Improved Correlations for Threshold Flooding and Entrainmentin Sieve Trays in Distillation/Absorption Columns

The design of tray distillation/absorption columns involves the utilization of tray evaluation procedures. These procedures are based on flooding and entrainment data originally available in graphs (Souders–Brown flooding constant, <i>C</i><sub>sb</sub>, and fractional entrainment, ψ). Aiming at using these data for computational applications, several algebraic correlations were proposed in the literature. However, a comparison of the predictions of these correlations and the original data reported by Fair (1961) indicates considerable deviations, which can compromise the accuracy of computational tools that use these expressions. In this article, a new set of parameters is determined for these correlations through reestimation of the correlation parameters using modern optimization techniques and the splitting of the correlation domain in multiple regions. The new set of parameters provides a significant reduction in the prediction errors. To demonstrate the importance of the utilization of the revised set of parameters, a comparison is made of column design results using the original and new parameters. The comparison indicates that the use of low-accuracy options affects the design, which can yield infeasible solutions. The evidence of design problems associated with the correlations is available in the literature, emphasizing the importance of the new set of parameters presented here.

Publication Details

Journal
Figshare
Published
2025-01-15
DOI
https://doi.org/10.1021/acs.iecr.4c03115.s001
Primary Topic
Process Optimization and Integration
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improved Correlations for Threshold Flooding and Entrainmentin Sieve Trays in Distillation/Absorption Columns

Figshare
Process Optimization and Integration
article

Improved Correlations for Threshold Flooding and Entrainmentin Sieve Trays in Distillation/Absorption Columns

article en

Abstract

The design of tray distillation/absorption columns involves the utilization of tray evaluation procedures. These procedures are based on flooding and entrainment data originally available in graphs (Souders–Brown flooding constant, <i>C</i><sub>sb</sub>, and fractional entrainment, ψ). Aiming at using these data for computational applications, several algebraic correlations were proposed in the literature. However, a comparison of the predictions of these correlations and the original data reported by Fair (1961) indicates considerable deviations, which can compromise the accuracy of computational tools that use these expressions. In this article, a new set of parameters is determined for these correlations through reestimation of the correlation parameters using modern optimization techniques and the splitting of the correlation domain in multiple regions. The new set of parameters provides a significant reduction in the prediction errors. To demonstrate the importance of the utilization of the revised set of parameters, a comparison is made of column design results using the original and new parameters. The comparison indicates that the use of low-accuracy options affects the design, which can yield infeasible solutions. The evidence of design problems associated with the correlations is available in the literature, emphasizing the importance of the new set of parameters presented here.

Figshare
Clean water and sanitation
Openalex Percentile: Top 49%
Process Optimization and Integration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.