Büyükada, Musa2021-06-232021-06-2320170960-85241873-2976https://doi.org/10.1016/j.biortech.2016.11.045https://hdl.handle.net/20.500.12491/9299The aim of present study is to investigate the thermogravimetric behaviour of the co-combustion of hazelnut hull (HH) and coal blends using three approaches: multi non-linear regression (MNLR) modeling based on Box-Behnken design (BBD) (1), optimization based on response surface methodology (RSM) (2), and probabilistic uncertainty analysis based on Monte Carlo simulation as a function of blend ratio, heating rate, and temperature (3). The response variable was predicted by the best-fit MNLR model with a predicted regression coefficient (R-pred(2)) of 99.5%. Blend ratio of 90/10 (HH to coal, %wt), temperature of 405 degrees C, and heating rate of 44 degrees C min(-1) were determined as RSM-optimized conditions with a mass loss of 87.4%. The validation experiments with three replications were performed for justifying the predicted-mass loss percentage and 87.5% +/- 0.2 of mass loss were obtained under RSM-optimized conditions. The probabilistic uncertainty analysis were performed by using Monte Carlo simulations. (C) 2016 Elsevier Ltd. All rights reserved.eninfo:eu-repo/semantics/closedAccessHazelnut HullCo-CombustionMulti Non-Linear RegressionResponse Surface OptimizationMonte Carlo SimulationsArticle10.1016/j.biortech.2016.11.045225106112278887262-s2.0-84997194262Q1WOS:000395693700012Q1