**3. Methodology**

## **3.1 Adaptive thermal comfort method**

Dynamic thermal simulations for this article were generated using the thermal analysis software EDSL Tas version 9.4.4 [26], which was simulated for Famagusta with hot and humid climatic conditions. The location of Famagusta can be seen in **Figure 1**. ASHRAE 55-2017 [28] standard for adaptive thermal comfort for 80% and 90% can


**Figure 1.** *Location of Famagusta on the map [27].*

be observed in **Figure 2**. Heat transfer (conduction) and energy transfer (convection) opportunities were analyzed for the internal and external surfaces of both opaque and transparent surfaces in an office. Moreover, the office environment was that of a regular office (3 m by 5 m), including standard construction materials with one inlet and outlet function. The three-dimension (3D) and plan of the case study building can be seen in **Figure 3**. Furthermore, the weather file for Famagusta was also used for the simulations, as shown in **Figure 4**. Transparent surfaces on opaque walls and window opening percentages ranged from 10 to 100% each. A typical section of the case study building can be seen in **Figure 5** along with its yearly performances. In this chapter, all of the simulations used 0.5 ach of infiltration and 0 W/m2 (lighting gain, occupancy/equipment gain) with 0.01 (CO2)/hr/m2 pollutant generations.

The opaque and transparent components of the case-study building are detailed in **Tables 1** and **2**. ASHRAE 55-2017 [28] was used to generate the acceptable thermal comfort conditions, shown in **Table 3** (80% and 90%), of a naturally ventilated office environment with minimum, maximum, and average yearly performances for solar gain (W), infiltration gain-heat lost (W), resultant temperature (°C), relative humidity (%), and external temperature (°C).

#### **Figure 2.**

*ASHRAE 55-2017 standard on acceptable limits for the resultant temperature of a naturally ventilated building with met: 1.0–1.3 and 0.5–1.0 clo when the prevailing mean outdoor temperature is greater than 10°C and less than 33.5°C [28].*

**Figure 3.** *The case study building.*

*Adaptive Thermal Comfort of an Office for Energy Consumption-Famagusta Case DOI: http://dx.doi.org/10.5772/intechopen.101077*

**Figure 4.** *Examples from the Famagusta weather file of (a) day 172 for 21st June representing the summer period and (b) day 355 for 21st December representing the winter period.*

Solar gain, heat lost, resultant temperature, relative humidity, and external temperature are the parameters analyzed in this article as the minimum, maximum, and yearly averages for the different window openings and sizes. Seasonal conduction and convection performances of the studied office are based on monthly analysis, taken in conjunction with opaque/glass surface performances for internal/external surfaces. Global solar radiation (W/m2 ), diffuse solar radiation (W/m2 ), cloud cover (0–1), dry bulb temperature (°C), relative humidity (%), wind speed (m/s), and wind direction (°) are parameters used in the weather file of Famagusta for simulations as seen in **Figure 4**.

### **3.2 Inter-model validation of the article**

An inter-model validation model for annual heat loss is used in this article because its numerical results are compared with previous results in the literature. Badeche and

#### **Figure 5.**

*Yearly average heat and energy transfer performance (for all window opening percentages with all window sizes) of the simulated office.*


#### **Table 1.**

*Solid wall properties of the case study building.*


*Adaptive Thermal Comfort of an Office for Energy Consumption-Famagusta Case DOI: http://dx.doi.org/10.5772/intechopen.101077*

> **Table 2.**

*Glass properties of the case study building.*


#### **Table 3.**

*The acceptable, cool, and hot months for the simulated office.*

Bouchahm [29] identify the optimum window-to-wall ratio (WWR) as 40–50% for energy saving in the Mediterranean climate. Goia [30] found that a WWR between 30–40% is needed for energy saving. Moreover, in this article, the optimum window-towall ratio (WWR) is 40% with a 20% window opening for heat loss, thus confirming harmony between the results (10% up or down for different studies), as shown in **Table 2**.
