《工程可靠度理论与应用》课程大纲及阅读书目（逐步更新）
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Course Outline (for tentative use at Hunan University, Spring 2011)
Latest updat on 03/29/2011, 6:00PM EST

Course:      Risk and Reliability for Engineers
Audiences:   Graduate students in engineering fields, at both MASc and PhD levels

Course Description
Themain purpose of this course is to provide the graduate students with a comprehensiveintroduction to basic concepts, theory, methods and techniques that are widely used in risk and reliability analysis in engineering design and other consultancy services (e.g., forensic engineering and engineering policy analysis).  Applications to reliability-based structural design and infrastructure management, and practical issues therein will also be discussed.  

Upon completion of the course the students are expected to have acquired the literacy of risk and reliability so that they can read research articles in related areas.  They are also expected to be able to perform statistical analysis of reliability data and to do a full probabilistic design of components and simple structures.

Starting with a review of probability and statistics, thecourse will cover (core contents are marked with x)
x1)  Structuralreliability methods
x2)  Reliability-basedstructural design
3)   Seismic hazard assessment (* tentative only, depending on the students' needs and preference)
x4)  Probabilistic failure modeling and statistical methods
x5)   Point processes and their applications in inspection and maintenance, and
6)  Systemreliability analysis (* may focus on structural system reliability, subject to students' preference)
7)   Reliability assessment of existing structures (* tentative only）
x8)   Quality control in construction engineering (* tentative only)

For Sciencenet readers, this course does not cover reliability testing and reliability growth, both extremely important topics in electrical engineering, and aeronautic and astronautic engineering.
 
Prerequisites
Although the key concepts and mathematical tools will be reviewed in the first lecture, thestudents are expected to have basic appreciation to probability and statistics,and mathematical optimization.  The students are strongly encouraged to review the undergraduate textbooks of probability and statistics.  

MATLABwill be used for solving assignment questions.  In particular, the students need to know how to write a MATLAB function, and are familiar with the Optimization and Statistical toolboxes.  To be more specific, the students must know how to use the functions 'fmincon', 'fminunc', 'fsolve' and 'fzero', and the random number generators provided in MATLAB.  The instructor will not teach MATLAB in class.  The students are strongly encouraged to consult the MATLAB help documentation if he/she does not know where to start.

Course Assessment
Thestudent’s performance will be evaluated based on the following three components:
(1)  Assignments (4 x 5% = 20%)
(2)   Class performance (10%).  This means you need to attend the class both physically and mentally.
(3)   Individual project (20% report + 10% presentation).  Requirements are specified below.
(4)  Final exam (40%).  3-hour closed book with one page (A4 size) self-made help sheet.

Note:  There is visible risk of failing to pass the course.  To pass the course, the student must demonstrate substantial efforts in studying the subject to significantly improve his/her understanding of the concepts, theory and methods discussed in the course.

Project Requirements
Each student should accomplish a course project and present his or her findings in the class.  Although it is free for the students to choose whatever topics that are relevant to the course subject, the students are encouraged to discuss this with supervisors and try best to fit into the thesis framework.  The instructor will also be willing to be consulted.

A one-page project proposal should be made and submitted to the instructor for approval at the beginning of the second meeting of the class. The project presentation will be scheduled at the second last lecture and each student will have 15 minutes including QA.  Although Chinese is normally used in the presentation, the students are strongly encouraged to present their work in English.  The final project report is due July 10, 2011 (to be confirmed, subject to administrative deadline).

An example project subject:  An Optimal Probabilistic Design of Reinforced Concrete Beam Subject to Bending, Shear and Torsions. A column design subject to both moments and thrust will also work.   This project will requires you to first formulate the design to a stochastic optimization problem, and then you need to identify and characterize the key uncertain parameters and limit states that will affect the safety of the beam.  You also need to define the optimal criteria.  Finally, you need to apply optimization technique and reliability method to  find the solution.

Another example:  The Optimal maintenance strategy of a highway bridge.  This is a time-dependent reliability plus optimization problem.

One more example is to write an review article in a selected topic (e.g. code calibration, material strength modeling, quality assurance, wind load modeling, stochastic modeling of historical earthquake/tsunami/typhoon/thunderstorm records) with which you, your supervisor and/or I will agree.

Textbook
There is no textbook specified  for this course.  Lecture notes will be made available for downloading later.



