Session: 07-01-01 Arctic Environments and Frontier Regions

Submission Number: 180447

Wave-Ice Interaction, AIs-Based Exposure, and Human Factors for Arctic Maritime Risk 

The rapid transformation of Alaska’s marginal ice zone (MIZ) is redefining the boundary between ocean engineering, navigation safety, and community risk. Building upon our earlier modeling and field efforts, this study introduces an integrated framework that connects physics-based wave–ice interaction simulations with AIS-derived vessel risk analytics and stakeholder-informed operational insights. First, new hydroelastic simulations are presented that resolve wave attenuation, overwash, and drift processes across variable floe thickness, elasticity, and viscoelastic damping. These results, validated against scaled flexible-plate experiments, quantify transmission and reflection coefficients under mixed wave spectra, providing reduced-order predictors suitable for Arctic operational design and control. Second, we advance our AIS–ice data fusion methodology by integrating multi-source products from Copernicus, ERA5, and the Alaska Sea Ice Program (ASIP). The improved model corrects for melt-season underestimation and nearshore misclassification through localized chart assimilation, achieving higher fidelity in identifying ice–ship encounter hotspots. Applying the IACS POLARIS Risk Index Outcome (RIO) framework to 8–10 years of Alaskan AIS traffic reveals pronounced exposure in the Bering and Chukchi Seas, with consistent seasonal risk elevation during spring breakup and autumn freeze-up. Finally, through structured stakeholder interviews and regional analyses, we translate these quantitative findings into practical decision variables—highlighting communication gaps, infrastructure constraints, and region-specific tolerance thresholds reported by mariners and coastal communities. The combined results demonstrate a scalable, cross-disciplinary approach for coupling hydroelastic physics, real-world vessel data, and human factors into an actionable decision-support system for Arctic maritime operations. This integrated framework supports improved forecasting, route planning, and resilient infrastructure design under increasing Arctic activity.

Presenting Author: Ersegun Deniz Gedikli University of Hawaii at Manoa

Presenting Author Biography: Dr. Deniz Gedikli is a professor of Ocean and Resources Engineering at the University of Hawaiʻi at Mānoa, where he directs the Fluid-Structure Interaction and Nonlinear Dynamics (FSI) Research Group. His work focuses on fluid- and ice-structure interactions in offshore and Arctic environments, marine renewable energy systems, and data-driven modeling of complex hydrodynamic responses. Prior to joining UH Mānoa, he was a postdoctoral scholar at the Norwegian University of Science and Technology (NTNU).

Authors:

Ersegun Deniz Gedikli University of Hawaii at Manoa
Oceana Francis University of Hawaii at Manoa
Grant Peel University of Hawaii at Manoa
Jonas Behnen University of Hawaii at Manoa
Virginia Groeschel University of Hawaii at Manoa
Ozgur Demir University of Hawaii at Manoa
Hayo Hendrikse Delft University of Technology