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Probabilistic Methods for Engineering Problems
- 1st Edition - January 1, 2023
- Authors: Julian Booker, Nader Zentuti, Josh Hoole
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 3 7 8 4 - 7
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 4 1 8 4 - 4
Probabilistic Methods for Engineering Problems presents statistical and probabilistic methods together with examples and case studies to support the development of probabili… Read more
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Request a sales quoteProbabilistic Methods for Engineering Problems presents statistical and probabilistic methods together with examples and case studies to support the development of probabilistic approaches to engineering problems. Probabilistic design is an opportunity for engineers to optimise the reliability and performance of the system they are working with. It provides a transparent means of explaining the safety aspects of engineering design decisions with a degree of clarity not provided by the deterministic ‘factor of safety’ approach. This book captures the recent focus on probabilistic approaches and advanced engineering practice in this area, to provide a comprehensive and up-to-date guide for practitioners and researchers alike.
Methods presented include the statistical characterisation of raw data, sensitivity studies, and the efficient execution of probabilistic routines. Effective methodologies are provided and applied to static, dynamic, fatigue and high temperature creep problem types, with applications across many industrial sectors. This book will be invaluable to any engineer seeking to evaluate their designs, conduct analyses and assessments in a more realistic way, and predict failure probability and reliability against targets.
- Describes how to use statistical tools for the management and characterisation of different types of data for design and service parameters
- Helps readers to systematically select the most appropriate probabilistic routine to suit their problem, and how to apply it effectively
- Features real industrial case studies, preparing the reader for likely implementation challenges with practical advice
Primary market/audience: Engineers and others in industry associated with modelling, reliability, quality and safety of components, plant and systems across all sectors.Secondary market/audience: Engineering masters students as a reference text for courses involving reliability, risk or quality management.
1. Introduction to Probabilistic Methods2. Statistically Characterising Data3. Modelling the Performance Function4. Surrogate Modelling5. Solving Performance Functions6. Predicting Failure and Reliability7. Sensitivity Analysis8. Risk Assessments and Setting Targets9. Engineering Case Studies Featuring Probabilistic Methods10. Strategies for Implementing Probabilistic Methods
- No. of pages: 400
- Language: English
- Edition: 1
- Published: January 1, 2023
- Imprint: Academic Press
- Paperback ISBN: 9780128237847
- eBook ISBN: 9780128241844
JB
Julian Booker
Julian Booker holds a Chair in Mechanical Design Engineering in the Department of Mechanical Engineering, University of Bristol. Julian is a leading authority on the development and application of design methods across a broad spectrum of disciplines. His research spanning over 20 years into design methods has led to the development of commercial software, a range of books and high impact factor journal publications, as well as helping deliver state of the art design solutions for industry, whilst making a substantial contribution to the academic field. His applied research into statistical and probabilistic methods has application to material failure assessments, structural integrity and the performance of machine components, structures and assemblies, with relevance to industry sectors including aerospace, automotive, energy and industrial. He currently has over 150 publications, including 60 journal papers and has personally presented papers at over 50 international conferences, and has authored 3 books. He is a Chartered Engineer and Fellow of the Institution of Mechanical Engineers.
Affiliations and expertise
Chair, Mechanical Design Engineering, Department of Mechanical Engineering, University of Bristol.NZ
Nader Zentuti
Nader Zentuti was awarded a PhD in Mechanical Engineering from the University of Bristol in 2019. His research focused on the implementations of probabilistic methods for high temperature structural integrity applications, a field in which he has
published 6 papers. He examined the uncertain long-term behaviour of metallic components in nuclear power plants. This was sponsored by EDF Energy as part of a UK-wide research focus on safety compliance and extending the operational lifetime
of existing plant assets. He delivered to EDF Energy a probabilistic framework for estimating failure rates of metallic components. He is currently a Data Scientist at Faculty, a company specialising in data science, machine learning and artificial
intelligence as applied to a wide range of industries including government, healthcare and engineering.
Affiliations and expertise
PhD, Mechanical Engineering, University of Bristol in 2019.JH
Josh Hoole
Josh Hoole has an MEng in Aerospace Engineering from the University of Bristol and is currently a Research Associate in Probabilistic Design working on fatigue problems in the aerospace sector. He has published 6 papers and will soon be submitting his PhD in the field of probabilistic design, with a focus on how `real-time’ in-service data and surrogate modelling methods can support the implementation of such approaches.
Affiliations and expertise
MEng, Aerospace Engineering, University of Bristol.
Research Associate, Probabilistic Design, aerospace sector.