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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
刚刚
1秒前
Espoir完成签到,获得积分10
1秒前
2秒前
嘿嘿发布了新的文献求助30
2秒前
酷波er应助Nell采纳,获得10
2秒前
jie完成签到,获得积分10
2秒前
2秒前
3秒前
4秒前
丘比特应助水123采纳,获得10
4秒前
4秒前
桐桐应助zhiyuanren采纳,获得10
4秒前
4秒前
李绅语发布了新的文献求助10
4秒前
鳗鱼忆南发布了新的文献求助10
6秒前
syh完成签到,获得积分10
6秒前
现代菠萝发布了新的文献求助10
6秒前
8秒前
桐桐应助chrysan采纳,获得10
8秒前
eric发布了新的文献求助10
8秒前
麻喽发布了新的文献求助10
9秒前
科研通AI6应助LAYWL采纳,获得10
9秒前
9秒前
领导范儿应助张景峒采纳,获得10
9秒前
慕青应助zlf采纳,获得10
10秒前
闫辰完成签到 ,获得积分10
10秒前
latata完成签到,获得积分10
10秒前
10秒前
脑洞疼应助JY采纳,获得10
10秒前
666完成签到,获得积分10
10秒前
万能图书馆应助辛勤又蓝采纳,获得10
12秒前
Os发布了新的文献求助10
12秒前
量子星尘发布了新的文献求助10
13秒前
Vivien完成签到,获得积分10
13秒前
13秒前
无限大山完成签到,获得积分10
13秒前
SciGPT应助谨慎的易蓉采纳,获得10
13秒前
pyh01完成签到,获得积分10
14秒前
大模型应助我谈采纳,获得10
15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
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 临床微生物学程序手册,多卷,第5版 2000
List of 1,091 Public Pension Profiles by Region 1621
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] | NHBS Field Guides & Natural History 1500
The Victim–Offender Overlap During the Global Pandemic: A Comparative Study Across Western and Non-Western Countries 1000
King Tyrant 720
Sport, Social Media, and Digital Technology: Sociological Approaches 650
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 5593599
求助须知:如何正确求助?哪些是违规求助? 4679468
关于积分的说明 14810164
捐赠科研通 4644508
什么是DOI,文献DOI怎么找? 2534573
邀请新用户注册赠送积分活动 1502632
关于科研通互助平台的介绍 1469366