09235nam a2200697 i 4500 9780750349314 IOP 20251030124215.0 m eo d cr cn |||m|||a 230701s2023 enka fob 000 0 eng d 9780750349314 ebook 9780750349307 mobi 9780750349291 print 9780750349321 myPrint 10.1088/978-0-7503-4931-4 doi (CaBNVSL)thg00083625 (OCoLC)1389632650 CaBNVSL eng rda CaBNVSL CaBNVSL QA76.9.S88 O663 2023eb PBU bicssc MAT042000 bisacsh Ooi, Melanie Po-Leen, author. 96565 Analytical evaluation of uncertainty propagation for probabilistic design optimisation / Melanie Po-Leen Ooi, Arvind Rajan, Ye Chow Kuang, Serge Demidenko. Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2023] 1 online resource (various pagings) : illustrations (some color). text rdacontent electronic isbdmedia online resource rdacarrier [IOP release $release] IOP ebooks. [2023 collection] "Version: 202306"--Title page verso. Includes bibliographical references. 1. Introduction -- 2. Uncertainty propagation -- 2.1. Averaging methods for estimating the measurand in nonlinear models -- 2.2. First-order linearisation and the normality assumption -- 2.3. The Monte Carlo method -- 2.4. The use of a mathematical representation of the probability density function -- 2.5. Uncertainty evaluation using moments -- 2.6. Summary 3. Probabilistic design optimisation -- 3.1. Robust design optimisation -- 3.2. Reliability-based design optimisation -- 3.3. Reliability-based robust design optimisation -- 3.4. Summary 4. Moment-based standard uncertainty in design optimisation -- 4.1. The derivation of the analytical moments of multivariate polynomials -- 4.2. A toolbox for moment-based standard uncertainty evaluation -- 4.3. Case studies for moment-based analytical standard uncertainty evaluation -- 4.4. A general framework for analytical moment-based reliability and robustness analysis -- 4.5. Summary 5. Moment-based expanded uncertainty evaluation in design optimization -- 5.1. The improved moment-constrained maximum entropy method -- 5.2. Test distributions for benchmarking and performance analysis -- 5.3. Reliability analysis of parametric distribution-fitting techniques : from unimodal to multimodal distributions -- 5.4. A toolbox for the MaxEnt algorithm -- 5.5. Summary 6. Real-world design optimisation problems : applications and usefulness -- 6.1. The framework for probabilistic design optimisation -- 6.2. Lithium-ion batteries : a reliability-based design optimisation framework -- 6.3. Vehicle design based on side-impact crashworthiness : the application of a reliability-based robust design optimisation problem -- 6.4. Fuel cells : parameter optimisation for reliable and robust operation -- 6.5. Magnetic sensor module design -- 6.6. A multistorey three-dimensional steel structure : reliability analysis and optimisation -- 6.7. Summary -- Appendix A. Lookup table for the parameters g and h in Tukey's gh distribution -- Appendix B. Lookup table for the Mellin transforms of various families of probability distribution. 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. Academic and commercial metrology, instrumentation and measurement research communities. Also available in print. Mode of access: World Wide Web. System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader. 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. Title from PDF title page (viewed on July 6, 2023). System design. 64691 Mathematical optimization. 65522 Optimization. bicssc 65528 MATHEMATICS / Optimization. bisacsh 96566 Rajan, Arvind (Data scientist), author. 96567 Kuang, Ye Chow, author. 96568 Demidenko, Serge, author. 96569 Institute of Physics (Great Britain), publisher. 17702 Print version: 9780750349291 9780750349321 IOP (Series). Release 23. IOP ebooks. 2023 collection. https://iopscience.iop.org/book/mono/978-0-7503-4931-4 E-Books 68379 68379