Aeration system optimization for a deep bed dryer for paddy grain using computational fluid analysis and the AHP-TOPSIS method

Highlights

● Drying is a crucial postharvest process for paddy grain and impacts the quality of both paddy and rice.

● A deep bed dryer is a convective dryer that relies on airflow, temperature and relative humidity as the primary drying parameters.

● An aeration system is necessary to distribute the drying air evenly throughout the drying chamber.

● The optimal aeration system was determined using computational fluid dynamics and the AHP-TOPSIS method.

● The most optimal aeration system is a model deep bed dryer with a sloping floor and circular pipe formation.

Abstract

In the context of food security, drying is a crucial postharvest process for paddy grain because it significantly impacts the quality of both paddy and rice. To conserve energy during the drying process, deep bed dryers are used as convective dryers that use a combination of ambient airflow and heating, thus relying on airflow, temperature, and relative humidity (RH) as the primary drying parameters. Consequently, an aeration system is necessary so that the drying air can penetrate the thick pile of paddy grain and distribute evenly throughout the drying chamber. This analysis aimed to determine the most optimal aeration system by using computational fluid dynamics (CFD) and the AHP-TOPSIS method. The quantitative and visual analysis of the airflow velocity, pressure, temperature, and RH was conducted using CFD on four different dryer aeration systems models, which were then ranked by preference value using the AHP-TOPSIS method. Model 4, with a sloping floor and circular pipe formation, was found to have the most optimal aeration system (preference value of 0.788) for a paddy grain deep bed dryer prototype.

Graphical abstract

Keywords

Deep bed dryer / air aeration system / CFD / AHP-TOPSIS / paddy grain drying

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Acknowledgements

This research was funded by Balai Pembiayaan Pendidikan Tinggi, Kemendikbudristek, and Lembaga Pengelola Dana Pendidikan (LPDP) through the Indonesian Education Scholarship (1083/J5.2.3/BPI.06/10/2021), and supported by Prof. Samsul Rizal of the Department of Mechanical and Industrial Engineering of Universitas Syiah Kuala in the application of Ansys software, which was funded by the LPDP and managed by Indonesian Science Fund (RISPRO/KI/B1/TKL/5/15448/2020).

Compliance with ethics guidelines

Diswandi Nurba, Sutrisno S. Mardjan, Dyah Wulandani, Loepold O. Nelwan, and I Dewa Made Subrata declare that they have no conflict of interest or financial conflicts to disclose. This article does not contain any studies with human or animal subjects performed by any of the authors.

RIGHTS & PERMISSIONS

The Author(s) 2024. Published by Higher Education Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0)