A 3D transient CFD model to predict heat and moisture transfer in on-farm stored grain silo through parallel computing using compiler directives: Impact of discretization methods on solution efficacy

Abstract

Computational fluid dynamics model parameters highly depend on the storage structure, grain conditions, and airflow properties. Solution methods obtained for the lab-scale bins cannot be extrapolated for a relatively large on-farm silo. To validate the above hypothesis, a model was developed and validated with stored barley aeration in a 1000t silo. A mathematical function was used to initialize the discrete initial conditions in the silo followed by using DEFINE_macros to execute parallel computing. Time-step analysis was conducted followed by optimization of the solution methods in terms of the accuracy and time frame of the model’s output. Results showed that with a time-step of 4 s, temperature and moisture error were 1.1–1.7 °C and 0.3% wb while mean relative deviation were 3.1–4.4% and 2.2%, respectively. COUPLED algorithm resulted in a similar accuracy as of SIMPLE scheme except within spatial and transient formulations. However, the former algorithm was observed to take almost 190% more time than the latter scheme, limiting the simulation efficiency in an on-farm silo. Green Gauss Node-based gradient technique was found to be the appropriate for discretizing large silos. Model showed 45 kJ kg⁻¹ energy emission that decreased the cooling potential of air in silo. As field evaluation of aeration strategies are time-consuming, this model can be used to obtain results that could shape the stored grain management practice.

Keywords:

• On-farm storage
• grain aeration
• computational fluid dynamics
• time-step size
• discretization schemes
• compiler directives

Acknowledgment

The authors would like to thank South Australian Grain Industry Trust (SAGIT) for funding the computers and software licenses and the Australian Commonwealth Government Research Training Program Scholarship for the study (project no. USA119). The authors also thank OPI Systems Inc. (Calgary, Alberta, Canada) for providing the platform to monitor the grain conditions and the Australian Growers Direct (AGD) for allowing us to use their on-farm grain silo to perform aeration experiments.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.