Industrial emergency planning modeling: a first step toward a robustness analysis tool.

The purpose of this paper is to present a model-based approach to the analysis of the robustness of industrial emergency plans, established by the European Union SEVESO II Directive. Robustness is defined in terms of the capacity of the mechanism to respond to deteriorated conditions. Analysis of emergency plans has been so far based mainly upon lessons learned from past major accidents or exercises, which do not allow for an integral analysis of the response mechanism. The proposed methodology is based upon a systemic, hierarchical and generic model of an internal or external industrial emergency plan, using the FIS modeling approach. The process generally found within an industrial emergency plan is identified through the model. Potential failures are estimated through an a priori analysis of the plan model and an a posteriori analysis of lessons learned from exercises and past accidents. Assessment of the plan's functions is carried out via assessment checklists, structured via the systemic model for each of the plan's process. This approach can hence be used as a toolbox both for the assessment of existing plans and the development of industrial emergency plans.

Data flow modeling for batch and hybrid processes.

A modeling approach of complex systems is presented. The goal is to define a modular and noncausal representation able to describe hybrid dynamics and to generate automatically the models corresponding to the different configurations of the real system. These models can then be used to simulate process evolution. In this paper we define the structure of the basic model blocks and the interactions of these blocks through different kinds of signals.