Optimization of Dimensional Factors Using AI Technique Affecting Solar Dryer Efficiency for Drying Agricultural Materials  

作　　者：Ravendra Kumar Ray A.C.Tiwari 

机构地区：[1]Department of Mechanical Engineering,University Institute of Technology(UIT-RGPV),Bhopal,462033,India

出　　处：《Computers, Materials & Continua》2025年第4期845-860,共16页计算机、材料和连续体(英文)

摘　　要：The design and development of solar dryers are crucial in regions with abundant solar energy,such as Bhopal,India,where seasonal variations significantly impact the efficiency of drying processes.The paper is focused on employing a comprehensive mathematical model to predict the dryer’s performance in drying the materials such as banana slices.To enhance this model,Hyper Tuned Swarm Optimization with Gradient Tree(HT_SOGT)was utilized to accurately predict and determine the optimal size of the dryer dimensions considering various mathematical calculations for material drying.The predictive model considered the influence of seasonal fluctuations,ensuring an efficient drying process with an objective function to optimize the drying time of an average of 7 hrs throughout the year.Across all recorded ambient temperatures(ranging from 16.985○C to 31.4○C),the outlet temperature of the solar dryer is consistently higher,ranging from 39.085○C to 66.2○C.The results show that the optimized dryer design,based on HT_SOGT modelling,significantly improves drying efficiency of the materials across varying conditions,making it suitable for sustainable applications in agriculture and food processing industries in the Bhopal region.

关 键 词：Solar dryer swarm optimization algorithm drying time drying efficiency IRRADIATION agricultural materials 

分 类 号：S226[农业科学—农业机械化工程]