A process modularity approach for chemical process intensification and inherently safer design

模块化(生物学) 过程(计算) 更安全的 工艺设计 固有安全性 计算机科学 过程集成 机组运行 能量(信号处理) 化学过程 在制品 高效能源利用 工艺工程 可靠性工程 生化工程 工程类 数学 运营管理 电气工程 操作系统 统计 生物 遗传学 化学工程 计算机安全
作者
Arick Castillo-Landero,Jorge Aburto,Jhuma Sadhukhan,Elías Martínez-Hernández
出处
期刊:Chemical Engineering Research & Design [Elsevier]
卷期号:168: 54-66 被引量:6
标识
DOI:10.1016/j.psep.2022.09.054
摘要

Process intensification through hybrid equipment combining unit operations has the potential for reducing energy demand and improving the safety of a chemical process. Selecting which unit operations to combine into an intensified unit is necessary in developing an intensified process that offers an inherently safer design with reduced energy demand. This paper presents a novel methodology to intensify a chemical process guided by modularity. A process network is decomposed into modules by applying a community detection algorithm to find the process units to be integrated into an intensified "module" to improve the Fire and Explosion Damage Index (FEDI). A case study for the separation of an ethanol-butanol-water mixture illustrates this approach. The results show that the safest design (lowest FEDI) is Alternative 1 which was developed using the approach and correlates with high modularity of 0.607. Energy use is reduced by 25.8% thus also leading to a more energy efficient process compared to the non-intensified design with a lower modularity (0.385). A rather empirically guided design was proposed as Alternative 2 which led to modularity of 0.533, but only 10% energy saving and no improvement in the FEDI. This demonstrates that intensification guided by modularity strengthens integration between the process units while improving both safety and energy efficiency. As such, the approach has a wide potential application to guide the intensification of chemical processes.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
量子星尘发布了新的文献求助10
1秒前
1秒前
adinike发布了新的文献求助10
1秒前
water完成签到,获得积分10
1秒前
领导范儿应助Cymatics采纳,获得10
1秒前
张熙媛发布了新的文献求助10
1秒前
ding应助liuyong采纳,获得10
2秒前
2秒前
dadaup完成签到 ,获得积分10
2秒前
木棉发布了新的文献求助10
2秒前
177ycd完成签到,获得积分10
2秒前
Puffkten发布了新的文献求助10
3秒前
塔巴德发布了新的文献求助10
3秒前
3秒前
Exist关注了科研通微信公众号
3秒前
Freekor发布了新的文献求助10
3秒前
3秒前
An发布了新的文献求助20
3秒前
margo发布了新的文献求助10
4秒前
4秒前
露亮完成签到,获得积分10
4秒前
purple发布了新的文献求助20
4秒前
ze完成签到,获得积分20
4秒前
easterway完成签到,获得积分10
5秒前
5秒前
Akim应助猫猫采纳,获得10
5秒前
丘比特应助abb先生采纳,获得30
5秒前
自然香岚完成签到,获得积分20
7秒前
完美的吃鱼完成签到,获得积分20
7秒前
露亮发布了新的文献求助10
7秒前
所所应助xiaoliu采纳,获得10
8秒前
fox199753206完成签到,获得积分10
8秒前
DamonChen发布了新的文献求助10
8秒前
斯文败类应助Li采纳,获得10
8秒前
Century发布了新的文献求助10
9秒前
9秒前
CodeCraft应助Qing采纳,获得10
9秒前
子衿完成签到,获得积分10
9秒前
11231完成签到,获得积分20
9秒前
Jasper应助张熙媛采纳,获得10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Reproduction Third Edition 3000
《药学类医疗服务价格项目立项指南(征求意见稿)》 880
花の香りの秘密―遺伝子情報から機能性まで 800
3rd Edition Group Dynamics in Exercise and Sport Psychology New Perspectives Edited By Mark R. Beauchamp, Mark Eys Copyright 2025 600
1st Edition Sports Rehabilitation and Training Multidisciplinary Perspectives By Richard Moss, Adam Gledhill 600
nephSAP® Nephrology Self-Assessment Program - Hypertension The American Society of Nephrology 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5624579
求助须知:如何正确求助?哪些是违规求助? 4710376
关于积分的说明 14950345
捐赠科研通 4778512
什么是DOI,文献DOI怎么找? 2553318
邀请新用户注册赠送积分活动 1515240
关于科研通互助平台的介绍 1475577