Abstract

This paper presents robust design optimisation (RDO) of offshore jacket platforms under random wave force. It is well-established that the direct Monte Carlo Simulation (MCS) is the most accurate way to deal with RDO under uncertainty. However, such approach requires extensive computational time for real complex structures. In the present study, a new cumulative distribution function (CDF)-based RDO formulation is proposed in the framework of dual response surface method (RSM) with due consideration to record-to-record variation of random wave force. The proposed approach avoids direct MCS in RDO, thereby evading several repetitive nonlinear dynamic analyses inside the optimisation loop. As the conventional least-squares method-based RSM may be erroneous in response approximation, the adaptive moving least-squares method is adopted in the present study to construct the response surfaces. The RDO is posed as a two-criterion equivalent optimisation problem, where the expected value of objective function and its standard deviation are optimised, satisfying constraint feasibility criteria under uncertainty. Two illustrative examples are presented to demonstrate the effectiveness of the proposed RDO approach. The results show that the proposed approach yields more accurate and robust solutions than the conventional least-squares method-based RDO approach when compared with the most accurate direct MCS-based RDO results.

摘要

本文介绍了随机波浪力下海上导管架平台的稳健设计优化 (RDO)。众所周知，直接蒙特卡罗模拟 (MCS) 是在不确定性下处理 RDO 的最准确方法。然而，这种方法需要大量计算时间来处理真实的复杂结构。在本研究中，在双响应面法 (RSM) 的框架内提出了一种新的基于累积分布函数 (CDF) 的 RDO 公式，并适当考虑了随机波浪力的记录间变化。所提出的方法避免了 RDO 中的直接 MCS，从而避免了优化循环内的多次重复非线性动态分析。由于传统的基于最小二乘法的 RSM 可能在响应近似中是错误的，本研究采用自适应移动最小二乘法构建响应面。RDO 被提出为一个双准则等价优化问题，其中优化目标函数的期望值及其标准差，满足不确定性下的约束可行性准则。提供了两个说明性示例来证明所提议的 RDO 方法的有效性。结果表明，与最准确的基于 MCS 的直接 RDO 结果相比，所提出的方法比传统的基于最小二乘法的 RDO 方法产生更准确和稳健的解决方案。在不确定性下满足约束可行性标准。提供了两个说明性示例来证明所提议的 RDO 方法的有效性。结果表明，与最准确的基于 MCS 的直接 RDO 结果相比，所提出的方法比传统的基于最小二乘法的 RDO 方法产生更准确和稳健的解决方案。在不确定性下满足约束可行性标准。提供了两个说明性示例来证明所提议的 RDO 方法的有效性。结果表明，与最准确的基于 MCS 的直接 RDO 结果相比，所提出的方法比传统的基于最小二乘法的 RDO 方法产生更准确和稳健的解决方案。