(92e) Process Innovation and Intensification Using Building Blocks

Li, J., Artie McFerrin Department of Chemical Engineering, Texas A&M University
Demirel, S. E., Artie McFerrin Department of Chemical Engineering, Texas A&M University
Hasan, M. M. F., Artie McFerrin Department of Chemical Engineering, Texas A&M University
Finding an optimal production pathway to convert raw materials into desired products is critical in chemical industry. The selection of equipment type and combinatorial nature of the equipment connectivity have been the key issue for achieving process design. Besides, discovery of novel chemical processes often requires “out-of-box” thinking and may not be achieved by simply connecting different equipment. For instance, the discovery of a feasible refrigeration cycle often requires the analysis of phase diagrams embedding rich process information for conceptual process design [1]. A novel refrigeration cycle can involve process intensification opportunities, e.g., multi-stream heat exchangers, which brings drastic improvements in term of size, sustainability, and energy efficiency [2-5]. However, discovery and identification of these chemical processes is not always intuitive and often becomes challenging while employing classic optimization-based process synthesis approaches.

Recently, building block-based process synthesis and intensification have shown promise for identifying many chemical process alternatives using fundamental phenomena and tasks [4, 6-7]. In this work, we describe a building-block based approach to enable the systematic discovery and optimization of novel process flowsheets. Thermodynamic relations from equation of state, e.g., Peng-Robinson equation of state, are described using quadratic surrogate models to reduce the computational complexity. The flowsheets will be screened among the rich connection information in the block superstructure with the surrogate thermodynamic relations. Unlike classic unit-based superstructure representation, the proposed block superstructure leverages on building blocks representing fundamental physiochemical phenomena. The block superstructure is constructed by assembling building blocks in a two-dimensional grid. These building blocks allow feed supplies and product withdrawing while connecting with each other through material and energy flow. The adjacent blocks are separated from each other through either semi-restricted boundaries for component redistribution or completely restricted boundaries for prohibiting mass flow. We will show how this building block representation yields various process configurations without a priori postulation of unit operations. We formulate this process innovation and intensification problem as a mixed-integer nonlinear optimization (MINLP) problem. The objective is to find innovative flowsheets with minimal total annual cost. The capability of the proposed approach will be demonstrated through several case studies on liquefied energy chain and refrigeration systems.


[1] Lim, W.; Choi, K.; Moon, I. (2013). Current status and perspectives of liquefied natural gas (LNG) plant design. Industrial & Engineering Chemistry Research, 52, 3065–3088.

[2] Lutze, P., Gani, R., Woodley, J. M. (2010). Process intensification: a perspective on process synthesis. Chemical Engineering Processing: Process Intensification, 49 (6), 547–558.

[3] Demirel, S. E., Li, J., and Hasan, M. M. F., (2017). Systematic Process Intensification using Building Blocks, Computers and Chemical Engineering, 105, 2-38.

[4] S.E. Demirel, J. Li, M.M.F. Hasan. Systematic Process Intensification. Current Opinion in Chemical Engineering, 2019, https://doi.org/10.1016/j.coche.2018.12.001.

[5] Tian, Y., Demirel, S. E., Hasan, M. M. F., Pistikopoulos, E. N. (2018). An Overview of Process Systems Engineering Approaches for Process Intensification: State of the Art. Chemical Engineering and Processing: Process Intensification, 133, 160-210.

[6] Li, J., Demirel, S. E., & Hasan, M. F. (2018). Process synthesis using block superstructure with automated flowsheet generation and optimization. AIChE Journal, 64(8), 3082-3100.

[7] Li, J., Demirel, S. E., & Hasan, M. F. (2018). Process integration using block superstructure. Industrial & Engineering Chemistry Research, 57(12), 4377-4398.