期刊
INTERNATIONAL JOURNAL OF THERMOPHYSICS
卷 42, 期 12, 页码 -出版社
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s10765-021-02907-9
关键词
Heptane; Methane; Propane; Thermal conductivity; Transient hot-wire
资金
- GPA Midstream Association
- Australian Research Council [LP130101018, IC150100019]
- Australian Research Council [LP130101018] Funding Source: Australian Research Council
Thermal conductivity measurements of three ternary hydrocarbon mixtures were conducted using a transient hot-wire apparatus, with results showing that the extended corresponding states (ECS) model can accurately represent the data at high pressure conditions without parameter tuning, while the SUPERTRAPP model has significant deviations when predicting natural gas thermal conductivities.
The prediction of thermophysical properties for hydrocarbon mixtures at high pressures, and conditions near the phase boundary or critical point is challenging. However, natural gas processing applications have an increasing need for reliable property predictions at such conditions. In this work, thermal conductivity measurements of three ternary mixtures (methane + propane with heptane at concentration up to 15 mol%) were carried out with a transient hot-wire apparatus. Measurements of the three ternary mixtures were conducted over the temperature range from (199.1 to 424.2) K and the pressure range between (10.41 and 31.55) MPa at single phase conditions with a relative combined expanded uncertainty (k = 2) between 0.015 and 0.056. The measured values were compared to predictions made with the extended corresponding states (ECS) model and SUPERTRAPP model implemented in the software packages REFPROP 10 and MultiFlash 6.2, respectively. The relative deviations of the measured thermal conductivities from the model predictions were (- 5.7 to + 2.4) % for the ECS model and (- 21.1 to - 0.6) % for the SUPERTRAPP model. This indicates the latter, older model should not be used to estimate natural gas thermal conductivities, particularly at high pressure conditions, while the ECS model is capable of representing the data within their uncertainty with no parameter tuning required.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据