Esd 342 Network Representations Of Complex Engineering Systems Spring 2010

Modern engineering systems—from power grids and supply chains to communication networks—are increasingly complex, interconnected, and difficult to manage. Understanding these systems requires moving beyond isolated components and learning how to model their structural relationships. This course introduces you to the core principles of network science applied directly to engineering architecture, helping you make sense of complexity through structured, analytical models. You will start with the absolute fundamentals, learning how to translate physical and logical systems into mathematical graph representations and design structure matrices (DSM). You will then progress to analyzing network topology, identifying critical vulnerabilities, and evaluating system robustness. To ensure your skills remain highly relevant, you will also explore modern data-driven network analysis patterns, including basic computational modeling and the integration of open-source network analysis libraries. What you'll learn: - Understand the foundational terminology of complex systems and network representations. - Create structural models of engineering systems using graph theory and design structure matrices. - Analyze network metrics such as degree distribution, centrality, and clustering coefficients to identify critical system nodes. - Evaluate system vulnerability, cascade failures, and structural robustness under different operational scenarios. - Apply network-based frameworks to real-world engineering case studies, including infrastructure and organizational flows. - Explore modern computational tools and data formats used to store and process large-scale network data. This text-based course is designed to guide you step-by-step, starting with essential definitions and theoretical frameworks before moving into practical modeling methodologies and analytical applications. This course is designed for engineering professionals, system architects, and technical analysts who are new to network science and want to build a solid, structured foundation in system complexity. No advanced mathematical background or prior network modeling experience is required. Master the structural dynamics of complex networks and start optimizing your engineering systems today.