Learning process patterns via multiple sequence alignment

doi:10.1016/j.compchemeng.2022.107676

Learning process patterns via multiple sequence alignment

2022-03-01

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Nikolaos V. Sahinidis *

DOI：10.1016/j.compchemeng.2022.107676

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Abstract

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Chemical process flowsheets contain a wealth of hidden information. By recognizing similarities in process flowsheets, engineers can understand how existing processes were designed and improve the design and operations of new processes. In previous work, we introduced a systematic methodology for comparing two flowsheets. Our present work proposes a novel method based on multiple sequence alignment to explore general patterns among multiple process flowsheets simultaneously without having to conduct pairwise comparisons of a given number of flowsheets. Additionally, we propose a decomposition strategy to identify inner patterns within a single flowsheet. Several case studies demonstrate that the proposed methodology can compare multiple flowsheets simultaneously to determine general patterns and effectively identify patterns from a single flowsheet. (C) 2022 Elsevier Ltd. All rights reserved.

Keywords:

Flowsheet comparison

Process pattern

Multiple sequence alignment

Tree decomposition

Learning process patterns via multiple sequence alignment

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