Download - Non-prototypical Engineered Systems
William M. Bulleit
Michigan Tech
Uncertainty in the Design of Non-prototypical Engineered Systems
ConceptDesignPrototype – with feedback to designProductionQA & Testing
(Element 14, Journal 1)
Product Development Cycle Electronic Products
ConceptDesignConstruction – feedback to design mostly
changes, not necessarily improvements
Non-prototypical Systems
Aleatory Of or related to chanceUncertainty generally not reduced by
increased knowledgeFlipping a coin - frequentist or subjective
EpistemicOf or related to lack of knowledgeUncertainty generally reduced by increased
knowledgeFlipping a coin - physics
Types of Uncertainty
Time – past and futureStatistical limits – never enough dataRandomness – nothing is one numberHuman error – screw ups happen
Sources of Uncertainty - Basic
Use changesPredict future loads based on past loadsDeteriorationIncreased time causes increased probability
of extreme load
Time
Only can take so many samples of anythingWe only have about a 100 years of load dataNever sure if the sample represents the
population
Statistical Limits
Seismic ground motions are random processes
Wind pressure is a random processCross sectional dimensions varyLive load varies spatially
Randomness
“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
Modeling – simplifications or misconceptionsContingency – it does not existInconsistent crudeness – one refined, one
not…Code complexity – what to choose?
Sources of Uncertainty - Design
Occupancy live load is assumed to be uniformly distributed
Wind load is assumed to be staticLoad variability is assumed to be
representative of load effect variabilityStrain distribution assumed to be linear
Modeling
“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
Tacoma Narrows
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
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
“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
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
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
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.)
“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
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
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
Low probability – high consequence eventsBlack swan eventsHuman/societal limitations
Conclusion
Questions?