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Modeling MEA with the CPA equation of state: A parameter estimation study adding local search to PSO algorithm

机译:使用CPA状态方程建模MEA:一项参数估计研究,将局部搜索添加到PSO算法中

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Due to the intensification of environmental constrains combined with the tendency to process crude oils with high C/H, S/H ratios and natural gas with increasing CO2/CH4 and H2S/CH4 ratios, acid gas removal from gas streams is probably the most required process in the petroleum and gas industries nowadays. Absorption with aqueous alkanolamines such as MEA, is one commonly used process for this purpose. On modeling MEA with CPA, it has been shown that only the co-volume b parameter does not present local minima near the final solution and, also, VLE data are not sufficient to estimate reliable parameters for MEA. This work proposes adding LLE information systematically in the CPA parameter estimation procedure. At first, the parameter search space is defined by the results from the PSO sensitivity analysis for VLE considering the experimental error for vapor pressures and liquid densities (objective function cut off). Then, two possible methodologies are discussed: the first one uses all the possible parameter sets and check them against the LLE and VLE experimental data. The second method explicitly incorporates LLE information into the objective function and uses both PSO and PSO-simplex hybrid algorithm to improve the convergence and refine the final solution. With this methodology it was possible to model simultaneously LLE and VLE. The CPA was then applied for a mixture containing cross-association (MEA-water) and the results show good agreement with experimental data indicating the effectiveness of the proposed strategies. (C) 2015 Elsevier B.V. All rights reserved.
机译:由于环境约束的加剧以及加工高C / H,S / H比的原油以及增加CO2 / CH4和H2S / CH4比的天然气的趋势,从气流中去除酸性气体可能是最需要的当今石油和天然气工业中的过程。为此目的,一种含水链烷醇胺如MEA的吸收是一种常用的方法。在使用CPA对MEA进行建模时,已经表明,只有co-volume b参数不会在最终解决方案附近出现局部最小值,而且,VLE数据不足以估计MEA的可靠参数。这项工作建议在CPA参数估计程序中系统地添加LLE信息。首先,参数搜索空间是由VLE的PSO灵敏度分析结果确定的,其中考虑了蒸汽压和液体密度的实验误差(目标函数被截断)。然后,讨论了两种可能的方法:第一种使用所有可能的参数集,并根据LLE和VLE实验数据对其进行检查。第二种方法将LLE信息明确纳入目标函数,并同时使用PSO和PSO-simplex混合算法来改善收敛性并完善最终解决方案。通过这种方法,可以同时对LLE和VLE进行建模。然后将CPA应用于包含交叉缔合(MEA-水)的混合物,结果与实验数据吻合良好,表明所提出策略的有效性。 (C)2015 Elsevier B.V.保留所有权利。

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