**2. Materials and methods**

#### **2.1 Calibration methodology**

CFD is today one of the most accurate tools to predict the movement of air within an internal enclosure. CFD simulations require adequate computational power in order to solve the governing equations the fluid flows. It is also of a paramount importance that in order to get reliable results, a validation procedure based on trusted experimental data should be performed. A mesh verification is also necessary to achieve a good agreement between model accuracy and computational cost.

In this work, a validation methodology for CFD models that combine natural and forced convection heat and flow transfer using experimental results is proposed. The validation steps and necessary parameters are described in the workflow shown in **Figure 2**. The diagram is divided into two parts, the left part represents the experimental test and the right part of the workflow represents the CFD model. The proposed method involves using the experimental boundary conditions set up at the room test as CFD model inputs. The variables used to feed the CFD models were (1) HVAC outlet air velocity, (2) HVAC air outlet temperature and (3) surface temperatures. The surface temperatures (3) were taken from the experimental test when steady-state condition was reached and were used as imposed inputs at the internal surfaces of the CFD model.

iteratively until the residual error falls within the admittance threshold of the

*Calibration Methodology for CFD Models of Rooms and Buildings with Mechanical Ventilation…*

*DOI: http://dx.doi.org/10.5772/intechopen.89848*

*Workflow for the validation methodology of CFD models using experimental results.*

The building used for the experimental campaign belongs to the *Instituto de Investigacion Tecnologica* within the *Escuela Politecnica Superior de Algeciras* and is located at the Algeciras University Campus of the University of Cadiz (Spain). An external view of the building is shown in **Figure 5**. The building is an educational facility dedicated mainly to work spaces, offices and meeting rooms. The internal spaces in the building are conditioned by a variable refrigerant volume (VRV) cooling system, placed on the top of Wall 1 (see **Figure 5**). The dimensions of the room were W = 2.92 m width, L = 4.22 m length and H = 2.80 m height (**Figure 5b**). Its external wall, which was partially underground, contained an operable window. The ceiling was a concrete slab with suspended ceiling modules. A standard door is

sensor error established.

**Figure 2.**

**7**

**2.2 Experimental model**

*2.2.1 Test room description*

The validation process starts with the design of the experiment, consisting of room preparation, air temperature sensors and surface temperature sensor placement (see **Figures 1** and **3**) and definition of case studies (see **Table 1**). In parallel, building geometry is introduced in the CFD tool. For every case study, the HAVC temperature and fan velocity are fixed. These values are used as boundary condition for the CFD model. During the experimental campaign, air temperatures and surface temperatures are collected, until the steady-state conditions are reached (see **Figure 4**). This process finalises with surface temperatures to feed the boundary conditions of the CFD model and air temperatures to be compared with the simulation ones. On the CFD side, once all boundary conditions have been introduced, simulations are performed keeping mesh goodness and convergence criteria (see sections 4.3 and 4.4). Previous air temperature measurements are compared with CFD model results. If the differences are larger than the own sensor accuracy error, the input parameters (1) and (2) are adjusted. This last step needs to be repeated

*Calibration Methodology for CFD Models of Rooms and Buildings with Mechanical Ventilation… DOI: http://dx.doi.org/10.5772/intechopen.89848*

**Figure 2.** *Workflow for the validation methodology of CFD models using experimental results.*

iteratively until the residual error falls within the admittance threshold of the sensor error established.
