## 6 Conclusions  
The paper presents the results of a combined numerical and experimental study of room air movement in a test university classroom with a controlled indoor environment. Both the 3D field results computed with the unsteady RANS technique and the real-scale long-term point velocity data measured with the thermo anemometer report about strong unsteadiness of the airflow. Low-frequency high-amplitude velocity fluctuations emerging due to airflow instability lead to strong time variation of the draught rate that corresponds to possible uncertainty in the percentage of dissatisfied persons due to unwanted local cooling/heating related to draught. For large indoor spaces with numerous interacting air supply jets, it is recommended to assess \(DR\) based on time records of both air velocity and air temperature not shorter than half an hour. The categorization procedure must be done for a sufficiently long interval. The recommendation/ guidance of such kind must be given in the standards since not all people dealing with categorization and assessment of the indoor thermal environment are professionals in the field of fluid mechanics. However, as it is not possible to specify a universal length of the time interval for the \(DR\) assessment procedure in case of a low-frequency unsteadiness occurs, a preliminary study of the \(DR\) sensitivity to the averaging period should be done during a categorization procedure. In case of categorization of the thermal environment, the time-point measurements or steady-state RANS computations would lead to wrong conclusions as well as they cannot be used for identification of the reasons for complaints due to draught discomfort, if strong unsteadiness of the airflow is expected. In general, the presented analyses demonstrated the importance of the combination of the unsteady computer simulations and long-term measurements for the correct assessment of both \(DR\) and thermal comfort, as well as for the proper categorization of the indoor thermal environment. The general recommendation is to perform measurements and simulations under design conditions, with respect to both occupancy and mode of operation. If geometry details and occupants are modelled in an engineering study, the grid has to be coarse to reduce the computational cost. Even in this case, the CFD problem formulation must be unsteady, and the turbulence model and the quality of the mesh must be sufficient to reproduce the main low-frequency pulsations. A study of the \(DR\) variation effects in case of an indoor space is filled with the furniture and occupants is planned as future work. Figure 12: Categorization of the classroom environment, based on measured \(DR\) time variation: (a) \(z=0.1\) m, (b) \(z=0.6\) m, (c) \(z=1.1\) m, and (d) \(z=1.7\) m (data for \(\theta=25^{\circ}\), case #1). To summarize, the \(DR\) assessment must be done for a sufficiently long interval allowing identification of the velocity field variations and the \(DR\) variation in the interval for assessment should be as small as possible. However, even if these conditions are fulfilled, the indoor space categorization could be uncertain, e.g., the indoor space could be related to different categories for successive relatively long periods of time. It is necessary to investigate what happens with the occupant's complaints if categorization in an indoor space varies in time. Thus, additional research is needed on how people perceive the thermal environment under the low-frequency unsteadiness. Analysis of the possible complaints about the thermal environment that cannot be discovered by local short-time measurements is also a field for future work. Conceptualization, P.S. and E.S. ; Data curation, D.M., N.I., G.P. and I.S. ; Formal analysis, D.M., N.I. and R.V. ; Funding acquisition, P.S., E.S., and N.I. ; Investigation, D.M., M.Z. and G.P. ; Methodology, D.M., N.I. and V.R. ; Project administration, P.S. and E.S. ; Resources, R.A.A. ; Supervision, P.S. and E.S. ; Validation, N.I. and M.Z. ; Visuilization, M.Z.