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Practice of Optimisation Theory in Geotechnical Engineering
Buch von Yin-Fu Jin (u. a.)
Sprache: Englisch

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Beschreibung
This book presents the development of an optimization platform for geotechnical engineering, which is one of the key components in smart geotechnics. The book discusses the fundamentals of the optimization algorithm with constitutive models of soils. Helping readers easily understand the optimization algorithm applied in geotechnical engineering, this book first introduces the methodology of the optimization-based parameter identification, and then elaborates the principle of three newly developed efficient optimization algorithms, followed by the ideas of a variety of laboratory tests and formulations of constitutive models. Moving on to the application of optimization methods in geotechnical engineering, this book presents an optimization-based parameter identification platform with a practical and concise interface based on the above theories. The book is intended for undergraduate and graduate-level teaching in soil mechanics and geotechnical engineering and other related engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering and operations research fields.
This book presents the development of an optimization platform for geotechnical engineering, which is one of the key components in smart geotechnics. The book discusses the fundamentals of the optimization algorithm with constitutive models of soils. Helping readers easily understand the optimization algorithm applied in geotechnical engineering, this book first introduces the methodology of the optimization-based parameter identification, and then elaborates the principle of three newly developed efficient optimization algorithms, followed by the ideas of a variety of laboratory tests and formulations of constitutive models. Moving on to the application of optimization methods in geotechnical engineering, this book presents an optimization-based parameter identification platform with a practical and concise interface based on the above theories. The book is intended for undergraduate and graduate-level teaching in soil mechanics and geotechnical engineering and other related engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering and operations research fields.
Über den Autor

Zhen-Yu Yin is an Associate Professor of Geotechnical Engineering at The Hong Kong Polytechnic University since 2018. Dr. Yin received his BSc in Civil Engineering from Zhejiang University in 1997, followed by a 5 years engineering consultancy at the Zhejiang Jiahua Architecture Design Institute. Then, he obtained his MSc and Ph.D. in Geotechnical Engineering at Ecole Centrale de Nantes (France) in 2003 and 2006 respectively. Then he has been working as postdoctoral researcher at Helsinki University of Technology (Finland), University of Strathclyde (Glasgow, UK), Ecole Centrale de Nantes and the University of Massachusetts (Umass-Amherst, USA). In 2010 he joined Shanghai Jiao Tong University as Special Researcher and received the honor of the "Professor of Exceptional Rank of Shanghai Dong-Fang(the Eastern) Scholar". In 2013, he joined Ecole Centrale de Nantes as an Associate Professor before moving to Hong Kong. Dr. Yin has published over 100 articles in peer-reviewed journals. He has been a member of the granular materials committee of American Society of Civil Engineers since 2012.

Yin-Fu Jin received his bachelor's degree in civil engineering from the Northwest A&F University in 2011 and received his Ph.D. degree in geotechnical engineering from Ecole Centrale de Nantes at France in 2016. He is mainly interested in soil mechanics and parameter identification. He has published more than 10 peer-reviewed papers in international journals such as Acta Geotechnica, International Journal for Numerical and Analytical Methods in Geomechanics, Ocean Engineering and Engineering Geology.

Zusammenfassung

Helps the readers quickly and accurately grasp the features of optimization methods

Provides various simulations of laboratory tests and the optimization-based parameter identification procedures

Serves as a guidebook for a free software platform, ErosOpt, which allows readers to conduct analytical research

Inhaltsverzeichnis
Introduction.- Methodology of parameter identification.- Optimisation algorithms.- Laboratory tests for mechanical behaviours of soils.- Constitutive modeling of soils.- ErosOpt platform.- Appendix A: NMS.- Appendix B: NMGA.- Appendix C: NMDE.
Details
Erscheinungsjahr: 2019
Fachbereich: Bau- und Umwelttechnik
Genre: Technik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 396
Inhalt: xxxvii
356 S.
28 s/w Illustr.
276 farbige Illustr.
356 p. 304 illus.
276 illus. in color.
ISBN-13: 9789811334078
ISBN-10: 9811334072
Sprache: Englisch
Herstellernummer: 978-981-13-3407-8
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Jin, Yin-Fu
Yin, Zhen-Yu
Auflage: 1st ed. 2019
Hersteller: Springer Singapore
Springer Nature Singapore
Maße: 241 x 160 x 27 mm
Von/Mit: Yin-Fu Jin (u. a.)
Erscheinungsdatum: 07.05.2019
Gewicht: 0,758 kg
preigu-id: 114824224
Über den Autor

Zhen-Yu Yin is an Associate Professor of Geotechnical Engineering at The Hong Kong Polytechnic University since 2018. Dr. Yin received his BSc in Civil Engineering from Zhejiang University in 1997, followed by a 5 years engineering consultancy at the Zhejiang Jiahua Architecture Design Institute. Then, he obtained his MSc and Ph.D. in Geotechnical Engineering at Ecole Centrale de Nantes (France) in 2003 and 2006 respectively. Then he has been working as postdoctoral researcher at Helsinki University of Technology (Finland), University of Strathclyde (Glasgow, UK), Ecole Centrale de Nantes and the University of Massachusetts (Umass-Amherst, USA). In 2010 he joined Shanghai Jiao Tong University as Special Researcher and received the honor of the "Professor of Exceptional Rank of Shanghai Dong-Fang(the Eastern) Scholar". In 2013, he joined Ecole Centrale de Nantes as an Associate Professor before moving to Hong Kong. Dr. Yin has published over 100 articles in peer-reviewed journals. He has been a member of the granular materials committee of American Society of Civil Engineers since 2012.

Yin-Fu Jin received his bachelor's degree in civil engineering from the Northwest A&F University in 2011 and received his Ph.D. degree in geotechnical engineering from Ecole Centrale de Nantes at France in 2016. He is mainly interested in soil mechanics and parameter identification. He has published more than 10 peer-reviewed papers in international journals such as Acta Geotechnica, International Journal for Numerical and Analytical Methods in Geomechanics, Ocean Engineering and Engineering Geology.

Zusammenfassung

Helps the readers quickly and accurately grasp the features of optimization methods

Provides various simulations of laboratory tests and the optimization-based parameter identification procedures

Serves as a guidebook for a free software platform, ErosOpt, which allows readers to conduct analytical research

Inhaltsverzeichnis
Introduction.- Methodology of parameter identification.- Optimisation algorithms.- Laboratory tests for mechanical behaviours of soils.- Constitutive modeling of soils.- ErosOpt platform.- Appendix A: NMS.- Appendix B: NMGA.- Appendix C: NMDE.
Details
Erscheinungsjahr: 2019
Fachbereich: Bau- und Umwelttechnik
Genre: Technik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 396
Inhalt: xxxvii
356 S.
28 s/w Illustr.
276 farbige Illustr.
356 p. 304 illus.
276 illus. in color.
ISBN-13: 9789811334078
ISBN-10: 9811334072
Sprache: Englisch
Herstellernummer: 978-981-13-3407-8
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Jin, Yin-Fu
Yin, Zhen-Yu
Auflage: 1st ed. 2019
Hersteller: Springer Singapore
Springer Nature Singapore
Maße: 241 x 160 x 27 mm
Von/Mit: Yin-Fu Jin (u. a.)
Erscheinungsdatum: 07.05.2019
Gewicht: 0,758 kg
preigu-id: 114824224
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