A multi-system model is proposed to simulate the interaction between the building portfolio, transportation network, and healthcare system of an earthquake-stricken community. The proposed simulation model and its capabilities are demonstrated through a case study that focuses on modeling the seismic resilience of a part of Shelby County, Tennessee. The building portfolio data was extracted from the database provided in Ergo-EQ software version 4.0 Beta 2. The studied area is approximately 14 km2 (5.4 mi2) with a population of approximately 40,000 which is considered a typical midsize community. The building portfolio consists of around 8600 buildings, mostly wooden that areas are typical of US residential communities.

A distributed simulation model is presented that integrates post-earthquake household decisions into quantifying the seismic resilience of communities subjected to earthquake sequences. A case study of a prototype community that comprises households with different socio-economic characteristics in accordance with a typical small U.S. community is used to show the influence that household decisions have on the overall seismic resilience of the community. The case study demonstrates the flexibility of the distributed computation scheme in linking models rooted in different disciplines.

In this project, we explore the efficiency of different machine learning (ML) methods in predicting the seismic collapse behavior of steel deep wide flange (W-shape) columns. Steel Column Net (SCNet), a database of more than nine hundred deep W-shape columns subjected to combined axial and lateral loads is collected and compiled. The efficiency of five ML classification models is explored to identify the failure modes of columns in a randomly assigned test set from SCNet. Whereas, the efficiency of four ML regression models is explored to predict the cumulative inelastic rotation of columns in a randomly assigned test set from SCNet.

Extreme natural hazards, such as severe earthquakes and hurricanes, can trigger intricate inter-dependencies between the critical infrastructure systems of society, including the built environment (e.g., buildings and bridges), elements of social organization (e.g., social power and cohesion), and institutional arrangements (e.g., policies, politics, economics, and disaster mitigation). Such inter-dependencies can adversely influence community resilience, i.e. the ability to recover from an extreme event, usually measured in terms of loss of life and economic cost. Our objective is to develop a computational framework that allows researchers from different natural hazards research sub-fields to link their computational models together to study the effects of infrastructure inter-dependencies on community resilience. In particular, our focus is on the inter-dependencies that arise between infrastructure robustness, social organization, and policy in the context of community resilience. Infrastructure robustness, which is the ability to respond favorably to the demands of extreme events (e.g. so that a building does not collapse during a severe earthquake), derives from policy. It directly impacts social organization and both play a role in determining casualty rates. Casualty rates, in turn, influence future policy.The “Simple Run-Time Infrastructure” (SRTI) is an open-source framework that can be used for data-communication across simulator programs in different languages. SRTI is based on a client-server structure and uses a publish-subscribe pattern to realize data communication between the distributed simulators for different fields. This approach provides a scalable, versatile, and user-friendly solution for integrating multiple discipline-specific models in hazards simulation. Each simulator is treated as a black box that interacts through the SRTI distributed computational platform. In this project, an example implementation that consists of a group of developed simulators for assessing the impacts of earthquakes on community resilience is presented. The shown example consists of fourteen simulators each of which represents a different aspect of the community. Thirteen of the developed simulators are implemented in MATLAB while the other simulator (i.e. visualization simulator) is implemented in NetLogo.