Strategy for additional buoy array installation in operational buoy-observation network in Korea. (15th December 2022)

• Record Type: Journal Article
• Authors: Kim, Nam-Hoon; Baek, Donghae; Kwon, Jae-il; Choi, Jin-Yong; Heo, Ki-Young
• Is Part Of: Ocean engineering. Volume 266(2022) Part 1
• Publication Date: 2022-12-15
• Subjects: Observation network -- Buoy array -- Multi-objective optimization -- Brute-force optimizer -- Pareto-optimal solutions; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2022.112746
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Ocean observations, such as buoys and research stations, incur enormous installation and operation costs. Therefore, it is necessary to optimally arrange the observation sites at suitable positions. In this study, a strategy for additional buoy installation in a currently operated buoy-observation network was proposed using the multi-objective optimization technique. The numerical simulation results of the Korea Operational Oceanographic System were used as input data. The surface current, water temperature, and salinity, which are parameters observed at buoys, were set as the design variables. The objective function was constructed by assigning weights to each design variable, and the optimal array was determined using a brute-force optimizer. The optimal solution is estimated in the form of Pareto-optimal solutions that can achieve optimal efficiency. Pareto-optimal solutions can produce candidates for optimal arrays, depending on which design variables are weighted. Each candidate array can effectively reproduce the local characteristics of the design variables, such as the speed and direction of the surface current and cold/hot bias of water temperature and salinity, which could not be obtained from the existing observation network. Such candidate arrays can provide multiple options according to the designer's intent in the decision-making process. Highlights: Proposed a strategy to install additional buoy-observation sites in existing network. Observable ocean variables were considered using multi-objective optimization. Weighted sum method combined objective functions and assigned weights to variables. The brute-force optimizer determined the most optimal design site combinations. The design variables were assigned weights based on the Pareto-optimal solutions.