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001 9780750349314
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020 _a9780750349314
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020 _a9780750349307
_qmobi
020 _z9780750349291
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024 7 _a10.1088/978-0-7503-4931-4
_2doi
035 _a(CaBNVSL)thg00083625
035 _a(OCoLC)1389632650
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aQA76.9.S88
_bO663 2023eb
072 7 _aPBU
_2bicssc
072 7 _aMAT042000
_2bisacsh
100 1 _aOoi, Melanie Po-Leen,
_eauthor.
_996565
245 1 0 _aAnalytical evaluation of uncertainty propagation for probabilistic design optimisation /
_cMelanie Po-Leen Ooi, Arvind Rajan, Ye Chow Kuang, Serge Demidenko.
264 1 _aBristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :
_bIOP Publishing,
_c[2023]
300 _a1 online resource (various pagings) :
_billustrations (some color).
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
490 1 _a[IOP release $release]
490 1 _aIOP ebooks. [2023 collection]
500 _a"Version: 202306"--Title page verso.
504 _aIncludes bibliographical references.
505 0 _a1. 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
505 8 _a3. Probabilistic design optimisation -- 3.1. Robust design optimisation -- 3.2. Reliability-based design optimisation -- 3.3. Reliability-based robust design optimisation -- 3.4. Summary
505 8 _a4. 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
505 8 _a5. 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
505 8 _a6. 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.
520 3 _aThis 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.
521 _aAcademic and commercial metrology, instrumentation and measurement research communities.
530 _aAlso available in print.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
545 _aAssociate 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.
588 0 _aTitle from PDF title page (viewed on July 6, 2023).
650 0 _aSystem design.
_964691
650 0 _aMathematical optimization.
_965522
650 7 _aOptimization.
_2bicssc
_965528
650 7 _aMATHEMATICS / Optimization.
_2bisacsh
_996566
700 1 _aRajan, Arvind
_c(Data scientist),
_eauthor.
_996567
700 1 _aKuang, Ye Chow,
_eauthor.
_996568
700 1 _aDemidenko, Serge,
_eauthor.
_996569
710 2 _aInstitute of Physics (Great Britain),
_epublisher.
_917702
776 0 8 _iPrint version:
_z9780750349291
_z9780750349321
830 0 _aIOP (Series).
_pRelease 23.
830 0 _aIOP ebooks.
_p2023 collection.
856 4 0 _uhttps://iopscience.iop.org/book/mono/978-0-7503-4931-4
942 _cE-Books
999 _c68379
_d68379