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The objective of this study is to create and test an integrated framework for assessment of vulnerability to uncertainty in complex projects. In the proposed framework, construction projects are conceptualized as metanetworks composed of different nodes (i.e., human agents, information, resources, and tasks) and links. The effects of uncertain events are translated into perturbations in the nodes and links of project metanetworks. These uncertainty-induced perturbations are reflected as transformations in a project's topological structure, and thus negatively affect the efficiency of the project's metanetwork. The extent of the variation in the efficiency of a project's metanetwork is used to determine the extent of vulnerability to uncertainty. The application of the proposed framework is shown in an illustrative case study related to a tunneling project. In the case study, various scenarios related to different uncertain events were simulated through the use of dynamic network analysis and Monte Carlo simulation. The illustrative case study demonstrated the application of the proposed framework for predictive assessment and proactive mitigation of vulnerability to uncertainty based on evaluation of dynamic interactions between various entities and networks in construction projects. The proposed framework integrates elements from complex systems, dynamic network analysis, and Monte Carlo simulation approaches, and it provides a novel computational framework for ex-ante evaluation of vulnerability to uncertainty in civil engineering projects. [ABSTRACT FROM AUTHOR]