Home / Special Issue / JST Vol. 28 (S1) 2020 / JST(S)-0553-2020


Statistical Analysis of Malaysian Timber’s Combustion Data from Cone Calorimeter Test

Sulaiha Ali, Siti Aslina Hussain, Mohd Zahirasri Mohd Tohir and Ahmad Ainuddin Nuruddin

Pertanika Journal of Science & Technology, Volume 28, Issue S1, December 2020

Keywords: ANOVA, combustion, cone calorimeter test, heat release rate, Malaysian timber

Published on: 16 September 2020

The information on the combustion properties of local timber is crucial in Malaysia as the archival material related to this subject matter is found to be very limited in scope and incomplete. The heat release rate (HRR) is the most precious variable of combustion properties as it provides the key to understand and quantify the hazard in fires. Thus, this work is to verify the reliability of the HRR obtained from cone calorimeter tests conducted upon six Malaysian wood species: Shorea laevis, Vatica rassak, Koompassia malaccensis, Heritiera, Shorea parvifolia and Cratoxylum arborescens. The single factor one-way analysis of variance (ANOVA) was used to investigate statistically significant differences between the means of the HRR dataset of each species during the combustion tests at three different heat fluxes. Later, the confidence interval estimation was occupied to determine the range around the HRR dataset, where the means of the data was likely to be found. The intraclass correlation coefficient (ICC) test was also implemented to assess the reliability of the heat release rate data obtained from the cone calorimeter test. From the surveillance, the P-values of all the six species were higher than α = 0.05, insinuating that the difference between the means of the dataset was not statistically significant. The confidence interval values consisting of the upper bound and lower bound limits indicate that the certainty that these ranges contain the true mean of the heat release rate dataset is 95%. Finally, the fact that heat release data received from the cone calorimeter test were highly reliable to statistically calculate the variation in measurements taken by a single instrument under the same condition confirmed by the ICC’s values of 0.82 to 0.99 that reflect good to excellent correlations.