International audienceThis paper presents an approach based on network theory to deal with risk interactions in large engineering projects. Indeed, such projects are exposed to numerous and interdependent risks of various nature, which makes their management more difficult. In this paper, a topological analysis based on network theory is presented, which aims at identifying key elements in the structure of interrelated risks potentially affecting a large engineering project. This analysis serves as a powerful complement to classical project risk analysis. Its originality lies in the application of some network theory indicators to the project risk management field. The construction of the risk network requires the involvement of the project manager and other team members assigned to the risk management process. Its interpretation improves their understanding of risks and their potential interactions. The outcomes of the analysis provide a support for decision-making regarding project risk management. An example of application to a real large engineering project is presented. The conclusion is that some new insights can be found about risks, about their interactions and about the global potential behavior of the project. 1. Introduction Projects are usually complex and risky. They require the timely accomplishment of a number of activities, carried out by a number of human and material resources. Unexpected conditions or planning errors may lead to failures which can undermine the successful realization of the project on numerous parameters, like time, cost, scope, quality, safety, security, health, and environment. We refer to such events as project risks, when they are identified, analyzed and treated before they occur. Within the same project, the existence of interrelated risks involves that the occurrence of one risk may trigger one or more other risks with potential propagation phenomena like reaction chains, amplification chains or loops. In this sense, in this paper we talk of risk interdependency between two risks. A consequence of a risk is then triggering of another risk and not the direct impact of the risk itself (e.g. on time, scope or cost), which of course exists but is not the focus here. The consequence of this complexity is a lack of capacity to anticipate and control the behavior of the project. Large engineering projects are facing a growing complexity, in both their structure and context due to the involvement of numerous, diverse and strongly interrelated elements [1-3]. This has sparked research works on the concept of complexity, under two main scientific approaches [4]. The first one, usually known as the field of descriptive complexity, considers complexity as an intrinsic property of a system. For example, Baccarini in [1] considers project complexity through the concepts of technological complexity and organizational complexity. He regards them as the core components of project complexity which he tries t
