核电厂管道冲蚀磨损分析中的重复测量和评估质量

V. I. Baranenko, O. M. Gulina, S. Mironov, N. L. Salnikov
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引用次数: 1

摘要

本文对碳钢管构件进行了冲蚀磨损(ECW)研究。在重复控制数据的基础上,给出了计算得到的ECW特性,即壁厚减薄和速率。结果表明,由于管道内表面沉积的腐蚀产物及其在运行过程中的迁移,这种估算具有很大的不确定性。此外,随着运行时间的增加,例如寿命的延长,预测结果与控制结果之间的差异会变大。这意味着估计剩余寿命的误差也会增加。本研究以VVER-440反应堆核电站给水管道(273×16 mm)和蒸汽管道(465×16mm)的壁厚测量数据为基础,在较长的时间间隔内进行了足够数量的重复测量。分析了利用Chexal-Horowitz流动加速腐蚀(FAC)模型(EKI-02和EKI-03软件工具)估算管道壁薄化和ECW速率的误差。由于沉积在管道内表面壁面的腐蚀产物是在一个大的时间基础上被夷平的,根据上述预测模型估计的ECW速率与根据当前控制数据估计的ECW速率相差不超过12.5%。在计算壁厚减薄时,由于控制数据有明显的过滤作用,在不升级模型的情况下,估计精度可以达到可接受的16%左右。
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Repeated measurements and quality of estimates in the analysis of NPP pipeline erosion-corrosion wear
The article presents a study carried out on carbon steel pipe components subjected to erosion-corrosion wear (ECW). Based on the repeated control data, the authors present the calculated ECW characteristics, i.e., the wall-thinning and rate. It is shown that such estimates contain great uncertainty due to corrosion products deposited on the pipeline inner surface and their migration during operation. In addition, with an increase in the operating time, for example, when the lifetime is extended, the difference between the forecast and the results of control becomes larger. This means that the error in the estimates of the residual lifetime also increases. The study is based on the data of wall thickness measurements of the feedwater pipeline (273×16 mm) and steam pipeline (465×16mm) of nuclear power plants with the VVER-440 reactors, for which a sufficient number of repeated measurements were performed over a large time interval. An analysis is made of the error in estimating the pipeline wall-thinning and ECW rate using Chexal-Horowitz Flow-Accelerated Corrosion (FAC) Model (EKI-02 and EKI-03 software tools). The estimate of the ECW rate according to the above forecast model differs from the estimate according to the current control data by no more than 12.5%, since the corrosion products deposited on the pipeline inner surface wall are leveled at a large time base. When calculating the wall-thinning, due to the obvious filtering of the control data, it is possible to achieve an acceptable accuracy of estimates, i.e., about 16% without upgrading the model.
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