Development and validation of hybrid drying kinetics models with finite element method integration for black paper in a v-groove solar dryer
Keywords:
Black pepper, Solar drying, Hybrid drying models, Finite element method, CurveExpert professionalAbstract
Preserving agricultural products requires drying techniques to avoid spoilage and financial setbacks. Sun drying is unreliable because of changing weather conditions; hybrid solar dryers provide an option. However, it is not easy to forecast the drying process of crops such, as black pepper due to its drying characteristics. This research examines how accurately different models predict the drying process of black pepper in a v Groove Hybrid Solar Dryer using a modeling framework and a Finite Element Method (FEM) inspired approach that is newly developed. Black pepper was dried for four days, with the moisture ratio data collected every 30 minutes from 8 AM to 5 PM. Twenty-seven drying kinetics models were tested on the data, with the Alibus model, Aghbashlo, and Infiltration Approximation models being the three best performers. To improve the accuracy of predictions, a total of 220 hybrid models were created by merging pairs of the 11 best-performing models using a specialized formula based on weights. The analysis indicated that more than thirty (30) hybrid models performed better than single models with Hybrid M28 (combining Logarithmic and Alibus), Hybrid M38 (pairing Lewis and Alibus), and Hybrid M101 (merging Infiltration Approximation and Kaleemullah), showing exceptional results. Furthermore, a model based on FEM was developed and validated using MATLAB and CurveExpert Professional to account for the physical diffusion characteristics. While it demonstrated good alignment with the experimental data, it equally acted as a solid foundation based on physics principles. The results highlighted the capability of combining hybrid and FEM based models to better understand intricate drying patterns in a more efficient way which can lead to improved solar drying system designs with enhanced reliability for future optimization efforts, across various crop types.
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Copyright (c) 2025 Ibrahim Adamu Mohammed, Majid Khan Majahar Ali, Sani Rabiu, Raja Aqib Shamim, Shahida Shahnawaz (Author)

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