Three dimensional models of porosity and airflow resistance in stored grain bulks

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The grain aeration and drying process is always at risk of failure because of its weather dependency. The presence of dockage, fines, and foreign materials (DFF) in stored grain exacerbates this issue further because the DFF in stored grain can plug the air space among grain kernels, causing uneven airflow resistance. The nonuniform airflow results in overdried grain at high airflow locations and wet (spoiled) grain at low airflow locations inside the same bin. The two major factors influencing the airflow resistance distribution are the pore structure among grain kernels (size, shape, connectivity, tortuosity of the pores, and orientation of the pore to the airflow direction) and properties of fluids (air velocity and viscosity). The pore structure is directly influenced by grain types (kernel size and shape) of the stored grain and amount and size of DFF. Porosity is strongly related to pore structure and airflow resistance in a bin. No model of airflow resistance considering the distribution of DFF (both in size and percentage) inside grain bulks has yet been developed, leading to a knowledge gap in this area. The long-term goal of my research program is to mathematically model the physical and biological behaviours of stored grain ecosystems. In the next 5 years, I will focus on objectives to fill this gap by developing 3D finite element airflow resistance models inside stored grain bulks and considering the effect of DFF (both size and percentage) on porosity and airflow resistance. To develop and validate these models, I propose to quantify the relationship among porosity, DFF size distribution, airflow direction, airflow velocity, and airflow resistance. The proposed experiments will use novel technique to characterize pore structures and measure air flow resistance distribution. The results from this research will not only contribute to the fundamental knowledge of pore structure and flow through grain bulks, but also provide a rational analysis tool for the design and operation of bulk solid storage systems. The developed airflow resistance distribution models will help design engineers to lay out the aeration system optimally and grain owners to conduct a optimal grain drying and aeration, so quality and quantity losses can be avoid and Canada's international reputation as a reputable, reliable, and consistent producer of high-quality grain can be maintained. Two MSc, 1 PhD, and 3 undergraduate students will be trained through this proposed program. An individualized training plan and approach will be developed. Through this rigorous training under an EDI (equity, diversity, and inclusion) environment, all students will be trained on the advanced management of stored grain and be prepared to become independent for their future careers. They will also advance their technical skills in areas important to grain storage management.