The Center conducts research on a large number of themes related with catastrophe modeling and resilience. This page provide some examples of our research thrust. For more information on our current research and potential collaborations on these and other topics, do not hesitate to contact us.

Wildfire Risk Assessment

Under strong wind and dry weather, power companies can enact Public Safety Power Shutoffs (PSPS). How should they determine if a shutoff is warranted? We propose a mechanistic approach to assess the risk that power conductor cables oscillate, encroach vegetation, and trigger a wildfire.

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Catmodeling applied to Zoonoses

With the ability to spread fast, zoonoses are a huge threat to our society. The CatModeling framework can help investigate and mitigate the spread of zoonoses.

We designed and implemented a protocol to analyze Ebola data using regression and machine learning techniques. Our results and conclusions are relevant to identify the regions in Sierra Leone at risk of Ebola spillover and, consequently, to design and implement policies for an effective deployment of resources (e.g., drug supplies) and other preventative measures (e.g., educational campaigns).

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Climate Change

The Center is very active in studying climate change, its implications for the built environment, its effect on long-term community resilience, and its impact on expected losses. Researchers of the Center are also involved with leadership roles in an initiative of the Structural Engineering Institute to define guidelines for the building codes of the future, to account for climate change.

Read more on this initiative.

Human Behavior Uncertainty Quantification

Recent studies have investigated connections between natural systems and related human impacts, such as those between the rainfall-runoff process and agricultural activities. This is primarily performed by using two-way connected, natural-human computer models. However, these coupled models require many parameters, which results in larger prediction uncertainty, especially when the observed data is limited. This study quantifies the relationship between model output uncertainty and model complexity. We found that, depending on the type of model used, the uncertainty of model outputs will likely increase with model complexity; however, active two-way feedback between natural and human systems could offset the impact of the natural system on output uncertainty by increasing human variations.

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Stochastic (inter)Dependencies 

After extreme events, a community’s socio-economic recovery depends on the recovery of its infrastructure systems, such as power and water distribution systems, transportation networks, communications systems, and critical buildings. We need to build resilient infrastructure systems to support the national economy and wellbeing of citizens, resist extreme events, and ensure their capacity to rapidly recover to full service afterwards. The PRAISys (Probabilistic Resilience Assessment of Interdependent Systems) platform performs post-event resilience analysis of communities by addressing stochastic interdependencies among infrastructure systems in a probabilistic way. 

The PRAISys project involved 58 scholars from many different scientific areas and institutions (43% from underrepresented groups in STEM).

Visit the official website of PRAISys.

Bridge Fragility and Resilience

Bridges are among the most important assets for our infrastructure, but the aging portfolio of bridges in the Nation is vulnerable to earthquakes and other natural hazards. Researchers in the Center have extensively studied bridges, their vulnerability under natural hazards, and their recovery patterns.

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Catmodeling applied to influenza in isolated and underserved communities

NSF's Predictive Intelligence for Pandemic Prevention program seeks to improve our ability to model and counteract epidemics. A team at Lehigh University is addressing this problem with a special focus on isolated and underserved communities. A first set of communities studied in this project consists of indigenous communities in the US. One of the research thrusts in this project focuses on the application of CatModeling as a general analytical paradigm to address the problem.

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Multi-HAzard quantization

The risk from natural hazards for a specific region is usually assessed predicting the losses associated with a set of representative extreme event scenarios. The selection of these scenarios is delicate, because computational resources constrain heavily the number of cases that can be investigated. Hence, the selected scenarios have to be as few as possible, and yet provide a comprehensive probabilistic description of the regional hazard. We developed a technique called "Multi-Hazard Quantization" that can capture simultaneously multiple hazard intensity measures spread over a region. The approach is grounded in solid mathematics and yields substantial enhancements in the computational efficiency of these analyses, enabling their applicability to practical-size problems and, ultimately, advancing disaster mitigation and response.

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Vulnerability of telecommunication infrastructure

After extreme events, telecommunication systems are essential for the emergency management teams. The welfare of communities demands reliable and uninterrupted operations of these systems. Unfortunately, telecommunication towers continue to be very vulnerable to strong wind events, which leads to large scale and long-term service interruptions and outages, which are associated with significant revenue losses and high repair costs. The Center studies wind loads, dynamic response, vulnerability, repairability, and regional failure correlation for these complex systems.

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Functionality fragility surfaces

To build resilient communities, the rapid functional recovery of infrastructure components and systems is essential to enable restoration and a prompt return to normality. This line of research proposes a simple and yet effective way to combine fragility analysis and recovery models to obtain a snapshot of the probabilistic functionality recovery for a region.

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Fragility and resilience of power lines

Hurricane Harvey in 2017 led to over 850 transmission structures downed or damaged and caused damages to over 1,200 km of transmission and distribution conductors. Hurricane Sandy in 2012 caused over 200 transmission line failures. Moreover, the increasing interdependence between the power infrastructure and other systems is a reason of major concern. The Center has developed a multi-scale probabilistic approach that goes from analyses of the mechanics of individual bolted connections to the electrical study of power lines spanning hundreds of thousands of miles.

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Hurricane simulation

Hurricanes are responsible for the dramatic increase of insured losses over the last years. Researchers at the Center have developed a state-of-the-art hurricane simulator that includes generation, track propagation, dissipation (on water and land), and non-symmetric wind field modules.

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Impact of natural hazards on transportation systems

The researchers of the Center have worked extensively on the resilience of transportation infrastructure against natural disasters. They have also been involved in preparing a report for the National Academies on how to increase the resilience of our transportation systems.

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Read the NASEM guidelines on infrastructure resilience.