A Chessboard Model for Simultaneous Optimization of Mass Exchange Networks

doi:10.19596/j.cnki.1001-246x.8566

Abstract

Abstract:

A chessboard model of mass exchange networks (CBM-MEN) is proposed. The CBM-MEN has characteristics of compact structure, simple expression, and flexible stream arrangement. A phase of eliminating mass exchanger is added to a random walk algorithm with compulsive evolution. The algorithm is combined with the chessboard model. During optimization process, the mass exchange load is used as an optimization variable. Finally, the simultaneous optimization method is applied to two cases, recovery of copper from liquid effluents of an etching plant and dephenolization of aqueous wastes. The total annual cost of optimized structures is decreased by 5.8‰ and 1.6‰, respectively. It shows that the method has good search domain and search capability.

Key words: mass exchange network, chessboard model, random walk algorithm with compulsive evolution, global optimization

Zhikang YI, Guomin CUI, Zhiqiang ZHOU, Yuan XIAO, Siheng XIONG, Xiubao MA. A Chessboard Model for Simultaneous Optimization of Mass Exchange Networks[J]. Chinese Journal of Computational Physics, 2023, 40(4): 500-510.

Figures/Tables 14

References 25

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rich stream	G/(kg·s^-1)	yⁱⁿ/(kg·kg^-1)	y^out/(kg·kg^-1)	lean stream	L/(kg·s^-1)	xⁱⁿ/(kg·kg^-1)	x^out/(kg·kg^-1)	Cost/(＄·s·kg^-1·a^-1)
R₁	0.25	0.13	0.1	S₁	∞	0.03	0.07	58 680
R₂	0.1	0.06	0.02	S₂	∞	0.001	0.002	704 160

rich stream	G/(kg·s^-1)	yⁱⁿ/(kg·kg^-1)	y^out/(kg·kg^-1)	lean stream	L/(kg·s^-1)	xⁱⁿ/(kg·kg^-1)	x^out/(kg·kg^-1)	Cost/(＄·s·kg^-1·a^-1)
R₁	0.25	0.13	0.1	S₁	∞	0.03	0.07	58 680
R₂	0.1	0.06	0.02	S₂	∞	0.001	0.002	704 160

Method	L₁/(kg·s^-1)	L₂/(kg·s^-1)	Number of trays	Packed height/m	Number of units	Splits rich/lean	TAC/(＄·a^-1)	difference/%
Ref.[9]	0.276	0.023	4	0.457	3	0/1	52 300^*	7.88
Ref.[24]	0.3	0.021	4	0.309	3	0/1	52 068^*	7.40
Ref.[13]	0.276 9	0.022 1	4	0.319	3	0/1	50 855^*	4.90
Ref.[23]	0.279	0.018 6	4	0.33	3	0/0	49 000	1.07
Ref.[4]	0.281	0.018 4	4	0.33	3	0/0	49 000	1.07
Ref.[15]	0.278 6	0.018 4	4	0.295	3	0/0	48 763	0.58
This work	0.27797	0.018 08	4	0.288 77	3	0/0	48 479	0.00

Method	L₁/(kg·s^-1)	L₂/(kg·s^-1)	Number of trays	Packed height/m	Number of units	Splits rich/lean	TAC/(＄·a^-1)	difference/%
Ref.[9]	0.276	0.023	4	0.457	3	0/1	52 300^*	7.88
Ref.[24]	0.3	0.021	4	0.309	3	0/1	52 068^*	7.40
Ref.[13]	0.276 9	0.022 1	4	0.319	3	0/1	50 855^*	4.90
Ref.[23]	0.279	0.018 6	4	0.33	3	0/0	49 000	1.07
Ref.[4]	0.281	0.018 4	4	0.33	3	0/0	49 000	1.07
Ref.[15]	0.278 6	0.018 4	4	0.295	3	0/0	48 763	0.58
This work	0.27797	0.018 08	4	0.288 77	3	0/0	48 479	0.00

rich stream		G/(kg·s^-1)		yⁱⁿ/(kg·kg^-1)		y^out/(kg·kg^-1)
R1		2		0.05		0.010
R2		1		0.03		0.006

lean stream	L/(kg·s^-1)		xⁱⁿ/(kg·kg^-1)		x^out/(kg·kg^-1)	Cost/(＄·s·kg^-1)
S1	≤5		0.005		0.015	free
S2	≤3		0.01		0.030	free
S3	∞		0.001 3		0.015	309 600