Bridge Management Based on Bayesian Decision Analysis with Sustainability Considerations

With increasing climate-induced stresses and ageing infrastructure worldwide, integrating sustainability into infrastructure management is essential. Structural Health Monitoring (SHM) systems provide valuable insights for assessing and maintaining the safety and integrity of ageing structures, but their implementation entails significant costs. Resources allocated to SHM could alternatively support other interventions, such as retrofitting, demolition, or bridge replacement, each with distinct implications for immediate costs, structural safety, and long-term sustainability. This paper presents a Bayesian decision analysis framework for optimizing management decisions in the context of sustainability. The framework quantifies the expected costs of various management actions, including SHM adoption, by balancing the potential benefits of monitoring data against implementation costs. It is applied to a case study on bridge management during a flood event, where scour threatens bridge foundations. The results highlight the potential of Bayesian analysis in supporting rational decision-making while integrating environmental sustainability considerations into infrastructure management.