Databases for Data-Centric Geotechnics forms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This second volume pertains to geotechnical structures. The opening chapter presents a substantial survey of performance databases and the effectiveness of our prediction models in matching the field measurements in these databases, based on (1) full-scale field tests, (2) 39 prediction exercises organized as a part of international conferences, and (3) comparison between numerical analyses and in-situ or field measurements conducted by the French LCPC. The focus is on the evaluation of the statistical degree of confidence in predicting various of quantities of interest such as capacity and deformation. The following 18 chapters then present databases on the performance of shallow foundations, spudcan foundations, deep foundations, anchors and pipelines, retaining systems and excavations, and landslides. The databases were compiled from studies undertaken in many countries such as Australia, Belgium, Bolivia, Brazil, Canada, China, Egypt, France, Germany, Hungary, Iran, Ireland, Japan, Kenya, Malaysia, Netherlands, Norway, Poland, Portugal, South Africa, the United Kingdom and the United States.
This volume on geotechnical structures is a companion to the volume on site characterization. Databases for Data-Centric Geotechnics represents the most diverse and comprehensive assembly of database research in a single publication (consisting of two volumes) to date. It follows from Model Uncertainties for Foundation Design, also published by CRC Press, and suits specialist geotechnical engineers, researchers and graduate students.
Chapter 10 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons [Attribution (CC BY)] 4.0 license.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Kok-Kwang Phoon is Cheng Tsang Man Chair Professor and Provost at the Singapore University of Technology and Design. He was awarded the ASCE Norman Medal twice in 2005 and 2020, and the Humboldt Research Award in 2017. He is the Founding Editor of Georisk, a Board Member of ISSMGE, and Fellow of the Academy of Engineering Singapore.
Chong Tang is a Professor at Dalian University of Technology in China and former senior research fellow at the National University of Singapore. He was awarded the ASCE Norman Medal in 2020.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Paperback. Condizione: new. Paperback. Databases for Data-Centric Geotechnics forms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This second volume pertains to geotechnical structures. The opening chapter presents a substantial survey of performance databases and the effectiveness of our prediction models in matching the field measurements in these databases, based on (1) full-scale field tests, (2) 39 prediction exercises organized as a part of international conferences, and (3) comparison between numerical analyses and in-situ or field measurements conducted by the French LCPC. The focus is on the evaluation of the statistical degree of confidence in predicting various of quantities of interest such as capacity and deformation. The following 18 chapters then present databases on the performance of shallow foundations, spudcan foundations, deep foundations, anchors and pipelines, retaining systems and excavations, and landslides. The databases were compiled from studies undertaken in many countries such as Australia, Belgium, Bolivia, Brazil, Canada, China, Egypt, France, Germany, Hungary, Iran, Ireland, Japan, Kenya, Malaysia, Netherlands, Norway, Poland, Portugal, South Africa, the United Kingdom and the United States.This volume on geotechnical structures is a companion to the volume on site characterization. Databases for Data-Centric Geotechnics represents the most diverse and comprehensive assembly of database research in a single publication (consisting of two volumes) to date. It follows from Model Uncertainties for Foundation Design, also published by CRC Press, and suits specialist geotechnical engineers, researchers and graduate students.Chapter 10 of this book is freely available as a downloadable Open Access PDF at under a Creative Commons [Attribution (CC BY)] 4.0 license. This is the second of a definitive guide to databases in geotechnical and rock engineering to enhance decision-making in geotechnical practice using data-driven methods. This volume presents databases on the performance of shallow, spudcan, and deep foundations; anchors and pipelines; retaining systems and excavations; and landslides. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781032579917
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Paperback. Condizione: new. Paperback. Databases for Data-Centric Geotechnics forms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This second volume pertains to geotechnical structures. The opening chapter presents a substantial survey of performance databases and the effectiveness of our prediction models in matching the field measurements in these databases, based on (1) full-scale field tests, (2) 39 prediction exercises organized as a part of international conferences, and (3) comparison between numerical analyses and in-situ or field measurements conducted by the French LCPC. The focus is on the evaluation of the statistical degree of confidence in predicting various of quantities of interest such as capacity and deformation. The following 18 chapters then present databases on the performance of shallow foundations, spudcan foundations, deep foundations, anchors and pipelines, retaining systems and excavations, and landslides. The databases were compiled from studies undertaken in many countries such as Australia, Belgium, Bolivia, Brazil, Canada, China, Egypt, France, Germany, Hungary, Iran, Ireland, Japan, Kenya, Malaysia, Netherlands, Norway, Poland, Portugal, South Africa, the United Kingdom and the United States.This volume on geotechnical structures is a companion to the volume on site characterization. Databases for Data-Centric Geotechnics represents the most diverse and comprehensive assembly of database research in a single publication (consisting of two volumes) to date. It follows from Model Uncertainties for Foundation Design, also published by CRC Press, and suits specialist geotechnical engineers, researchers and graduate students.Chapter 10 of this book is freely available as a downloadable Open Access PDF at under a Creative Commons [Attribution (CC BY)] 4.0 license. This is the second of a definitive guide to databases in geotechnical and rock engineering to enhance decision-making in geotechnical practice using data-driven methods. This volume presents databases on the performance of shallow, spudcan, and deep foundations; anchors and pipelines; retaining systems and excavations; and landslides. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9781032579917
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Condizione: New. Kok-Kwang Phoon is Cheng Tsang Man Chair Professor and Provost at the Singapore University of Technology and Design. He was awarded the ASCE Norman Medal twice in 2005 and 2020, and the Humboldt Research Award in 2017. He is the Founding Editor of. Codice articolo 3381499012
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Paperback. Condizione: new. Paperback. Databases for Data-Centric Geotechnics forms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods. This second volume pertains to geotechnical structures. The opening chapter presents a substantial survey of performance databases and the effectiveness of our prediction models in matching the field measurements in these databases, based on (1) full-scale field tests, (2) 39 prediction exercises organized as a part of international conferences, and (3) comparison between numerical analyses and in-situ or field measurements conducted by the French LCPC. The focus is on the evaluation of the statistical degree of confidence in predicting various of quantities of interest such as capacity and deformation. The following 18 chapters then present databases on the performance of shallow foundations, spudcan foundations, deep foundations, anchors and pipelines, retaining systems and excavations, and landslides. The databases were compiled from studies undertaken in many countries such as Australia, Belgium, Bolivia, Brazil, Canada, China, Egypt, France, Germany, Hungary, Iran, Ireland, Japan, Kenya, Malaysia, Netherlands, Norway, Poland, Portugal, South Africa, the United Kingdom and the United States.This volume on geotechnical structures is a companion to the volume on site characterization. Databases for Data-Centric Geotechnics represents the most diverse and comprehensive assembly of database research in a single publication (consisting of two volumes) to date. It follows from Model Uncertainties for Foundation Design, also published by CRC Press, and suits specialist geotechnical engineers, researchers and graduate students.Chapter 10 of this book is freely available as a downloadable Open Access PDF at under a Creative Commons [Attribution (CC BY)] 4.0 license. This is the second of a definitive guide to databases in geotechnical and rock engineering to enhance decision-making in geotechnical practice using data-driven methods. This volume presents databases on the performance of shallow, spudcan, and deep foundations; anchors and pipelines; retaining systems and excavations; and landslides. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9781032579917
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