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Probabilistic approaches for geotech...

Cao, Zijun.

Probabilistic approaches for geotechnical site characterization and slope stability analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Probabilistic approaches for geotechnical site characterization and slope stability analysisby Zijun Cao, Yu Wang, Dianqing Li.
作者:	Cao, Zijun.
其他作者:	Wang, Yu.
出版者:	Berlin, Heidelberg :Springer Berlin Heidelberg :2017.
面頁冊數:	xvi, 190 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Slopes (Soil mechanics)Stability.
電子資源:	http://dx.doi.org/10.1007/978-3-662-52914-0
ISBN:	9783662529140$q(electronic bk.)

Probabilistic approaches for geotechnical site characterization and slope stability analysis
Cao, Zijun.

Probabilistic approaches for geotechnical site characterization and slope stability analysis[electronic resource] /by Zijun Cao, Yu Wang, Dianqing Li. - Berlin, Heidelberg :Springer Berlin Heidelberg :2017. - xvi, 190 p. :ill. (some col.), digital ;24 cm.

Introduction -- 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.

This 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.

ISBN: 9783662529140$q(electronic bk.)

Standard No.: 10.1007/978-3-662-52914-0doiSubjects--Topical Terms:

276439
Slopes (Soil mechanics)
--Stability.

LC Class. No.: TA749

Dewey Class. No.: 624.151363

Probabilistic approaches for geotechnical site characterization and slope stability analysis
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505 0 $a Introduction -- 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.
520 $a This 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.
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