**2. Experimental methods**

#### **2.1. Materials**

For the manufacture of CFI boards the raw materials can be divided into two kinds, matrix raw materials and foam raw materials. Firstly, the matrix raw materials were composed of FA, clay, feldspar, and quartz, which were all driven from the same region in China. Secondly, the foam raw materials included CW and other additives. Here, CW was used as a main raw material and SiC was applied as a foaming agent. The chemical characteristics of the main raw materials were measured by X-ray fluorescence (XRF) scan and are shown in **Table 1**. It can be seen that for all main raw materials, SiO2 and Al<sup>2</sup> O3 possess the dominating proportions with the total proportion of 81.87, 71.53, 86.10, 95.77 and 84.01 wt%. It is interesting to note that for feldspar the total contents of K<sup>2</sup> O and Na2 O are high: 11.72 wt%.

In addition, the crystalline phases of the raw materials are determined by X-ray diffraction (XRD) (D/MAX-PC 2500, Rigaku), and the XRD patterns are presented in **Figure 1**. It can be seen that FA is a heterogeneous material. Firstly, the major crystalline phases of FA are quartz and mullite with a small amount of gypsum. Secondly, it is interesting to note that parts of FA belong to the amorphous phase due to the observed low and broad diffraction bands in the range of 20–30o . Moreover, for CW, the main structure is quartz.

## **2.2. Preparation**

realise the energy saving in buildings [6]. As ceramic foam insulation (CFI) is one of the notable methods to reduce the energy use in buildings, it has been widely developed in recent years. As we all know, the building insulation materials are generally sorted into two groups, organic insulation materials and inorganic insulation materials. Organic insulation materials, such as polystyrene foam, often lead to a series of problems related to combustion, environmental toxicity, and adhesive incompatibility with cement and ceramic structures. In addition, organic insulation materials usually exert short working life, for instance, foam plastic only can ensure the required heat resistance in about 8 years. However, inorganic materials, such as CFI, are excellent building insulation materials, which have many advantages compared with other thermal insulation materials, including chemically inactive, noncombustible, low moisture absorption, chemically stable, long-time stable in physical properties, environmental friendly, and long use life [7]. For the above reasons, this study is motivated to propose a

On the other hand, according to the investigation in literature, it is known to us that the traditional manufacture of ceramic materials often requires massive amount of natural raw materials, such as clay and feldspar [8–10]. However, recently, taking into consideration the big challenges in environmental protection and energy saving, nontraditional raw materials are needed in the synthesis process of the ceramic materials. Therefore, the development of innovative ceramic materials by using huge amounts of alternative raw materials, especially

Hence, in this research, according to our previous work [11–13], two solid wastes were applied as the main raw materials for the synthesis of FCI. Firstly, fly ash (FA), a by-product of thermal generation in coal power stations, is used as the main raw material in the matrix part of the FCI [14]. According to the statistics, more than 750 million tonnes of FA are generated each year, but only less than 50% of FA is utilised. In China, the annual output of FA reached almost 600 million tonnes, which results in very serious environmental pollution, such as groundwater contamination [15–17]. Secondly, the reclaimed waste is the ceramic waste (CW). Statistics show that in the ceramic industry about 30% of the daily production will turn into solid waste. As we all know, CW is not recycled in any form at present [18]. Therefore, both solid wastes will cause serious environmental pollution [19–20]. So it is neces-

Based on the previous work of our research [11–13], we are therefore motivated to prepare FCI by using FA and CW as the main raw materials. Moreover, since the study of heat transfer behaviour of FCI and its energy-saving function in buildings was important to guide the synthesis process of FCI, in this study, the foaming behaviour, the thermal conductivity, and its energysaving function were investigated experimentally and were modelled by simulative method.

For the manufacture of CFI boards the raw materials can be divided into two kinds, matrix raw materials and foam raw materials. Firstly, the matrix raw materials were composed of

novel FCI for saving energy in buildings.

130 Recent Advances in Porous Ceramics

solid waste, will be important to the environmental protection.

sary to develop an effective way to recycle FA and CW.

**2. Experimental methods**

**2.1. Materials**

In this research, for the matrix part, 50 wt% FA will be used as the main raw material in all batches. While, for the foam part, only CW will be utilised as the raw material with only 1% SiC. In this study, according to the previous work, the detailed steps of the preparation are shown as follows.

Firstly, all raw materials were thoroughly mixed and milled in the proportion as shown in **Table 2**. Here, quartz content in the batches 1–5 varied from 0 to 20 wt%. Then, mixtures were wet ground in two ball mills for 15 h to obtain the homogeneous slurries. The slurries were sieved to pass through a 200-mesh screen and dried at 110°C for 12 h. Subsequently, the two mixtures were granulated in a moist condition and samples were hydraulically compacted using uniaxial pressing at 10 MPa. Finally, the shaped samples were dried at 105°C for 3 h, followed by calcination in a muffle furnace at the preset sintering temperature, and the sintered samples were cooled naturally.

