Numerical simulation and structural optimization of forced convection oven

Temperature uniformity is a fundamental parameter for a forced convection oven to guarantee food baking quality. In this study, computational fluid dynamics (CFD) simulation is employed to analyze the air flow and heat transfer within a forced convection oven. Subsequent experimental measurements were conducted to explore the temperature variations inside the oven. The maximum deviation between the numerical simulation results and the experimental data was 2.70%, demonstrating the high accuracy of the simulation model. Based on the established simulation model, we can meticulously investigate the impact of fan structures on the airflow and temperature fields. Carefully designing the fan structure can significantly enhance temperature uniformity across the oven’s baking racks, reducing the standard deviation of temperatures on the second and third baking racks from 5.46°C and 6.69°C to 2.26°C and 2.46°C, respectively. This study provides a robust design strategy for forced convection ovens, yielding tangible benefits for practical application and market competitiveness.

Authors

Institutions

Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Published
2024-09-16
DOI
https://doi.org/10.1177/09544062241277321
Primary Topic
Wind and Air Flow Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Numerical simulation and structural optimization of forced convection oven

Yunfei Chen, Hao Chen, Mo Chen, Zhen Yan et al.
1 links
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Wind and Air Flow Studies
article

Numerical simulation and structural optimization of forced convection oven

Yunfei Chen, Hao Chen, Mo Chen, Zhen Yan, Zheng Zhu, YuFeng Bie, Dai Wan, Chao Li, Yan Zhang
article en

Abstract

Temperature uniformity is a fundamental parameter for a forced convection oven to guarantee food baking quality. In this study, computational fluid dynamics (CFD) simulation is employed to analyze the air flow and heat transfer within a forced convection oven. Subsequent experimental measurements were conducted to explore the temperature variations inside the oven. The maximum deviation between the numerical simulation results and the experimental data was 2.70%, demonstrating the high accuracy of the simulation model. Based on the established simulation model, we can meticulously investigate the impact of fan structures on the airflow and temperature fields. Carefully designing the fan structure can significantly enhance temperature uniformity across the oven’s baking racks, reducing the standard deviation of temperatures on the second and third baking racks from 5.46°C and 6.69°C to 2.26°C and 2.46°C, respectively. This study provides a robust design strategy for forced convection ovens, yielding tangible benefits for practical application and market competitiveness.

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering ScienceVol. 238(23)
Nanjing Tech University (CN), Southeast University (CN)
Openalex Percentile: Top 85%
Wind and Air Flow Studies
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.