The purpose of the present paper is to mathematical simulation of heat transfer in enclosures of wood-based building when exposed to thermal radiation from forest fire front. One-dimensional mathematical model is used. Mathematically, heat transfer in building enclosures is described by system of non-stationary equations of heat conduction with corresponding initial and boundary conditions. It is suggested to use several scenarios of forest fire impact. Temperature distribution on wall depth is obtained for different scenarios of forest fire impact on building enclosures.
Forest fires have a negative impact on the economy in a number of regions, especially in Wildland Urban Interface (WUI) areas. An important link in the fight against fires in WUI areas is the development of information and computer systems for predicting the fire safety of infrastructural facilities of Russian Railways. In this work, a numerical study of heat transfer processes in the enclosing structure of a wooden building near the forest fire front was carried out using the technology of parallel computing. The novelty of the development is explained by the creation of its own program code, which is planned to be put into operation either in the Information System for Remote Monitoring of Forest Fires ISDM-Rosleskhoz, or in the information and computing system of JSC Russian Railways. In the Russian Federation, it is forbidden to use foreign systems in the security services of industrial facilities. The implementation of the deterministic model of heat transfer in the enclosing structure with the complexity of the algorithm O (2N2 + 2K) is presented. The program is implemented in Python 3.x using the NumPy and Concurrent libraries. Calculations were carried out on a multiprocessor cluster in the Sirius University of Science and Technology. The results of calculations and the acceleration coefficient for operating modes for 1, 2, 4, 8, 16, 32, 48 and 64 processes are presented. The developed algorithm can be applied to assess the fire safety of infrastructure facilities of Russian Railways. The main merit of the new development should be noted, which is explained by the ability to use large computational domains with a large number of computational grid nodes in space and time. The use of caching intermediate data in files made it possible to distribute a large number of computational nodes among the processors of a computing multiprocessor system. However, one should also note a drawback; namely, a decrease in the acceleration of computational operations with a large number of involved nodes of a multiprocessor computing system, which is explained by the write and read cycles in cache files.
Forest fires are one of the strongest natural phenomena, occurring both for natural and man-made reasons. Forest fires entail not only economic losses, but also affect the ecological, biological and demographic picture of the region of its origin and far beyond its borders. Around the world, work is underway to develop effective methods for predicting the impact of a forest fire on the environment, the speed and direction of propagation and impact on various infrastructure facilities near the wildland–urban interface (WUI). The purpose of the work is to review recent and significant research works on the physical and chemical processes in wooden construction materials during WUI fires. As a result of the analysis of literary sources, works devoted to the modeling and experimental study of various physical and chemical processes, namely, the impact of forest fires on residential and industrial facilities, heat and mass transfer in structural materials, drying processes, pyrolysis, and ignition of structural materials, are highlighted. The results of the analysis of literature sources and promising directions are presented in the Discussion section. The formulated conclusions are presented in the Conclusion section. The main conclusion is that the existing experimental and theoretical work can be integrated into the developed deterministic–probabilistic approach for predicting the impact of a forest fire on buildings.
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