cement-based high-thermal conductive composites

Cold Regions Science and Technology 86 (2013) 22–35

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Self-deicing road system with a CNFP high-efficiency thermal source and MWCNT/cement-based high-thermal conductive composites Hui Li ⁎, Qiangqiang Zhang, Huigang Xiao School of Civil Engineering, Harbin Institute of Technology, Harbin, 150090, China

a r t i c l e

i n f o

Article history: Received 30 March 2012 Accepted 15 October 2012 Keywords: Deicing CNFP Thermo-electrical property MWCNT/cement-based composite Snow-melting

a b s t r a c t A novel self-deicing road system with utilization of solar energy was proposed in this paper, this system is consisted of a carbon nano-fiber polymer (CNFP) thermal source, an AlN-ceramic insulated encapsulation layer, a multiwall carbon nanotube (MWCNT)/cement-based thermal conduction layer and a thermally insulated substrate. The electric and thermo-electric properties of a CNFP, which is composed of individual carbon nano-fibers (10–200 nm), were tested. The property of high thermo-electric efficiency was verified, and the resistivity of the CNFP exhibited piecewise linear temperature-dependent characteristics within a certain temperature range (0–280 °C). The MWCNT/cement-based composite, which was filled with 3% by weight MWCNT, was proposed as the thermal conduction layer because its thermal conduction properties are superior to those of cement with other fillers and to those of common cement-based composites. To ensure the efficient operation of the CNFP, an AlN-ceramic wafer (0.5 mm) was employed as the electro-insulated layer because of its favorable insulating and thermo-conductive properties. The constructed system was applied in deicing and field snow-melting studies, in which the effects of ambient temperature, heat flux density and ice thickness on the deicing and snow-melting performance of the self-deicing system were investigated. The efficiency, repeatability, cost and feasibility of the self-deicing road system in both deicing and snow-melting applications were analyzed. Indices for evaluating the deicing or snow-melting performance of the self-deicing road system were proposed and the optimal values for each parameter are presented. © 2012 Elsevier B.V. All rights reserved.

1. Introduction In the winter, snow and ice on the roads not only frequently block traffic but also seriously endanger people's lives and assets, even potentially threatening the operation of national defense facilities, such as airport runways and ship decks, during periods of war. The official statistics indicate that snow and ice are the cause of 10% to 15% of traffic accidents annually (Feng and Li., 2009; Hou et al., 2002; Yehia et al., 2000), leading to tremendous economic losses and casualties. Although traditional snow-clearing or deicing methods, such as mechanical sweeping and chemical measures (i.e., sodium chloride, calcium chloride and magnesium chloride), have been widely used in transportation systems, these methods are limited by their potentially harmful effects on the environment and on reinforced concrete (such as pollution and corrosion) (Harnick et al., 1980; Lee et al., 2000; Litvan, 1976; Wang et al., 2006). Some special techniques, such as Aircraft Deicing Fluids (ADFs), have proven to be very effective, but they are very expensive and thus not practical for wide use in road

⁎ Corresponding author. Fax: +86 451 86282013. E-mail addresses: [email protected] (H. Li), [email protected] (Q. Zhang), [email protected] (H. Xiao). 0165-232X/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.coldregions.2012.10.007

deicing (George and Charles, 2011). Therefore, the development of a controllable, efficient and low cost deicing technology is still needed. A number of snow-melting/deicing techniques utilizing terrestrial heat power were developed by Ferrara et al. (Ferrara and Haslett, 1975; Lee, 1984; Long and Baldwin, 1981; Tanaka, 1981). Because of their inconvenience, low efficiency and high cost, these techniques were not adapted for widespread application. Conductive concrete, which also plays a role as the structural material in roads, is regarded as a potential avenue to the development of a self-deicing road system. In 1999, a type of conductive concrete filled with steel fiber was proposed in (Yehia et al., 2000), and the deicing performance of this concrete in bridges was investigated. Although this technique can deice a certain amount of ice on the bridge, it has not been widely used for deicing/snow melting to date because of issues such as high resistivity, low electro-thermal efficiency and steel fiber corrosion. A conductive concrete filled with carbon fiber was also proposed, with the goal of utilizing the Joule heating effect to melt snow (Hou et al., 2002). Despite a great improvement in the electro-thermal efficiency, this material was still not widely used in deicing/snow melting because of low thermal efficiency, high resistance and applied voltage. Fortunately, a new deicing method based on a carbon nanofiber heating element was developed by Chang et al. (2009). the feasibility of this deicing method was verified, the thermal conductivity of this system was still relatively low, and the effect of the heat

