2016
DOI: 10.1016/j.apenergy.2016.05.045
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Application of response surface methodology to investigate the effect of different variables on conversion of palm kernel shell in steam gasification using coal bottom ash

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Cited by 81 publications
(27 citation statements)
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“…A high F ‐value and low p ‐value indicate that the model is significant to predict the responses. Both the coefficient of determination ( R 2 ) and the adjusted coefficients of determination ( R 2 adj ) indicate goodness‐of‐fit for the model 21 …”
Section: Resultsmentioning
confidence: 99%
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“…A high F ‐value and low p ‐value indicate that the model is significant to predict the responses. Both the coefficient of determination ( R 2 ) and the adjusted coefficients of determination ( R 2 adj ) indicate goodness‐of‐fit for the model 21 …”
Section: Resultsmentioning
confidence: 99%
“…We used the Response Surface Methodology (RSM) to optimize the test conditions as it is a useful technique for analyzing and optimizing a response with respect to the independent variables 25 . The most popular RSM technique, and one that is able to be used to fit the second order polynomial equations, is Central Composite Design (CCD), a useful method to evaluate the curvature of the non‐linear response surface 21 . In present work, we used a three‐level, three‐factor central compost design consisting of 18 experiments to investigate the effect of phase change temperature and the amount of PCMs located inside the freezer on the reduction rates of energy consumption and of temperature fluctuations.…”
Section: Methodsmentioning
confidence: 99%
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