Arctic Sea Ice Prediction Based on Multi‐Scale Graph Modeling With Conservation Laws DOI Creative Commons

Lan Wei,

Nikolaos M. Freris

Journal of Geophysical Research Atmospheres, Journal Year: 2024, Volume and Issue: 130(1)

Published: Dec. 26, 2024

Abstract Arctic sea ice prediction is critical for exploring climate change, resource extraction, and shipping route planning. This paper introduces a novel neural network model, Ice Graph Attention neTwork (IceGAT), that trained to predict concentration (SIC) from number of atmospheric, oceanic, land surface measurements. It based on two design principles: (a) the complex spatial interactions in weather dynamics are captured via series graphs corresponding different resolutions (b) incorporation physical conservation laws moisture potential vorticity. We devise main variants with 1 hr 24 temporal resolution determine optimal input horizon be 5 days. IceGAT features leading accuracy (96.7%; +2.4% over current state‐of‐the‐art) low inference time (1/4 s, single GPU). An online implementation (based data ERA5) alongside supplementary videos our shared code accessible at: https://lannwei.github.io/IceGAT/ .

Language: Английский

Vessel turnaround time prediction: A machine learning approach DOI
Zhong Chu, Ran Yan, Shuaian Wang

et al.

Ocean & Coastal Management, Journal Year: 2024, Volume and Issue: 249, P. 107021 - 107021

Published: Jan. 20, 2024

Language: Английский

Citations

14

PSO-Based Predictive PID-Backstepping Controller Design for the Course-Keeping of Ships DOI Creative Commons
Bowen Lin, Mao Zheng, Bing Han

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(2), P. 202 - 202

Published: Jan. 23, 2024

Ship course-keeping control is of great significance to both navigation efficiency and safety. Nevertheless, the complex navigational conditions, unknown time-varying environmental disturbances, dynamic characteristics ships pose difficulties for ship course-keeping. Thus, a PSO-based predictive PID-backstepping (P-PB) controller proposed in this paper realize efficient rapid ships. The takes ship’s target course, current yawing speed, as well motion parameters into consideration. In design controller, PID improved by introducing control. Then, combined with backstepping balance stability Subsequently, are optimized utilizing Particle Swarm Optimization (PSO), which can adaptively adjust value various scenarios, thus further increase its efficiency. Finally, validated carrying out simulation tests scenarios. results show that it improves error time-response specification 4.19% 9.71% on average, respectively, efficiently achieve under

Language: Английский

Citations

8

Potential benefits of climate change on navigation in the northern sea route by 2050 DOI Creative Commons
Mohamed Rami Mahmoud, Mahmoud Roushdi,

Mostafa Aboelkhear

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Feb. 2, 2024

Abstract Climate change has been inducing a continuous increase in temperatures within the Arctic region, consequently leading to an escalation rates of ice depletion. These changes have profound implications for navigation along Northern Sea Route (NSR). However, access NSR is constrained specific temporal intervals when sea thickness reaches threshold that permits safe passage ships. This research employs climate model simulations and Polar Operational Limit Assessment Risk Indexing System framework investigate navigational feasibility diverse ship types during calendar years 2030, 2040, 2050, under SSP2-4.5 SSP5-8.5 scenarios. Different categories were analyzed context these two Results indicate considerable variation navigability different across scenarios years. In general, polar ships demonstrate higher potential throughout most year, while pleasure crafts are periods. findings bear significant future shipping NSR. As continues melt, anticipated become more accessible ships, albeit with availability remaining contingent on category seasonal considerations.

Language: Английский

Citations

6

An Improved VO Method for Collision Avoidance of Ships in Open Sea DOI Creative Commons
Mao Zheng, Kehao Zhang, Bing Han

et al.

Journal of Marine Science and Engineering, Journal Year: 2024, Volume and Issue: 12(3), P. 402 - 402

Published: Feb. 26, 2024

In order to effectively deal with collisions in various encounter situations open water environments, a ship collision avoidance model was established, and multiple constraints were introduced into the velocity obstacle method, method determine domain by calculating safe distance of approach proposed. At same time, based on is analyzed, relative set cone obtained solving common tangent line within ellipse. The timing starting determined risk, for ending Finally, comparing simulation experiments improved algorithm those traditional actual experiment results manual maneuvering, it shown that can avoid distances comply navigation experience different situations. has better performance behavior. It certain feasibility practical applicability.

Language: Английский

Citations

6

Self-tuning iterative learning control for an USV: Application to an autonomous berthing operation with an avoidance obstacle mechanism DOI
Xiaoxue Wu, Xinying Miao, Wei Wang

et al.

Ocean Engineering, Journal Year: 2024, Volume and Issue: 301, P. 117548 - 117548

Published: March 21, 2024

Language: Английский

Citations

5

Predicting vessel arrival times on inland waterways: A tree-based stacking approach DOI
Jinyu Lei, Zhong Chu, Yong Wu

et al.

Ocean Engineering, Journal Year: 2024, Volume and Issue: 294, P. 116838 - 116838

Published: Jan. 24, 2024

Language: Английский

Citations

4

Performance Evaluation of Deep Learning Image Classification Modules in the MUN-ABSAI Ice Risk Management Architecture DOI Creative Commons
Ravindu G. Thalagala, Oscar De Silva,

Dan Oldford

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(2), P. 326 - 326

Published: Jan. 8, 2025

The retreat of Arctic sea ice has opened new maritime routes, offering faster shipping opportunities; however, these routes present significant navigational challenges due to the harsh conditions. To address challenges, this paper proposes a deep learning-based risk management architecture with multiple modules, including classification, assessment, floe tracking, and load calculations. A comprehensive dataset 15,000 images was created using public sources contributions from Canadian Coast Guard, it used support development evaluation system. performance YOLOv8n-cls model assessed for classification modules its fast inference speed, making suitable resource-constrained onboard systems. training were conducted across platforms, Roboflow, Google Colab, Compute Canada, allowing detailed comparison their capabilities in image preprocessing, training, real-time generation. results demonstrate that Image Classification Module I achieved validation accuracy 99.4%, while II attained 98.6%. Inference times found be less than 1 s Colab under 3 on stand-alone system, confirming architecture's efficiency condition monitoring.

Language: Английский

Citations

0

Research progress of energy storage materials for polar navigation applications DOI

Jun Ji,

Yuanzhe Gu,

Xuelai Zhang

et al.

Journal of Energy Storage, Journal Year: 2025, Volume and Issue: 113, P. 115604 - 115604

Published: Feb. 4, 2025

Language: Английский

Citations

0

Navigational challenges in Svalbard: insights from a research expedition DOI Creative Commons
Meriç Karahalil, Burcu Özsoy, Özgün Oktar

et al.

WMU Journal of Maritime Affairs, Journal Year: 2025, Volume and Issue: unknown

Published: March 17, 2025

Language: Английский

Citations

0

RouteView 2.0: A Real-time Operational Planning System for Vessels on the Arctic Northeast Passage DOI
Adan Wu, Tao Che, Jinlei Chen

et al.

Environmental Modelling & Software, Journal Year: 2025, Volume and Issue: unknown, P. 106464 - 106464

Published: April 1, 2025

Language: Английский

Citations

0