## 2 Case Setup  
The office is located on the first floor of the building and has the following geometrical dimensions: 4.73 \(\times\) 5.03 m, with a height of 4.24 m. As shown in Figure 1 the office is composed of two thick external masonry walls each containing a large window. The window in the southeastern direction occupies 13.1 m\({}^{2}\), while the one in the northwestern direction is smaller (7.5 m\({}^{2}\)). Each window has a single-glazed glass with a thickness of 4 mm. The fan-coil unit is located under the SE window with an air exit surface of 0.08 \(\times\) 0.65 m (A = 0.052 m\({}^{2}\)). Moreover, four different work stations are located inside the office room. For simplicity, 1 to 4 were assigned to each station to easily recall them in the following paragraphs. The fan-coil unit works at three different air-flow rate levels corresponding to three different velocities of the inlet air. The minimum was 1 m/s and the maximum was 2 m/s. In this study, medium velocity of 1.5 m/s was not considered. The air was discharged with an angle of 45\({}^{\circ}\), as shown in Figure 1c, at a temperature of 16 \({}^{\circ}\)C during summer-cooling and at 33 \({}^{\circ}\)C in winter-heating season. The HVAC system worked in a steady-state condition at the fixed inlet temperature of the fan coil since the local control system was not available. The governing equations were the Mass (1), Momentum (2), and Energy (3) balance equations for steady-state, incompressible, and turbulent flows:  
\[\vec{\
abla}\cdot\vec{v}=0 \tag{1}\]  
\[\rho_{0}[(\vec{v}\cdot\vec{\
abla})\vec{v}=-\
abla(p+\rho_{0}gz)+\rho_{0}g \beta(T-T_{0})\
abla z+\vec{\
abla}\cdot\vec{v_{eff}} \tag{2}\]  
\[\vec{\
abla}\cdot[\vec{v}(\rho e+p)]=\vec{\
abla}\cdot[(k+k_{t})\
abla T+\tau _{eff}^{*}\cdot\vec{v}] \tag{3}\]  
where \(\vec{v}\) is the velocity vector, \(p\) is the pressure, \(\beta\) is the thermal expansion coefficient, \(\tau_{eff}\) is the effective stress tensor, \(e\) is the specific enthalpy, \(k\) is the thermal conductivity, and \(k_{t}\) the turbulent thermal conductivity. The 3D governing differential equations were solved through the finite-volume method implemented through CFD software STARCCM+. A second-order upwind scheme was adopted to convert the governing equations into a set of algebraic discretized equations, and the semi-implicit method for pressure-linked equation (SIMPLE Algorithm) was  
Figure 1: (**a**) Office schematic; (**b**) overview of the furniture layout inside the office; (**c**) fan-coil schematic with vector inlet at 45\({}^{\circ}\). utilised to solve the pressure-velocity coupling problem. The convergence of the simulation solutions was monitored by controlling the values of residuals, velocity, and temperature on several randomly spread probes in the room. To optimise the solution convergence, linear under-relaxation factor ramps where used. The Reynolds stress transport (RST) turbulence model and elliptic blending (near-wall Reynolds-stress turbulence closure) were used to best solve the involved turbulence. In this model, seven equations need to be solved: six equations for the Reynolds stresses (Equations (4) and (5); symmetric tensor) and one for the isotropic turbulent dissipation. Thus, the computational time is significantly increased with respect to the two equations models, but it can predict complex flows more accurately due to its capacity to naturally account for the effects of turbulence anisotropy ([PERSON] et al. [19]). \[T_{RANS}=-\rho R+\frac{2}{3}tr(R)I \tag{4}\]  
where \(\rho\) is the density, \(I\) is the identity tensor, and \(R\) is the Reynolds stress tensor. \[R=\left( \begin{array}{ccc}\frac{\overline{u^{\prime}u^{\prime}}}{\overline{u^ {\prime}v^{\prime}}}&\overline{\overline{u^{\prime}v^{\prime}}}&\overline{ \overline{v^{\prime}w^{\prime}}}\\ \overline{u^{\prime}w^{\prime}}&\overline{v^{\prime}w^{\prime}}&\overline{w^{ \prime}w^{\prime}}\end{array}