Verified Uncertainty Quantification for Infrastructure Safety
Roger Paredes Leonardo Dueñas-Osorio
Dept. of Civil and Environmental Engineering, Rice University
Spring 2022 Virtual Semi-Annual Meeting
April 29, 2022
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
System-level Uncertainty Quantification
Quantitative support for decision analysis
Data and models
Community goals
Uncertainty Quantification
Decision Making
State-of-the-art is largely heuristic
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
System-level Uncertainty Quantification
State-of-the-practice techniques to enable computation
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
Verifying Heuristic Uncertainty Quantification
Example: Failure probability p
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
Verifying Heuristic Uncertainty Quantification
Heuristics in engineering
Heuristic | Solution Verification |
Restoration Strategy (Optimization) | Objective function |
Failure Probability (UQ) | Exhaustive simulation / enumeration |
Polynomial-time evaluation
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
Verifying Heuristic Uncertainty Quantification
Heuristics in engineering
Heuristic | Solution Verification |
Restoration Strategy (Optimization) | Objective function |
Failure Probability (UQ) | Exhaustive simulation / enumeration |
System Failure Probability
Failure modes A & B
NP-hard problem
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
System-level Uncertainty Quantification
Data and models
Community goals
Uncertainty Quantification
Decision Making
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
System-level Uncertainty Quantification
Data and models
Community goals
Uncertainty Quantification
Decision Making
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
Verified Uncertainty Quantification
Algorithms for system-level UQ today (mainly heuristic, e.g., IN-CORE)
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
Exact Uncertainty Quantification Possible?
How tree-like is real infrastructure?
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
Exact Uncertainty Quantification: Seaside
Electricity Service Failure Probability
Paredes, R., Dueñas‐Osorio, L. & Hernandez‐Fajardo, I. Decomposition algorithms for system reliability estimation with applications to interdependent lifeline networks. Earthq. Eng. Struct. Dyn. 47, 2581–2600 (2018).
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/
Principled Sampling-based UQ: Seaside
Electricity Service Failure Probability
Paredes, R., Dueñas-Osorio, L., Meel, K. S. & Vardi, M. Y. Principled network reliability approximation: A counting-based approach. Reliab. Eng. Syst. Saf. 191, 106472 (2019).
Stopping-rule with (ε,δ)-approximation guarantees
NIST Center for Risk-Based Community Resilience Planning
roger.paredes@rice.edu | https://paredesroger.github.io/