Knowledge of sea state conditions is of central importance for a wide range of maritime operations. This thesis presents two novel numerical methods for estimating unimodal and bimodal short-crested seas. Both methods are formulated in the frequency domain as parametric models and employ the JONSWAP spectrum to parameterise the wave spectra. The developed numerical procedures are validated through extensive tests, using synthetic ship motion data, generated by a MATLAB code, specifically developed for this research. Additionally, the unimodal method is further validated using a set of full-scale data. The results demonstrate promising performances and confirm the accuracy of the proposed estimation techniques. Overall, this study demonstrates that these numerical approaches can significantly enhance the ship safety and contribute to the environmental protection if appropriately integrated with the on-board decision-making systems.

Sea state monitoring by ship motion measurement and analysis to increase the safety of ships and navigation

Ascione, Silvia
2026

Abstract

Knowledge of sea state conditions is of central importance for a wide range of maritime operations. This thesis presents two novel numerical methods for estimating unimodal and bimodal short-crested seas. Both methods are formulated in the frequency domain as parametric models and employ the JONSWAP spectrum to parameterise the wave spectra. The developed numerical procedures are validated through extensive tests, using synthetic ship motion data, generated by a MATLAB code, specifically developed for this research. Additionally, the unimodal method is further validated using a set of full-scale data. The results demonstrate promising performances and confirm the accuracy of the proposed estimation techniques. Overall, this study demonstrates that these numerical approaches can significantly enhance the ship safety and contribute to the environmental protection if appropriately integrated with the on-board decision-making systems.
10-apr-2026
Inglese
Inglese
PISCOPO, Vincenzo
Università degli Studi di Napoli Parthenope
92
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/368333
Il codice NBN di questa tesi è URN:NBN:IT:UNIPARTHENOPE-368333