Flow pattern identification for three‐phase distillation with a nonequilibrium modeling
Flow pattern identification for three‐phase distillation with a nonequilibrium modeling
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DOI：
10.1002/apj.559
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发表时间：
2011-05
影响因子：
1.8
通讯作者：
L. Chen;J. Repke;Shuqing Wang
中科院分区：
文献类型：
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作者：
L. Chen;J. Repke;Shuqing Wang
对不确定的气-液-液流体动力学的恐惧使工艺工程师远离了三相参与，其中最不确定的是第二液相的流动模式。为此，提出了一种基于第一性原理模型的三相精馏流型识别策略。在实验室层析填充柱上进行了代表性实验，并将实验结果作为估计的参考数据。建立了严格考虑相间传质的动态非平衡模型。然后使用多重射击方法将得到的估计问题离散化，形成具有有限数量决策变量的大规模NLP问题。计算结果表明，二次液的流动形式与液气载荷密切相关，对三相柱内分离效率的变化起着至关重要的作用。版权所有©2011科廷科技大学和约翰威利父子有限公司
The fear of the uncertain vapor–liquid–liquid hydrodynamics has guided process engineers away from a three-phase involvement, of which the most uncertain is the flow pattern of the second liquid phase. Hence, a first-principle model-based estimation strategy was proposed to identify the flow pattern in the three-phase distillation. Representative experiments were performed in a laboratory-sclae packed column, and the results were sampled as reference data for the estimation. A dynamic nonequilibrium (NEQ) model was built up to consider the inter-phase mass transfer rigorously. The resulting estimation problem was then discretized using the multiple-shooting method, to formulate a large-scale NLP problem with a finite number of decision variables. The estimated results reveal that the flow pattern of the second liquid has a close relationship with the liquid and gas loads, and it could play a critical role for the variation of the separation efficiency inside a three-phase column. Copyright © 2011 Curtin University of Technology and John Wiley & Sons, Ltd.