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A new model for volume fraction measurements of horizontal high-pressure wet gas flow using gamma-based techniques

机译:基于伽马技术的水平高压湿气流量的体积分数测量的新模型

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摘要

The accurate predictions of void fraction and gas volume fraction are important in characterizing wet gas flow, as they are the basic input for determining other key flow parameters, such as flow velocity and flow rate of each phase. In previous studies, empirical relationships were used to predict void fraction and gas volume fraction, which have limited applicability due to the lack of detailed structural and dynamic information involved in two-phase flow. Hence, in this work, attempts are being made to develop a model based on a simplified two-phase interfacial structure. A slip ratio based equal-diameter double-circle model is proposed to predict the void fraction and gas volume fraction using gamma ray attenuation method for high-pressure wet gas conditions. Model predictions were verified against experiments in a 172.0 mm inner diameter horizontal pipe. Nitrogen and kerosene were used as the test fluids with gas volume fractions ranging from 92% to 100%. The relative errors in the line-averaged void fraction predicted by the slip ratio based model were within +/- 2%. In addition, this model can be used to explain the relationship between the key flow parameters and further to predict the optimal measuring angle of the gamma rays. The line-averaged void fraction measured by the gamma ray attenuation method at a proper angle predicted by the model is equal to the gas volume fraction for these high-pressure wet gas conditions, with an average relative error of 0.2%.
机译:空隙级分和气体体积分数的精确预测是在表征湿气体流动的基本输入中是重要的,因为它们是用于确定其他关键流量参数的基本输入,例如每个相的流速和流速。在先前的研究中,使用经验关系来预测空隙部分和气体体积分数,这具有由于缺乏两相流的详细结构和动态信息而具有有限的适用性。因此,在这项工作中,正在尝试基于简化的两相界面结构开发模型。提出了一种基于平均直径的双圆模型的滑移比以使用伽马射线衰减方法来预测空隙率和气体体积分数,用于高压湿气体条件。验证了模型预测,验证了172.0 mm内径水平管中的实验。使用氮气和煤油作为试验流体,气体体积级分的测量液为92%至100%。基于滑移比模型预测的线平均空隙部分中的相对误差在+/- 2%之内。另外,该模型可用于解释关键流量参数之间的关系,进一步预测伽马射线的最佳测量角度。通过伽马射线衰减法以由模型预测的适当角度测量的线平均空隙级分等于这些高压湿气体条件的气体体积分数,平均相对误差为0.2%。

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