个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:日本广岛大学
学位:博士
所在单位:船舶工程学院
学科:船舶与海洋结构物设计制造
电子邮箱:huangyi@dlut.edu.cn
A combined first- and second-order theory for the deckwetness prediction of sandglass-type floating body in irregular head waves
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论文类型:期刊论文
发表时间:2017-07-01
发表刊物:MARINE STRUCTURES
收录刊物:SCIE、EI、Scopus
卷号:54
页面范围:23-37
ISSN号:0951-8339
关键字:Deckwetness; Sandglass-type FPSO; Second-order slowly varying loads; Non-Gaussian process
摘要:Deckwetness is one of the most important problems for seakeeping performance. With regard to the conventional ship-type Floating Production, Storage, and Offloading Units (FPSOs), the deckwetness depends on the relative vertical motion which is dominated usually by the first-order wave frequency loads. However, it can not apply to the deck wetness prediction of the sandglass-type FPSO since the influence of second-order slowly varying loads is remarkable. In this paper, a combined first- and second-order theory accounting for the first-order wave loads and nonlinear second-order slowly varying loads, is established to predict the decicwetness occurrence. By using the second-order Volterra series model, the relative vertical motion between the bow and incident wave surface can be described as a stationary non-Gaussian process. Then general formulas are derived for the prediction of the deckwetness occurrence for the sandglass-type floating body, based on the mathematical characteristics of the relative vertical motion process. As an application, the theory presented is discussed with reference to the decicwetness prediction of the sandglass-type floating model. Therein, a time domain analysis is employed to get the relative vertical motion response whereby the above formulas can be efficiently calculated. The influence factors including the length of the time simulation and the randomness of the wave phase are examined. Next, the convergence of the results is investigated with the increase of the order of non-Gaussian terms included in the formulas. By comparing with the experimental data, the reasonability and validity of the proposed method are proved. (C) 2017 Elsevier Ltd. All rights reserved.