High pressure multi-component vapor-liquid equilibrium data and model predictions for the LNG industry

被引:9
|
作者
Hughes, Thomas J. [1 ]
Guo, Jerry Y. [1 ]
Baker, Corey J. [1 ]
Rowland, Darren [1 ]
Graham, Brendan F. [1 ]
Marsh, Kenneth N. [1 ]
Huang, Stanley H. [2 ]
May, Eric F. [1 ]
机构
[1] Univ Western Australia, Sch Mech & Chem Engn, Fluid Sci & Resources Div, Crawley, WA 6009, Australia
[2] Chevron Energy Technol Co, Houston, TX 77002 USA
来源
基金
澳大利亚研究理事会;
关键词
LNG; Natural gas; Distillation; Phase equilibrium; Gas purification; EQUATION-OF-STATE; TEMPERATURES;
D O I
10.1016/j.jct.2017.05.023
中图分类号
O414.1 [热力学];
学科分类号
摘要
Accurate simulations of scrub columns in liquefied natural gas (LNG) plants are challenging, requiring frequent solution of the non-linear equations governing vapor-liquid equilibrium (VLE), material, and energy balances for multi-component mixtures. Reliable fluid property predictions at high pressures and low temperatures are thus crucial; however, no high-quality multi-component VLE data at conditions relevant to the LNG scrub column are available to test commonly-used equations of state (EOS). Here we report VLE measurements at pressures to 9 MPa and temperatures from (203 to 273) K for mixtures containing CH4, C2H6, C3H8, iC(4)H(10), nC(4)H(10) and/or N-2. Far from the mixture's critical point, the GERG-2008 EOS predictions were more accurate than the Peng-Robinson EOS predictions. Above 7 MPa both EOS under-predicted the liquid phase's methane content and over-predicted its butane content by 10-50 times the experimental uncertainty. Rowland et al.'s recent revision of the GERG model reduced the maximum deviations by (17-35)%. Further optimizations should improve the constituent binary departure functions and hence improve the description of multicomponent VLE data, particularly at conditions relevant to LNG production. (C) 2017 Elsevier Ltd.
引用
收藏
页码:81 / 90
页数:10
相关论文
共 50 条
  • [1] Multi-component vapor-liquid equilibrium model for LES of high-pressure fuel injection and application to ECN Spray A
    Matheis, Jan
    Hickel, Stefan
    INTERNATIONAL JOURNAL OF MULTIPHASE FLOW, 2018, 99 : 294 - 311
  • [2] Artificial neural network aided vapor-liquid equilibrium model for multi-component high-pressure transcritical flows with phase change
    Srinivasan, Navneeth
    Yang, Suo
    PHYSICS OF FLUIDS, 2024, 36 (08)
  • [3] Prediction of vapor-liquid equilibria for multi-component systems at high pressure with binary interaction function
    Liu, GH
    Dai, SS
    CHEMICAL JOURNAL OF CHINESE UNIVERSITIES-CHINESE, 2000, 21 (12): : 1875 - 1879
  • [4] In situ adaptive tabulation of vapor-liquid equilibrium solutions for multi-component high-pressure transcritical flows with phase change
    Zhang, Hongyuan
    Srinivasan, Navneeth
    Yang, Suo
    JOURNAL OF COMPUTATIONAL PHYSICS, 2024, 500
  • [5] Thermodynamic consistency of vapor-liquid equilibrium data at high pressure
    Bertucco, A
    Barolo, M
    Elvassore, N
    AICHE JOURNAL, 1997, 43 (02) : 547 - 554
  • [6] Thermodynamic consistency of vapor-liquid equilibrium data at high pressure
    Universita di Padova, Padova, Italy
    AIChE J, 2 (547-554):
  • [7] A Lattice Boltzmann model for multi-component vapor-liquid two phase flow
    Gong, Bin
    Liu, Xuan
    Qin, Guan
    Shiyou Kantan Yu Kaifa/Petroleum Exploration and Development, 2014, 41 (05): : 633 - 640
  • [8] A Lattice Boltzmann model for multi-component vapor-liquid two phase flow
    Gong Bin
    Liu Xuan
    Qin Guan
    PETROLEUM EXPLORATION AND DEVELOPMENT, 2014, 41 (05) : 695 - 702
  • [9] Vapor-liquid critical properties of multi-component fluid mixture
    Cai, J
    Qiu, DL
    Zhang, LN
    Hu, Y
    FLUID PHASE EQUILIBRIA, 2006, 241 (1-2) : 229 - 235
  • [10] Pressure dependence of vapor-liquid equilibrium ratio of trace component
    Ikari, A
    Esaki, S
    Ohtake, T
    KAGAKU KOGAKU RONBUNSHU, 1999, 25 (03) : 488 - 490