ABOUT THE COURSE Considering the importance of offshore structures, one has to recognize that there are other intrinsic uncertainties such as material properties, analysis methods, design procedures etc, which are addressed rationally. A detailed knowledge of reliability of offshore structures using probabilistic tools becomes need of the hour for both industry and academia. Offshore activities, on one hand, lead to increase in societal wealth, and, on the other hand, make society vulnerable to risks. An offshore engineer is usually accountable for the decisions that he takes. A hallmark of professionalism is to quantify the risks and benefits involved. The present course aims to introduce the basics of the structural reliability analysis procedures. The Registrants would benefit from the course by learning the basics of reliability-based design and principles underlying code calibration, which would provide the groundwork to embark upon research in this field. Key focus will be on safety and reliability issues of offshore facilities during analysis and design, inspection and planning.
INTENDED AUDIENCE Engg faculty, students & researchers
Core course for branches of engg at PG level
Elective course for branches of engg at UG level
Elective at Diploma level
PRE-REQUISITES UG/PG/Ph.D of all engg branches and PG of applied sciences; Diploma students can also register
INDUSTRIES THAT WILL VALUE THIS All academic institutes, all consultancy organizations like Technip, L&T, DNV etc.
350 students have enrolled already!!
Srinivasan Chandrasekaran is currently a Professor in the Dept. of Ocean Engineering, Indian Institute of Technology Madras, India. He has teaching, research and industrial experience of about 23 years during which he has supervised many sponsored research projects and offshore consultancy assignments both in India and abroad. His active areas of research include dynamic analysis and design of offshore platforms, Development of geometric forms of complaint offshore structures for ultra-deep water oil exploration and production, sub-sea engineering, Rehabilitation and retrofitting of offshore platforms, structural health monitoring of ocean structures, seismic analysis and design of structures and risk analyses and reliability studies of offshore and petroleum engineering plants. He has been also a visiting fellow under the invitation of Ministry of Italian University Research to University of Naples Federico II, Italy for a period of two years during which he conducted research on advanced nonlinear modelling and analysis of structures under different environmental loads with experimental verifications. He has about 110 research publications in International journals and refereed conferences organized by professional societies around the world. Seven text books authored by him are quite popular amongst graduate students of civil and ocean engineering and recommended as reference material for class room studies and research as well. He also delivered Six web-based courses namely: i) Dynamic analysis of ocean structures (Both MOODLE and NPTEL); ii) Ocean structures and materials; iii) Advanced marine structures; and iv) Health, safety & Management in offshore and petroleum engineering (Both MOODLE and NPTEL). He is a member of many National and International professional bodies and delivered many invited lectures and key note address in the international conferences, workshops and seminars in India and abroad.
Nagavinothini.R, Senior Research Scholar, Department of Ocean Engineering, IIT Madras Areas of Interest: Dynamic analysis of offshore compliant platforms, Design of offshore structures, Computer methods of analysis of structures, Risk and reliability of structures.
Venkata Kiran, Senior Research Scholar, Department of Ocean Engineering, IIT Madras Areas of interest: Quantitative risk analysis, Reliability availability and maintainability.
Week 1: Introduction to reliability Week 2: Rules of probability Week 3: Random variables Week 4: Levels of reliability Week 5: Reliability methods Week 6: System reliability Week 7: Reliability - Application problems Week 8: Variables in reliability analysis Week 9: Fatigue reliability Week 10: Risk Assessment Week 11: Risk analysis methods Week 12: Risk and Hazard SUGGESTED READING
a) Text books:
1. Almond R.G. An extended example for testing graphical belief, Technical Report No. 6.1992.
2. Chakrabarti, S.K. 1990. Non-linear Method in Offshore Engineering, Elsevier Science Publisher, The Netherlands.
3. Chakrabarti, S.K. 1994. Offshore Structure Modeling: World Scientific, Singapore.
4. Chandrasekaran, S. and Bhattacharyya, S.K. 2011. Analysis and Design of Offshore Structures. HRD Center for Offshore and Plant Engineering (HOPE), Changwon National University, Republic of Korea, pp. 285.
