A General Framework for Process Synthesis, Integration, and Intensification

被引:33
作者
Demirel, Salih Emre [1 ]
Li, Jianping [1 ]
Hasan, M. M. Faruque [1 ]
机构
[1] Texas A&M Univ, Artie McFerrin Dept Chem Engn, College Stn, TX 77843 USA
基金
美国国家科学基金会;
关键词
CONCEPTUAL PROCESS SYNTHESIS; CHEMICAL-PROCESSES; NETWORK SYNTHESIS; HEAT INTEGRATION; PROCESS DESIGN; SUPERSTRUCTURE; OPTIMIZATION; METHODOLOGY; SYSTEMS; MODELS;
D O I
10.1021/acs.iecr.8b05961
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Process synthesis, integration, and intensification are the three pillars of process design. Current synthesis and integration methods are able to find optimal design targets and process configurations when all the alternatives are known beforehand. Process intensification, on the other hand, combines multiple physicochemical phenomena and exploits their interactions to create innovative designs. Often times, these designs are not known beforehand, and a phenomena-level representation of chemical processes are required to identify them. This disconnection between the three paradigms limits the ability to systematically discover optimal design pathways. We demonstrate that the building block representation, originally proposed in our earlier work on process intensification (Demirel, Li, and Hasan, Comput. Chem. Eng., 2017, 150, 2-38), has the potential to bridge this gap. Depending on the attributes assigned to the interior and the boundaries of these two-dimensional abstract building blocks, they can represent various intensified or isolated phenomena at the lowest level, various tasks at the equipment level, and various unit operations at the flowsheet level. This common multiscale representation enables an mixed-integer nonlinear optimization-based single framework for the sequential or simultaneous synthesis, integration, and intensification of chemical processes. Such a general framework is critical to reduce the risk of eliminating potential intensification pathways and candidate flowsheets at the conceptual design stage. The framework is demonstrated using a case study on an ethylene glycol process.
引用
收藏
页码:5950 / 5967
页数:18
相关论文
共 72 条
[11]   The RAPID Manufacturing Institute - Reenergizing US efforts in process intensification and modular chemical processing [J].
Bielenberg, James ;
Palou-Rivera, Ignasi .
CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION, 2019, 138 :49-54
[12]   Generalized disjunctive programming model for the optimal synthesis of thermally linked distillation columns [J].
Caballero, JA ;
Grossmann, IE .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2001, 40 (10) :2260-2274
[13]   Recent Developments and Challenges in Optimization-Based Process Synthesis [J].
Chen, Qi ;
Grossmann, I. E. .
ANNUAL REVIEW OF CHEMICAL AND BIOMOLECULAR ENGINEERING, VOL 8, 2017, 8 :249-283
[14]   SYNTHESIS OF NONEQUILIBRIUM REACTIVE DISTILLATION PROCESSES BY MINLP OPTIMIZATION [J].
CIRIC, AR ;
GU, DY .
AICHE JOURNAL, 1994, 40 (09) :1479-1487
[15]   Learning surrogate models for simulation-based optimization [J].
Cozad, Alison ;
Sahinidis, Nikolaos V. ;
Miller, David C. .
AICHE JOURNAL, 2014, 60 (06) :2211-2227
[16]   Process intensification of reactive separator networks through the IDEAS conceptual framework [J].
da Cruz, Flavio Eduardo ;
Manousiouthakis, Vasilios I. .
COMPUTERS & CHEMICAL ENGINEERING, 2017, 105 :39-55
[17]   Systematic process intensification [J].
Demirel, Salih Emre ;
Li, Jianping ;
Hasan, Faruque .
CURRENT OPINION IN CHEMICAL ENGINEERING, 2019, 25 :108-113
[18]   Systematic process intensification using building blocks [J].
Demirel, Salih Emre ;
Li, Jianping ;
Hasan, M. M. Faruque .
COMPUTERS & CHEMICAL ENGINEERING, 2017, 105 :2-38
[19]  
Demirel SE., 2017, Computing and Systems Technology Division 2017 - Core Programming Area at the 2017 AIChE Annual Meeting, V2017-October, P199
[20]  
Demirel SE., 2018, Computer Aided Chemical Engineering, V44, P445, DOI DOI 10.1016/B978-0-444-64241-7.50069-0