LEADER 04224nam 22007095 450 001 9911001465403321 005 20251204110828.0 010 $a981-15-9105-9 024 7 $a10.1007/978-981-15-9105-1 035 $a(CKB)4100000011569143 035 $a(DE-He213)978-981-15-9105-1 035 $a(MiAaPQ)EBC6396080 035 $a(PPN)252505506 035 $a(EXLCZ)994100000011569143 100 $a20201113d2021 u| 0 101 0 $aeng 135 $aurcn#|||||||| 181 $ctxt$2rdacontent 181 $csti$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPractice of Bayesian Probability Theory in Geotechnical Engineering /$fby Wan-Huan Zhou, Zhen-Yu Yin, Ka-Veng Yuen 205 $a1st ed. 2021. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2021. 215 $a1 online resource (xxvii, 324 pages, 205 illustrations, 137 illustrations in colour) 300 $a"Jointly published with Tongji University Press." 311 08$aPrint version: 9789811591044 9811591040 311 08$a981-15-9104-0 320 $aIncludes bibliographical references. 327 $aProblem of Uncertainties in Geotechnical Engineering -- Estimation of SWCC and Permeability for Granular Soils -- Modeling SWCC for Coarse-Grained and Fine-Grained Soil -- Model Updating and Uncertainty Analysis for Creep of Clay -- Effect of Loading Duration on Uncertainty in Creep Analysis for Clay -- Model Class Selection for Sand with Generalization Ability Evaluation -- Parametric Identification of Advanced Soil Models for Sand -- Estimation of Pullout Shear Strength of Grouted Soil Nails -- Selection of Physical and Chemical Properties of Natural Fibers for Predicting Soil Reinforcement -- An Efficient Probabilistic Back-analysis Method for Braced Excavations. 330 $aThis book introduces systematically the application of Bayesian probabilistic approach in soil mechanics and geotechnical engineering. Four typical problems are analyzed by using Bayesian probabilistic approach, i.e., to model the effect of initial void ratio on the soil?water characteristic curve (SWCC) of unsaturated soil, to select the optimal model for the prediction of the creep behavior of soft soil under one-dimensional straining, to identify model parameters of soils and to select constitutive model of soils considering critical state concept. This book selects the simple and easy-to-understand Bayesian probabilistic algorithm, so that readers can master the Bayesian method to analyze and solve the problem in a short time. In addition, this book provides MATLAB codes for various algorithms and source codes for constitutive models so that readers can directly analyze and practice. This book is useful as a postgraduate textbook for civil engineering, hydraulic engineering, transportation, railway, engineering geology and other majors in colleges and universities, and as an elective course for senior undergraduates. It is also useful as a reference for relevant professional scientific researchers and engineers. 606 $aEngineering geology 606 $aGeotechnical engineering 606 $aArtificial intelligence 606 $aComputer simulation 606 $aProbabilities 606 $aGeoengineering 606 $aGeotechnical Engineering and Applied Earth Sciences 606 $aArtificial Intelligence 606 $aComputer Modelling 606 $aProbability Theory 615 0$aEngineering geology. 615 0$aGeotechnical engineering. 615 0$aArtificial intelligence. 615 0$aComputer simulation. 615 0$aProbabilities. 615 14$aGeoengineering. 615 24$aGeotechnical Engineering and Applied Earth Sciences. 615 24$aArtificial Intelligence. 615 24$aComputer Modelling. 615 24$aProbability Theory. 676 $a519.542 700 $aZhou$b Wan-Huan$01226316 702 $aYin$b Zhen-Yu 702 $aYuen$b Ka-Veng 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911001465403321 996 $aPractice of Bayesian probability theory in geotechnical engineering$92847404 997 $aUNINA