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优化设计萃取隔板精馏塔分离苯-环己烯体系

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苯和环己烯共沸物的高效节能分离是常见的工业难题,而EDWC(萃取隔板精馏塔)在共沸物的分离中具有重要的应用前景,目前公开的文献中鲜有关于EDWC工艺对苯和环己烯分离的报道.以氯化胆碱/乙酰丙酸摩尔比为1∶2作为萃取剂,探索EDWC技术在苯和环己烯分离中的应用,采用粒子群算法对该工艺进行优化设计.考虑到粒子群算法是一种随机优化算法,引入变异系数对算法的稳定性能进行评价.最后,引入年度总成本、二氧化碳排放量、㶲损失3个定量指标从经济性、环境性和热力学性3个方面对EDWC工艺和传统的两塔萃取精馏工艺进行全面对比.结果表明:与传统的两塔萃取精馏工艺相比,EDWC工艺可减少19.15%的年度总成本、36.08%的二氧化碳排放量19.99%的㶲损失以及8.03%的萃取剂消耗量.EDWC工艺分离苯和环己烯混合物具有优异的分离效率和显著的节能优势.
Optimal design of extractive dividing wall column for separating benzene-cyclohexene
The high efficiency and energy-saving separation of benzene and cyclohexene azeotrope is a common industrial problem,while the EDWC(extractive dividing wall column)has a significant application prospect in the separation of azeotropes.Fewer literature was reported for separating benzene and cyclohexene by EDWC.By using choline chloride and levulinic acid with molar ratio 1∶2 as the extraction solvent,the EDWC process was explored for the separation of benzene and cyclohexene,with the optimal flow sheet designed by the PSO(particle swarm algorithm).Considering that PSO was a stochastic optimization algorithm,the coefficient of variation was introduced to evaluate its stability.Finally,three quantitative indicators of the annual total cost CTA,carbon dioxide emissions and exergy loss were calculated to comprehensively compare the EDWC process with the CED(conventional extractive distillation)process in terms of the economy,environment and thermodynamics aspects.The results show that compared with the CED process,the EDWC process can reduce CTA by 19.15%,carbon dioxide emissions by 36.08%,exergy loss by 19.99%,and extraction solvent consumption by 8.03%.The EDWC process for separating benzene and cyclohexene azeotrope has excellent separation efficiency and significant energy saving advantages.

extractive dividing wall columnoptimal designenergy savingAspen Plusparticle swarm algorithm

张豪豪、李运昌、刘宇航、刘继三、陈锦溢、华超、陆平

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中国科学院 过程工程研究所绿色过程与工程重点实验室,北京 100190

中国科学院大学化学工程学院,北京 100049

宁夏福泰材料科技有限公司,宁夏石嘴山 753600

华陆工程科技有限责任公司,陕西西安 710065

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萃取隔板精馏塔 优化设计 节能 Aspen Plus 粒子群算法

宁夏回族自治区重点研发计划湖北三峡实验室开放创新基金项目

2022BFH02007SC231002

2024

化学工程
华陆工程科技有限责任公司

化学工程

CSTPCD北大核心
影响因子:0.438
ISSN:1005-9954
年,卷(期):2024.52(7)
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