Environmental contours and optimal design

TL;DR

This paper explores how classical and buffered environmental contours relate to risk measures like value-at-risk and conditional value-at-risk, and how these connections can optimize structural design to minimize failure risk.

Contribution

It establishes theoretical links between environmental contours and risk measures, providing new representations for optimal design problems using these contours.

Findings

Classical contours relate to value-at-risk in design optimization.

Buffered contours connect to conditional value-at-risk for risk-sensitive design.

Derived conditions for optimal structural design based on environmental contours.

Abstract

Classical environmental contours are used in structural design in order to obtain upper bounds on the failure probabilities of a large class of designs. Buffered environmental contours serve the same purpose, but with respect to the so-called buffered failure probability. In contrast to classical environmental contours, buffered environmental contours do not just take into account failure vs. functioning, but also to which extent the system is failing. This is important to take into account whenever the consequences of failure are relevant. For instance, if we consider a power network, it is important to know not just that the power supply is failed, but how many consumers are affected by the failure. In this paper, we study the connections between environmental contours, both classical and buffered, and optimal structural design. We connect the classical environmental contours to the risk measure value-at-risk. Similarly, the buffered environmental contours are naturally connected to the convex risk measure conditional value-at-risk. We study the problem of minimizing the risk of the cost of building a particular design. This problem is studied both for value-at-risk and conditional-value-at-risk. By using the connection between value-at-risk and the classical environmental contours, we derive a representation of the design optimization problem expressed via the environmental contour. A similar representation is derived by using the connection between conditional value-at-risk and the buffered environmental contour. From these representations, we derive a sufficient condition which must hold for an optimal design. This is done both in the classical and the buffered case. Finally, we apply these results to solve a design optimization problem from structural reliability.