Asymptotic Expansions for Reliabilities and Moments of Uncertain Dynamic Systems PDF Download

Author: Christos H. Papadimitriou
Publisher:
ISBN:
Category : Asymptotic expansions
Languages : en
Pages : 54

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Author: Ehsan Noroozinejad Farsangi
Publisher: CRC Press
ISBN: 1000418065
Category : Technology & Engineering
Languages : en
Pages : 522

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Book Description
Increasing demand on improving the resiliency of modern structures and infrastructure requires ever more critical and complex designs. Therefore, the need for accurate and efficient approaches to assess uncertainties in loads, geometry, material properties, manufacturing processes, and operational environments has increased significantly. Reliability-based techniques help develop more accurate initial guidance for robust design and help to identify the sources of significant uncertainty in structural systems. Reliability-Based Analysis and Design of Structures and Infrastructure presents an overview of the methods of classical reliability analysis and design most associated with structural reliability. It also introduces more modern methods and advancements, and emphasizes the most useful methods and techniques used in reliability and risk studies, while elaborating their practical applications and limitations rather than detailed derivations. Features: Provides a practical and comprehensive overview of reliability and risk analysis and design techniques. Introduces resilient and smart structures/infrastructure that will lead to more reliable and sustainable societies. Considers loss elimination, risk management and life-cycle asset management as related to infrastructure projects. Introduces probability theory, statistical methods, and reliability analysis methods. Reliability-Based Analysis and Design of Structures and Infrastructure is suitable for researchers and practicing engineers, as well as upper-level students taking related courses in structural reliability analysis and design.

Author: Efstratios Nikolaidis
Publisher: CRC Press
ISBN: 0203483936
Category : Mathematics
Languages : en
Pages : 1216

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Book Description
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

Author: P.D. Spanos
Publisher: CRC Press
ISBN: 9789058090393
Category : Computers
Languages : en
Pages : 628

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Book Description
Proceedings of the June, 1998 conference. Seventy contributions discuss Monte Carlo and signal processing methods, random vibrations, safety and reliability, control/optimization and modeling of nonlinearity, earthquake engineering, random processes and fields, damage/fatigue materials, applied prob

Author: Isaac Elishakoff
Publisher: Oxford University Press, USA
ISBN: 9780198526315
Category : Language Arts & Disciplines
Languages : en
Pages : 282

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Book Description
The finite element method (FEM) can be successfully applied to various field problems in solid mechanics, fluid mechanics and electrical engineering. This text discusses finite element methods for structures with large stochastic variations.

Author: Hector Jensen
Publisher: Springer
ISBN: 3030128199
Category : Science
Languages : en
Pages : 231

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Book Description
This book combines a model reduction technique with an efficient parametrization scheme for the purpose of solving a class of complex and computationally expensive simulation-based problems involving finite element models. These problems, which have a wide range of important applications in several engineering fields, include reliability analysis, structural dynamic simulation, sensitivity analysis, reliability-based design optimization, Bayesian model validation, uncertainty quantification and propagation, etc. The solution of this type of problems requires a large number of dynamic re-analyses. To cope with this difficulty, a model reduction technique known as substructure coupling for dynamic analysis is considered. While the use of reduced order models alleviates part of the computational effort, their repetitive generation during the simulation processes can be computational expensive due to the substantial computational overhead that arises at the substructure level. In this regard, an efficient finite element model parametrization scheme is considered. When the division of the structural model is guided by such a parametrization scheme, the generation of a small number of reduced order models is sufficient to run the large number of dynamic re-analyses. Thus, a drastic reduction in computational effort is achieved without compromising the accuracy of the results. The capabilities of the developed procedures are demonstrated in a number of simulation-based problems involving uncertainty.

Author: W. Q. Zhu
Publisher: CRC Press
ISBN: 0203492951
Category : Technology & Engineering
Languages : en
Pages : 626

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Book Description
Collection of technical papers presented at the 5th International Conference on Stochastic Structural Dynamics (SSD03) in Hangzhou, China during May 26-28, 2003. Topics include direct transfer substructure method for random response analysis, generation of bounded stochastic processes, and sample path behavior of Gaussian processes.

Author: Fu-Kuo Chang
Publisher: CRC Press
ISBN: 9781566766050
Category : Technology & Engineering
Languages : en
Pages : 824

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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: American Society of Civil Engineers
Publisher:
ISBN:
Category : Civil engineering
Languages : en
Pages : 904

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Book Description
Vols. 29-30 include papers of the International Engineering Congress, Chicago, 1893; v. 54 includes papers of the International Engineering Congress, St. Louis, 1904.