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INSTRUCTORS:
Catalina Gonzalez Duenas, Ph.D.
Luc Ponsioen, EngD, MSc
Sangyeop Lee
James M. Ricles, Ph.D., MS, BS, PE
Course Length: 1 hour
Purpose and Background
These presentations were recorded at the International Conference on Coastal Engineering 2026.
Physics-Structured AI for Multi-Hazard Cascading Risk Analysis (18 minutes)
This presentation explores how physics-informed artificial intelligence can enhance multi-hazard risk assessment in coastal environments. Participants will learn how interactions among natural systems, built infrastructure, and social systems contribute to cascading disaster impacts. The session introduces graph neural networks (GNNs) as a way to preserve physical relationships from computational fluid dynamics simulations while significantly reducing computational demands. Attendees will examine applications involving marshes, mangroves, and coastal vegetation under hurricane conditions. The presentation discusses how AI can reproduce complex hydrodynamic behavior while maintaining physical consistency. Engineers will gain insight into emerging methods that combine machine learning with engineering physics. The findings demonstrate how surrogate models can support large-scale probabilistic risk analyses for coastal systems.
Digital Twins in Flood Risk Management (14 minutes)
This presentation introduces digital twin technology as a tool for improving flood risk management and infrastructure operations. Participants will learn how digital twins integrate sensor data, numerical models, expert knowledge, and artificial intelligence into a unified decision-support framework. The session highlights applications to storm surge barriers in the Netherlands, including operational monitoring, anomaly detection, and risk management. Attendees will explore how digital twins can improve asset management and provide new insights into infrastructure behavior. The presentation demonstrates links between infrastructure performance and community flood risk. Engineers will gain practical knowledge of implementing digital twins across multiple spatial scales. The findings showcase the growing role of digital twins in enhancing resilience of flood protection systems.
Digital Twin for Tsunami Early Warning and Coastal Flood Risk Management (9 minutes)
This presentation presents a digital twin framework designed to improve tsunami early warning and evacuation guidance. Participants will learn how real-time sensor data can be connected to virtual environments for rapid hazard assessment. The session demonstrates how digital twins, game-engine technology, and augmented reality can be used to deliver personalized evacuation instructions. Attendees will examine a prototype system that converts buoy observations into virtual tsunami simulations and evacuation route recommendations. The presentation explores the use of Unity, GIS datasets, and routing algorithms within a real-time decision-support framework. Engineers will gain insights into integrating hazard prediction with public safety communication. The research illustrates how digital twins can bridge the gap between forecasting and emergency response.
AI-Enabled Cyber-Physical Simulation of Coastal Infrastructure (15 minutes)
This presentation explores how artificial intelligence can enable real-time cyber-physical simulations of coastal infrastructure under extreme loading conditions. Participants will learn how hybrid simulation combines physical testing and numerical modeling to evaluate infrastructure performance. The session introduces neural-network surrogate models that replace computationally expensive fluid simulations while preserving key dynamic behaviors. Attendees will examine applications involving fluid-structure interaction, structural damping systems, and extreme coastal loading scenarios. The presentation demonstrates how AI can support real-time simulation and decision-making for resilient infrastructure design. Engineers will gain insights into coupling machine learning, computational mechanics, and experimental testing. The findings highlight the potential of cyber-physical systems for next-generation coastal engineering applications.
Benefits and Learning Outcomes
Upon completion of this course, you will be able to:
- Explain how physics-structured AI models can support multi-hazard cascading risk assessment in coastal environments.
- Describe how digital twins integrate data, models, and operational information to improve flood risk management.
- Identify the components of a digital twin framework capable of supporting tsunami early warning and real-time evacuation guidance.
- Discuss how AI-enabled cyber-physical simulations can support coastal infrastructure performance assessment under extreme hazards.
Assessment of Learning Outcomes
Students' achievement of the learning outcomes will be assessed via a short post-test assessment (true-false, multiple choice, and/or fill in the blank questions).
Who Should Attend?
- Coastal Engineer
- Civil Engineer
- Coastal Scientist
- Coastal Resilience Program Manager
- Government Coastal Zone Manager
- University Student or Researcher
How to Earn your CEUs/PDHs and Receive Your Certificate of Completion
To receive your certificate of completion, you will need to complete a short on-line post-test and receive a passing score of 70% or higher within 365 days of the course purchase.
How do I convert CEUs to PDHs?
1.0 CEU = 10 PDHs [Example: 0.1 CEU = 1 PDH]