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Combustion model of effective-potential fire loads based on data fusion: Quantitative methods for predicting solid fuel fires in tunnel | Synapse
March 3, 2026
Combustion model of effective-potential fire loads based on data fusion: Quantitative methods for predicting solid fuel fires in tunnel
YY
Yunping Yang
XL
Xiaosong Li
HZ
Hongjin Zhang
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Key Points
Effective-potential fire loads indicate the significant risk solid fuel fires pose in tunnel settings, unresolved by existing models.
The analysis reveals a fire load reduction of up to 50% using advanced data fusion techniques to optimize predictions.
Combustion modeling employs quantitative methods to assess fire risks based on integrated data from various sources.
These innovative measures highlight the need for enhanced safety standards in tunnel designs due to potential fire hazards.
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Yang et al. (Tue,) studied this question.
synapsesocial.com/papers/69a75b46c6e9836116a22593
https://doi.org/https://doi.org/10.1016/j.ijheatmasstransfer.2026.128424
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