Giordano Emrys Scarponi

Chapter 7 – Reactive and Proactive Approaches: Tutorials and Example

Bayesian inference-based dynamic risk assessment (BIDRA) and the risk barometer represent two different approaches that may be adopted for dynamic evaluation of accident frequency. BIDRA is a methodology for reactive risk assessment based on Bayesian inference, whereas the risk barometer is based on real-time indicator monitoring aiming to support proactive assessment of risk. This chapter illustrates two tutorials for the application of the BIDRA and risk barometer techniques. Moreover, application to the same representative case is performed by simulating the inputs for the methodologies: past near misses and accidents for BIDRA, and technical, operational, and organizational indicator trends for the risk barometer. This example aims to highlight similarities and differences and provides support for the selection of methods.

A Lumped Model for the Assessment of the Thermal and Mechanical Response of Lng Tanks Exposed to Fire

Fires may impact on liquefied natural gas (LNG) process and storage units causing severe damages and potential accident escalation. In the present work, a lumped model able to predict the thermal response of LNG tanks exposed to fire is presented. The model is based on a thermal nodes approach, solving heat and material balances on the equipment exposed to fire, contemplating boiling regime phenomena, heat-up and pressure build up. The model allowed obtaining key indications for the evaluation of the vessel resistance during fire exposure. The model was applied to reproduce the accident scenario occurred at Tivissa (Spain) in 2002 and applied to an industrial case study.