Response based analysis (RBA) has been developed for prediction of extreme N-year return period responses and design metocean conditions of offshore structures. For applying the RBA, the behaviour of the offshore system subjected to a long history of metocean conditions needs to be predicted, and then, the probabilistic analysis is applied to estimate its long-term responses. Due to the large number of analysis cases required, the structural simulation is usually performed either by simplifying the structural model or by using computationally efficient tools, such as frequency-domain (FD) analysis. These approaches usually decrease the accuracy of predictions mainly when they are utilized for nonlinear systems. On the other hand, employing time-domain (TD) simulations leads to more accurate results but it is computationally expensive. Application of RBA for a weathervaning FPSO, which is the subject of the present study, makes TD analysis an essential requirement because of a highly nonlinear behaviour of the system. In the present study, an efficient methodology is proposed that aims at reducing the computational efforts of RBA by joint application of TD and FD simulations in combining the structural and statistical analyses through a single process, such that the number of time-consuming TD simulations is minimized. After initial screening using the results from FD simulations, the methodology identifies the response events (storms) that contribute the most to the N-year response and sets out an iterative process in which only those events that are most important are analysed by fully-coupled TD simulations. Within such events, a similar approach is also applied to intervals (sea states) where only the most contributing intervals are analysed in TD, and the remaining intervals are left for a less accurate FD analysis without sacrificing the overall accuracy. The proposed methodology provides a robust framework for distinguishing between “mild” and “severe” response events, without specifying any predefined limits for the metocean parameters or making a subjective judgement. Although it is developed for the mooring system of a weathervaning FPSO, it should also be applicable to any type of offshore structure and any structural response. This paper is the first part of the study and concentrates on the development of the efficient methodology to optimize the application of RBA to FPSO mooring systems, whilst its detailed application is subject of the second part of the study.

已经开发了基于响应的分析（RBA），用于预测极端N年回报期的响应和海上结构的设计海洋状况。为了应用RBA，需要预测海上系统长期受海洋条件影响的行为，然后，应用概率分析来估计其长期响应。由于需要大量的分析案例，通常通过简化结构模型或使用计算效率高的工具（例如频域（FD）分析）来执行结构仿真。这些方法通常主要在将其用于非线性系统时降低预测的准确性。另一方面，采用时域（TD）仿真可以得到更准确的结果，但计算量大。RBA在风标FPSO中的应用是本研究的主题，由于系统的高度非线性行为，TD分析成为必不可少的要求。在本研究中，提出了一种有效的方法，其目的是通过将TD和FD仿真联合应用，从而通过单个过程将结构分析和统计分析结合起来，从而减少RBA的计算工作量，从而使耗时的TD仿真数量减少。最小化。在使用FD模拟的结果进行初步筛选之后，该方法确定了对N年响应贡献最大的响应事件（暴风雨），并提出了一个迭代过程，在该过程中，只有最重要的那些事件才由全耦合分析。 TD模拟。在这样的事件中 类似的方法也适用于间隔（海况），其中仅在TD中分析最重要的间隔，而其余间隔留给精度较低的FD分析，而不会牺牲整体精度。所提出的方法提供了一个可靠的框架，用于区分“轻度”和“严重”响应事件，而无需为气象参数指定任何预定义的限制或做出主观判断。尽管它是为风标FPSO的系泊系统开发的，但它也应适用于任何类型的海上结构和任何结构响应。本文是研究的第一部分，重点在于开发有效的方法，以优化RBA在FPSO系泊系统中的应用，