William Bulleit's fPET-2010 presentation

1. William M. Bulleit Michigan Tech Uncertainty in the Design of Non-prototypical Engineered Systems

2. Concept Design Prototype – with feedback to design Production QA & Testing (Element 14, Journal 1) Product Development Cycle Electronic Products

3. Concept Design Construction – feedback to design mostly changes, not necessarily improvements Non-prototypical Systems

4. Aleatory Of or related to chance Uncertainty generally not reduced by increased knowledge Flipping a coin - frequentist or subjective Epistemic Of or related to lack of knowledge Uncertainty generally reduced by increased knowledge Flipping a coin - physics Types of Uncertainty

5. Time – past and future Statistical limits – never enough data Randomness – nothing is one number Human error – screw ups happen Sources of Uncertainty - Basic

6. Use changes Predict future loads based on past loads Deterioration Increased time causes increased probability of extreme load Time

7. Only can take so many samples of anything We only have about a 100 years of load data Never sure if the sample represents the population Statistical Limits

8. Seismic ground motions are random processes Wind pressure is a random process Cross sectional dimensions vary Live load varies spatially Randomness

9. “To err is human, to anticipate is design.” Anonymous “Good judgment comes from experience, and experience comes from bad judgment.” Attributed to Mark Twain Design

10. Modeling – simplifications or misconceptions Contingency – it does not exist Inconsistent crudeness – one refined, one not… Code complexity – what to choose? Sources of Uncertainty - Design

11. Occupancy live load is assumed to be uniformly distributed Wind load is assumed to be static Load variability is assumed to be representative of load effect variability Strain distribution assumed to be linear Modeling

12. “I am persuaded that many more failures of foundations or earth structures occur because a potential problem has been overlooked than because the problem has been recognized but incorrectly or imprecisely solved.” Ralph B. Peck Human Error/Modeling Error

13. Tacoma Narrows

14. Contingent: dependent on something not yet certain. In engineering design contingency refers to the need to visualize a system and perform analysis and design on the envisioned system before it can be built. (Scientists typically analyze existing systems.) [H. Simon, The Sciences of the Artificial] Contingency increases uncertainty Contingency

15. Engineers’ designs are not consistently crude. Some portions of a code are well researched and based on engineering science, and some have been in the code for decades (EFW for concrete T-beams). Inconsistent Crudeness

16. “A heuristic is anything that provides a plausible aid or direction in the solution of a problem but is in the final analysis unjustified, incapable of justification, and potentially fallible.” B. V. Koen, Discussion of the Method Heuristic

17. We use them to help solve problems and perform designs that would otherwise be intractable or too expensive to perform. Ex. 1: 0.2% offset method gives the yield stress of the steel. Ex. 2: The dynamics of the wind load can be ignored in the design of buildings. Ex. 3: Occupancy live load is uniformly distributed. Heuristics

18. Use characteristic values (e.g., 5th percentile) Use design provisions that have stood the test of time, but update as necessary (possibly due to failures) Check designs and inspect construction (Quality control) Make appropriately conservative assumptions in analysis (What is appropriate?) Dealing with Uncertainty

19. Check complex analyses with simpler methods where possible. Use your own experience. Recognize that heuristics are used in all engineering design and think about their limits Dealing with Uncertainty (Cont.)

20. “The person who insists on seeing with perfect clearness before deciding, never decides.” Henri F. Amiel “Choosing not to decide is a decision.” Anonymous Decisions

21. Reflection by the engineer on a design may be a way to enhance future similar designs Reflection may also work as a type of feedback (e.g., Citicorp Building, 1978, William Le Messurier) Reflection

22. Prototypical versus non-prototypical systems are distinguished by the amount and timing of feedback Design of prototypical systems involves relatively rapid feedback during design and more feedback during operation (e.g., automobiles, computers, light bulbs) Non-prototypical systems receive essentially no feedback during design, and only slow feedback during their life (e.g., Tacoma Narrows, Deepwater Horizon) Time and Again

23. Low probability – high consequence events Black swan events Human/societal limitations Conclusion

24. Questions?