. Because no single individual has the expertise to write a book with such a di.verse scope, a group of 39 authors from universities, research laboratories, and industries from six countries in three continents was invited to write 30 chapters covering the various aspects of probabilistic structural mechanics. The editor and the authors believe that this handbook will serve as a reference text to practicing engineers, teachers, students and researchers. It may also be used as a textbook for graduate-level courses in probabilistic structural mechanics. The editor wishes to thank the chapter authors for their contributions. This handbook would not have been a reality without their collaboration.
Author: Manolis Papadrakakis
Publisher: CRC Press
ISBN: 020388163X
Category : Technology & Engineering
Languages : en
Pages : 672
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Book Description
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
Author: Haym Benaroya
Publisher: CRC Press
ISBN: 9780824723156
Category : Science
Languages : en
Pages : 770
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Book Description
Certainty exists only in idealized models. Viewed as the quantification of uncertainties, probabilitry and random processes play a significant role in modern engineering, particularly in areas such as structural dynamics. Unlike this book, however, few texts develop applied probability in the practical manner appropriate for engineers. Probability Models in Engineering and Science provides a comprehensive, self-contained introduction to applied probabilistic modeling. The first four chapters present basic concepts in probability and random variables, and while doing so, develop methods for static problems. The remaining chapters address dynamic problems, where time is a critical parameter in the randomness. Highlights of the presentation include numerous examples and illustrations and an engaging, human connection to the subject, achieved through short biographies of some of the key people in the field. End-of-chapter problems help solidify understanding and footnotes to the literature expand the discussions and introduce relevant journals and texts. This book builds the background today's engineers need to deal explicitly with the scatter observed in experimental data and with intricate dynamic behavior. Designed for undergraduate and graduate coursework as well as self-study, the text's coverage of theory, approximation methods, and numerical methods make it equally valuable to practitioners.
Author: Y. K. Lin
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Guiliano Augusti
Publisher: CRC Press
ISBN: 9780412222306
Category : Architecture
Languages : en
Pages : 586
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Book Description
This book presents the most important applications of probablistic and statistical approaches and procedures to structural engineering.
Author: Tshilidzi Marwala
Publisher: John Wiley & Sons
ISBN: 111915300X
Category : Technology & Engineering
Languages : en
Pages : 248
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Book Description
Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering Tshilidzi Marwala and Ilyes Boulkaibet, University of Johannesburg, South Africa Sondipon Adhikari, Swansea University, UK Covers the probabilistic finite element model based on Bayesian statistics with applications to aeronautical and mechanical engineering Finite element models are used widely to model the dynamic behaviour of many systems including in electrical, aerospace and mechanical engineering. The book covers probabilistic finite element model updating, achieved using Bayesian statistics. The Bayesian framework is employed to estimate the probabilistic finite element models which take into account of the uncertainties in the measurements and the modelling procedure. The Bayesian formulation achieves this by formulating the finite element model as the posterior distribution of the model given the measured data within the context of computational statistics and applies these in aeronautical and mechanical engineering. Probabilistic Finite Element Model Updating Using Bayesian Statistics contains simple explanations of computational statistical techniques such as Metropolis-Hastings Algorithm, Slice sampling, Markov Chain Monte Carlo method, hybrid Monte Carlo as well as Shadow Hybrid Monte Carlo and their relevance in engineering. Key features: Contains several contributions in the area of model updating using Bayesian techniques which are useful for graduate students. Explains in detail the use of Bayesian techniques to quantify uncertainties in mechanical structures as well as the use of Markov Chain Monte Carlo techniques to evaluate the Bayesian formulations. The book is essential reading for researchers, practitioners and students in mechanical and aerospace engineering.
Author: Pijush Samui
Publisher: Butterworth-Heinemann
ISBN: 0128165464
Category : Computers
Languages : en
Pages : 592
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Book Description
Handbook of Probabilistic Models carefully examines the application of advanced probabilistic models in conventional engineering fields. In this comprehensive handbook, practitioners, researchers and scientists will find detailed explanations of technical concepts, applications of the proposed methods, and the respective scientific approaches needed to solve the problem. This book provides an interdisciplinary approach that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil engineering, to electronics, electrical, earth sciences, climate, agriculture, water resource, mathematical sciences and computer sciences. Specific topics covered include minimax probability machine regression, stochastic finite element method, relevance vector machine, logistic regression, Monte Carlo simulations, random matrix, Gaussian process regression, Kalman filter, stochastic optimization, maximum likelihood, Bayesian inference, Bayesian update, kriging, copula-statistical models, and more. - Explains the application of advanced probabilistic models encompassing multidisciplinary research - Applies probabilistic modeling to emerging areas in engineering - Provides an interdisciplinary approach to probabilistic models and their applications, thus solving a wide range of practical problems
