This paper presents a new procedure for the optimization of the mooring design of floating platforms, in which an automatic design sequence is also established. Regarding the optimization philosophy, the following aspects are dealt with:
• The optimization of the platform heading and its mooring pattern, taking into account the environmental force spreading;
• optimum line length or line tension for each mooring line, associated to the optimization of the mooring line materials and sizes.
Basically, the main goal of this paper is to introduce a new method, which will provide the quickest way to find the best mooring system, defined here as that which minimizes platform responses.A genetic algorithm (GA) is applied in this contribution, and this paper describes exactly the procedure of developing a GA code directed toward the solution of mooring design optimization problems. In order to prove the efficiency and the vast potential of the proposed algorithm as a design tool, sample moorings are analyzed for different environmental conditions and the final results, including the time required to run them, are presented. 相似文献
—Ocean wave propagation is slow,visible and measurable,so a wave theory can be used to approxi-mately predict the imminnent wave force on an offshore structure based on measured,real-time wave elevation nearthe structure.This predictability suggests the development of a more efficient algorithm,than those that have beendeveloped for structures under wind and seismic loads,for the active vibration control of offshore structures.Thepresent study delveops a mutiple-step predictive optimal control(MPOC)algorithm that accounts for multiple-step external loading in the determibation of optimal control forces.The control efficiency of the newly developedMPOC algorithm has been investigated under both regular(single-frequency)and irregular(multiple-frequency)wave loads,and compared with that of two other well-known optimal control algorithms:classical linear optimalcontrol(CLOC)and instantaneou optimal control(IOC). 相似文献
为了提高AVO(amplitude versus offset)反演结果的精度和横向连续性,本文提出了一种新的AVO反演约束方法,该方法结合贝叶斯原理和卡尔曼滤波算法实现了对反演参数纵向和横向的同时约束.文章首先结合反演参数的纵向贝叶斯先验概率约束和反演参数的横向连续性假设建立了与卡尔曼滤波算法对应的AVO反演系统的数学模型,然后将该数学模型代入卡尔曼滤波算法框架,利用卡尔曼滤波算法实现了双向约束AVO反演.二维模型测试和实际数据测试结果表明,相对于单纯的纵向贝叶斯先验概率约束,双向约束能更准确地刻画参数的横向变化,得到更准确、横向连续性更好的反演结果.