Session Abstracts:
Associate Professor
Stanford University
LES for wind load analysis: The future is now
Abstract: This talk explores the current capabilities and future prospects of leveraging large-eddy simulations (LES) for accurate peak wind load predictions in the building design process. It begins with a summary of validation studies comparing LES-predicted wind pressures with wind tunnel measurements for both low- and high-rise buildings. A real-world example will then highlight how LES can make a difference in the building design process. The talk will conclude by outlining the vast opportunities offered by emerging approaches such as multi-fidelity modeling, machine learning, and novel educational platforms, demonstrating how these innovations can shape the future of wind load calculations powered by LES.
Rice University
Smart and equitable models for quantifying multi-hazard risk and resilience of infrastructure
Abstract: Risk-informed decisions that promote resilience (or the ability of infrastructure to withstand, adapt to and recover from stressors) require confident predictions of structure-to-system performance now and into the future. However, this future brings uncertainties regarding dynamic, evolving conditions; challenges with respect to a legacy of disparate impacts of natural hazards and infrastructure (under)investment; and opportunities related to smart systems and emerging data, algorithms, and cyberinfrastructure. This presentation describes a paradigm shift toward smart and equitable multi-hazard resilience modeling, highlighting the characteristics and dimensions of such a modeling framework intended to infuse intelligence and promote equity considerations in both algorithms and outcomes of infrastructure resilience pursuits. Along the way we probe practical illustrations related to quantifying parameterized structural fragility, risk, and resilience of infrastructure systems subjected to multiple hazards, highlighting gaps and opportunities for future research in this domain.
Associate Professor
University at Buffalo
A Workflow for Evaluating Wildfire Risk in Wildland-Urban Interface Communities
Co-Authors: Fernando Szasdi-Bardales (University at Buffalo)
Abstract: Wildfires have long played a critical role in maintaining healthy ecosystems, serving as natural regulators of vegetation and biodiversity. However, recent shifts in climate patterns and increased human activities have escalated the frequency and intensity of these fires. This change has transformed wildfires from a natural phenomenon into a threat to communities. The economic and social impacts have become increasingly severe, with recent years marking some of the most destructive and costly wildfire events in history. Despite extensive research on the behavior of wildfire inside the wildland, methodologies for simulating fire spread inside wildland-urban interface (WUI) areas remain underdeveloped. Equally lacking is a robust, scalable workflow for assessing wildfire risk inside communities, integrating the behavior of fire across wildland and WUI. This requires consideration of both spatial and temporal variability in environmental factors and fuel conditions (vegetation and urban). This presentation discusses the development of a workflow designed to evaluate community-level wildfire damage potential, incorporating the location and likelihood of ignition in the wildland, weather conditions, wind fields, and fire spread dynamics in the wildland and WUI. In collaboration with local stakeholders, the framework has been applied to a real community on the West Coast. The findings provide actional insights for local officials, enabling them to prioritize relevant mitigation measures. Additionally, the workflow offers a template that can be adapted for risk assessment in other WUI communities.