## 2 Materials and Methods
### CFD Simulation Methodology  
The CFD analysis was performed using Fire Dynamics Simulator (version 6.7.9), an open-source CFD software package dedicated to modeling low-speed turbulent flows using the LES (Large Eddy Simulation) approach to turbulence. The software was developed by the National Institute of Standards and Technology (NIST) [32] and is an extensive tool for predicting velocity distributions, smoke flow, and fire development [33; 34; 35]. The software solves the LES equations (temporally and spatially filtered Navier-Stokes equations) to directly resolve the large turbulent scales responsible for the turbulent transport of mass and momentum. In this simulation, the flow is primarily driven by the positive pressure ventilator. The transport of subgrid-scale momentum is modeled using an eddy viscosity approach based on the Deardorff model [36]. Further details on the implementation of the SGS model can be found in the FDS technical reference guide [37]. The FDS program uses explicit time steps with automatic control to maintain the maximum Courtant-Friedrischs-Lewy CFL condition in the domain in the range of 0.8 to 1.0 [38]. The update of the velocity equation solution occurs repeatedly for each time step until the maximum velocity error is reduced below a specified tolerance threshold (set at 0.001 m/s).  
The analysis employed an isothermal flow model. Pyrosim 2022.3.1208 software was used for visualizing the model. The boundary condition for the air jet generated by the positive pressure ventilator was described using the \"Velocity Patch\" function [37], which allows for the assignment of a non-uniform velocity profile on the surface of the  
Figure 2: Diagram of the test configuration to assess the velocity profile in the immediate area of the ventilator impeller, where 1—measurement point of the dynamic pressure of the air jet; 2—hub on the impeller shaft (dead flow zone).  
ventilator. This function was implemented by providing flow velocity values obtained from experimental studies. The boundary condition for the volume flow rate generated by the ventilator was the product of the average velocities on the surface of the ventilator's impeller and the area of the impeller surface, which corresponds to a value of 12,600 m\({}^{3}\)/h (Table A1). The airflow on the impeller surface was measured using the \"volume flow in the gas phase\" function [20]. This simulation setup provided a detailed and accurate representation of the ventilator's performance in generating airflow, which was essential for the analysis of its impact on the environment in a firefighting or rescue operation.  
For the CFD simulation, a geometry corresponding to the real dimensions of the test setup and the ventilator was developed. The spatial model was constructed on a Cartesian computational grid divided into 447,252 computational cells, each with dimensions of 0.05 \(\times\) 0.05 \(\times\) 0.05 m. The level of detail for all elements of the model, including the ventilator housing and the test setup structure, was designed with an accuracy corresponding to the grid cell resolution, i.e., 5 cm. As part of the work performed, an analysis of the mesh convergence was performed, which showed that the indicated value was optimal, i.e., it allows for the assessment of the positioning distance of the positive pressure ventilator without the need to engage too much computing power.  
The remaining parameters of the model were as follows: atmospheric pressure: 1013.3 hPa; ambient temperature: 15 \({}^{\circ}\)C; primary materials used in the model construction: steel and wood; relative humidity: 50%; atmospheric temperature gradient: 0.03 K/m. The model was equipped (Figure 3) with measurement points to record the airflow velocity on the surface of the door opening (the same layout as in the experimental tests conducted in real-world conditions), with a total of 50 measurement points.