## 1 Introduction
Other standards that deal with thermal comfort models used for design, assessment, and categorization of the indoor thermal environment, are ANSI/ASHRAE Standard 55-2017 [27] and EN 16798-1:2019 [28]. ISO 7730:2005 [11] defines, and EN 16798-1:2019 [28] applies four types of local discomforts: radiant asymmetry in both the horizontal (left-right, front-back) and the vertical plane (top-bottom), the vertical temperature difference between the ankle and head level, floor temperature, and DR. ANSI/ASHRAE Standard 55-2017 [27] applies only the first three discomforts. ISO 7730:2005 [11] provides models for evaluation of the percentage of dissatisfied (PD) due to each of these discomforts. The two other standards [27; 28] prescribe design criteria for the indoor thermal environment and suggest some procedures for the design. Satisfying all requirements of one of the standards during the design of the thermal environment in densely occupied spaces with total volume ventilation is a complicated task. The numerical simulations based on Computational Fluid Dynamics (CFD) are relatively easy tools for designing the thermal environment indoors [29; 30; 31]. Typically, RANS (Reynolds Averaged Navier-Stokes) technique combined with a turbulence model and models for evaluation of all indices characterizing the indoor thermal environment is applied [32]. There are models for all indices, except for the DR. The prediction of DR, based on steady-state CFD simulations with applied RANS technique, is relatively easy since all needed quantities are provided by the numerical solution [33]. However, RANS results depend strongly on the particular turbulence model used. RANS uncertainties could be significant, especially when modelling is applied to a fully-developed turbulent jet in combination with a moderate Reynolds number flow in low-velocity occupied zone [34]. To get more accurate predictions of turbulent flows, an unsteady eddy-resolving technique should be applied, like Large Eddy Simulation, LES [35], implicit LES or, in case of limited computational resources, Unsteady RANS (URANS). Calculation of DR based on discrete physical measurements or unsteady CFD simulation, e.g., URANS technique, is much more complicated. DR assessment based on numerical predictions and measurements requires information for the length of the time interval, over which mean air temperature, mean air velocity, and turbulence intensity, are calculated. Information about the sampling rate (1/\(\Delta\tau\)) is also needed. No version of [11], even the last one, has provided information for these quantities. The reason is that the DR model was developed based on an exposure period of 15 min [25]; an analogue constant temperature thermo anemometer measured the air velocity, and the definition of a sampling rate was meaningless. A procedure for assessment of DR in practice was developed later in collaboration between the Technical University of Denmark and Technical University of Sofia research groups; this procedure was described in detail in [36]. The measuring interval and the sampling rate were set to 3 min and 5 Hz, respectively. However, these values cannot be universally applied since impulse sources (fans, fan coils) and air terminal devices (ATD) with different characteristics are used in the ventilated spaces (with different size and shape). As a result, flows characterized by a wide variety of time and length scales would exist in the particular indoor space. [PERSON] et al. [16] also provided criticism towards the existing standards in terms of DR: they found out that the standards do not specify how to select relevant conditions and locations for measurement of DR. The study has also concluded that the standards do not provide questionnaires for the assessment of occupant dissatisfaction, which are detailed enough. The objective of this paper is to initiate discussions for improvement of the ISO 7730:2005 [11] procedure for DR assessment in indoor spaces when strong unsteadiness of the airflow is expected.