Using machine learning to understand the behavior of added resistance of a ship in waves
Ships experience resistances of various origins. The influence of the added resistance of a ship in waves is significant enough not to be ignored. The analysis drawn to attention identifies the different relations between the added resistance and the various factors of contribution factors, direct a...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/141813 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-141813 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1418132023-03-04T19:40:43Z Using machine learning to understand the behavior of added resistance of a ship in waves Ong, Rayner Junjie Liu Shukui School of Mechanical and Aerospace Engineering raynerong11@hotmail.com Engineering::Mechanical engineering Ships experience resistances of various origins. The influence of the added resistance of a ship in waves is significant enough not to be ignored. The analysis drawn to attention identifies the different relations between the added resistance and the various factors of contribution factors, direct and indirect. These factors range from the ship profile to wave character. This report analyses the waterline of the vessel at a given angle of wave. At given angles, part of the waterline will only be exposed. Therefore, this report seeks to identify and enhance on the current diffraction calculation method. This report will also attempt to work on relationship between the diffraction added resistance and wave spectra theories employed by different theories. Experimental data collected are processed using machine learning tools to aid the in-depth analysis of the added resistance. Bachelor of Engineering (Mechanical Engineering) 2020-06-11T01:42:46Z 2020-06-11T01:42:46Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/141813 en MA4079 application/pdf Nanyang Technological University |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Engineering::Mechanical engineering |
spellingShingle |
Engineering::Mechanical engineering Ong, Rayner Junjie Using machine learning to understand the behavior of added resistance of a ship in waves |
description |
Ships experience resistances of various origins. The influence of the added resistance of a ship in waves is significant enough not to be ignored. The analysis drawn to attention identifies the different relations between the added resistance and the various factors of contribution factors, direct and indirect. These factors range from the ship profile to wave character. This report analyses the waterline of the vessel at a given angle of wave. At given angles, part of the waterline will only be exposed. Therefore, this report seeks to identify and enhance on the current diffraction calculation method. This report will also attempt to work on relationship between the diffraction added resistance and wave spectra theories employed by different theories. Experimental data collected are processed using machine learning tools to aid the in-depth analysis of the added resistance. |
author2 |
Liu Shukui |
author_facet |
Liu Shukui Ong, Rayner Junjie |
format |
Final Year Project |
author |
Ong, Rayner Junjie |
author_sort |
Ong, Rayner Junjie |
title |
Using machine learning to understand the behavior of added resistance of a ship in waves |
title_short |
Using machine learning to understand the behavior of added resistance of a ship in waves |
title_full |
Using machine learning to understand the behavior of added resistance of a ship in waves |
title_fullStr |
Using machine learning to understand the behavior of added resistance of a ship in waves |
title_full_unstemmed |
Using machine learning to understand the behavior of added resistance of a ship in waves |
title_sort |
using machine learning to understand the behavior of added resistance of a ship in waves |
publisher |
Nanyang Technological University |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/141813 |
_version_ |
1759853969099718656 |