Burning velocity is one of the fundamental flammability parameters, and the maximum burning velocity is a crucial criterion of flammability classification of refrigerants. In this study, an experimental system for measuring the burning velocity of low-carbon flammable gases was established based on ISO standard 817. The combustion reactions of mixture refrigerants consisting of R1243zf, RE170 and flame retardants (R13I1, R134a, or R125) were experimentally investigated. In addition, a combustion reaction kinetic model applicable to R1243zf and its mixtures was established, consisting of 178 species and 1442 elementary reactions. The modified kinetic mechanism reproduced the ISO 817 vertical-tube-derived burning-velocity dataset for R1243zf and its mixtures with a mean deviation of 14.5
This article studied the temperature evolution and flame ejection of enclosure fires with the upper and lower openings. Experiments were conducted inside a reduced-scale enclosure with the side length of 0.4 m, which has two openings of the same size, vertically distributed and separated at a distance. Temperature inside the enclosure and flame behavior were recorded for different window sizes, heat release rates and opening separation distances. Result shows that: (1) Temperature inside enclosure rises as total HRR increases, and falls as the opening separation distance increases. This is because air flow rate entering the enclosure increases with the increase of opening separation distance. (2) Critical HRR of ejection rises as the window size increases, and decreases as the increase of opening separation distance. This is because that when the upper opening position is higher, flames are more likely to eject out from the opening after reaching the enclosure top. (3) A normalized separation distance was proposed, which well characterized the effect of separation distance on inside temperature and flame ejection, and the temperature and critical flame ejection were correlated well by the normalized distance. This study for the first time revealed the temperature evolution and flame ejection inside a double-opening enclosure, analyzed the effect of opening separation distance, and proposed the models to quantify the inside temperature and critical HRR for flame ejection, which would make a significant contribution in the theory of building fire dynamics.
In this work, the combustion dynamics and smoke spread behavior of 18,650 lithium-ion batteries (LIBs) with varying states of charge (SOC: 25
The integration of flame-retardant (FR) materials into electrical cables mitigates fire hazards; however, the widespread industrial practice of pairing flame-retarded sheaths with non-flame-retarded insulations offers protection only below a critical external heat flux. Beyond this threshold, the sheath’s suppression capacity is exceeded, allowing the insulation to pyrolyze and significantly elevate the fire risk. While non-FR insulations are widely utilized for their dielectric strength, flexibility, durability, and cost-effectiveness, their contribution to fire growth remains a concern and requires further elucidation. Therefore, this study investigates the fire behavior of two industrial cables: MKEM-HF, comprising solely an FR sheath, and XMK-HF, consisting of an FR sheath over a highly flammable insulation, under a heat flux exceeding the sheath capacity to protect the inner insulation layer. Thermogravimetric (TGA) and Differential Scanning Calorimetry (DSC) analyses were conducted to characterize thermal degradation of the cable layers and develop pyrolysis models. Cone calorimetry at 50 kW · m^-2 assessed fire behavior under gasification and flaming, for both single- and multi-cable configurations. MKEM-HF displayed a descending MLR-HRR profile over time, whereas XMK-HF exhibited a continuously rising trend with a dominant final peak, driven by the decomposition of the insulation. A classical 1D slab model of the cone calorimetry was used for inverse estimation of thermal properties and heats of combustion. A geometrical modification on the 1D model allowed the simulation of early insulation exposure, offering a possible approach for modeling the sheath’s mechanical rupture. A more advanced 2D model, accounting for cylindrical geometry and improved boundary coupling, demonstrated superior performance in transient heat transfer and peak prediction compared to the 1D model. The study highlights the critical influence of non-flame-retarded insulation on cable fire behavior and demonstrates the necessity of advanced modeling approaches beyond simple slab approximations to capture these effects.
Fires inflict substantial losses of life and property annually, posing a severe threat to global cultural heritage, particularly wooden structures such as timber arch lounge bridges. Timber arch lounge bridges, also known as Chinese covered timber bridges or covered bridges, feature complex fire spread dynamics, which poses a challenge to the accuracy and real-time capability of fire prediction technology. However, existing computational fluid dynamics (CFD) simulation methods, when applied to timber arch lounge bridges, are computationally expensive and impractical for real-time applications. To address these challenges, this study proposed a fire prediction fusion framework with high temporal resolution and long-term forecasting capability based on spatiotemporal attention mechanisms. First, the sparsity prediction module generates a sparse sequence through recurrent iterative operations. Subsequently, the interpolation module interpolates the missing values to form a complete prediction sequence. The fusion framework demonstrated enhanced long-term prediction performance across both timber arch lounge bridge and closed-building layouts compared to the baselines. Moreover, the fusion framework achieves a 36-fold speed increase over conventional CFD methods in timber arch lounge bridge layouts, indicating its performance advantage. While the current model is trained and validated under a specific fire scenario, these results suggest that the proposed framework has the potential to provide a high-accuracy real-time fire prediction method for emergency management and fire-fighting rescue.
