Dynamic Simulation of Critical Urban Infrastructure for Defense-Oriented Resilience Planning Using AI

Urban infrastructure is under attack. It’s facing mounting risks from both physical and cyber-physical threats. These threats include natural disasters, terrorist attacks, and cascading system failures. This paper presents a multidisciplinary simulation and decision-support framework: Dynamic Simulation of Critical Urban Infrastructure for Defense-Oriented Resilience Planning Using AI (DSCUI-DORP-AI). This publication is Part I: Foundations and Frameworks for AI-Enhanced Urban Infrastructure Resilience, the first in a three-part research series. Part I establishes the theoretical foundation and system architecture for integrating mechanical system dynamics, artificial intelligence (AI), and urban network modeling. It introduces key concepts that are essential for understanding modern infrastructure: infrastructure interdependency, resilience metrics, and modular simulation design. The framework is designed to facilitate real-time response planning and long-term risk reduction in defense-sensitive urban environments. The upcoming Part II: Multibody Dynamic Modeling of Urban Infrastructure Using the Rui Method will detail the application of the Transfer Matrix Method for efficient simulation of structural behavior under extreme loads. Part III: AI-Driven Damage Prediction and Optimization of Urban Resilience Strategies will present the AI and optimization layer. This layer will enable failure prediction and scenario-based planning. This comprehensive suite of tools is designed to meet the needs of engineers, planners, and policymakers seeking to create smart, secure, and resilient urban systems.