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Investigation of different sources in order to optimize the nuclear metering system of gas-oil-water annular flows

机译:不同来源的调查,以优化气油 - 水环形流动核计量系统

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摘要

The used metering technique in this paper is based on the multienergy (at least dual) gamma-ray attenuation. The aim of the current study is investigation of different combinations of sources in order to find the best combination for precise metering gas, oil and water percentages in annular three-phase flows. The required data were generated numerically using Monte Carlo N Particle extended (MCNPX) code. As a matter of fact, the current investigation devotes to predict the volume fractions in the annular three-phase flow, on the basis of a multienergy metering system including different radiation sources and one sodium iodide detector, using the hybrid model. Since the summation of volume fractions is constant, a constraint modeling problem exists, meaning that the hybrid model must predict only two volume fractions. Six hybrid models associated with the number of applied radiation sources are employed. The models are applied to predict the oil and gas volume fractions. For the next step, the hybrid models are trained based on numerically obtained data from the MCNPX code. The results show that the best prediction results are obtained for the oil and gas volume fractions of a system with the (Am-241 & Cs-137) radiation sources.
机译:本文的使用计量技术基于多焦(至少双)伽马射线衰减。目前研究的目的是调查不同组合的来源,以便在环形三相流动中找到精确计量气体,油和水百分比的最佳组合。使用Monte Carlo N粒子扩展(MCNPX)代码数值方式生成所需数据。事实上,基于包括混合模型的不同辐射源和一个碘化钠检测器的多型计量系统,目前的研究致力于预测环形三相流动中的体积分数。由于体积分数的总和是恒定的,因此存在约束建模问题,这意味着混合模型必须仅预测两个体积分数。采用与应用辐射源数量相关联的六种混合模型。施加模型以预测油和气体体积分数。对于下一步,基于来自MCNPX代码的数值获得的数据训练混合模型。结果表明,用(AM-241&CS-137)辐射源的系统的油和气体体积分数获得最佳预测结果。

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