#Staruml sysytem sequence diagram software#

It is composed of one part relating to the system ability to resist the feared event and another part relative to its ability to be back on its nominal state after the feared event. The vulnerability is assessed by a simulation-based approach. There are two types of relationships: the one first is functional (dependence), while the second one is dysfunctional (influence). We have thus proposed an approach to model interdependence compatible with the graph theory. relationships between components of the same or different networks - are a determining factor for any vulnerability model. In a multi network analysis environment, interdependences, i.e. A literature review will allow us to identify the graph model which best suits the context of the thesis. In order to achieve this, we will adopt graph theory representation. The proper vulnerability analysis is based on the analysis objects modelling. The first one deals with the vulnerability assessment, while the second one focuses on the decision aiding process to be implemented for the assessed vulnerability management. The scientific approach is divided into two complementary parts. The aim is to model the vulnerability to take efficient decisions. It starts from the observation that infrastructure such as water supply or power grid has significant influence on natural disasters’ indirect consequences. This thesis deals with infrastructure network vulnerability analysis in the natural disaster context. This paper illustrates how each of these cases has been realized, explains how this work can be used to advance different aspects of crisis management preparedness and discusses if and why learning in virtual worlds can be more effective than from real world events. Application prototypes cover different risk (floods, snowstorms, earthquakes, forest fires, accidental pollutions, mass accidents) and illustrate how the CRISMA framework can be used in a relatively simple but integrated manner to develop fully fledged decision support applications. CRISMA targeted use cases in the preparatory phase of crisis management: short and long-term planning, desktop training and assessment in field trainings.

#Staruml sysytem sequence diagram software#

The EU FP7 project CRISMA (– “Modelling crisis management for improved action and preparedness” has developed a methodology and software framework for simulation-based decision support systems.

The best available alternative is learning by doing in a simulated crisis situation or during an exercise. Due to rarity of such events, many crisis managers, regional planers and other stakeholders have no first-hand experience in handling them. 'Learning by doing' to improve resilience and planning is difficult to do, especially for low-probability/high-impact events and for multi-hazards with cascading effects.

Success of crisis management largely depends on: (1) inherent resilience of the society (2) preparedness level of the first responders and (3) right 'gut feeling' of crisis managers. This paper provides foundation to go towards a decision aiding process. The analysis might lead to decisions to enhance weak points. Vulnerability analysis is not end in itself. Parameters static and dynamic attributes are identified. Hence any analysis might begin by parameters identification. It depends on the system robustness and resilience. We found out that vulnerability is multi-views. Inherent vulnerability assessment constraints are also presented. The approach is based on views from infrastructure initial and final states. We provide vulnerability assessment methodology and formula. Our method includes territory specifics, flow circulation, influence of mitigation and aggravation factors, feared event evaluation. The way of including environmental relevant parameters is presented. Through a case study, a methodology is presented. This paper deals with robustness and resilience assessment of such systems under natural disaster. A failure in a natural disaster context could lead to a crisis situation. Infrastructure network failure such as power grid, gas and telecommunication systems might perturb societies well-functioning.