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010   $a3-662-52914-9
024 7 $a10.1007/978-3-662-52914-0
035   $a(CKB)3710000000778078
035   $a(DE-He213)978-3-662-52914-0
035   $a(MiAaPQ)EBC4627973
035   $a(PPN)194801764
035   $a(EXLCZ)993710000000778078
100   $a20160806d2017      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aProbabilistic Approaches for Geotechnical Site Characterization and Slope Stability Analysis /$fby Zijun Cao, Yu Wang, Dianqing Li
205   $a1st ed. 2017.
210  1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2017.
215   $a1 online resource (XVI, 190 p. 55 illus., 7 illus. in color.) 
311   $a3-662-52912-2 
320   $aIncludes bibliographical references at the end of each chapters.
327   $aIntroduction -- Literature Review -- Bayesian Framework for Geotechnical Site Characterization -- Quantification of Prior Knowledge through Subjective Probability Assessment -- Probabilistic Characterization of Young's Modulus of Soils Using Standard Penetration Tests -- Probabilistic Site Characterization Using Cone Penetration Tests -- Practical Reliability Analysis of Slope Stability by Advanced Monte Carlo Simulations in a Spreadsheet -- Efficient Monte Carlo Simulation of Parameter Sensitivity in Probabilistic Slope Stability Analysis -- Summary and Concluding Remarks.
330   $aThis is the first book to revisit geotechnical site characterization from a probabilistic point of view and provide rational tools to probabilistically characterize geotechnical properties and underground stratigraphy using limited information obtained from a specific site. This book not only provides new probabilistic approaches for geotechnical site characterization and slope stability analysis, but also tackles the difficulties in practical implementation of these approaches. In addition, this book also develops efficient Monte Carlo simulation approaches for slope stability analysis and implements these approaches in a commonly available spreadsheet environment. These approaches and the software package are readily available to geotechnical practitioners and alleviate them from reliability computational algorithms. The readers will find useful information for a non-specialist to determine project-specific statistics of geotechnical properties and to perform probabilistic analysis of slope stability.
606   $aEngineering geology
606   $aEngineering?Geology
606   $aFoundations
606   $aHydraulics
606   $aGeotechnical engineering
606   $aNumerical analysis
606   $aComputer simulation
606   $aGeoengineering, Foundations, Hydraulics$3https://scigraph.springernature.com/ontologies/product-market-codes/T23020
606   $aGeotechnical Engineering & Applied Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/G37010
606   $aNumerical Analysis$3https://scigraph.springernature.com/ontologies/product-market-codes/M14050
606   $aSimulation and Modeling$3https://scigraph.springernature.com/ontologies/product-market-codes/I19000
615  0$aEngineering geology.
615  0$aEngineering?Geology.
615  0$aFoundations.
615  0$aHydraulics.
615  0$aGeotechnical engineering.
615  0$aNumerical analysis.
615  0$aComputer simulation.
615 14$aGeoengineering, Foundations, Hydraulics.
615 24$aGeotechnical Engineering & Applied Earth Sciences.
615 24$aNumerical Analysis.
615 24$aSimulation and Modeling.
676   $a624.15
700   $aCao$b Zijun$4aut$4http://id.loc.gov/vocabulary/relators/aut$0970635
702   $aWang$b Yu$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aLi$b Dianqing$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910254353703321
996   $aProbabilistic Approaches for Geotechnical Site Characterization and Slope Stability Analysis$92206199
997   $aUNINA