## 2 Derivation and Analysis for Statistical Indoor EZ  
Figure 1 presents the derivation process to obtain the statistical indoor EZ for an actual NPP environment by investigating electromagnetic fields using a statistical method. To examine the indoor electromagnetic fields, the transmitting antenna is placed in an arbitrary location, and the received power is observed in all indoor locations. The proposed statistical indoor EZ is achieved according to the following procedure: first, the indoor space around the transmitting antenna is classified into multiple observation regions. In Figure 1a, \(\phi_{T}\) is the azimuth angle around the transmitting antenna. At the same time, the indoor space around the transmitting antenna is divided into 12 regions (_Region n_ from _Region 1_ to _Region 12_), each with a 30\({}^{\circ}\) angle range. EZ boundaries of each region are independently defined within each separate observation region, and the detailed information of each region is listed in Table 1. Second, the received power (by half wavelength dipoles for Rx. and Tx. antennas) is obtained at as many locations as possible in each region, when the total radiated power of the transmitting antenna is assumed to be 1 W. The received power can be obtained through electromagnetic simulations using the modeled indoor NPP environment or by using actual measurements. Herein, each received power datum within each region is arranged according to the azimuth angle and distance from the transmitting antenna. For example, the obtained received power data in _Region n_ tend to gradually decrease with distance, as shown in Figure 1b. Third, the regression model [10; 11; 12; 13; 14] (\(f_{1}\)) is applied for this stored received power data, which helps us to observe the tendency of the received power according to the distance. The regression model (\(f_{1}\)) is derived based on a quadratic function, as indicated by the solid line in Figure 1b. The received power typically decreases in inverse proportion to the square of the distance from the transmitting antenna. The quadratic regression model is a general method to fit the data with a curved distribution [12; 13; 14]. The quadratic regression model can be expressed as below:  
\[f_{1}(d)=a_{1}\cdot d^{2}+a_{2}\cdot d+a_{3} \tag{1}\]  
where \(d\) is the distance from the transmitting antenna, and \(a_{1}\), \(a_{2}\) and \(a_{3}\) are coefficients that best fit the received power data. However, using the obtained regression model is not suitable for the boundary of the statistical indoor EZ. This is because, when applying the general regression function (\(f_{1}\)) to the statistical indoor EZ, there are too many locationswhere the received power exceeds the allowable received power (\(-10.6\) dBm according to the _Regulatory Guide 1.180_[3,8]). Therefore, the margined regression model (\(f_{2}\)), where 95% of the data lie below the curve, is defined based on the general regression model (\(f_{1}\)), as shown by the dashed line in Figure 1b. The margined regression model (\(f_{2}\)) can be defined as below:  
\[f_{2}(d)=f_{1}(d)\cdot K \tag{2}\]  
where \(K\) is the offset of the margined regression model, which makes it possible to determine a reasonable boundary of the statistical indoor EZ. Finally, the boundaries (\(d_{n}\)) of each region (_Region n_) are determined by finding the intersection between the allowable received power (\(-10.6\) dBm) and the margined regression model, as indicated in Figure 1b. This distance \(d_{n}\) is the boundary of the statistical indoor EZ at the specific azimuth range (_Region n_). By using the proposed statistical indoor EZ, we can obtain a less complicated EZ that can be easily applied to the actual NPPs. Then, the I&C equipment can be intuitively placed outside the proposed indoor EZ to satisfy safety issues in accordance with _Regulatory Guide 1.180_.