* Lecture 1 (Introduction): Uncertainty and Risk, Interpretation of Probability, Modeling Issues, Reliability Analysis in Risk Management context, Decision Making under Uncertainty, Potential Application Areas (Reliability-Based Design/Optimization/Assessment, Risk/Safety Assessment of New Technologies (e.g., nuclear energy, innovative green energy, high-speed rail, high-voltage transmission line, genetically-modified food, and stem-cell technology), Reliability Testing and Growth, Sustainable Infrastructure Development, Policy Analysis, etc.)
Reading Materials (You must read the following articles before attending the class):

Apostolakis (1990) Concept of Probability in Safety Assessments of Technological.pdf

Kaplan_Garrick (1981) quantification of risk.pdf

Pate-Cornell (1996RESS) Uncertainties in risk analysis.pdf

Aven (2011) Alternative uncertainty representations.pdf

Der Kiureghiana_Ditlevsen (2009) aleatory vs epsitemic uncertainties.pdf

Oberkampf (2004) challenge problems on uncertainty modeling.pdf

Draper (1995) model uncertainty w discussions.pdf  (Skip this for the first time)

Freudenburg (1988) perceived vs real risk in PRA.pdf

Ang (2011) Life-cycle design of civil infrastructures.pdf (This is a poorly written paper by a big name!)

* Lecture 2 (Review of Probability): Probability Spaces, Bonferroni Bound (Inclusion-Exclusion Identity) and its applications to System Reliability, Total Probability and its Applications to Risk Analysis, Generating Function, Relation between Moments and Distributions (inverse problem in probability, maximum entropy theory), Moments and Distributions of Functions of Random Variables, Monte Carlo simulation, Sum of Random Variables (Convolutions and Central Limit Theorem), Extreme Value Theorem, Dependence Measures (correlations and copula), Rosenblatt and Nataf Transformation, Copula view of Nataf Transformation
Lecture Notes:
Reading Materials:

Leemis (1986) common univariate dists.pdf

Lebrun_Dutfoy (2009) Nataf transformation from the copula viewpoint.pdf

* Lecture 3 (Structural Reliability Methods) Formulation of Structural Reliability Problems, First-Order Reliability Methods (Cornell's definition, Hasofer-Lind's geometric interpretation, Rackwitz-Fiesller's algorithm), Equivalence of Tail Normalization to the Rosenblatt Transformation, Second-Order Reliability Methods, Descriptive vs. Normative Reliability Analysis (Calibration to observed failure records?)
Reading Materials:
Shinozuka (1983) Basic analysis of structural safety.pdf


* Lecture 4 (Reliability-Based Structural Design) Evolution of Structural Design Philosophies, Search for Safety Measure of Invariance, Reliability Calibration, LRFD, Comparison of Design Codes (Chinese Codes, ISO 2394, ASCE 7, NBCC and CHBDC), Load Combination, Design Life and its Implications, Dead Load and its impact on light-weight structure

Ellingwood (1994) prob-based codified design.pdf

Ellingwood (1996) Reliability-based condition assessment.pdf

* Lecture 5 (Probabilistic Failure Modeling) Failure rate modeling, Cumulative Damage Models, Point Processes, Applications to Fatigue and Corrosion.
Reading Materials
-Aalen, O. O., Gjessing, H. K. (2001) Understanding the shape of the hazard rate: a process point of view.  Statistical Science, 16(1), 1-13. (with comments)

Aalen_Gjessing.pdf

-Gavrilov, L. A., Gavrilova, N. S. (2001). The reliability theory of aging and longevity. Journal of Theoretical Biology, 213(4): 527-545. (An interesting paper showing the major difference between technical and biological systems.  A technical system can often be described by Weibull distribution with a power-law failure rate, whereas a biological system is better described by Gumbel distribution with a Gompertz/exponential law of failure rate.  The authors speculated that this difference can be accredited to the different degrees of redundancy.)

Gavrilov_Gavrilova (2001) The Reliability Theory of Aging and Longevity.pdf

* Lecture 6 (Statistical Methods of Reliability Data) Maximum Likelihood Method, Large-Sample Theory (Asymptotic Solutions) and Small-Sample Method (Bootstrap Simulation), Bayesian Updating and Markov Chain Monte Carlo simulation

* Lecture 7 (Time-Dependent Structural Reliability)  Formulations, First-passage problem, dynamic reliability, Fokker-Planck-Kolmogorov Equation and Solutions, Contemporary Development (Grigoriu's generalized Levy system)

vanNoortwijk (2004) two models for deterioration civil infrast.pdf

vanNoortwijk (2004) probabilistic models for deteriorating structures.. review a.pdf

* Lecture 8 (Maintenance Optimization and Life-Cycle Costing) Types of Maintenance, Economic Life vs. Design Life, Block Replacement with/without minimum Repairs, Age Replacement, Condition-Based Maintenance, Applications of Structural Health Monitoring (SHM) to Maintenance Optimization, Components of Life-Cycle Costs, Uncertainties of LCCs, Life-Cycle Optimization



日读经书三起，日看纲目数页。But where is your bible, where are your titles?

