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

Area of Science:

• Engineering
• Environmental Science
• Energy Research

Background:

• Traditional cookstoves contribute to indoor air pollution and low energy efficiency.
• Optimizing cookstove design is crucial for improving health and reducing fuel consumption.

Purpose of the Study:

• To design and develop an improved mud cookstove by optimizing key parameters.
• To evaluate the impact of design parameters on thermal efficiency and emissions (CO, PM2.5).

Main Methods:

• Fabrication of field-scale prototypes with varied design parameters.
• Performance testing for thermal efficiency and emissions (CO, PM2.5).
• Modeling using Response Surface Methodology (RSM) and optimization via desirability functions.

Main Results:

• Achieved Tier-3 thermal efficiency and Tier-4/Tier-5 for PM2.5 and CO emissions.
• Optimized models predicted efficiency (26.21-33.08%), CO (1.72-2.59 g/MJd), and PM2.5 (95-252 mg/MJd).
• Validation trials showed less than 16% average error.

Conclusions:

• Fractional factorial design, RSM, and desirability functions are effective for optimizing biomass cookstove performance.
• The developed mud cookstove design offers significant improvements in efficiency and emission reduction.
• This approach provides a robust framework for enhancing cookstove technology.