(92e) Process Innovation and Intensification Using Building Blocks
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.
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