Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/154771
Title: Rational processing of monitored ship voyage data for improved operation
Authors: Liu, Shukui
Loh, Meici
Leow, Weichi
Chen, Haoliang
Shang, Baoguo
Papanikolaou, Apostolos
Keywords: Engineering::Mechanical engineering
Issue Date: 2020
Source: Liu, S., Loh, M., Leow, W., Chen, H., Shang, B. & Papanikolaou, A. (2020). Rational processing of monitored ship voyage data for improved operation. Applied Ocean Research, 104, 102363-. https://dx.doi.org/10.1016/j.apor.2020.102363
Journal: Applied Ocean Research
Abstract: This paper presents a method for the rational processing of ship voyage data for improved ship operation. The proposed approach is based on a physical modeling method, in which the ship resistance-propeller-engine model is first developed by using available ship information and basic hydrodynamics. For the analysis of operational scenarios in realistic environmental conditions, seaway data are retrieved from WaveWatchIII® hindcast (Tolman, 2002; WAVEWATCH, 2020). The added resistances due to wind is predicted using a standard method recommended by ITTC and the added resistance in waves using a newly developed semi-empirical method of Liu and Papanikolaou (2020). Then, the recorded speed-power data is projected to the calm water condition based on the resistance and thrust identity method. In a second step, we apply simple, yet rational, filtering criteria to filter out the data points polluted by ship's accelerations, the rate of change of course, as well as wave conditions. The developed processing and filtering method is applied to the analysis of the monitored data of three voyages of a chemical carrier and the obtained results are discussed. The prospects of extending the presented method to the study of a time-varying ship speed performance and fuel consumption analysis procedure, in which hull fouling can be studied, is briefly outlined.
URI: https://hdl.handle.net/10356/154771
ISSN: 0141-1187
DOI: 10.1016/j.apor.2020.102363
Schools: School of Mechanical and Aerospace Engineering 
Rights: © 2020 Elsevier Ltd. All rights reserved
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:MAE Journal Articles

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