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Expanded fluid-based thermal conductivity model for hydrocarbons and crude oils

机译:扩展的基于流体的碳氢化合物和原油导热系数模型

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Thermal conductivity data for crude (mainly heavy) oils and mixtures of crude oils and pure hydrocarbons were collected at temperatures from 20 to 125 degrees C and pressures up to 10 MPa using a hot wire apparatus. A criterion was established to screen out data that were affected by convection. The screened data and data from the literature were used to develop an Expanded Fluid (EF) based thermal conductivity model for pure hydrocarbons, crude oils and their mixtures. The proposed model is applicable across the entire phase diagram including the critical region; however, it does not predict the critical enhancement of thermal conductivity observed in the vicinity of the critical point. The model inputs are the density of the fluid, the pressure, the dilute gas thermal conductivity, the compressed state density, and three other fluid specific parameters. The gas thermal conductivity is calculated from a well-established correlation. The compressed state density is obtained from the literature or from fitting the EF viscosity model to viscosity data. The three fluid specific parameters are determined by fitting the model to thermal conductivity data. The model fits the data of 63 pure hydrocarbons at temperatures from -150 to 330 degrees C and pressures up to 200 MPa with average deviation of 4%, except in the vicinity of the critical point (0.97 < reduced temperature < 1.1). The model also fits the data of 7 different crude oils at temperatures and pressures up to 150 degrees C and 10 MPa to within 0.3% of the experimental data. Mass based mixing rules were proposed for the model parameters of mixtures. The data for 19 pure hydrocarbon binaries at atmospheric pressure were predicted with average deviation of 0.5% and that of 8 bitumen/solvent pseudobinaries, at pressures up to 10 MPa, was predicted with average deviation of 1.6%. The introduction of binary interaction parameters into the mixing rules halved the magnitude of the deviations.
机译:使用热线仪在20至125摄氏度的温度和最高10 MPa的压力下收集原油(主要是重油)以及原油和纯烃混合物的热导率数据。建立了一个标准以筛选出受对流影响的数据。筛选出的数据和来自文献的数据用于建立基于膨胀流体(EF)的纯烃,原油及其混合物的导热系数模型。所提出的模型适用于整个相图,包括关键区域。然而,它不能预测在临界点附近观察到的导热率的临界提高。模型输入为流体密度,压力,稀气体导热系数,压缩态密度和其他三个流体特定参数。气体热导率是根据公认的相关性计算得出的。压缩态密度是从文献中获得的,或者是通过将EF粘度模型拟合到粘度数据而获得的。通过将模型拟合到热导率数据,可以确定三个特定于流体的参数。该模型拟合了63种纯烃的数据,温度范围为-150至330摄氏度,压力高达200 MPa,平均偏差为4%,但临界点附近(0.97 <降低的温度<1.1)除外。该模型还拟合了7种不同原油在高达150摄氏度和10 MPa的温度和压力下的数据,仅占实验数据的0.3%以内。针对混合物的模型参数,提出了基于质量的混合规则。预测大气压下19种纯烃二元数据的平均偏差为0.5%,预测压力高达10 MPa时8种沥青/溶剂假二元的数据平均偏差为1.6%。将二元相互作用参数引入混合规则,将偏差的大小减半。

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