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Design and Performance Evaluation of a Charcoal Briquetting Machine Using Dimensional Analysis and Computational Fluid Dynamics (CFD)

Author

Listed:
  • Promise C. Okoye

    (Department of Mechanical Engineering, Chukwuemeka Odumegwu Ojukwu University, Uli – Nigeria)

  • Sunday C. Anyaora

    (Department of Mechanical Engineering, Nnamdi Azikiwe University, Awka, Nigeria)

  • Chisom V. Okeke

    (Department of Electrical/Electronic Engineering, Chukwuemeka Odumegwu Ojukwu University, Nigeria)

  • Ifeanyichukwu U. Onyenanu

    (Department of Mechanical Engineering, Chukwuemeka Odumegwu Ojukwu University, Uli – Nigeria)

Abstract

This study delineates the design and performance assessment of a charcoal briquetting apparatus created through the application of dimensional analysis and Computational Fluid Dynamics (CFD) to augment efficiency, throughput, and energy optimization. A screw-type briquetting apparatus was constructed utilizing a 3 HP motor and achieving an optimized throughput of 41.88 kg/hr, functioning at an efficiency of 79.46%. Buckingham’s π theorem was utilized to derive dimensionless models pertinent to essential performance metrics (efficiency, throughput, and energy consumption) predicated on parameters such as pressure, moisture content, feed rate, and die geometry. CFD simulations and SolidWorks-based Finite Element Analysis were employed to substantiate stress, strain, and displacement distributions across the components of the machine. Experimental validation exhibited a strong correlation between predicted and actual values, with coefficients of determination R² = 0.7646 for efficiency and R² = 0.9532 for throughput, thereby affirming the robustness of the models. The study concludes that the integration of dimensional analysis with parametric simulation markedly enhances the prediction of machine performance. It is recommended that prospective research incorporates environmental impact assessments and cost-benefit analyses for rural-scale deployment, in addition to refining boundary conditions in CFD models for more precise heat transfer predictions.

Suggested Citation

Handle: RePEc:cxi:ijans0:v:3:y:2025:i:2:id:334
DOI: 10.61424/ijans.v3i2.334
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