CFD—Assisted Expert System for N 2 -Controlled Atmosphere Process of Rice Storage Silos

Phakkawat Angsrisuraporn, Chawit Samakkarn, Lertsak Lekawat, Sasathorn Singkhornart and Jatuporn Thongsri ()
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Phakkawat Angsrisuraporn: College of Advanced Manufacturing Innovation, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
Chawit Samakkarn: College of Advanced Manufacturing Innovation, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
Lertsak Lekawat: College of Advanced Manufacturing Innovation, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand
Sasathorn Singkhornart: Department of Food and Nutrition, Faculty of Home Economics Technology, Rajamangala University of Technology Krungthep, Bangkok 10120, Thailand
Jatuporn Thongsri: College of Advanced Manufacturing Innovation, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand

Sustainability, 2024, vol. 16, issue 5, 1-20

Abstract: Since organic rice storage silos were faced with an insect problem, an owner solved this problem using the expert system (ES) in the controlled atmosphere process (CAP) under the required standard, fumigating insects with an N 2 , reducing O 2 concentration to less than 2% for 21 days. This article presents the computational fluid dynamics (CFD) assisted ES successfully solved this problem. First, CFD was employed to determine the gas flow pattern, O 2 concentration, proper operating conditions, and a correction factor ( K ) of silos. As expected, CFD results were consistent with the experimental results and theory, assuring the CFD’s credibility. Significantly, CFD results revealed that the ES controlled N 2 distribution throughout the silos and effectively reduced O 2 concentration to meet the requirement. Next, the ES was developed based on the inference engine assisted by CFD results and the sweep-through purging principle, and it was implemented in the CAP. Last, the experiments evaluated CAP’s efficacy in controlling O 2 concentration and insect extermination in the actual silos. The experimental results and owner’s feedback confirmed the excellent efficacy of ES implementation; therefore, the CAP is effective and practical. The novel aspect of this research is a CFD methodology to create the inference engine and the ES.

Keywords: control atmosphere; computational fluid dynamics; expert system; fumigation; inference engine; insect extermination; rice storage; sweep through purging; sustainable development goals; SDGs (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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