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Comparison of Linear Level I Green-Naghdi Theory with Linear Wave Theory for Prediction of Hydroelastic Responses of VLFS 被引量:5
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作者 宋皓 崔维成 刘应中 《China Ocean Engineering》 SCIE EI 2002年第3期283-300,共18页
Very Large Floating Structures (VLFS) have drawn considerable attention recently due to their potential significance in the exploitation of ocean resources and in the utilization of ocean space. Efficient and accurate... Very Large Floating Structures (VLFS) have drawn considerable attention recently due to their potential significance in the exploitation of ocean resources and in the utilization of ocean space. Efficient and accurate estimation of their hydroelastic responses to waves is very important for the design. Recently, an efficient numerical algorithm was developed by Ertekin and Kim (1999). However, in their analysis, the linear Level I Green-Naghdi (GN) theory is employed to describe fluid dynamics instead of the conventional linear wave (LW) theory of finite water depth. They claimed that this linear level I GN theory provided better predictions of the hydroelastic responses of VLFS than the linear wave theory. In this paper, a detailed derivation is given in the conventional linear wave theory framework with the same quantity as used in the linear level I GN theory framework. This allows a critical comparison between the linear wave theory and the linear level I GN theory. It is found that the linear level I GN theory can be regarded as an approximation to the linear wave theory of finite water depth. The consequences of the differences between these two theories in the predicted hydroelastic responses are studied quantitatively. And it is found that the linear level I GN theory is not superior to the linear wave theory. Finally, various factors affecting the hydroelastic response of VLFS are studied with the implemented algorithm. 展开更多
关键词 hydroelastic responses very large floating structures linear wave theory of finite water depth linear level I Green-Naghdi theory thin plate theory
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Predicting urbanization level by main element analysis and multiple linear regression---taking Xiantao district in Hubei Province as an example
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作者 Li BingyiDepartment of Urban Planning & Architecture, Wuhan Urban Construction Institute,Wuhan 430074, CHINA 《Journal of Geographical Sciences》 SCIE CSCD 1998年第1期90-91,93-94,共4页
In this paper we firstly select main factors relating to urbanization level of Xiantao District in Hubei Province by main element, then, make model of urbanization level by analysis of multiple liner regression, and l... In this paper we firstly select main factors relating to urbanization level of Xiantao District in Hubei Province by main element, then, make model of urbanization level by analysis of multiple liner regression, and lastly predict its urbanization level 展开更多
关键词 urbanization level main element analysis multiple linear regression Xiantao Hubei PROVINCE
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A Production Inventory Model of Constant Production Rate and Demand of Level Dependent Linear Trend
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作者 Shirajul Islam Ukil Md. Sharif Uddin 《American Journal of Operations Research》 2016年第1期61-70,共10页
The proposed model considers the products with finite shelf-life which causes a small amount of decay. The market demand is assumed to be level dependent and in a linear form. The model has also considered the constan... The proposed model considers the products with finite shelf-life which causes a small amount of decay. The market demand is assumed to be level dependent and in a linear form. The model has also considered the constant production rate which stops attaining a desired level of inventories and that is the highest level of inventories. Production starts with a buffer stock and without any sort of backlogs. Due to the market demand and product’s decay, the inventory reduces to the level of buffer stock where again the production cycle starts. With a numerical search procedure the proof of the proposed model has been shown. The objective of the model is to obtain the total average optimum inventory cost and optimum ordering cycle. 展开更多
关键词 Production Inventory level Dependent Linear Trend Constant Production Rate
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