Development of an environmental monitoring system from on-board motions of vessel movements with machine learning techniques

• Grant number: 21/00409-2
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date until: November 01, 2021
• End date until: April 30, 2025
• Field of knowledge: Engineering - Mechanical Engineering
• Principal Investigator: Eduardo Aoun Tannuri
• Grantee: Gustavo Alencar Bisinotto
• Host Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

This research project comprises the investigation of model-based and data driven methodologies involved in the estimation of environmental loads acting on ships and oceanic systems, in order to design a monitoring system for ocean wave and current. The proposed system relies on the on-board measurements obtained from the vessel movements, its mathematical model and the information from other commonly available sensors. Machine learning theory combined with state observation techniques will be addressed in the project to deal with the complexity of the estimation task and to increase the robustness of the results. Among the applications of an environmental monitoring system are the support for operational decisions or advice on marine activities, including personnel and environmental safety, fuel and route consumption and others. In addition, Dynamic Positioning (DP) systems are benefited, since improvements on the system overall efficiency can be achieved by feed forward controllers based on the pre-compensation of the environmental loads. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

BISINOTTO, GUSTAVO A.; DE MELLO, PEDRO C.; QUEIROZ FILHO, ASDRUBAL N.; IANAGUI, ANDRE S. S.; SIMOS, ALEXANDRE N.; TANNURI, EDUARDO A.. Estimating wave spectra from the motions of dynamically positioned vessels: An assessment based on model tests. APPLIED OCEAN RESEARCH, v. 121, p. 14-pg., 2022-03-01. (21/00409-2)