Fabrizio Lagasco , Ambra Zuccarino , Alessandro Largo , Giovanni Gambaro , Carlo Ruzzo , Anita Santoro , Felice Arena
{"title":"浮式多用途海上平台整体运动与结构变形预测:平台自动化与控制系统设计背景下的工程方法","authors":"Fabrizio Lagasco , Ambra Zuccarino , Alessandro Largo , Giovanni Gambaro , Carlo Ruzzo , Anita Santoro , Felice Arena","doi":"10.1016/j.apor.2025.104701","DOIUrl":null,"url":null,"abstract":"<div><div>Integrating renewable energy sources with aquaculture systems on floating Multi-purpose Offshore Installations (MOI) offers an innovative and sustainable solution to harness the vast potential of the ocean. Despite several designs have been attempted, the difficulties to prove at harsh environment in real scale remain the main challenge. Whilst the industrial target of the proposed platform design is to enable automated aquaculture production supported by wind, wave and solar energy harvesting technologies in a profitable way benefiting of the available energy resources, as well as of the healthier conditions for fish farming, the technical challenge is focused on the capacity to withstand the harsh environment of the deep waters installation and to guarantee structural integrity during the in-service lifetime. Test before Invest principle requires studying these installations through increasing steps, experiencing prototypes at various scales to investigate about the installation dynamics and capacity to resist the loading conditions over the operative life. The full-scale design, among others, has to consider how to secure insurance coverage for the asset over its operational lifetime, and how to support decisions on extending the asset’s service life, particularly following the replacement of long-lead technological components at the 25-year mark. Designing robust and efficient control and monitoring system based on key structural and deformation data measurements through the operative life may support these achievements, even if practical applications are not available yet. In the context of the design of an innovative MOI developed within “The Blue Growth Farm” (BGF) European Commission (EC) funded H2020 project, the challenge to study and implement a model to predict the floating platform movement and deformation under in-service loading has emerged to be key to define an efficient automation and control system for the installation. This paper describes the engineering process adopted to achieve this objective, considering the novelty of the platform concept and the lack of similar industrial MOI automation and control experience. The proposed methodology focuses on the use of machine learning (ML) techniques and its validation process by exploiting data acquired during an experimental campaign at sea developed on a scaled version (prototype) of the proposed infrastructure. Tests carried out aimed at capturing the complex structure dynamics through data recorded in a wide experimental campaign between May and September 2021 at the Natural Ocean Engineering Laboratory (NOEL) of Reggio Calabria (Italy).</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"161 ","pages":"Article 104701"},"PeriodicalIF":4.4000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Global movement and structural deformation prediction of a floating multi-purpose offshore platform: an engineering approach in the context of the design of the platform automation and control system\",\"authors\":\"Fabrizio Lagasco , Ambra Zuccarino , Alessandro Largo , Giovanni Gambaro , Carlo Ruzzo , Anita Santoro , Felice Arena\",\"doi\":\"10.1016/j.apor.2025.104701\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Integrating renewable energy sources with aquaculture systems on floating Multi-purpose Offshore Installations (MOI) offers an innovative and sustainable solution to harness the vast potential of the ocean. Despite several designs have been attempted, the difficulties to prove at harsh environment in real scale remain the main challenge. Whilst the industrial target of the proposed platform design is to enable automated aquaculture production supported by wind, wave and solar energy harvesting technologies in a profitable way benefiting of the available energy resources, as well as of the healthier conditions for fish farming, the technical challenge is focused on the capacity to withstand the harsh environment of the deep waters installation and to guarantee structural integrity during the in-service lifetime. Test before Invest principle requires studying these installations through increasing steps, experiencing prototypes at various scales to investigate about the installation dynamics and capacity to resist the loading conditions over the operative life. The full-scale design, among others, has to consider how to secure insurance coverage for the asset over its operational lifetime, and how to support decisions on extending the asset’s service life, particularly following the replacement of long-lead technological components at the 25-year mark. Designing robust and efficient control and monitoring system based on key structural and deformation data measurements through the operative life may support these achievements, even if practical applications are not available yet. In the context of the design of an innovative MOI developed within “The Blue Growth Farm” (BGF) European Commission (EC) funded H2020 project, the challenge to study and implement a model to predict the floating platform movement and deformation under in-service loading has emerged to be key to define an efficient automation and control system for the installation. This paper describes the engineering process adopted to achieve this objective, considering the novelty of the platform concept and the lack of similar industrial MOI automation and control experience. The proposed methodology focuses on the use of machine learning (ML) techniques and its validation process by exploiting data acquired during an experimental campaign at sea developed on a scaled version (prototype) of the proposed infrastructure. Tests carried out aimed at capturing the complex structure dynamics through data recorded in a wide experimental campaign between May and September 2021 at the Natural Ocean Engineering Laboratory (NOEL) of Reggio Calabria (Italy).</div></div>\",\"PeriodicalId\":8261,\"journal\":{\"name\":\"Applied Ocean Research\",\"volume\":\"161 \",\"pages\":\"Article 104701\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Ocean Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0141118725002871\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, OCEAN\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Ocean Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0141118725002871","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, OCEAN","Score":null,"Total":0}
Global movement and structural deformation prediction of a floating multi-purpose offshore platform: an engineering approach in the context of the design of the platform automation and control system
Integrating renewable energy sources with aquaculture systems on floating Multi-purpose Offshore Installations (MOI) offers an innovative and sustainable solution to harness the vast potential of the ocean. Despite several designs have been attempted, the difficulties to prove at harsh environment in real scale remain the main challenge. Whilst the industrial target of the proposed platform design is to enable automated aquaculture production supported by wind, wave and solar energy harvesting technologies in a profitable way benefiting of the available energy resources, as well as of the healthier conditions for fish farming, the technical challenge is focused on the capacity to withstand the harsh environment of the deep waters installation and to guarantee structural integrity during the in-service lifetime. Test before Invest principle requires studying these installations through increasing steps, experiencing prototypes at various scales to investigate about the installation dynamics and capacity to resist the loading conditions over the operative life. The full-scale design, among others, has to consider how to secure insurance coverage for the asset over its operational lifetime, and how to support decisions on extending the asset’s service life, particularly following the replacement of long-lead technological components at the 25-year mark. Designing robust and efficient control and monitoring system based on key structural and deformation data measurements through the operative life may support these achievements, even if practical applications are not available yet. In the context of the design of an innovative MOI developed within “The Blue Growth Farm” (BGF) European Commission (EC) funded H2020 project, the challenge to study and implement a model to predict the floating platform movement and deformation under in-service loading has emerged to be key to define an efficient automation and control system for the installation. This paper describes the engineering process adopted to achieve this objective, considering the novelty of the platform concept and the lack of similar industrial MOI automation and control experience. The proposed methodology focuses on the use of machine learning (ML) techniques and its validation process by exploiting data acquired during an experimental campaign at sea developed on a scaled version (prototype) of the proposed infrastructure. Tests carried out aimed at capturing the complex structure dynamics through data recorded in a wide experimental campaign between May and September 2021 at the Natural Ocean Engineering Laboratory (NOEL) of Reggio Calabria (Italy).
期刊介绍:
The aim of Applied Ocean Research is to encourage the submission of papers that advance the state of knowledge in a range of topics relevant to ocean engineering.