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Ignition ability prediction model of biomass fuel by arc beads using logistic regression

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Abstract

Wildland–urban interface fires are a severe fire hazard due to biomass ignition caused by arc beads. This study investigated how the energy, diameter, and number of arc beads affect biomass ignition probabilities. An improved experimental method was used to generate arc beads of various arc energies. Here, α-cellulose materials, which are well-characterised as biomass, were used as fuels. A high-speed camera recorded ignition phenomenology, revealing two ignition behaviours of rolling and embedding. The results revealed that an electrical fault arc energy of approximately 175 J was the most dangerous ignition condition. Ignition phenomenology was categorised into ignition and non-ignition, and it was observed that ignition could only occur during the bead rolling process. Contrarily, non-ignition occurred when its bounce even spun plenty of times. Ignition limits, namely the ignition region, potential ignition region, and non-ignition region, were determined. Furthermore, a novel predictive logistic regression-based ignition probability model was established, which indicated that the ignition occurrence of an arc bead was highly dependent on the diameter of the arc bead. The developed mathematical model can reasonably predict the ignition ability of biomass fuel ignition by arc beads.

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Abbreviations

\(f_{{\mathrm{i}}}\) :

Predicted value

g :

Dependent variable, between 0 and 1

\(I_{{\mathrm{n}}}\) :

Value of the instantaneous current (A)

N ig :

Number of tests resulting in flaming ignition

N sum :

Total experiments

P :

Probability of ignition (%)

P model :

Predicted value of the ignition probability model (%)

P 1 :

Observed ignition probability (%)

P 2 :

Evaluation of ignition hazard (%)

R 2 :

Correlation coefficient

\(t_{{\mathrm{n}}}\) :

Arcing time (s)

\(U_{{\mathrm{n}}}\) :

Value of instantaneous voltage (V)

\(W_{{{\mathrm{arc}}}}\) :

Arc energy (J)

x :

Independent variable, in this paper, indicated arc energy (J)

y :

Dependent variable, in this paper, indicated bead diameter (mm)

\(y_{{\mathrm{i}}}\) :

Actual value

\(\overline{y}\) :

Average of the actual value

z :

Independent variable, its variation range is in the real number interval

\(\theta\) :

A parameter

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Acknowledgements

This study was funded by the National Natural Science Foundation of China (No. 52074213), the Natural Science Youth Foundation of Shaanxi Province (2023-JC-QN-0398); the Natural Science Youth Foundation of Hebei Province (E2021507002); the Program of CSC funded by China Scholarship Council (No. 202008610260). In addition, the authors gratefully acknowledge the technical assistance of Prof. Drebenstedt Carsten of Technical University Bergakademie Freiberg (Germany).

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Authors and Affiliations

  1. Postdoctoral Program, Xi’an University of Science and Technology, 58, Yanta Mid. Rd., Xi’an, 710054, Shaanxi, People’s Republic of China

    Hui-Fei Lyu

  2. School of Safety Science and Engineering, Xi’an University of Science and Technology (XUST), Xi’an, 710054, Shaanxi, People’s Republic of China

    Cai-Ping Wang, Jun Deng & Wei-Feng Wang

  3. Department of Fire Protection Engineering, China People’s Police University, Langfang, 065000, Hebei, People’s Republic of China

    Yang Li

  4. Department of Safety, Health, and Environmental Engineering, National Yunlin University of Science and Technology, Yunlin, 64002, Taiwan, ROC

    Chi-Min Shu

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  1. Hui-Fei Lyu
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Contributions

H-FL was involved in article ideas and experimental tests, and wrote the paper. C-PW further deeply discussed experimental ideas. JD completed the data testing. W-FW completed the data analysis. YL improved analysis methods. C-MS helped in review and editing.

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Correspondence to Hui-Fei Lyu or Chi-Min Shu.

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Lyu, HF., Wang, CP., Deng, J. et al. Ignition ability prediction model of biomass fuel by arc beads using logistic regression. J Therm Anal Calorim 148, 4745–4757 (2023). https://doi.org/10.1007/s10973-023-12023-5

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