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A KNN BASED COLLAPSE METHODOLOGY AND RECENT QUALIFICATION OF FLEXIBLE PIPES IN DEEPWATER APPLICATION

机译:基于KNN的折叠方法和深水应用柔性管的最新资格

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As the flexible pipe industry targets more on deepwater applications, collapse performance of flexible pipes becomes a key challenge due to the huge hydrostatic pressure during installation and service. The collapse strength of flexible pipes largely depends on the structural characteristics of carcass, pressure sheath and pressure armor layers. Therefore, the collapse prediction methodology involving a sound modeling of these layers is essential. Over the years, Baker Hughes have collected a large amount of collapse testing data. The prediction tool needs to be validated and calibrated against all the collapse tests for best accuracy. In this paper, the latest progress of the collapse prediction methodology and qualification tests are presented. A generalized collapse model was developed to predict the collapse pressure of flexible pipes. This model incorporates the advantages of both the weighted kNN regression technique and an analytical collapse model. It is able to reproduce the exact collapse pressure on the pipes tested and can predict the collapse pressure of other pipe designs not tested. As part of the qualification process, the capacity to prevent collapse must be demonstrated. Several flexible pipes were designed based on this generalized prediction methodology for deep water application, and pipe samples were manufactured using industrial production facilities for collapse tests. The results show that flexible pipes following current design guidelines are suitable for deepwater applications.
机译:由于柔性管道行业对深水应用进行了更多地,柔性管的塌陷性能成为由于安装和服务期间宽敞的静水压力而成为关键挑战。柔性管的坍塌强度主要取决于胎体,压力护套和压力铠装层的结构特性。因此,涉及这些层的声音建模的崩溃预测方法是必不可少的。多年来,Baker Hughes收集了大量的崩溃测试数据。预测工具需要验证并校准所有折叠测试以获得最佳精度。在本文中,提出了崩溃预测方法和资格测试的最新进展。开发了广义崩溃模型以预测柔性管的塌陷压力。该模型包括加权KNN回归技术和分析折叠模型的优点。它能够在测试的管道上重现确切的塌陷压力,可以预测其他管道设计的塌陷压力。作为资格过程的一部分,必须证明防止崩溃的能力。基于该广义预测方法设计了几种柔性管,用于深水应用,使用工业生产设施制造管样品进行折叠试验。结果表明,电流设计指南后的柔性管适用于深水应用。

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