{"title":"Simulation Program for Modeling Temperature Distribution in a Food Dehydrator","authors":"Esther Hee Ying Lim, A. H. Tan, C. Cham","doi":"10.1109/CSPA57446.2023.10087530","DOIUrl":null,"url":null,"abstract":"A simulation program is designed and developed for modeling the temperature distribution of a food dehydrator with infrared heating. A segmentation approach is utilized with energy balance implemented in each segment. The program incorporates heat transfers based on conduction, convection and radiation. Nonlinear optimization is applied to select the radiative heat absorption ratio as well as several parameters related to unmeasured material properties in the model. The resulting model has a very low complexity compared to the existing methods. The predictive capability of the model is tested and the model uncertainty is estimated to be approximately 1. 78°c. The accuracy is sufficient for the application considered. Additionally, the simulation program is user-friendly.","PeriodicalId":268233,"journal":{"name":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 19th IEEE International Colloquium on Signal Processing & Its Applications (CSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPA57446.2023.10087530","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A simulation program is designed and developed for modeling the temperature distribution of a food dehydrator with infrared heating. A segmentation approach is utilized with energy balance implemented in each segment. The program incorporates heat transfers based on conduction, convection and radiation. Nonlinear optimization is applied to select the radiative heat absorption ratio as well as several parameters related to unmeasured material properties in the model. The resulting model has a very low complexity compared to the existing methods. The predictive capability of the model is tested and the model uncertainty is estimated to be approximately 1. 78°c. The accuracy is sufficient for the application considered. Additionally, the simulation program is user-friendly.