Development of a Custom Framework for Assessing and Calculating Physical Infrastructure Resilience Score

Community resilience can be defined as a community's capability to proactively anticipate, absorb, recover from, and adapt to actual or potential adverse events in a timely and efficient manner. This encompasses the restoration and enhancement of fundamental functions and structures. One of the most important dimensions in community resilience is Physical Infrastructure, which includes transportation systems, communication networks, utilities, and all physical systems of a region or nation that often produce goods and services. The aim of this study is to review physical infrastructure-based frameworks and propose a custom framework for Jefferson County, TX, US. The concept of resilience is heavily influenced by functionality and interdependency, which are critical in determining the resilience score. To achieve this at the beginning stage, variable assessment was done by expert perspective orientation. Then, Principal Component Analysis (PCA) was utilized. The PCA allows for the condensation of data into definable and utilizable subsets, while FA extracts factors which contribute and assigns specific weights based on the eigenvalues and corresponded eigenvectors to each indicator, component, and dimension over time. In this study, we use selected variables in the energy field as main component of physical infrastructure dimension to create a model. For calculations based on this data, Python™ programming was employed. By revealing the energy scores, decisionmakers will be able to plan and implement practical solutions to increase corresponding resilience in the communities that leads to decrease recovery time and costs on a disaster event.