Systems Modeling Approach for Sustainable Infrastructure: Fid-Bau Portal

Systems Modeling Approach for Sustainable Infrastructure

El-Adaway, Islam

Management of our infrastructure systems is not only associated with engineering and economic constraints; it is intricately tied to public policy and institutional control considerations. As such, using simulation models that incorporate aspects of population movements, infrastructure assessment, living conditions, and health data with spatial data modeling, and collectively relate them to the different sustainability indicators could be an ideal tool for providing better information for the sustainability of our infrastructure systems. This paper presents a systems modeling approach to assess the social, environmental, and economic changes within community host systems as a result of civil infrastructure projects, and provide better information to associated stakeholders. In previous research, the author developed three novel benchmarks (i.e. nature, work, and flow) to holistically analyze our infrastructure systems from a sustainability perspective. The "work benchmark" defines the behavioral relationships between the construction processes and the associated stakeholders; the "nature benchmark" studies the interactions between the construction processes and the surrounding ecosystems, and the "flow benchmark" will analyze the overall system change. In this paper, the author shows how the "flow benchmark" will be used to demonstrate technological integration between macro-level system dynamics modeling, micro-level agent-based simulation, and multi-objective optimization to measure the overall system change. Integrating these techniques in a single framework will combine the strengths of the three methodologies and mitigate their deficiencies on stand-alone basis. This aggregation will evaluate societal vulnerability through analyzing which sustainability indicators have the most significant correlation to the affected infrastructure systems. This will create a knowledge base of simulated dataset to understand the micro-level behaviors of community stakeholders in relation to the societal macro-level sustainability outcomes. The envisaged system will analyze qualitatively and quantitatively the various sustainability indicators to help attain Pareto optimal resource balance in our communities. When successful, this innovative systems framework will provide life-cycle analysis method for estimating the probability distributions of financial cost, loss of service and societal costs, and environmental impacts. This will answer important management questions such as "what should we do?", "what if we do?', and "what are the expected societal consequences?", which will promote informed management and decision making.