Coupled Response of Flexible Multi-Buoy Offshore Floating Photovoltaic Array under Waves and Currents
Journal of Marine Science and Engineering(2025)
Zhongtian Technology Marine Engineering Co. | Huadian Heavy Industries Co.
Abstract
To study the response of a flexible offshore floating photovoltaic (FPV) array under waves and a current, a numerical model is established using OrcaFlex. The effects of different waves and currents, as well as their coupled effects on the motion response of the offshore PFV array and the tension in the connectors and moorings under different static tensions, are investigated. Differences are illustrated between the responses of the buoys at different positions and under different moorings under the wave. With the relaxed moorings, the surge response of the buoy facing the wave increased by 159.3% compared with the buoy facing away from the wave. The current causes the overall drift of the array, which greatly influences the buoys facing the current. The mooring tension facing the wave restricts the motion of the buoys under the same direction as the wave and current, which shows that the trend of the buoys’ responses with the wave decreases with the increase in the current velocity, as the pitch reduces to 76.9% under relaxed moorings. There is a significant difference between the results obtained by the superposition summation wave and current loads and the ones of the combined wave–current. With the increase in the wave–current angle, the response is increased by 348.2% as the constraint of the moorings and the connectors is weakened.
MoreTranslated text
Key words
offshore floating photovoltaic,multi-buoy array,coupled response,connector tension
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper