Resilience Engineering
Models and Analysis
Nonfiction, Science & Nature, Technology, Environmental, Mathematics, Applied
| Author: | Nii O. Attoh-Okine | ISBN: | 9781316564059 |
| Publisher: | Cambridge University Press | Publication: | April 7, 2016 |
| Imprint: | Cambridge University Press | Language: | English |
| Author: | Nii O. Attoh-Okine |
| ISBN: | 9781316564059 |
| Publisher: | Cambridge University Press |
| Publication: | April 7, 2016 |
| Imprint: | Cambridge University Press |
| Language: | English |
With an eye towards environmental sustainability, this book presents a step-by-step approach to formulating the resilience of civil infrastructure and energy systems. It provides a concise explanation of resilience terminology, a general overview of theoretical models and analyses, and a clear guide to practical applications, covering critical topics such as interdependent infrastructures and geologic carbon sequestration. Additionally, it contains a general introduction to selected data science topics, so readers can acquire the tools to formulate and analyze resilience engineering problems in depth. Informed by the author's extensive practical experience and thorough academic background, this book includes examples to illustrate key computational algorithms, end-of-chapter exercises and references, and an entire chapter devoted to case studies. Intended for practitioners of resilience engineering with a background in probability, this book offers a balanced blend of background, theory, and practical examples to address one of the most important emerging topics of modern times.
With an eye towards environmental sustainability, this book presents a step-by-step approach to formulating the resilience of civil infrastructure and energy systems. It provides a concise explanation of resilience terminology, a general overview of theoretical models and analyses, and a clear guide to practical applications, covering critical topics such as interdependent infrastructures and geologic carbon sequestration. Additionally, it contains a general introduction to selected data science topics, so readers can acquire the tools to formulate and analyze resilience engineering problems in depth. Informed by the author's extensive practical experience and thorough academic background, this book includes examples to illustrate key computational algorithms, end-of-chapter exercises and references, and an entire chapter devoted to case studies. Intended for practitioners of resilience engineering with a background in probability, this book offers a balanced blend of background, theory, and practical examples to address one of the most important emerging topics of modern times.
