Improving cooling rate in a cold room by using a parametric study coupled with computational fluid dynamics

The cooling dynamics of fruits depend on the flow conditions around the biological material. Computational fluid dynamics (CFD) coupled with a design of experiments (DOE) was implemented to reveal how a design variable (bin open area) and an operational variable (cold air mass flow at the inlet) affect turbulence and therefore the cooling kinetics. The CFD model was first validated against experimental local velocities inside the bins with an error of 14% to later be used in the parametric study (simulated data was consistent with experimental data). A clear non-homogeneity in turbulence distribution (vertical stratification) was found and therefore different local cooling rates. For this cooling room, the bin located in the top are cooling faster (8.1 hour 7/8th cooling time) that the bin located in the bottom (14.7 hours 7/8th cooling time). A 65% reduction in the mass flow rate shows a 21% increment in 7/8th cooling time and 57% increment in the lateral bin open area with a constant the flow rate, shows 9% increments in the 7/8th cooling time but with a 2 hours (7/8th cooling time) reduction in the difference between the bin in the top and the bin in the bottom which implied better homogeneity.

Authors

Institutions

Publication Details

Journal
eVitroKhem
Published
2025-01-01
DOI
https://doi.org/10.56294/evk2025153
Citations
1
Primary Topic
Food Supply Chain Traceability
Type
article
Field-Weighted Citation Impact
1.16
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improving cooling rate in a cold room by using a parametric study coupled with computational fluid dynamics

Dustin Tahisin Gómez Rodrí­guez, Natali López-Mejía, Wilmer Cruz-Guayacundo, Hugo Fabián Lobatón García
1 citations
eVitroKhem
Food Supply Chain Traceability
1.16
article

Improving cooling rate in a cold room by using a parametric study coupled with computational fluid dynamics

Dustin Tahisin Gómez Rodrí­guez, Natali López-Mejía, Wilmer Cruz-Guayacundo, Hugo Fabián Lobatón García
article en
1 citations

Abstract

The cooling dynamics of fruits depend on the flow conditions around the biological material. Computational fluid dynamics (CFD) coupled with a design of experiments (DOE) was implemented to reveal how a design variable (bin open area) and an operational variable (cold air mass flow at the inlet) affect turbulence and therefore the cooling kinetics. The CFD model was first validated against experimental local velocities inside the bins with an error of 14% to later be used in the parametric study (simulated data was consistent with experimental data). A clear non-homogeneity in turbulence distribution (vertical stratification) was found and therefore different local cooling rates. For this cooling room, the bin located in the top are cooling faster (8.1 hour 7/8th cooling time) that the bin located in the bottom (14.7 hours 7/8th cooling time). A 65% reduction in the mass flow rate shows a 21% increment in 7/8th cooling time and 57% increment in the lateral bin open area with a constant the flow rate, shows 9% increments in the 7/8th cooling time but with a 2 hours (7/8th cooling time) reduction in the difference between the bin in the top and the bin in the bottom which implied better homogeneity.

eVitroKhemVol. 4
Kubota (Japan) (JP), Universitaria Agustiniana (CO)
Affordable and clean energy
Openalex Percentile: Top 21%
Food Supply Chain Traceability
1.16
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.

Improving cooling rate in a cold room by using a parametric study coupled with computational fluid dynamics — Dustin Tahisin Gómez Rodrí­guez, Natali López-Mejía, et al. · eVitroKhem (2025) | TGRS Research Map | TGRS