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Evaluating the Improvement of Cross-Correlation-Based Flow Measurement by Periodic Fluid Injection

机译:通过周期性流体注射评估基于互相关的流量测量的改进

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摘要

Nuclear power plants (NPPs) require accurate measurement of mass flow rates. Advanced flowmeters have been widely applied in several current industries; however, the operating environment in NPPs is especially harsh because of high temperature, high radiation, and extremely corrosive conditions. Several of the advanced reactor designs, such as liquid sodium pool reactors and integral small modular reactors, do not have conventional primary piping systems. These designs require an alternative method to accurately measure primary flow. Cross-correlation function (CCF) flow estimation can estimate the flow velocity indirectly without any specific instruments for flow measurement. The target flow rate is derived by the delay time between two sensors located near each other along the flow direction. Temperature sensors are a common choice for this function because they are reliable, economical, and widely used in various industries. The delay time is inferred by applying the CCF to the signals collected from two or more sensors. CCF flow estimation can be performed in any structure of the flow region, not limited to pipes. One challenge for the CCF flow estimation is that the accuracy of the flow measurement is mainly determined by the inherent local process variation, which is small compared to the uncorrelated noise. To differentiate the process variations from the uncorrelated noise, this paper demonstrates periodic fluid injection of a different temperature before the sensors to amplify common process variation. The feasibility and accuracy of this method have been investigated through a physical flow loop experiment designed to verify the CCF flow estimation using fluid injection. Several parameters must be selected when designing the fluid injection CCF measurement system, such as the distance between the fluid injection site and the sensors, the injection period, and the injection flow rate. A series of tests was conducted to investigate whether these parameters were related to the accuracy of the CCF flow estimation and to identify appropriate values for these parameters for different flow regimes. The results show that the fluid injection method improves the flow measurement performance, and the appropriate design of flow injection and measurement geometry produces better flow characterization performance over a range of flow rates.
机译:核电站(NPPS)需要精确测量质量流量。高级流量计已广泛应用于几个当前行业;然而,由于高温,高辐射和极其腐蚀性,NPPS中的操作环境尤其严苛。几个先进的反应器设计,如液体钠池反应器和整体小型模块化反应器,没有传统的主要管道系统。这些设计需要一种替代方法来准确测量主要流程。互相关函数(CCF)流量估计可以间接地估计流速,而没有任何用于流量测量的仪器。目标流速由沿着流动方向彼此靠近的两个传感器之间的延迟时间来源。温度传感器是这种功能的常见选择,因为它们是可靠的,经济的,并且广泛应用于各种行业。通过将CCF应用于从两个或更多个传感器收集的信号来推断延迟时间。 CCF流程估计可以在流动区域的任何结构中执行,不限于管道。 CCF流程估计的一个挑战是流量测量的准确性主要由固有的本地过程变化决定,与不相关的噪声相比很小。为了区分从不相关的噪声的过程变化,本文展示了传感器之前的不同温度的周期性流体注入,以放大普通过程变化。通过物理流回路实验研究了该方法的可行性和准确性,该实验旨在使用流体注入验证CCF流量估计。在设计流体喷射CCF测量系统时,必须选择几个参数,例如流体喷射部位和传感器之间的距离,喷射时段和注射流量。进行了一系列测试以研究这些参数是否与CCF流程估计的准确性有关,并为不同流动制度识别这些参数的适当值。结果表明,流体注入方法改善了流量测量性能,流动喷射和测量几何形状的适当设计在一系列流速上产生了更好的流量表征性能。

著录项

  • 来源
    《Nuclear Technology》 |2021年第11期|1725-1745|共21页
  • 作者单位

    University of Tennessee Department of Nuclear Engineering Knoxville Tennessee 37996;

    University of Tennessee Department of Nuclear Engineering Knoxville Tennessee 37996;

    University of Tennessee Department of Nuclear Engineering Knoxville Tennessee 37996;

    University of Tennessee Department of Nuclear Engineering Knoxville Tennessee 37996;

    University of Tennessee Department of Nuclear Engineering Knoxville Tennessee 37996;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cross correlation; flow rate inference; thermal-hydraulic experiments; signal-to-noise ratio;

    机译:交叉相关;流量推理;热液压实验;信噪比;

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