This new approach represents chemical processes as abstract blocks arranged in a two-dimensional grid. Mathematical-programming-based optimization can identify the best design for intensification at the equipment and flowsheet levels.
Process intensification (PI) is a design concept with transformative prospects for the chemical process industries (CPI) (1). It is defined as any design activity that substantially improves one (or more) of several process performance metrics, including size, energy efficiency, environmental footprint, and safety (2). Intensification can be achieved by exploiting the synergies, trade-offs, and dynamics between and among multiple competing phenomena that exist within a process. Examples of PI include dividing-wall columns, reactive distillation columns, membrane reactors, reverse-flow reactors, sorption-enhanced processes, static mixers, and more. (Reference 3 provides an extensive review of PI state of the art.)
As CPI companies strive to create processes that are more energy-efficient and sustainable, there is a need to incorporate novel and out-of-the-box solutions when designing an intensified process. Several process synthesis approaches for systematic identification of optimal process configurations have been developed (4). Process integration approaches are also applicable (5, 6).
However, the traditional paradigm of unit-operation-based process synthesis and integration does not always have the mechanisms required for systematic identification of novel designs. At the heart of this challenge remains the question: How should we represent chemical processes in a way that will enable automatic generation and screening of intensification pathways without knowing the equipment and flowsheet alternatives beforehand (7)?
Resolving this challenge requires new representation methods to foster creativity at the conceptual design stage. Design methodologies have been proposed in the past that, rather than rely on unit operations, instead employ more fundamental representations, such as generalized modular representation (8, 9), phenomena building blocks (PBB) (10, 11), elementary process functions (12), and the infinite dimensional state‐space (IDEAS) approach (13). These methods highlight the usefulness of using fundamental driving forces for transformation (8, 9) and/or observing chemical processes as a collection of the fundamental physicochemical phenomena (10, 11, 14) that are the basis of all unit operations. These bottom-up approaches enable many more flowsheet variants to be generated than an approach that relies on representations only at the unit-operations level.
Recently, our group has proposed a new representation of chemical processes using abstract building blocks (15–20). These blocks (which are explained in detail in the next section) are different from the traditional blocks that are used to represent unit operations. A systematic arrangement of these building blocks incorporates numerous plausible design and intensification pathways. It also enables a mathematical-programming-based optimization method to simultaneously identify the best design for intensification at the equipment and flowsheet levels. This building block approach shows promise as a systematic design and intensification technique that would not require specification of process alternatives beforehand.
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