projects
Monitoring ice accumulation for surface ships traveling in the Arctic
2014-2018
PI: Dr. Christopher J. Earls. Cornell University. Sponsored by the Office of Naval Research (ONR).
Develop stochastic inversion framework for monitoring evolving surface ship mass properties during Arctic operations
Establish proof of concept for framework, demonstrated at both full-scale and 1:23 model-scale. Framework utilizes existing on-board ship telemetry and validated sea-keeping software
Exercise the framework for various ice configurations at model-scale, for a single variable and multi-variable inversion scenarios
Implement computer vision algorithm to determine incoming ocean wave time history and infer forces on a ship at sea in near real time
Peer Reviewed Papers and Conference Proceedings
Yolanda C. Lin and Christopher J. Earls. Validation experiment of a single-view image sequence algorithm to identify scale and sea state characteristics. IEEE Journal of Oceanic Engineering. Published online February 2021.
Yolanda C. Lin and Christopher J. Earls. Multi-parameter stochastic inversion for first and second moment mass properties of a model-scale ship with topside ice accumulation. Applied Ocean Research, 82, January 2019
Yolanda C. Lin and Christopher J. Earls. Stochastic inversion framework to monitor evolving mass properties of a ship at sea during arctic operations. The 30th American Towing Tank Conference. Conference Proceedings. October 3-5, 2017
Yolanda C. Lin, Christopher J. Earls, Joel T. Park, and Tim C. Smith. Stochastic inversion for the roll gyradius second moment mass property in ships at full-scale and model-scale. Applied Ocean Research, 63:24–35, February 2017
Invited Presentations and Seminars
CEE Graduate Student Seminar at Cornell. Ice aboard!? Monitoring ice accumulation on a ship surface during Arctic operation. November 16, 2017 in Ithaca, NY. Seminar presentation.
The 30th American Towing Tank Conference. Stochastic inversion framework to monitor evolving mass properties of a ship at sea during arctic operations. October 3-5, 2017 in West Besthesda, Maryland. Oral presentation.
9th Annual Civil and Environmental Engineering Graduate Research Symposium at Cornell University. Stochastic inversion framework to monitor evolving mass properties of a ship at sea. March 24, 2017 in Ithaca, NY. Poster presentation.
SIAM Conference on Computational Science and Engineering. Convergence study for stochastic inversion framework to monitor evolving surface ship mass properties during arctic operations. February 28, 2017 in Atlanta, Georgia. Poster presentation.
7th Annual Civil and Environmental Engineering Graduate Research Symposium at Cornell University. Inferring mass properties of R/V Melville with stochastic ice accumulation. March 20, 2015 in Ithaca, NY. Poster presentation.
In the media
The Cornell Chronicle. Cornell engineers look to help arctic ships assess ice buildup. February 15, 2017.