#### **2.3. Characterisation**

For the matrix part, the obtained samples were measured for moisture absorption (MA) capacity and rupture modulus.


**Table 1.** Chemical composition of main raw materials.

**Figure 1.** XRD patterns of the main raw materials.

The moisture absorption (MA) capacity was tested according to the following method. Firstly, the dried mass of the sintered sample (*M*d, *kg*) was measured. Secondly, the sample was put into boiled water for 5 h and then was soaked for another 24 h. Finally, in water, the mass of the suspended sample (*M*s1, *kg*) was determined, and the saturated mass (*M*s2, *kg*) was measured. So M*A* (%) can be obtained as follows:

$$MA = \frac{M\_{\odot} - M\_{\downarrow}}{M\_{\downarrow}} \times 100\tag{1}$$

The rupture modulus, *R* (*MPa*), is calculated by the following formula:

$$R = \frac{3Fl}{2\,\text{bh}^2} \tag{2}$$

The bulk density (*ρ<sup>b</sup>*

Then, the weight *Mc*

**3. Simulation methods**

Firstly, the effective thermal conductivity (*ke*

by our research group. In this simulation, *ke*

*<sup>k</sup>*<sup>e</sup> <sup>=</sup> *Qtotal* <sup>×</sup> *<sup>L</sup>* \_\_\_\_\_\_\_\_\_

the sample, m; and *A* is the area of the sample, m2

where *Qtotal* is the total heat flow through the sample, W; *Th*

In addition, each unit's dimension is equalled to 0.001 m.

) of final sintered sample was determined by referencing the Chinese

Preparation and Numerical Modelling of Ceramic Foam Insulation for Energy Saving in Buildings

of the sample was measured. Finally, the bulk density was calculated by

can be obtained as follows:

and *Tl*

Secondly, the

133

in the water was measured by hanging

http://dx.doi.org/10.5772/intechopen.71393

× *ρ*water (3)

) was simulated by a simulation model developed

) <sup>×</sup> *<sup>A</sup>* (4)

were the known tempera-

Standards Specifications. In particular, three parameters were detected. Firstly, the sintered samples were dried at 110°C for 24 h and then restored to room temperature in a balance

samples were immersed in boiled water for 3 h, then removed the heating and made samples

on the hook of the precision electronic balance. Thirdly, after the above process, samples were taken out of the water and the redundant water on the surface was wiped using a wet cloth.

*M*<sup>b</sup> − *M*<sup>c</sup>

For thermal conductivity measurements, a series of rectangular briquettes were prepared separately. The thermal conductivities of the samples were measured in a vapour-tight envelope by using a guarded hotplate apparatus (IMDRY3001-II). For the experiment, the hotplate of the apparatus was set to 33°C and the cold plate was cooled by water at 17°C. The sample was mounted between the two plates, and then, the thermal conductivity of the sample was tested when the temperatures of the two plates became stable. Here, the measurement uncertainty

(*Th* − *Tl*

tures of the two surfaces perpendicular to the direction of heat flow, K; *L* is the thickness of

In our simulation, by comparing several grids and the results, the whole sample was finally meshed as a grid of *X × Y × Z*. For each axis, the grid numbers are X = *A*0.5, Y = *L,* and Z = *A*0.5.

Then, by using the thermal conductivity matrix (*TCM* = *ones (X, Y, Z)*), each unit's thermal conductivity value was determined. For the matrix part of the sample, the thermal conductivity value of each unit is set as the thermal conductivity of the matrix board. For the foam part, the unit thermal conductivity value is set randomly. For example, there were two thermal conductivity values in the foam sample, from thermal conductivity value of the solid material and the thermal conductivity value of the air. Firstly, the volume fractions of the solid material and the air were calculated. Secondly, for each unit, a random number (r*n*) was generated to decide which thermal conductivity value would be endowed. For instance, for one unit*,*

.

desiccator. In this status, the specimen's weight was accurately measured, *Ma*.

using the following formula, in which *ρ*water was the density of water.

and repeatability of GHP were controlled within ±3% and ±1%, respectively.

to still stay in the water for 1 h. Samples' weight M<sup>b</sup>

*<sup>ρ</sup><sup>b</sup>* <sup>=</sup> \_\_\_\_\_\_ *<sup>M</sup>*<sup>a</sup>

where *F* is the failing load (*N*); *l* is the distance between two support bars (mm); *b* is the width of the specimen (mm); and *h* is the minimum thickness of the sample (mm).

For the foam part, the sintered samples were tested regarding bulk density and measured thermal conductivity.


