Optimal monitoring location for risk tracking of geotechnical systems: theory and application to tunneling excavation risks

TL;DR

This paper develops a computational framework to identify optimal monitoring locations in geotechnical systems, enhancing risk assessment accuracy for tunneling-induced settlement damage using a novel sensitivity metric.

Contribution

It introduces a new metric called sensitivity of information (SOI) for optimal monitoring location selection, improving reliability updating in geotechnical risk management.

Findings

The framework effectively identifies monitoring locations that maximize reliability updates.

Application to tunneling risks demonstrates computational efficiency and practical relevance.

The method enhances early detection and risk mitigation in underground infrastructure.

Abstract

The maturity of structural health monitoring technology brings ever-increasing opportunities for geotechnical structures and underground infrastructure systems to track the risk of structural failure, such as settlement-induced building damage, based on the monitored data. Reliability updating techniques can offer solutions to estimate the probability of failing to meet a prescribed objective using various types of information that are inclusive of equality and inequality. However, the update in reliability can be highly sensitive to monitoring location. Therefore, there may exist optimal locations in a system for monitoring that yield the maximum value for reliability updating. This paper proposes a computational framework for optimal monitoring location based on an innovative metric called sensitivity of information (SOI) that quantifies the relative change in unconditional and conditional reliability indexes. A state-of-the-practice case of risks posed by tunneling-induced settlement to buildings is explored in-depth to demonstrate and evaluate the computational efficiency of the proposed framework.