CEE 251L
Uncertainty, Design, and Optimization
Henri P. Gavin
Description from DukeHub
Principles of design as a creative and iterative process involving problem statements, incomplete information, conservative assumptions, constraining regulations, and uncertain operating environments. Parameterization of costs and constraints and formulation of constrained optimization problems. Analytical and numerical solutions to constrained optimization problems. Axioms of probability, probability distributions, and Monte Carlo simulation. Evaluation of design solutions via sensitivity and risk analysis. Application to design problems in structural, environmental, and electrical engineering.
Skills
- data and statisticsdescription: "probability" and 1 more
- designdescription: "design" and 2 more
- lab workhas a lab component
AI-resilient: 2 of 5
- Yes: Physical, lab or field work · "laboratory"
- No: Live work with people
- Yes: Judgment someone is accountable for · "risk"
- No: A craft you practice with your hands or body
- No: Small, in-person format
The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works
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