# Improving the Energy Efficiency of the Modular Buildings
## 3 Methodology
### Thermal Model and Calibration (Everton Site)  
The model was constructed based on the dimensions of the drying room (Table 1), followed by the creation of a construction template utilising the materials listed in Table 2. Subsequently, the thermal template was developed using the temperature profile derived from sensor data, as illustrated in Figure 3. Additionally, all internal gains of the room (as listed in Table 3), air infiltration, microflow openings (as specified in Table 4), and adjacent conditions (as outlined below in this section) were incorporated into the model. To accurately forecast the average heating load within the building and calibrate the model based on actual performance, an extensive analysis of data from temperature and humidity sensors was conducted. The challenge arose in delineating the specific profile followed by each heater, as these profiles exhibited variations from one heater to another. Additionally, the weekly profiles for a given heater displayed fluctuations throughout the month, complicating the calibration process. To streamline this calibration effort, a pragmatic approach was adopted, identifying the most frequently recurring profile in the drying room across multiple heaters. This predominant profile indicated that the heaters were consistently switched on from 4 to 7 am and from 4 to 11 pm on weekdays. December and January data were used to calibrate the model (refer to Figure 5), as this is the only dataset that was available then, with a designated \"OFF\" period during weekends. Noteworthy is the exception in June, during which the system was always inactive due to the absence of recorded rainfall in that particular month. In addition, lighting and extractor consumption were included in the simulation. Figure 4: STH sensors distribution. \begin{table}
\begin{tabular}{l l l} \hline \hline  & **Sensible Gain (W)** & **Daily Profile** \\ \hline People & 90 pp & 0.44 \\ (Occupancy) & (700 people) & 0.44 \\ Lighting & 36 W per bulb (42 bulbs) & 0.44 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Different internal gains. The weather file used is Liverpool John Lennon United Kingdom, which contains historical weather data of the nearest site to Everton (17 km from Everton) already stored in the software library. Figure 6 shows John Lennon's monthly maximum, minimum, and average outdoor air dry bulb temperatures along with RH. It is evident that Liverpool experiences extreme temperature fluctuations that range from +27 \({}^{\circ}\)C in summer to -7 \({}^{\circ}\)C in winter during the year (according to IES weather data), and typically, heaters run at the end of the day shift from (4-11 p.m.) with another boost early in the morning before the shift from 4-7 a.m. (Figure 5). In addition, in Liverpool, rain is not restricted to winter; it could rain throughout all four seasons even in summer, which increases the energy bill. Consequently, the fan heaters used for drying purposes will run for a long time assumed to be 9 h to dry construction work garments. The calibration process involved a meticulous examination that extended to a comparative analysis of the actual monthly energy consumption of the drying room, derived from the readings of the energy meter installed in two units adjacent to the cleaner store on the right (as depicted in Figure 1). This energy meter was strategically placed to monitor and record the comprehensive usage of energy. The available monthly data spans from January through August, providing a comprehensive temporal scope for the calibration endeavour. The calibration was not solely reliant on real-time data but also incorporated \begin{table}
\begin{tabular}{l l l} \hline \hline  & **Description** & **Profile** \\ \hline Air infiltration & Flow: 2.23 1/s-m\({}^{2}\) (3.2 ACH) & On continuously, based on airtightness test results. Opening time is assumed to be 10 min for 5 times a day. \\ Door & Opening angle 90\({}^{\circ}\) & \\ Window & Opening angle 20\({}^{\circ}\) & \\ \hline \hline \end{tabular}
\end{table}