5. Cowell RG, Dawid AP, Lauritzen SL, Spiegelhalter DJ. Probabilistic networks and expert systems. New York: Springer; 1999. 6. Gelman A, Carlin JB, Stern HS, Rubin DB. Bayesian data analysis. London: Chapman & Hall; 1995. p. 1-526. 7. Halder, A. and Mahaderan, S., “First order and Second order Reliability Method” Probabilistic Structural Mechanics Hand Book, Edited by C. (Raj) Sundararajan, Chapman and Hall, PP. 27-52, 1995.
8. Jensen FV. Bayesian networks and decision graphs. New York: Springer; 2001. 9. Pearl J. Probabilistic reasoning in intelligent systems. San Francisco, CA: Morgan Kaufmann; 1988. 10. Srinivasan Chandrasekaran. 2014. Advanced Theory on Offshore Plant FEED Engineering, Changwon National University Press, Republic of South Korea, pp. 237. ISBN:978-89-969792-8-9
11. Srinivasan Chandrasekaran. 2015. Advanced Marine structures, CRC Press, Florida, ISBN 9781498739689
12. Srinivasan Chandrasekaran. 2015. Dynamic analysis and design of ocean structures. Springer. ISBN: 978-81-322-2276-7.
13. Srinivasan Chandrasekaran. 2016a. Offshore structural engineering: Reliability and Risk Assessment. CRC Press, Florida, ISBN:978-14-987-6519-0 Research articles
1. Arnasaki S, Takagi Y, Mizuno 0, Kikuno T. A Bayesian belief network for assessing the likelihood of fault content. In:
Proceedings of the 14th international
symposium on software reliability engineering; 2003. p. 215-26.
2. Barlow RE. Using influence diagrams. Accelerated
Life Testing and Experts' Opinions in Reliability 1988:145-50. 3.Bobbio A. Portinale L. Minichino M. Ciancamerla
E. Improving the analysis of dependable systems by mapping fault trees into
Bayesian networks. Reliab Eng Syst Saf
4.Boudali H, Dugan JB. A continuous-time Bayesian
network reliability modeling, and analysis framework. IEEE Trans Reliab
5.Box, G. E. P., and Tiao, G. C., “Bayesian
Inference in Statical Analysis”, Addison-Wesley, Reading, MA 1973.
6.Breitung, K., “Asymptotic Approximation for
Multi-normal Integrals”, Journal of Engineering Mechanics Division, ASCE,
110(3), PP. 357-366, 1984
7.Cooper GF, Herskovits E. A Bayesian method for
the induction of probabilistic networks from data. Mach Learn 1992:9(4):309-47.
8.Gopal C, Kuolung H, Nader A. A new approach to
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9.Cornel, C. A., “A Probability Based Structural
Code”, Journal of the American Concrete Institute, 66(12), PP. 974-085, 1969.
10.Coyle T. Arno RG. Hale PS. Application of the
minimal cut set reliability analysis methodology to the gold book standard
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11.Dahll G. Gran BA. The use of Bayesian belief
nets in safety assessment of software based systems. Special Issues Int J
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12.Der Kiureghian, Lin, H. Z., and Hwang, S. F.,
“Second order Reliability Approximation”, Journal of Engineering Mechanics
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13.Fenton N. Krause P. Neil M. Software
measurement: uncertainty and causal modeling. IEEE Software 2002;10(4):116-22.
14.Fiessler, B., Neumann, H. J., and Rackwitz, R.,
“Quadratic Limit States in Structural Reliability”, Journal 0of Engineering
Mechanics Division, ASCE, 105(4), PP. 661-676, 1979.
