TY - JOUR
T1 - Numerical methods for monitoring and evaluating the biofouling state and effects on vessels’ hull and propeller performance
T2 - A review
AU - Valchev, Iliya
AU - Coraddu, Andrea
AU - Kalikatzarakis, Miltiadis
AU - Geertsma, Rinze
AU - Oneto, Luca
PY - 2022
Y1 - 2022
N2 - Monitoring and evaluating the biofouling state and its effects on the vessel's hull and propeller performance is a crucial problem that attracts the attention of both academy and industry. Effective and reliable tools to address this would allow a timely cleaning procedure able to trade off costs, efficiency, and environmental impacts. In this paper, the authors carry out a critical review, accompanied with summary tables, of the biofouling problem with a particular focus on the shipping industry and the state-of-the-art techniques for monitoring and evaluating the biofouling state and its effects on the vessel's hull and propeller performance. In particular, different techniques are grouped according to the three main families of numerical models that have been designed and exploited in the literature: Physical Models (i.e., models relying on the mechanistic knowledge of the phenomena), Data-Driven Models (i.e., models relying on historical data about the phenomena together with Artificial Intelligence), and Hybrid Models (i.e., a hybridisation between Physical and Data-Driven Models). A conclusion from the performed review, open problems, and future direction of this field of research is detailed at the end of the review.
AB - Monitoring and evaluating the biofouling state and its effects on the vessel's hull and propeller performance is a crucial problem that attracts the attention of both academy and industry. Effective and reliable tools to address this would allow a timely cleaning procedure able to trade off costs, efficiency, and environmental impacts. In this paper, the authors carry out a critical review, accompanied with summary tables, of the biofouling problem with a particular focus on the shipping industry and the state-of-the-art techniques for monitoring and evaluating the biofouling state and its effects on the vessel's hull and propeller performance. In particular, different techniques are grouped according to the three main families of numerical models that have been designed and exploited in the literature: Physical Models (i.e., models relying on the mechanistic knowledge of the phenomena), Data-Driven Models (i.e., models relying on historical data about the phenomena together with Artificial Intelligence), and Hybrid Models (i.e., a hybridisation between Physical and Data-Driven Models). A conclusion from the performed review, open problems, and future direction of this field of research is detailed at the end of the review.
KW - Biofouling
KW - Data-driven models
KW - Hybrid models
KW - Performance modelling
KW - Physical models
KW - Vessel hull and propeller status
UR - http://www.scopus.com/inward/record.url?scp=85127024518&partnerID=8YFLogxK
U2 - 10.1016/j.oceaneng.2022.110883
DO - 10.1016/j.oceaneng.2022.110883
M3 - Review article
AN - SCOPUS:85127024518
SN - 0029-8018
VL - 251
JO - Ocean Engineering
JF - Ocean Engineering
M1 - 110883
ER -