2018 AIChE Annual Meeting

(51e) SPICE: A Computer-Aided Platform for Simultaneous Process Synthesis and Intensification

Authors

Li, J. - Presenter, Artie McFerrin Department of Chemical Engineering, Texas A&M University
Demirel, S. E., The Dow Chemical Company
Hasan, F., Texas A&M University
Process intensification improves the process performance and brings technical innovation with improved controllability, sustainability and energy efficiency [1-3]. Process synthesis identifies the best process alternatives under several design constraints to generate desired products from available raw materials, while giving insights on optimal unit operation type and their interconnections [4-7]. Several computer-aided tools and software frameworks already exist for integrating the process synthesis methods and simulation packages to automatically generate the desired process flowsheets [8-11].

In this work, we describe the update on SPICE (Systematic Process Intensification of Chemical Enterprises) computational framework to involve process intensification within process synthesis framework. We have recently proposed block superstructure to address process synthesis for process intensification and formulated a corresponding mixed-integer nonlinear optimization (MINLP) model [1,5]. This MINLP model serves as the basis for SPICE. Specifically, the proposed SPICE framework enables: 1) collection of model input data on feeds, products and materials through a user-friendly interface; 2) determination of block superstructure size via a mixed integer linear (MILP) optimization model; 3) generation of optimal block configurations by solving the MINLP model via commercial solvers; 4) conversion of obtained block configuration to equipment-based process flowsheets. With these features, SPICE framework automates the generation and optimization of process flowsheets including intensified alternatives without postulating their existence a priori. The fundamental MINLP model embedded in SPICE involves general mass and energy conservations, product demand and purity requirements, reaction and separation modeling formulations, and material selection constraints.

Additionally, we will discuss an MILP-based method for determining the block superstructure size with full connectivity. We interpret each block as node and flow connections in block superstructure as path segments connecting these nodes. The proposed MILP model involves constraints on the identification of initial and destination block for each path, path propagation for achieving node connectivity and elimination of forbidden path overlaps. Through the SPICE framework, we investigate several process synthesis and intensification examples including methanol production process and several reactive and hybrid separation processes. The results show promise towards identifying novel intensified options within process synthesis framework without postulating flowsheet alternatives a priori. With these case studies, the versatile capabilities of the software framework are demonstrated in terms of data collection and transferring, as well as automatic generation and optimization of process flowsheets.

References:

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[5] Li, J., Demirel, S.E., Hasan, M.M.F. Process Synthesis using Block Superstructure with Automated Flowsheet Generation and Optimization. AIChE Journal, 2018, under review.

[6] Li J., Demirel S.E., Hasan M.M.F. Process Integration using Block Superstructure. Industrial & Engineering Chemistry Research, 2018, 57: 4377–4398.

[7] Li J., Demirel S.E., Hasan M.M.F. Fuel Gas Network Synthesis Using Block Superstructure. Processes. 2018, 6(3): 23.

[8] Kravanja Z, Grossmann IE. PROSYN-an automated topology and parameter process synthesizer. Computers & Chemical engineering. 1993, 17: S87–S94.

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[11] Tula AK, Babi DK, Bottlaender J, Eden MR, Gani R. A computer-aided software-tool for sustainable process synthesis-intensification. Computers & Chemical Engineering. 2017, 105:74–95.