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Selection of Environmental Conditions for Nearshore Structure Design
作者姓名:DONGSheng  GANBuhong  HAOXiaoli
作者单位:DONG Sheng 1),*,GAN Buhong 1,2),HAO Xiaoli 1) 1) College of Engineering,Ocean University of China,Qingdao 266071,P.R.China 2) Shengli Offshore Drilling Company,Dongying 257055,P.R.China
基金项目:教育部留学回国人员科研启动基金,the Scientific Research Foundation for Young Scholars of Ocean University of China
摘    要:1 Introduction InChina ,coastalcitiesaremostlyregionaleconomicdevelopmentcenters.Becauseoftheirspecialgeogra phiclocations ,typhoonsandassociatedstormsurgescauseheavylossesoflivesandproperties.In 1 992 Qing daowasfloodedduetothecoincidenceoftheastrono m…

关 键 词:近海工程  结构设计  统计方法  潮汐  波浪  
收稿时间:17 January 2003
修稿时间:21 July 2003

Selection of environmental conditions for nearshore structure design
DONGSheng GANBuhong HAOXiaoli.Selection of Environmental Conditions for Nearshore Structure Design[J].Journal of Ocean University of China,2004,3(1):111-114.
Authors:Email author" target="_blank">Dong?Sheng?Email author  Gan?Buhong  Hao?Xiaoli
Institution:1. College of Engineering, Ocean University of China, Qingdao 266071, P. R. China
2. College of Engineering, Ocean University of China, Qingdao 266071, P. R. China ;Shengli Offshore Drilling Company, Dongying 257055, P.R. China
Abstract:Different from the traditional one dimensional extreme value statistical method, practical design criteria for nearshore structure design are presented based on joint probability theory in this paper. The proposed procedure considers the combined effect of tide level, huge waves and wind affecting coastal structures. The Importance Sampling Procedure (ISP) is utilized to solve the joint distribution of non Gaussian correlated multivariate distributions. The calculation results show that the ISP is a simulating technique with the advantages of efficiency and high convergency. Finally the environmental conditions are given using this technique for near shore structure design in the Qingdao area.
Keywords:environmental variables  multi  dimensional joint probability  stochastic simulation  engineering design
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