Uncertainty estimation by Bayesian approach in thermochemical conversion of walnut hull and lignite coal blends

- Walnut hull was utilized in (co-)combustion with lignite coal.
- Thermal behaviors of (co-)combustion process was investigated.
- MNLR technique was used to predict the mass loss percentage.
- Bayesian approach was found quite effective in identification of uncertainties.

The main purpose of the present study was to incorporate the uncertainties in the thermal behavior of walnut hull (WH), lignite coal, and their various blends using Bayesian approach. First of all, thermal behavior of related materials were investigated under different temperatures, blend ratios, and heating rates. Results of ultimate and proximate analyses showed the main steps of oxidation mechanism of (co-)combustion process. Thermal degradation started with the (hemi-)cellulosic compounds and finished with lignin. Finally, a partial sensitivity analysis based on Bayesian approach (Markov Chain Monte Carlo simulations) were applied to data driven regression model (the best fit). The main purpose of uncertainty analysis was to point out the importance of operating conditions (explanatory variables). The other important aspect of the present work was the first performance evaluation study on various uncertainty estimation techniques in (co-)combustion literature.

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