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<p>This work focuses on the design and development of an improved mud cookstove by optimizing 5 key design parameters: primary air area ratio, secondary air inlet area, L/D ratio, pot gap and grate height, and understanding their effect on the performance. Multiple field-scale prototypes were fabricated at various combinations of design parameters and tested for responses: thermal efficiency, CO and PM<sub>2.5</sub> emissions per MJ of energy delivered to the cooking pot. The results of the responses were then modelled using the RSM (Response Surface Methodology) technique to fit second-order quadratic models for predicting cookstove performance. Results showed that the improved mud cookstove can achieve Tier-3 performance for thermal efficiency and Tier-4 and Tier-5 performance for PM<sub>2.5</sub> and CO, respectively. The RSM models were then used with a desirability function for robust parameter optimization under different model weights to maximize efficiency and minimize emissions, which resulted in the range of responses for cookstove performance, i.e., η = 26.21–33.08%, CO = 1.72–2.59&#xa0;g/MJ<sub>d</sub> and PM = 95–252&#xa0;mg/MJ<sub>d</sub> obtained at different factor levels. Conformity trials for validating the modelled results showed &lt; 16% average error, suggesting that fractional factorial design, RSM, and desirability functions are useful tools optimizing the performance of a biomass cookstove.</p>

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Multiparameter design optimisation of a mud-based natural draft biomass cookstove using response surface methodology and desirability function

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月6日

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  • Ankit Gupta,
  • Roshan Wathore,
  • Rajat Hedaoo,
  • Hemant Bherwani,
  • Ashwinkumar S. Dhoble,
  • Nitin Labhasetwar

摘要

This work focuses on the design and development of an improved mud cookstove by optimizing 5 key design parameters: primary air area ratio, secondary air inlet area, L/D ratio, pot gap and grate height, and understanding their effect on the performance. Multiple field-scale prototypes were fabricated at various combinations of design parameters and tested for responses: thermal efficiency, CO and PM2.5 emissions per MJ of energy delivered to the cooking pot. The results of the responses were then modelled using the RSM (Response Surface Methodology) technique to fit second-order quadratic models for predicting cookstove performance. Results showed that the improved mud cookstove can achieve Tier-3 performance for thermal efficiency and Tier-4 and Tier-5 performance for PM2.5 and CO, respectively. The RSM models were then used with a desirability function for robust parameter optimization under different model weights to maximize efficiency and minimize emissions, which resulted in the range of responses for cookstove performance, i.e., η = 26.21–33.08%, CO = 1.72–2.59 g/MJd and PM = 95–252 mg/MJd obtained at different factor levels. Conformity trials for validating the modelled results showed < 16% average error, suggesting that fractional factorial design, RSM, and desirability functions are useful tools optimizing the performance of a biomass cookstove.