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Reliability Of Geotechnical Structures at Meripustak

Reliability Of Geotechnical Structures by Davin Tuft, Scitus Academics

Books from same Author: Davin Tuft

Books from same Publisher: Scitus Academics

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  • General Information  
    Author(s)Davin Tuft
    PublisherScitus Academics
    ISBN9781681176840
    Pages300
    BindingHardcover
    LanguageEnglish
    Publish YearJanuary 2018

    Description

    Scitus Academics Reliability Of Geotechnical Structures by Davin Tuft

    Reliability-based design is relatively well established in structural design. Reliability based design and assessment methods are used to make design and operational decisions that meet specified target reliability levels. As modern structures require more critical and complex designs, the need for accurate approaches to assess uncertainties in loads, geometry, material properties, manufacturing processes and operational environments has increased significantly. Reliability assessment techniques help to develop safe designs and identify where significant contributors of uncertainty occur in structural systems, or, where further research, testing and quality control could increase the safety and efficiency of the structure. The book presents an overview on how reliability can play a complementary role within prevailing norms in geotechnical practice to address situations where some measured data and past experience exist for limited sitespecific data to be supplemented by both objective regional data and subjective judgment derived from comparable sites elsewhere. Reliability of Geotechnical Structures presents all the essential information for a non-specialist to calculate and interpret the reliability index and risk of geotechnical structures in a realistic and robust way. It will be a valuable reference for graduate and post graduate students studying structural reliability, probabilistic analysis and optimization under uncertainty; as well as engineers, researchers, and technical managers who are concerned with theoretical fundamentals, computational implementations and applications for probabilistic analysis.



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