Journals
A detailed list of readings is provided below.  For structural engineering students, Structural Safety, Probabilistic Engineering Mechanics, Journal of Structural Engineering (ASCE), and Structural Dynamics and Earthquake Engineering are the major journals in which most of significant research articles are published.  For students whose research are more towards infrastructure management, Reliability Engineering and System Safety, IEEE Transactions on Reliability, and Journal of Infrastructure Systems (ASCE) should be well read.  Students who are interested in statistical aspects of reliability problems may find Lifetime Data Analysis very useful.



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Readings in Risk and Reliability for Engineers

Precaution
This reading list is by no means complete.  My intention of preparing the list was to help you identify the most suitable book for your study and research.  I also singled out some important references that you do not want to miss reading them.  In this sense, a professor is just a wire to books.


Bibliography of Uncertainty Modeling/Mathematics --- Appetizers
Uncertainty itself means confusion.  Therefore, there is no surprise that conflicting assertions pervade in uncertainty modeling and interpretation of results from risk analysis.  A little dip to historical development of the subject might help.  For this, "Against the Gods: the remarkable story of risk" by Bernstein (1996), Wiley, represents one of the best for leisure reading, whereas "The Emergence of Probability" by Hacking (2006), Cambridge, can be served as a good material for very serious readers, as the subtitle of the book -- a philosophical study of early ideas about probability induction and statistical inference -- has suggested.  For an introduction to mulitdisciplinary perspectives of the uncertainty and risk study, "Uncertainty and Risk: Multidisciplinary Perspective" edited by Bammer and Simthson (2008) can be referred to.  Taleb (2010)'s "The Black Swan: the Impact of the Highly Improbable", Random House, 2nd Ed, is another book that is very popular in north American MBA class.  This book points out the blind spots of human thinking when dealing with uncertainties.  Tsunami in Japan Tohoku earthquake (March 11, 2011) is a grave example of the black swan.

Probability will be exclusively used in this course as the tool of uncertainty modeling.  Fancy theories such as fuzzy sets or possibility theory, evidence theory, and granular sets are not discussed, although I could point to you a few references to start with if your supervisor is forcing your to "follow the suit".  If that is the case, I usually will persuade you and your supervisor to repent, as I am a very orthodox guy.  Nevertheless, I will sway back and forth between the frequentist and Bayesian, if you know what I mean.  Lindley (2006) "Understanding Uncertainty", Wiley, gives an excellent introduction to the Bayesian framework of uncertainty modeling.  

For students who work heavily on probabilistic modeling, the following two books are my recommendation.  The first book is a little old, but it seems never outdated.  The two volumes deal with discrete and continuous probabilities, respectively.  The second book is a good reference with numerical features included.

* Feller (1968,1971) An Introduction to Probability Theory and its Applications, Vols. 1 & 2,  Wiley.
* Tijms (2004) A First Course in Stochastic Models, Wiley.

For statistical inference, the following book is one of the best at the graduate level.  If you feel it too difficult to follow, go back to Kalbfleisch (1985).
* Casella and Berger (2001) Statistical Inference, Duxbury, 2nd Ed.

Monographs on Risk Analysis
* Haimes (2009) Risk Modeling, Assessment, and Management. Wiley, 3rd ed.
   A PhD of water resources, Prof. Haimes provides us a book representing one of those that are most relevant for civil engineering applications.  His recent job in transplanting the Input-Output model in economics into criticality analysis of infrastructure network was well received by the community of security of critical infrastructure.

* Bedford and Cooke (2001) Probabilistic Risk Analysis: Foundation and Methods, Cambridge.
   Cooke is famous in elicitation of expert opinions, which is discussed in Chapter 10.

* Aven (2008) Risk Analysis: Assessing Uncertainties beyond Expected Values and Probabilities. Wiley.
   A Norwegian scholar in risk analysis, Aven gives a very lucid presentation of the basic concepts of risk and risk analysis.  The book includes six examples of applications, covering civil engineering (road tunnel, offshore installation), system safety, financial risk analysis, and emergency preparedness.

* Klugman, Panjer and Willmot (2008) Loss Models: From Data to Decisions.  Wiley, 3rd ed.
   This actually is a textbook for actuarial sciences.  However, students from Disaster Prevention Engineering might find it useful.

