Thomas Rodding Kjeldsen

Risk and Uncertainty for Civil Engineering (eBook, PDF)

• Format: PDF

Produktbeschreibung

This textbook introduces the fundamental concepts of probability, risk, and uncertainty, and shows their relevance in civil engineering projects. With an emphasis on applied probability and statistics, the book aids students in developing an intuitive understanding of the methods to apply in practice.

Drawing from real-world examples, readers are introduced to risk assessment and analysis techniques, enabling them to identify, evaluate, and prioritise potential risks. It gives realistic examples of how spreadsheet tools such as Microsoft Excel can be used to solve problems involving probability, and practical approaches such as Monte Carlo simulations and decision trees are explained in a clear, accessible manner, empowering students to make informed decisions under uncertain and variable conditions. The book also emphasises the importance of effective communication, equipping students with essential skills for working in multidisciplinary teams and with different stakeholders.

Risk and Uncertainty for Civil Engineering serves as an introductory textbook for undergraduate students in civil engineering, as well as a useful primer for postgraduate students.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 220
• Erscheinungstermin: 29. Januar 2025
• Englisch
• ISBN-13: 9781040229767
• Artikelnr.: 72735375

Autorenporträt

Thomas Rodding Kjeldsen is Reader in the Department of Architecture and Civil Engineering, University of Bath, UK, where he teaches introductory courses on engineering risk and uncertainty to undergraduate and postgraduate civil engineering students.

Inhaltsangabe

1. Introduction. 2. Random variables and probability distributions. 3.
Parameter estimation. 4. Data visualisation. 5. Uncertainty analysis of
engineering systems. 6. Monte Carlo simulations. 7. Structural reliability
analysis. 8. Complex systems. 9. Decision-making in an uncertain world. 10.
Hypothesis testing. 11. Linear regression models. 12. Low probability, high
impact events. 13. Risk communication. 14. Useful Excel functions.