## 5 Results and Discussion
The first group of computational experiments examined the effects of various forest fires on a wall made from unpainted wood materials. As it was established as a result of modeling, the wall heats up mainly at the stage preceding the ignition, and heating occurs in the surface layers of wood with a thickness of about 2 cm. Temperature distributions in the plywood enclosure were obtained. The results are shown in Figure 10.0 Although the propagation speed is not high, the surface temperature exceeds 800 \({}^{\circ}\)C for an exposure time of 425 s. The results disagree with the results in [61]. This discrepancy can be caused by the feature of rounding numbers in different programming language; the feature of parallel calculation. A high intensity surface forest fire has a significant effect on surface temperature. After 350 s of exposure, the temperature at the boundary and the heat flux reaches their limit values, and the boundary condition can no longer be calculated. This phenomenon can be associated with the fact that the wood begins to smolder and give off to the environment a heat flux equal to the heat flux from the forest fire front and no further heating occurs. In a crown fire, the critical temperature is reached within one minute of exposure. Critical temperatures are reached in the range of heights from 1 to 10 m. Temperature fields were calculated in various materials of construction. Figure 13 shows the temperature distribution over the depth of the material. The scenario of a low-intensity ground forest fire was considered. The exposure time is 425 s. As can be seen in Figure 13, the maximum heating of the material corresponds to pine wood. The least effect of heat flow is observed for facing cardboard and fiberboard with a density of 1000 kg/m\({}^{3}\). Temperatures reach critical values, while the falling heat flux is not large. Figure 10.1 Impact of surface forest fires (high intensity) on various materials from a distance of 20 m for 350 s of exposure—temperature distribution along the wall thickness. Figure 14 shows the temperature distribution over the depth of the material. A scenario of a high-intensity surface forest fire was considered. The exposure time is 350 s since further recalculation of the boundary conditions does not occur. The temperatures at the border are above critical. In this case, ignition of the structure is inevitable. A crown forest fire was not considered, since in the event of such a fire developing near the building, the owner can only be saved through evacuation. Thus, it can be seen that the ignition of the structures of a wooden building occurs in a fairly short exposure time. The computation time of the sequential prediction algorithm is longer than the ignition time of structures under the scenarios presented in this work. The demand for reducing the simulation time is extremely high, otherwise such models will not be of practical importance. Possible ways to reduce the simulation time include a decrease in the resolution of the computational grid, which will cause a significant drop in the simulation accuracy; at sufficiently low resolutions, the temperature data in the near-surface layer can differ several times, which is unacceptable. The second option considered in this paper is distributed computing. With parallel calculations, it is possible to achieve the speed of calculating temperature fields on computational grids with a high resolution comparable to the speed of calculating temperature fields with a low resolution. With a low accuracy of calculating the temperature fields, parallel calculations will not have advantages, but on the contrary will be inferior in speed to a simple synchronous algorithm, since the operating time of each individual process will be less than the calculation time, and a further increase in the calculation processes will increase the operating time of the algorithm presented in the work by value \(2n\), where \(n\) is the number of additional processes involved in the calculation.