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Analytical Evaluation of Uncertainty Propagation for Probabilistic Design Optimisation by Melanie Po-Leen Ooi (Hardback)
£120.00
Available
Product Ref. (e.g. ISBN, SKU)
9780750349291
Published:
16 Jun 2023
Format:
Hardback
Number of pages:
275 pages
Dimensions:
254x264x16mm
Weight:
0.474kgs
Author:
This book presents a novel approach to the evaluation and dealing with uncertainties of parameters and processes in technical systems with application to the probabilistic optimisation of engineering design while achieving the required high levels of efficiency, robustness, and reliability.
This monograph introduces several recently developed and applied analytical-based theoretical approaches and practical techniques for uncertainty evaluation and probabilistic design optimisation for the robustness and reliability of technical systems of various complexity and applications. This is enhanced by the inclusion of relevant real-world case studies.
The book will be useful for researchers, engineers, and designers of complex, multi-parameter technical systems that must guarantee a specified level of functional reliability. It presents several real-world case studies helping to comprehend in detail the developed techniques and their benefits. In addition, it offers free access to the online toolboxes developed by the authors to support the calculation of uncertainties and guides the readers on the practical use of such tools.
Key Features:
Cohesively combines three important research, development, and real-world engineering practice areas (i) uncertainty and its evaluation, propagation, modelling, etc., and, (ii) complex technical systems design optimisation involving advanced probabilistic theories, techniques, and tools, and (iii) development of such theories This is arguably the first monograph systematically and comprehensively presenting the new area of moment-based uncertainty propagation and its practical applications. The book offers a significant volume of additional explanations, guidelines and tools enabling the readers to utilise the presented material in their research, design, and engineering practice. It provides free access to developed application-specific online tools and benchmark test distributions for expanded uncertainty. The practical application section of the monograph presents several real-world case study solutions.About the Author: Associate Professor Melanie Ooi received her B.Eng. (Hons.), M.Eng.Sc. (Research) and Ph.D. from Monash University in the areas of Electronics, Computer Engineering, and Computational Intelligence. She is currently an Associate Professor and Assistant Dean (Research) of the School of Engineering, University of Waikato, New Zealand as well as an Adjunct Professor of Sunway University, Malaysia. She is the recipient of several awards including the 2019 Rutherford Discovery Fellowship from the New Zealand Royal Society, 2017 Mike Sargeant Career Achievement Award from the Institution of Engineering and Technology (IET), 2014 Outstanding Young Engineer Award from the Instrumentation and Measurement Society (I&MS) of the Institute of Electrical and Electronics Engineers (IEEE), 2014 Excellence Award from the International Education Association of Australia, 2011 Citation for Outstanding Contributions to Student Learning from the Australian Learning and Teaching Council. She was the youngest female elevated to the IET Fellow grade. Associate Professor Ooi is a U.K. Chartered Engineer and Senior Member of the IEEE. She is a guest editor for the IEEE Transactions in Instrumentation and Measurement, Administrative Committee Member of IEEE I&MS as well as Secretary and Member of the Society's Technical Committee on Fault-Tolerant Measurement Systems (TC-32). Dr Arvind Rajan is a Data Scientist at DNS Technology in Melbourne, Australia. He received his B.Eng. (First Class Hons.) and Ph.D. degrees from Monash University, in 2015 and 2018, respectively. He is a Member of IEEE, IEEE I&MS, and its Technical Committee (TC-32) on Fault Tolerant Measurement Systems. He is also a Member of the Institution of Engineering and Technology (IET). He was the winner of the IEEE I&MS 2017 Graduate Fellowship Award. In 2018 Dr Rajan was awarded the Monash University Vice-Chancellor's Commendation for Doctoral Thesis Excellence. Dr Ye Chow Kuang received his B.Eng. (Hons.) degree in electromechanical engineering and Ph.D. in non-invasive diagnostic techniques from the University of Southampton. In 2005-2018 he was Associate Professor at Monash University specialising in machine intelligence, machine vision, and uncertainty modelling in engineering design. He is currently with the Faculty of Science and Engineering, University of Waikato, New Zealand. He is Chair of the Technical Committee on Fault Tolerant Measurement Systems of the IEEE I&MS (TC-32). He is also a Member of IET and U.K. Chartered Engineer. He was a co-recipient of the 2014 Excellence Award from the International Education Association of Australia, and the 2012 IEEE I&MS Faculty Course Development Award. Professor Serge N. Demidenko received a five-year electrical engineer qualification in computer engineering from the Belarusian State University of Informatics and Radio Electronics, and Ph.D. from the Institute of Engineering Cybernetics of the Belarusian Academy of Sciences. He is currently a Professor at the School of Food and Advanced Technology, Massey University, New Zealand. He is also an Adjunct Professor at Sunway University, Malaysia where he previously was a Dean at the School of Engineering and Technology. Professor Demidenko is a Chair of the IEEE Technical Field Awards Council, Member of the IEEE Awards Board, Conferences Committee, and Fellow Committee. He is also the Past Chair of the IEEE Joseph F. Keithley Award in Instrumentation and Measurement. From 2002 to 2015 he was a Founder and Chair of the IEEE I&MS Technical Committee on Fault Tolerant Measurement Systems. He is a Fellow of IEEE and IET, U.K. Chartered Engineer as well as a Member of the European Academy of Sciences and Arts.
| Number of pages | 275 |
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