GeoEngineerings

Theodoros Triantafyllidis ... 420 pages - Publisher: Springer; (August, 2019) ... Language: English - AmazonSIN: B07WRWR23F.

This book provides essential insights into recent developments in fundamental geotechnical engineering research. Special emphasis is given to a new family of constitutive soil description methods, which take into account the recent loading history and the dilatancy effects. Particular attention is also paid to the numerical implementation of multi-phase material under dynamic loads, and to geotechnical installation processes. In turn, the book addresses implementation problems concerning large deformations in soils during piling operations or densification processes, and discusses the limitations of the respective methods. Numerical simulations of dynamic consolidation processes are presented in slope stability analysis under seismic excitation. Lastly, achieving the energy transition from conventional to renewable sources will call for geotechnical expertise. Consequently, the book explores and analyzes a selection of interesting problems involving the stability and serviceability of supporting structures, and provides new solutions approaches for practitioners and scientists in geotechnical engineering. The content reflects the outcomes of the Colloquium on Geotechnical Engineering 2019, held in Karlsruhe, Germany in September 2019.

Damian Beben ... 223 pages - Publisher: Springer (March, 2020) - Language: English - AmazonSIN: B085L6LNBQ.

The primary objective of this book is to provide designers with a set of analysis and design specifications for soil-steel bridges and culverts, also called flexible structures. Brief but informative, this guide is based on a quick look up approach to code applications, design and analysis methods/calculations as well as applications and solved examples. The book addresses the unique aspects of soil-steel bridges: design and analysis as well as examples of applications, numerical analysis and modeling techniques, corrosion and durability problems, service life and maintenance, and impact of moving loads.

Dirk P. Kroese; Zdravko I. Botev; Thomas Taimre; Radislav Vaisman .... 532 pages - Language: English - AmazonSIN: B081S6BQ2Y - Publisher: Chapman and Hall/CRC; (November, 2019).

The purpose of Data Science and Machine Learning: Mathematical and Statistical Methods is to provide an accessible, yet comprehensive textbook intended for students interested in gaining a better understanding of the mathematics and statistics that underpin the rich variety of ideas and machine learning algorithms in data science. Key Features: Focuses on mathematical understanding. + Presentation is self-contained, accessible, and comprehensive. + Extensive list of exercises and worked-out examples. + Many concrete algorithms with Python code. + Full color throughout.