Fall 1999

CE 810 - Reliability-Based Design in Civil Engineering

Text: Ayyub, B. M., and McCuen, R. H. (1997). Probability, statistics, & reliability for engineers. CRC Press, Boca Raton, Florida.
References:
  1. Smith, G. N. (1986). Probability and statistics in civil engineering: An introduction. Nichols Publishing Co., New York.
  2. Benjamin, J. R., and Cornell, C. A. (1970). Probability, statistics, and decision for civil engineers. McGraw-Hill, New York.
  3. Harr, M. E. (1987). Reliability-based design in civil engineering. McGraw-Hill, New York.
  4. Madsen, H. O., Krenk, S., and Lind, N. C. (1986). Methods of structural safety. Prentice-Hall, Englewood Cliffs, New Jersey.
  5. Ang, A. S., and Tang, W. H. (1984). Probability concepts in engineering planning and design. Volumes 1 & 2, Wiley, New York.
Prerequisite: Basic statistics and probability (STT 351 or equivalent). Elementary matrix algebra.
Instructor: Ron Harichandran. 3546 Engineering Building. Phone: 355-5107.
E-Mail: harichan@cee.msu.edu; Tel: 355-5107; Fax: 353-6883.
Office Hours: Monday - 1:50 to 2:40 p.m.; Wednesday ­ 3:00 to 3:50 p.m.; Friday - 10:20 to 11:10 a.m.
Class Web Site: www.egr.msu.edu/classes/ce810

Course Goals and Objectives

You will learn to use elements of probability and statistics in a civil engineering context. More specifically, you will:

Performance Evaluation and Expectations

Your performance in the course will be evaluated based on the following components:

Homework, exams and individual term projects must be done independently. You may consult others regarding homework and term projects, but must complete the work by yourself. Consultations are not permitted for exams. Evidence of plagiarism or cheating will result in a score of 0.0 for all those involved.

Two measures are used to assign grades. The first is your overall raw percentage score which measures your absolute performance, and the second is an overall standardized T-score which measures your relative performance in the class. T-scores are calculated for each exam and homework using

and the overall T-score is computed by weighting each individual T-score by the percentage weight for each exam and homework. For any given exam or homework, the class average translates to a T-score of 50.

You are assigned the more favorable grade based on these two measures using the cut-off scores shown in Table 1, with Gm denoting the grade assigned to the class average. The value of Gm is adjusted to reflect the class composition (e.g., a class of good students vs. a class of poor students), and the level of difficulty of exams. Typically, in a class of good students with a raw class average of about 80%, Gm = 3.0.

The T-score more fairly accounts for somewhat erratic performances. A student who does poorly in one exam but makes up for it by performing progressively better in the other exams would receive a more favorable grade based on the T-scores than on the raw scores. For example, consider the data in Table 2 in which all scores are out of 100. Student A did very poorly in the first exam, scored slightly above average in the second exam, and well above average in the third exam. Student B on the other hand, scored slightly above average in the first two exams, but below average in the third exam. Based on the raw scores, Student A would receive a grade of 2.0 while Student B would receive a 2.5. However, based on the T-scores, with Gm = 3.0, both students would receive a grade of 2.5. In fact, based on the T-scores, Student A's overall performance would be judged to be a little better than Student B's.

Miscellaneous Issues

Providing Feedback: Continuous feedback on the course, especially on how it could be improved, is encouraged. Feedback may be provided with complete anonymity using the Web-based form at: www.egr.msu.edu/cee/forms/feedbk.html.

Dropping this Course: The last day to drop this course with a 100% refund and no grade reported is Sept. 23. The last day to drop this course with no refund and no grade reported is Oct. 19. If you do drop the course you should immediately make a copy of your amended schedule to verify that this was implemented by the computer system.

Religious Observance: If you wish to be absent from class to observe a religious holiday, make arrangements in advance with the instructor.

Missing Class to Participate in a Required Activity: To be excused from this class to participate in a required activity for another course or a university-sanctioned event, you must provide the instructor with adequate advanced notice and a written authorization from the faculty member of the other course or from a university administrator.

Course Topics

Topic

References
Basic probability theory Text: Sec. 2.4­2.7, 3.1­3.3, Chap. 9. Ref. 1: Chap. 1. Ref. 2: Sec. 2.1. Ref. 3: Sec. 1.1­1.3, 3.8.
Review of elementary matrix algebra Handout. Ref. 1: Chap. 7. Ref. 3: Appendix A.
Random variables and vectors: Distributions, moments, transformations Text: Sec. 3.4­3.5, 4.1­4.3. Ref. 1: Chap. 2. Ref. 2: Sec. 2.2­2.4.3. Ref. 3: Sec. 1.4, 1.5, 1.7, 1.8, 1.10, 2.7.
Moments of non-linear functions: FOSM analysis and the point estimate method Text: Sec. 4.3.3. Ref. 2: Sec. 2.4.4. Ref. 3: 4.5­4.10.
Common probability distributions Text: Sec. 3.6­3.8. Ref. 1: Chap. 3 & 6. Ref. 2: Sec. 3.1­3.6. Ref. 3: Sec. 1.6, 1.9, 1.11, 2.1­2.3.
Simulation of random variables and vectors Text: Chap. 7
Level II reliability analysis: Reliability indices, first order second moment (FOSM) method, invariance Text: Sec. 8.1­8.3.1. Ref. 3: Sec. 3.1­3.4, 3.10, 4.5­4.7. Ref. 4: Sec. 4.1­4.3.
Hasofer-Lind reliability index and applications in structural and geotechnical engineering Text: Sec. 8.3.2. Ref. 1: Chap. 4 and 5. Ref. 4: Sec. 4.4.
Use of reliability analysis in development of design specifications Handout. Ref. 4: Chap. 3 and 6.