A fire risk pre-warning framework for high-rise buildings based on unascertained method

Area of Science:

• Fire Safety Engineering
• Risk Assessment
• Building Science

Background:

• Increasing global focus on high-rise building fire prevention and control.
• Need for scientific indicator systems in fire risk assessment models.
• Challenges posed by the uncertainty of fire occurrence in complex structures.

Purpose of the Study:

• To establish an early warning framework for fire risk in high-rise buildings.
• To develop a scientific indicator system for high-rise building fire risk assessment.
• To provide a reliable decision support system for fire disaster prevention.

Main Methods:

• Combined event analysis method with building design fire codes to identify 11 key risk factors.
• Established a high-rise building fire risk warning tree.
• Employed the unascertained method for fire risk modeling and early warning.
• Validated methodology through case studies and empirical data analysis.
• Compared unascertained method results with K-means clustering.

Main Results:

• Identified 11 critical risk factors impacting high-rise building fire prevention.
• Developed a functional fire risk warning tree for indicator systems.
• The unascertained method demonstrated higher accuracy in predicting building fires compared to the K-means method.
• Empirical validation confirmed the methodology's effectiveness.

Conclusions:

• The unascertained method provides a more accurate prediction of building fires.
• The developed framework offers a reliable decision support system for high-rise building fire prevention and control.
• This research contributes to enhancing fire safety strategies in tall structures.