Well, I wish you will not feel full already after completing the appetizers.  As a old man's wisdom, if you cannot finish the appetizers, you'd better skip them and just leave more space for the main courses.  The key, however, is that you need to know how much you can really eat.  Here are the main courses:

Monographs on Structural Reliability --- Juicy Beef
* Melchers (1996) Structural Reliability Analysis and Prediction, Wiley, 2nd Ed.
 One of the best books.  In comparison with Ditlevsen and Madsen (2005), Melchers put his feet deeper into the structural engineering ground.  However, there are quite a few major mistakes that you need to be careful.  Some of the discussions in time-dependent reliability are misleading at the best.  HNU Library (foreign references room, FR hereafter) has both editions.  Before leaving HNU, I made a photocopy of the book.  This is the only technical book I brought from China to Canada.  

* Madsen, Krenk and Lind (1986) Methods of Structural Safety.  Prentice Hall.
  HNU Library (FR) has this book. I might have left many scripts in the book when I studied at the library.  I apologize for this.  If you do not have time completing the whole book, you should at least read the first 7 pages, discussing the early development of structural reliability.  When I met Prof. Lind in 2006, I made a promise to him that I will continue on the Third, Fourth and even Fifth phases of the development.  I should dig out a photo and post it here.  I will do this later.

* Ditlevsen and Madsen (1996) STRUCTURAL RELIABILITY METHODS. Wiley.
  Prof. Ditlevsen maintains his own research website from which a PDF file of this book with revision can be downloaded.  He has been one of the major contributors to the community of Structural Reliability.

Monographs on Mathematical Reliability  --- Dry Beef
* Barlow and Proschan (1965) Mathematical Theory of Reliability, Wiley.
   The classics of mathematical reliability.  HNU Library has the translation edition. A key concept in the classical mathematical reliability is the failure rate family.  An important tool used is the total positivity that is invented by Karlin in 1960s.  

* Singpurwalla (2006) Reliability and Risk: a Bayesian Perspective, Wiley.
   Singpurwalla can be said to be the modern representative of the "Seattle School" of reliability after Barlow.  As the title suggests, this book take a Bayesian perspective. To be precise, he takes de Finetti's subjective Bayesian framework.  The first three chapters are the theoretical foundation.  This book also summarizes the work in dynamic survival analysis, for which Singpurwalla (1996) is an extremely important review paper.

Monographs on System Reliability --- Stewed Beef with Potatoes
* Hoyland and Rausand (2004) System Reliability Theory: Models and Statistical Methods, Wiley, 2nd Ed.
   A very good introduction text for system reliability.  The only drawback is that it is not deep enough.

* Ericson II (2005) Hazard Analysis Techniques for System Safety. Wiley.
   This book is written by an industrial expert.  It mainly deals with the hazard analysis for technical systems.  Some contemporary techniques such as Petri net analysis, common cause failure analysis, and management oversight risk tree analysis are introduced.

Monographs on Statistical Reliability --- A Soup?
* Lawless (2004) Statistical Models and Methods for Lifetime Data, Wiley, 2nd Ed.
   If my memory works well, the first edition of this book (1982?) was translated into Chinese and the HNU library have one copy of the Chinese edition.  This book is very sharp in statistical concepts and likelihood method is almost exclusively used.  Most of examples are from biostatistical applications.  Prof. Lawless served as the editor of Lifetime Data Analysis.  I got only 85 from his statistical course: Event History Data Analysis, in my PhD program.  If you need a little more makeup in statistics and maximum likelihood method in particular, you are referred to Kalbfleisch (1985) Probability and Statistical Inference, Vol 2: Statistical Inference. Springer.  

* Meeker and Escobar (1998) Statistical Methods for Reliability Data, Wiley.
   This is one of the best book in statistical methods for reliability data.  The authors' two-stage nonlinear method is nowadays  widely used in industry.  


------------ // to be edited later// -------------------------
Research Articles --- Some Dessert
Updated 03/22/2011 8:21pm EST

Statistical Seismology
Owing to the Japan earthquake on March 11, 2011, the subject of seismic hazard assessment suddenly caught my interest.  My question here is: can we unify the modeling strategies for failures? For civil and mechanical materials,there are many different types of failure mechanisms, for example, fracture, fatigue, corrosion, and creep. Earthquake is a kind of fracture failure; the only difference might be the large scale and hence the spatial distribution matters a whole lot.  

Statistical seismology deals with the statistical modeling of earthquake records, with attempt to reveal the magnitude-location-time relationship. Although the model itself will not tell exactly when an earthquake will occur and how large it will be, it will definitely help the seismic hazard assessment.  A good reference is Daley and Vere-Jones (2003, 2007).  Vere-Jones from New Zealand is one of the pioneers of statistical seismology.

Vere-Jones (1970) Statistical Models for earthquake occurrence.pdf

Decision Making under Uncertainty
Expected Utility Theory -- a Normative Model by D. Bernoulli, von Neumann, Savage
Cumulative Prospect Theory -- a Descriptive Model by Kahneman and Tversky