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Synthesis of mass exchanger networks in a two-step hybrid optimization strategy

机译:两步混合优化策略中群众交换网络的合成

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We present a new method for the synthesis of mass exchanger networks (MENs) involving packed columns. Simultaneous synthesis of MENs is typically done through the use of mixed-integer nonlinear program (MINLP) optimization, with simplifications made in the mathematical representations of the exchangers due to computational difficulty in solving large non-convex mixed-integer problems. The methodology proposed in this study makes use of the stage-wise based superstructure MINLP formulation for the network synthesis. This stage-wise superstructure model incorporates fixed mass transfer coefficients, fixed column diameters, no pressure drops, and unequal compositional mixing for models. In this paper, the simplified MINLP model is further improved by including a detailed individual packed column design in a non-linear programming (NLP) sub-optimization step, where orthogonal collocation is utilized for the partial differential equations, and optimal packing size, column diameter, column height, pressure drops, and fluid velocities. Detailed designs are then used to determine correction factors that update the simplified stage-wise superstructure models to more accurately portray the chosen design. Once the MINLP is updated with these correction factors, the model is re-run, with new correction factors obtained. This iterative procedure is repeated until convergence between the objective function of the MINLP and that of the NLP sub-optimization is achieved, or until a maximum number of iterations is reached. The methodology is applied to two examples and is shown to be robust and effective in generating new topologies, and in finding superior networks that are physically realizable. (C) 2017 Elsevier Ltd. All rights reserved.
机译:我们提出了一种涉及包装列的群众交换网络(男性)的新方法。通常通过使用混合整数非线性程序(MINLP)优化来进行同时合成,以简化在求解大型非凸混合整数问题方面的计算难题,在交换器的数学表示中进行。本研究中提出的方法利用基于阶段的基于Superstructure MinLP制剂进行网络合成。该阶段明智的上部结构模型包括固定的传质系数,固定柱直径,无压降和模型的不等组成混合。在本文中,通过在非线性编程(NLP)子优化步骤中包括在非线性编程(NLP)子优化步骤中的详细的单独包柱设计,进一步改善了简化的MINLP模型,其中正交绑定用于部分微分方程,以及最佳打包大小,列直径,柱高,压降和流体速度。然后使用详细设计来确定更新简化舞台上层建筑模型以更准确地描绘所选择的设计的校正因子。使用这些校正因子更新MINLP后,模型重新运行,获得了新的校正因子。重复该迭代过程,直到MINLP的目标函数与NLP子优化的目标函数之间的收敛,或者直到达到最大数量的迭代。该方法应用于两个示例,并且被证明是在生成新拓扑中的稳健和有效,并且在找到物理可实现的卓越网络中。 (c)2017 Elsevier Ltd.保留所有权利。

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