**Table 2.** Batch compositions of the samples (wt%).

The bulk density (*ρ<sup>b</sup>* ) of final sintered sample was determined by referencing the Chinese Standards Specifications. In particular, three parameters were detected. Firstly, the sintered samples were dried at 110°C for 24 h and then restored to room temperature in a balance desiccator. In this status, the specimen's weight was accurately measured, *Ma*. Secondly, the samples were immersed in boiled water for 3 h, then removed the heating and made samples to still stay in the water for 1 h. Samples' weight M<sup>b</sup> in the water was measured by hanging on the hook of the precision electronic balance. Thirdly, after the above process, samples were taken out of the water and the redundant water on the surface was wiped using a wet cloth. Then, the weight *Mc* of the sample was measured. Finally, the bulk density was calculated by using the following formula, in which *ρ*water was the density of water.

$$
\rho\_b = \frac{M\_\text{\\_}}{M\_\text{\\_} - M\_\text{\\_}} \times \rho\_{\text{water}} \tag{3}
$$

For thermal conductivity measurements, a series of rectangular briquettes were prepared separately. The thermal conductivities of the samples were measured in a vapour-tight envelope by using a guarded hotplate apparatus (IMDRY3001-II). For the experiment, the hotplate of the apparatus was set to 33°C and the cold plate was cooled by water at 17°C. The sample was mounted between the two plates, and then, the thermal conductivity of the sample was tested when the temperatures of the two plates became stable. Here, the measurement uncertainty and repeatability of GHP were controlled within ±3% and ±1%, respectively.

## **3. Simulation methods**

The moisture absorption (MA) capacity was tested according to the following method. Firstly, the dried mass of the sintered sample (*M*d, *kg*) was measured. Secondly, the sample was put into boiled water for 5 h and then was soaked for another 24 h. Finally, in water, the mass of the suspended sample (*M*s1, *kg*) was determined, and the saturated mass (*M*s2, *kg*) was mea-

*Md*

where *F* is the failing load (*N*); *l* is the distance between two support bars (mm); *b* is the width

For the foam part, the sintered samples were tested regarding bulk density and measured

Clay 20 20 20 20 20 — Feldspar 30 25 20 15 10 — Quartz — 5 10 15 20 —

SiC — — — — — 1

Matrix part Fly ash 50 50 50 50 50 —

Foam part Ceramic waste — — — — — 100

× 100 (1)

<sup>2</sup> bh2 (2)

**No. 1 No. 2 No. 3 No. 4 No. 5 No. 6**

sured. So M*A* (%) can be obtained as follows:

**Figure 1.** XRD patterns of the main raw materials.

132 Recent Advances in Porous Ceramics

*MA* <sup>=</sup> *<sup>M</sup>*s2 \_\_\_\_\_\_\_ <sup>−</sup> *Md*

*R* = \_\_\_\_ <sup>3</sup>*Fl*

thermal conductivity.

**Table 2.** Batch compositions of the samples (wt%).

The rupture modulus, *R* (*MPa*), is calculated by the following formula:

of the specimen (mm); and *h* is the minimum thickness of the sample (mm).

Firstly, the effective thermal conductivity (*ke* ) was simulated by a simulation model developed by our research group. In this simulation, *ke* can be obtained as follows:

$$k\_o = \frac{Q\_{\text{total}} \times L}{(T\_h - T\_l) \times A} \tag{4}$$

where *Qtotal* is the total heat flow through the sample, W; *Th* and *Tl* were the known temperatures of the two surfaces perpendicular to the direction of heat flow, K; *L* is the thickness of the sample, m; and *A* is the area of the sample, m2 .

In our simulation, by comparing several grids and the results, the whole sample was finally meshed as a grid of *X × Y × Z*. For each axis, the grid numbers are X = *A*0.5, Y = *L,* and Z = *A*0.5. In addition, each unit's dimension is equalled to 0.001 m.

Then, by using the thermal conductivity matrix (*TCM* = *ones (X, Y, Z)*), each unit's thermal conductivity value was determined. For the matrix part of the sample, the thermal conductivity value of each unit is set as the thermal conductivity of the matrix board. For the foam part, the unit thermal conductivity value is set randomly. For example, there were two thermal conductivity values in the foam sample, from thermal conductivity value of the solid material and the thermal conductivity value of the air. Firstly, the volume fractions of the solid material and the air were calculated. Secondly, for each unit, a random number (r*n*) was generated to decide which thermal conductivity value would be endowed. For instance, for one unit*,*

if *rn* was smaller than the solid material's volume fraction, the thermal conductivity of the solid material would be endowed. Otherwise, this unit would be endowed with the thermal conductivity of the air (*ka* = 0.026 W/(m•K) [21]).

In this simulation programme, the steady-state energy equation for three-dimensional heat transfer was established as the control equation. For each unit, the sum of heat flow towards this unit was equal to that away from it. In addition, the solution conditions were defined by using the temperature field matrix: *T* = *ones (X, Y, Z).* For the surfaces perpendicular to the heat flow direction, they belonged to the first-class boundary condition and the temperatures of these two surfaces were equalled to 33°C and 17°C. As in the experiment, the sample panel was surrounded by thermal insulation fibre; similarly, the four surfaces that surrounded the panel were insulated perfectly. Finally, *ke* will be obtained through the iterative calculation.

Secondly, the energy-saving effect of FCI was evaluated by EnergyPlus software [22–24]. In this research, an ideal building is applied as the calculation model for energy consumption. In addition, the energy consumption of buildings with different kinds of external walls was compared systematically.
