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# OBJECTIVES AND APPROACHES 1 Model Summary

## Active Building Envelope System(ABE)：Wind

### 3. OBJECTIVES AND APPROACHES 1 Model Summary

The studied model of author’s team could be compared with the model of Dr. Steve Van Dessel’s group. We added the return-air inlet (B vent opening) in the x direction. In the y direction it was guided by the wind turbine air flow through the Swiss roll heat exchanger to produce air-conditioning of the forced convection from an A vent opening. This opening could be considered of several kinds of thermal generations and can become the ABE system heat source. Here it was a simplified model.

These vent opening only set up for 1 to 2 people and considered only for 1 to 2 people’s average heat volume for heating and lighting system. The system’s total heat

load can better simulate the real buildings in a single unit of about 4m x 4m x 4m of the ventilation, and thermal conditions. The thermal resistance of the analog circuit, such as (Fig. 3) shows, of which the best

Fig. 3 Thermal resistance-analog circuit of the new ABE model system

insulation Rwall setting becomes a dramatically large value to make the calculation of overall thermal resistance easier.

### ( )

+

= +

ij j

ij i i i

R R T j T q

1

(1)

According to Gauss-Seidel iteration method [8] - steps that the form of finite difference equations we can achieve the inside ventilation and heat conditions of active building envelope’s global driven. More details of the building equipment configuration are shown in Fig.

4, which indicated the new analytical model of a single dwelling space of ABE system.

Fig. 4 The new analytical model of a single dwelling space of ABE system

3.2 Software and Model Input Parameters

Use Airpak software [9] to input and establish building’s models for analysis.

Model-related input data values are as follows:

1. Air flow volume rate at opening: 1.5m3/s.

2. Wind speed at opening:10m/s

3. Numbers of opening: 1 set, 1 set for blow downward wind, each of size 0.25 meters long, 0.2 meters wide.

4. Temperature at opening: 14℃, return-air temperature:

24℃.

5. The body heat volume of 1 to 2 people totaling 72 - 144W. Floor heat volume can be neglected. Lighting heat flux is average 100W /m2

6. The surrounding air wind field can be incompressible.

The external flow field should meet the three-dimensional dynamic flow control.

7. When simulate air flow of air conditioning the volume is required to change the maximum load value so the distribution of air flow can meet environmental requirements. Therefore, the air-conditioned environment used air-conditioning designed day peak environmental load as the input values. The model used is in a steady state condition in order to simplify the ABE system air-flow simulation procedure.

3.3 Input Parameters for Analysis of Wind Speed at Opening

According to Nielsen’s (1978) [10] test for wind speed at opening, we obtained the relevant data by Grapher software (shown as Fig. 5). Similar curve of wind speed

Fig. 5 Nielsen’s (1978) [10] test for wind speed at vent opening

distribution obtained, in order to get quadratic regression equation for the analysis as follows:

h c b y h a y u

u ⎟+

⎜ ⎞

⎝ + ⎛

⎟⎠

⎜ ⎞

= ⎛

2

0

(2)

a=-1.4287,b=1.4287,c=0.7619

Integration above equation from 0 to 1 yields the average air speed value equal to 1.0.

000 . 2 1

3

2 1

0 2

3 1 0

2

0

=

+

+

=

+

+

=

### ∫

h c y h y b h y

h d y h c b y h a y u

u

(3)

That means the above quadratic curve equation of speed distribution integrated in the range of 0 to 1 (y/h) is equivalent to speed with the same average flow speed.

In accordance with the wind speed at opening, obtain results of the average wind speed from equation (3) at 10 grid-point locations of opening and then key in the Airpack software.

3.4 Input Parameters

When using the Airpack software the setting values is as follows:

2. Flow model: Turbulent (κ-εtwo equation model).

3. Opening:

Temperature at opening: 14 ℃ Turbulence intensity: 10%

3.5 Set the Boundary Conditions

By using the Airpak software together with the Central Weather Bureau’s meteorological data to calculate and simulate atmospheric wind field as boundary conditions.

Input parameters of the external environment are the local wind direction, wind speed, boundary layer thickness and terrain factor. The prediction equation of atmospheric wind field is:

( )

⎪⎪

⎟⎟

⎜⎜

=

⎟⎟ <

⎜⎜

=

d H h

U d

d H h

U d h U

met a met

a

met met met

d a h

met met

met (5)

Umet = The average wind speed in the vicinity of weather station

Hmet = Anemometer’s height amet = Weather station terrain factor

dmet = Weather station boundary layer thickness a = Different ground conditions of the terrain

factor

d = different ground conditions of the boundary layer thickness

In this paper, we use the Hsinchu area anemometer height of 15.6m, terrain factor of 0.19 and boundary layer thickness of 350m.

3.6 Relaxation Factor

When doing analytical analysis, variables cross effects each other so easily led to divergence of various numbers of flow field data, it is necessary to introduce relaxation factor to increase the number of data values to deliver the stability of the simulation data set, such as the relaxation system shown in Table 1.

Table 1 Under-relaxation coefficients

Pressure 0.7 Momentum 0.3 Temperature 0.9

Viscosity 1.0

Body forces 0.1

Turbulent Kinetic energy 0.5 Turbulent dissipation rate 0.5 3.7 Set of Convergence Value

For the purposes of solving any number of flow field changes in the iterative process, Simulation convergence criteria as shown in table 2.

Table 2 Convergence criteria Flow Energy Turbulent

Kinetic energy

Turbulent dissipation

rate

0.001 1e-6 0.001 0.001

3.8 Analysis of Independent Grid

Due to coarse or fineness of grid points may lead to different numerical results, thereby affecting the credibility of the results, analysis of independent grid must be used at different set of grid points in the same physical quantity and observe when the grid points increases, whether the physical quantities will be differed. If it were very different, continued to increase grid points until the grid is fine enough did not affect the physical quantities then to stop the increase of grid points. Fig. 6 is this paper’s numerical model to solve

Fig. 6 Numerical model to solve the domain outside the 30m x 30m x 15m volume with a simulated outdoor environment around 4m x 4m x 4m volume within the analog ABE system

the domain outside the 30m x 30m x 15m volume with a simulated outdoor environment around 4m x 4m x 4m volume within the analog ABE system, while the numerical simulation of computational domains as shown in Fig. 7, including 24 thermoelectric cooling module and ventilation of air inlet and opening.

Fig. 7 The numerical simulation of computational domains

Verification of the numerical grids (Fig. 8, Fig. 9): in the same the settings conducted analysis of independent grid. Compared calculation results differences and the results showed that the grid point number of 91,646, 124,892, 132,762, 187,542, etc. different grid numbers generated slight different results. With the best error R is the best set of grid points.

Fig. 8 The cross-sectional planes of 3D numerical grid

Fig. 9 The 3D numerical grid system

N u

u u R

n t

n

### ∑

= n

+ ⎟⎟⎠

⎜⎜ ⎞

⎛ −

= 1

2

0 1

(4)

n+1: The speeds (m/s) obtained from previous number of grid points

n: The speeds (m/s) obtained from current number of grid points

0: Speeds of the opening (10m/s) N: Number of sampling points

Error R results as shown in Table 3. Compared grid 4 and grid 3, u/u0 error was 7.3E-07 <8.9E-06, both are completely convergent. Namely, the set of grid with grid number of 187,542 is the best grid. Therefore, we use grid 4 to calculate air flow field.

Table 3 Verification of independent grids Test Grid 1 Grid 2 Grid 3 Grid 4 Error% 0 3.7e-4 8.9e-6 7.3e-7

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