Experimental study of compartment fire development and ejected flame thermal behavior for a large-scale light timber frame construction

Zhang, Yuchun; Yang, Xiaolong; Luo, Yueyang; Gao, Yunji; Liu, Haiyan; Li, Tao

doi:10.1016/j.csite.2021.101133

Cited by 7 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results of experimental research into the specific aspects of combustion of an indoor wooden frame construction are presented in [18]. In particular, the temperature in the combustion zone, weight loss of burning materials, temperature profiles outside the openings-facade wall and the size of emerging flame were estimated.…”

Section: Nomentioning

confidence: 99%

Influence of Compartment Fire Behavior at Ignition and Combustion Development Stages on the Operation of Fire Detectors

Жданова

Волков

Sviridenko

et al. 2022

Fire

View full text Add to dashboard Cite

This paper presents experimental research findings for those involved in the early phase of fire in office buildings. Class A model fires with a reaction area from 5 cm2 to 300 cm2 were chosen for investigation. To mock up a fire, the following combustible materials typical of offices were used: wood pieces, heat-insulated linoleum, paper and cardboard. The main characteristics of a model fire were recorded: temperature in the combustion zone, heat release, time of complete burnout and concentration of flue gas components. Typical trends and histograms of changes of these characteristics over time were presented; stages of ignition, flame combustion and smoldering were illustrated. The key characteristics of fire detector activation at different stages of model fire combustion were analyzed. Dead bands and operation conditions of a group of detectors (smoke, heat, optical, flame), their response time and errors were identified. It has been established that the most effective detectors are flame and smoke detectors. Specific operational aspects of detectors were established when recording the ignition of different types of model fires. The viability of combining at least two detectors to record fire behavior was established. Recommendations were made on using the obtained findings when optimizing the systems for detecting and recording the start of a compartment fire.

show abstract

Section: Nomentioning

confidence: 99%

Influence of Compartment Fire Behavior at Ignition and Combustion Development Stages on the Operation of Fire Detectors

Жданова

Волков

Sviridenko

et al. 2022

Fire

View full text Add to dashboard Cite

show abstract

“…If a fire with good ventilation cannot be controlled in time, the ambient temperature will increase rapidly from the development stage, which may even cause a flashover and lead to catastrophic consequences that threaten life and possession. [1][2][3][4] Thus, a positive early fire detection and alarm technology are essential as the initial stage is the best time for firefighting. Traditional fire detection technology is usually based on the detectors, such as smoke, temperature, and optical flame detectors, which are triggered by the corresponding threshold.…”

Section: Introductionmentioning

confidence: 99%

“…As is well‐known, fire development usually consists of four stages: initial stage, development stage, fully developed stage, and extinguishing stage. If a fire with good ventilation cannot be controlled in time, the ambient temperature will increase rapidly from the development stage, which may even cause a flashover and lead to catastrophic consequences that threaten life and possession 1‐4 . Thus, a positive early fire detection and alarm technology are essential as the initial stage is the best time for firefighting.…”

Section: Introductionmentioning

confidence: 99%

An efficient fire detection algorithm based on multi‐scale convolutional neural network

et al. 2021

Self Cite

View full text Add to dashboard Cite

Video fire detection (VFD) technology has shown a broad application prospect with the popularization of camera monitoring systems. Since the initial stage is the best time for firefighting, it's crucial to develop a robust algorithm for early warning. In this paper, an efficient VFD fusion algorithm is presented. First, the fire candidate areas (FCA) are located quickly based on low-level visual features to guarantee well timeliness. Furthermore, a multi-scale convolutional neural network with spatial pyramid pooling is built and trained on the dedicated flame data set without the requirement of sample labeling. In this case, FCA with different aspect ratios and scales can be accurately identified. The method is fully tested on various databases of arbitrarysized images and videos. Experimental results show that the proposed fusion algorithm, in addition to improving the detection efficiency, also ensures the accurate identification of flames on different scales.

show abstract

Resistance to Fire

Makovická Osvaldová,

Fatriasari

2023

The Society of Fire Protection Engineers Series

View full text Add to dashboard Cite

Experimental study of compartment fire development and ejected flame thermal behavior for a large-scale light timber frame construction

Cited by 7 publications

References 18 publications

Influence of Compartment Fire Behavior at Ignition and Combustion Development Stages on the Operation of Fire Detectors

Influence of Compartment Fire Behavior at Ignition and Combustion Development Stages on the Operation of Fire Detectors

An efficient fire detection algorithm based on multi‐scale convolutional neural network

Resistance to Fire

Contact Info

Product

Resources

About