Motion Prediction of Catamaran with a Semisubmersible Bow in Wave

Author:

Sun Hanbing1,Jing Fengmei2,Jiang Yi3,Zou Jin4,Zhuang Jiayuan5,Ma Weijia5

Affiliation:

1. Ph. D., Harbin Engineering University, China

2. Ph.D., College of Shipbuilding Engineering Harbin Engineering University Nan tong street Harbin HLJ P. R. CHINA

3. M. Sc., Harbin Engineering University, China

4. Prof., Harbin Engineering University, China

5. Ph.D. Harbin Engineering University, China

Abstract

Abstract Compared with standard vessels, a slender catamaran with a semi-submerged bow (SSB) demonstrates superior seakeeping performance. To predict the motion of an SSB catamaran, computational fluid dynamics methods are adopted in this study and results are validated through small-scale model tests. The pitch, heave, and vertical acceleration are calculated at various wavelengths and speeds. Based on the overset grid and motion region methods, this study obtains the motion responses of an SSB catamaran in regular head waves. The results of the numerical studies are validated with the experimental data and show that the overset grid method is more accurate in predicting the motion of an SSB catamaran; the errors can be controlled within 20%. The movement data in regular waves shows that at a constant speed, the motion response initially increases and then decreases with increasing wavelength. This motion response peak is due to the encountering frequency being close to the natural frequency. Under identical sea conditions, the motion response increases with the increasing Froude number. The motion prediction results, that derive from a short-term irregular sea state, show that there is an optimal speed range that can effectively reduce the amplitude of motion.

Publisher

Walter de Gruyter GmbH

Subject

Mechanical Engineering,Ocean Engineering

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3