Highlights Enhanced PHAST model reduces simulation time by up to 60% using the 3-point secant method. Temperature and moisture prediction errors reduced by 18% and 22%, respectively. Model integrates energy balance and grain property functions for greater accuracy. Validated tool improves decision-making for large-scale grain storage operations. Abstract. Accurate grain storage simulation is crucial for minimizing post-harvest losses and ensuring food security. This study aimed to enhance the computational efficiency and accuracy of the Post-Harvest Aeration and Storage Simulation Tool (PHAST) model for on-farm grain management. Experimental data from drying operations for corn (2920 tonnes) and rough rice (1510 tonnes) using natural air drying (NAD) and natural air drying with a heater (NADH) were used to validate the modified model. By incorporating energy balance considerations, temperature-dependent grain properties, and the 3-point secant method for root approximation, the model required 54%-60% less time than the current simulation technique based on the 2-point secant method. This was mainly due to 43%-55% fewer iterations per time step with the 3-point secant method. Furthermore, the model’s temperature and moisture error margins were reduced by 18% and 22%, respectively. The results demonstrated that the enhanced PHAST model accurately predicted temperature and moisture profiles, outperforming the original version in terms of accuracy and computational efficiency. The findings of this study provide valuable insights for developing more reliable and efficient grain-storage simulation tools that support informed decision-making by farmers. Keywords: 3-point secant method, Finite difference modeling, Grain drying heaters, Natural air drying, PHAST.
Panigrahi et al. (Thu,) studied this question.