Minimum reflux calculation for multicomponent distillation in multi‐feed, multi‐product columns: Algorithms and examples

Abstract In this work, we present the first algorithm for identifying the minimum reboiler vapor duty requirement for a general multi‐feed, multi‐product (MFMP) distillation column separating ideal multicomponent mixtures. This algorithm incorporates our recently developed shortcut model for MFMP columns. We demonstrate the accuracy and efficiency of this algorithm through case studies. The results obtained from these case studies provide valuable insights into the optimal design of MFMP columns. Many of these insights go against the existing design guidelines and heuristics. For example, placing a colder saturated feed stream above a hotter saturated feed stream sometimes leads to a higher energy requirement. Furthermore, decomposing a general MFMP column into individual simple columns may lead to incorrect estimation of the minimum reflux ratio for the MFMP column. Thus, the algorithm presented here offers a fast, accurate, and automated approach to synthesize new, energy‐efficient, and cost‐effective MFMP columns.

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Publication Details

Journal
AIChE Journal
Published
2025-08-11
DOI
https://doi.org/10.1002/aic.70016
Citations
1
Primary Topic
Process Optimization and Integration
Type
article
Field-Weighted Citation Impact
1.21
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article

Minimum reflux calculation for multicomponent distillation in multi‐feed, multi‐product columns: Algorithms and examples

Mohit Tawarmalani, Zheyu Jiang, Rakesh Agrawal
1 citations
AIChE Journal
Process Optimization and Integration
1.21
article

Minimum reflux calculation for multicomponent distillation in multi‐feed, multi‐product columns: Algorithms and examples

Mohit Tawarmalani, Zheyu Jiang, Rakesh Agrawal
article en
1 citations

Abstract

Abstract In this work, we present the first algorithm for identifying the minimum reboiler vapor duty requirement for a general multi‐feed, multi‐product (MFMP) distillation column separating ideal multicomponent mixtures. This algorithm incorporates our recently developed shortcut model for MFMP columns. We demonstrate the accuracy and efficiency of this algorithm through case studies. The results obtained from these case studies provide valuable insights into the optimal design of MFMP columns. Many of these insights go against the existing design guidelines and heuristics. For example, placing a colder saturated feed stream above a hotter saturated feed stream sometimes leads to a higher energy requirement. Furthermore, decomposing a general MFMP column into individual simple columns may lead to incorrect estimation of the minimum reflux ratio for the MFMP column. Thus, the algorithm presented here offers a fast, accurate, and automated approach to synthesize new, energy‐efficient, and cost‐effective MFMP columns.

AIChE JournalVol. 71(11)
Oklahoma State University (US), Purdue University West Lafayette (US)
Affordable and clean energy
Openalex Percentile: Top 18%
Process Optimization and Integration
1.21
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Minimum reflux calculation for multicomponent distillation in multi‐feed, multi‐product columns: Algorithms and examples — Mohit Tawarmalani, Zheyu Jiang, et al. · AIChE Journal (2025) | TGRS Research Map | TGRS