15.Ghokale S, Lyu M, Trivedi K. Reliability
simulation of component based software systems. In: Proceedings of the
international symposium on software reliability engineering (ISSRE'98); 1998.
16.Ghokale S, Wong E, Trivedi K, Horgan JR. An
analytical approach to architecture based software reliability prediction. In:
Proceedings of the symposium on application specific systems and software
engineering technology (ASSET '98). TX: Dallas; 1998.
17.Gran BA, Helminen A. A Bayesian belief network
for reliability assessment. Safecornp 2001 20012187:35-45.
18.Gran BA. Dahill G. Eisinger S. Lund EJ, Norstrom
JG. Strocka P. Ystanes BJ. Estimating dependability of programmable systems
using Bbns. In: Proceed-ings of the Safecornp 2000. Berlin: Springer; 2000. p.
19.Helminen A, Pulld<inen U. quantitative
reliability estimation of a computer-based motor protection relay using Bayesian
networks. Safecomp 2003;2788:92-102.
20.Helminen A. Reliability estimation of
software-based digital systems using Bayesian networks. Technical Report.
Helsinki University of Technology Espoo, 2000. p. 1-50.
21.Herald T, Ramirez-Marquez JE. System element
obsolescence replacement optimization via life cycle cost forecasting. NJ:
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22.Hugin Expert. (2007), Aalborg, Denmark
23.Krishnarnurthy S. Mathur AP. On the estimation
of reliability of a software system using reliabilities of its components. In:
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1997. p. 146.
24.Lagnseth H, Portinale L. Bayesian networks in
reliability. Tech Rep 2005.
25.Littlewood B. Popov P. Strigini L. Assessment of
the reliability of fault-tolerant software: a bayesian approach. In:
Proceedings of the 19th international
conference on computer safety, reliability and security (SAFECOMP 2000). Berlin: Springer; 2000
26.Pant K, Brandt S. Null convention logic, a
complete and consistent logic for
asynchronous digital circuit synthesis. In: Proceedings of the
international conference on application specific systems, architectures, and processors (ASAP '96); 1996. p. 261-73.
27.Rackwitz, R., and Fiessler, B., Note on Discrete
Safety Checking When Using Non-Normal Stochastic Models for Basic Variables.
Loads Project Working Session. Cambridge, Massachusetts: Massachusetts
Institute of Technology. 1976.
28.Serene-Safety and Risk Evaluation Using Bayesian
Nets, (2006), <http:// www.hugin.d k/serene/ > (2008).
29.Shinozuka, M., “Basic Analysis of Structural
Safety”, Journal of the Structural Division, ASCE, 109(3), PP. 721-740, 1983.
30.Sigurdsson JH, Walls LA, Quigley JL. Bayesian
belief nets for managing expert judgment
and modeling reliability. Qual Reliab Eng Int 2001;17:181-90.
31.Spiegelhalter D. Thomas A. Best N. Gilks W. Bugs
0.5 Bayesian inference using Gibbs sampling manual (Version Ii). MRC
Biostatistic Unit 1996;1:1-59.
32.Tvedt, L., “Distribution of Quadratic forms in
Normal Space-Application to Structural Reliability”, Journal of the Engineering
Mechanics Division, ASCE, 116(6), PP. 1183-1197, 1990. CERTIFICATION EXAM
The exam is optional for a fee.
Date and Time of Exams: April 28 (Saturday) and April 29 (Sunday) : Afternoon session: 2pm to 5pm
Exam for this course will be available in one session on both 28 and 29 April.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published.
Final score will be calculated as : 25% assignment score + 75% final exam score
25% assignment score is calculated as 25% of average of Best 8 out of 12 assignments
E-Certificate will be given to those who register and write the exam and score greater than or equal to 40% final score. Certificate will have your name, photograph and the score in the final exam with the breakup. It will have the logos of NPTEL and IIT MADRAS. It will be e-verifiable at nptel.ac.in/noc.