Forensic assessment of a bridge downfall using Bayesian networks

Bayesian networks proved to be a useful tool in many technical fields as well as in forensic sciences. The present paper proposes a novel application of Bayesian networks in forensic engineering, focusing on the analysis of technical causes of a catastrophic bridge downfall. During repair a road bridge over important railway lines suddenly slipped down from temporary supports. Incidentally at the same time an intercity train approached the location and crashed into the collapsed bridge at a high speed. The accident resulted in great societal and economic consequences. Forensic investigation concerning causes of the bridge collapse was complicated due to the additional damage caused by the train. Moreover, the remaining structural elements of the collapsed bridge and temporary supports were shortly after the accident removed to renew railway traffic. Background materials of the investigation and additional detailed structural analyses did not reveal any convincing evidence of the initiation cause. Critical consideration of all possible causes including aerodynamic effects supplemented by a causal (Bayesian) network finally resulted in identification of the most significant causes including insufficient foundation and overall stiffness of temporary supports.

► Novel application of Bayesian networks in forensic engineering is proposed.
► Quantitative and qualitative information is considered together.
► A complex forensic investigation is divided into smaller sub-tasks.
► Technique facilitates identification of the most significant causes of collapse.