Scattering Characteristics of Fire Smoke and Dust Aerosol in Aircraft Cargo Compartment

Zhou, Yong; Shi, Long; Li, Cong; Zhang, Heping; Zheng, Rong

doi:10.1007/s10694-023-01430-7

Fire Technol

2023

DOI: 10.1007/s10694-023-01430-7

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Scattering Characteristics of Fire Smoke and Dust Aerosol in Aircraft Cargo Compartment

Yong Zhou,

Long Shi,

Cong Li

et al.

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Cited by 3 publications

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Efficient detection of different fire scenarios or nuisance incidents using deep learning methods

Özyurt

2024

Journal of Building Engineering

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Efficient detection of different fire scenarios or nuisance incidents using deep learning methods

Özyurt

2024

Journal of Building Engineering

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Experimental Study on Early Fire Smoke Characteristics in a High-Volume Space: A Fire Detection Perspective

Wang,

Zhang,

et al. 2024

Fire

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High-volume space structures are characterized by high combustible loads, rapid fire development, difficulty in firefighting, and potential building collapse risks, making early fire detection particularly crucial. The effectiveness of early fire detection technologies relies on their ability to adapt to the characteristics of smoke-dominant combustion products in the protected space. However, there is a lack of targeted research on the characteristics of the smoke generated during the early low-power stages of fires in high-volume spaces, which has not supported the development of early fire detection technologies for such environments. To address this, this paper presents an experimental study that, for the first time, collects data on fire smoke parameters such as temperature, velocity, concentration, and particle size at heights ranging from 6.5 m to 18.5 m using lightweight sensors. The study analyzes the characteristic and correlations of these parameters and their impact on early fire detection in high-volume spaces for the first time, presenting variation patterns in the plume velocity and particle size distribution of early fire smoke with height. It identifies three patterns of particle size distribution, contrasting with previous studies, and offers a qualitative explanation for these findings. This research enhances the understanding of early fire smoke signals in large spaces and offers valuable insights for developing more accurate and efficient fire detection strategies and technologies.

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Study on Response Time Hysteresis Model of Smoke Detectors in Aircraft Cargo Compartment

Cui,

Ruan,

Wang

et al. 2024

Fire

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A fire in the cargo compartment has a major impact on civil aviation flight safety, and according to the airworthiness clause of the CCAR-25, the detector must sound an alarm within 1 min of a fire in the cargo compartment. As for the cargo compartment of large transport aircrafts, the internal space is high and open, and the smoke movement speed becomes slower with significant cooling in the process of diffusion. Hysteresis can occur in smoke detectors because of their internal labyrinth structure, which causes the detector’s internal and external response signals to be out of sync. This research employs a numerical simulation to examine the detector response parameters under an ambient wind speed of 0.1–0.2 m/s and fits a Cleary two-stage hysteresis model, where τ1= 0.09u−1.43 and τ2= 0.67u−1.59. Finally, multiple full-scale cargo cabin experiments were conducted to validate the prediction model. The results show that the model’s predicted alarm range is 43.1 s to 49.0 s, and the actual alarm time obtained by the experiment falls within this interval, confirming the model’s accuracy and providing theoretical support for the structural design and layout of the aircraft cargo cabin smoke detector.

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Scattering Characteristics of Fire Smoke and Dust Aerosol in Aircraft Cargo Compartment

Cited by 3 publications

References 7 publications

Efficient detection of different fire scenarios or nuisance incidents using deep learning methods

Efficient detection of different fire scenarios or nuisance incidents using deep learning methods

Experimental Study on Early Fire Smoke Characteristics in a High-Volume Space: A Fire Detection Perspective

Study on Response Time Hysteresis Model of Smoke Detectors in Aircraft Cargo Compartment

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