Comparative Study of Fire Resistance and Char Formation of Intumescent Fire-Retardant Coatings Reinforced with Three Types of Shell Bio-Fillers

Three types of shell bio-fillers, including eggshell (CES), conch shell (CHS) and clamshell (CMS), were prepared by cleaning, ultrasonication and pulverizing processes of biowastes, and then applied to intumescent fire-retardant coatings. The effects of shell bio-fillers with different polymorphs on the fire resistance and char-forming of intumescent fire-retardant coatings were investigated by cone calorimeter test, fire protection tests, smoke density test, thermogravimetric analysis (TG), and the fire resistance and char-forming mechanism of bio-fillers in intumescent fire-retardant coatings were proposed. The results show that three kinds of bio-fillers exert an excellent synergistic effect on enhancing the fire resistance and char-forming properties of the intumescent fire-retardant coatings, while clamshell has the best synergistic efficiency among the bio-fillers. Especially, IFRC-CMS coating containing 3 wt% clamshell shows the best fire protection performance and lowest smoke production and heat release, which offers an equilibrium backside temperature of 134.6 °C at 900 s, a flame-spread rating of 14.4, and a smoke density rating value of 22.8%. The synergistic efficiency of bio-fillers in the intumescent coatings depends on the polymorphs of CaCO3 in bio-fillers, and aragonite CaCO3 shows a higher synergistic efficiency compared to calcite CaCO3 and the mixture of aragonite and calcite CaCO3. The CMS composed of aragonite shows the best synergistic effect, CHS composed of aragonite and calcite comes second, and CES composed of calcite has the weakest synergistic effect.

Towards Fire Prediction Accuracy Enhancements by Leveraging an Improved Naïve Bayes Algorithm

To improve fire prediction accuracy over existing methods, a double weighted naive Bayes with compensation coefficient (DWCNB) method is proposed for fire prediction purposes. The fire characteristic attributes and attribute values are all weighted to weaken the assumption that the naive Bayes attributes are independent and equally important. A compensation coefficient was used to compensate for the prior probability, and a five-level orthogonal testing method was employed to properly design the coefficient. The proposed model was trained with data collected from the National Institute of Standards and Technology (NIST) fire database. Simulation comparisons show that the average prediction accuracy of the proposed method is 98.13%, which is 5.08% and 2.52% higher than the methods of naive Bayes (NB) and double weighted naive Bayes (DWNB), respectively. The experimental results show that the average accuracies of the DWCNB method for test fire and interference sources were 97.76% and 98.24%. Prediction accuracies were 5.06% and 3.74% higher than those of the NB and DWNB methods.

Technique for Studying of the Dynamics of Changes of a Smoky Environment Parameters during the Transition of Pyrolysis to Flame Combustion

The existing methods for monitoring the performance of multi-criteria fire detectors do not provide for verification of their characteristics in the conditions of transition from smoldering to flame burning. The aim of the work is the development of the research methods of the environmental parameters during the transition from smoldering (pyrolysis) to flame combustion for simulation a test fire while checking the quality of multi-criteria fire detectors.A technique to conduct research of environmental parameters under conditions of heating wood samples of different sizes to a temperature of selfignition and burning crumpled and smooth paper has been developed.Changes in the concentration of carbon monoxide, specific optical density, and scattering ability during the transition from smoldering (pyrolysis) to flame burning of prepared wood and crumpled paper were studied for the first time.It is shown that the controlled environmental parameters during the transition from smoldering pyrolysis to flame burning change together. Conclusion: the speed of growth of the scattering ability of smoke decreases by 2.4 times, the speed of increase in the specific optical density and concentration of carbon monoxide increases by 2 and 5.3 times (respec-tively), during the transition from pyrolysis to flame burning of wood.