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

23

flux density, wind speed, the surrounding temperature and the thickness of the ice layer on the deicing performance of this method were not investigated (Chang et al., 2009). Afterwards, another new method of deicing with carbon fiber heating wire (CFHW) buried inside concrete slab was proposed by Zhao et al. (2010). To verify the feasibility of the proposed deicing approach, the appropriate space of embedded CEHW in concrete slab and the deicing/snow-melting performance of this slab in laboratory and field environments were studied by the experiments, which indicated that the electro-thermal method of CFHW for bridge deck deicing is practicable (Zhao et al., 2010, 2011). Obviously, the key factor that determines the applicability of electro-thermal-based deicing approach is the electro-thermal efficiency. Based on its good electro-thermal properties, the CNFP-based selfdeicing system for roads, consisting of a thermally insulated epoxy substrate, a CNFP high-efficiency thermal source, an AlN ceramic wafer insulated capsulation layer and a MWCNT/cement-based highly thermo-conductive layer, was proposed in this study. The deicing and snow-melting performance of this system in both a chilled and an ambient environment was investigated. The high efficiency, repeatability, low cost and feasibility of a CNFP-based road self-deicing system for both deicing and snow-melting applications were validated through this study. 2. Experiment for material properties Carbon nano-fiber polymers (CNFPs) made from carbon nano-fibers (CNFs) exhibit low resistance, high thermal conductivity and high temperature stability and can be incorporated into a self-deicing road system as a highly efficient thermal source with an excellent electro-thermal property. Additionally, the unique thermal conduction properties of carbon nano-tubes (CNTs) make them a promising heat transfer candidate (Chung, 1994, 2001; Hone et al., 1999; Moisala et al., 2006; Peebles, 1994; Saito et al., 1998). In this study, the materials used included CNFP and a cement-based composite containing multi-walled carbon nano-tubes. The properties of these two materials were investigated first. 2.1. Electro-thermal and electrical resistance properties of CNFPs 2.1.1. Materials and methods CNFP with the dimensions 210× 285 × 0.38 mm, made from carbon nano-fibers with lengths of 10–200 nm, was purchased from Inorganic Specialists, Inc. (USA). DAD-87 and DAD-40 electrically conductive resins obtained from the Shanghai Research Institute of Synthetic Resins (Shanghai, China) were used as the electrodes and wire connection nodes, respectively, on the CNFP specimens. The test included two cases.. Case 1 was a test involving the investigation of the electro-thermal properties of the CNFP and used samples with the dimensions 35 × 70× 0.38 mm. Case 2 was a test for measuring the resistivity of the CNFP using specimens with the dimensions 20× 40× 0.38, 20× 60 × 0.38and 20 × 80 × 0.38 mm (considering the size effect). All of the CNFP samples were sandwiched between two glass plates (100× 100 mm) and were first dried at 150 °C for 2 hours in an oven to remove the absorbed water and avoid buckling. DAD-87 was then printed transversely on the dried CNFP samples to form the electrodes, which are approximately 3 mm wide, for the electrothermal property study and resistivity measurement, and the samples were dried at 200 °C for 2 hours in the oven. DAD-40, which consists of two components, was mixed at a ratio of 1:1 and was used to connect the copper wires to the formed electrodes. The CNFP samples with formed electrodes and copper wires were further dried at 80 °C for 2 hours in the oven. The fabricated CNFP samples are shown in Fig. 1. To incorporate CNFP into a self-deicing road system as a thermal source, it is necessary to investigate its temperature-dependent electro-thermal properties under various temperature conditions. First,

Fig. 1. The CNFP specimens used for (a) investigation of the electro-thermal properties and (b) measuring the resistivity based on the four-probe method with three different specimen sizes of ① 20 × 40 × 0.38 mm, ② 20 × 60 × 0.38 mm and ③ 20 × 80 × 0.38 mm.

CNFP specimens were placed in a refrigerator or in a temperaturecontrollable oven to simulate a change in ambient temperature, and then DC power was applied between the two electrodes to heat the specimens. The temperature of the CNFP sample was monitored using a Center 309 thermometer with a constant applied voltage and at a certain ambient temperature. The applied voltages used were 4, 6, 8 and 10 V, and the ambient temperature was varied in the range of − 30 to 100 °C. As shown in Fig. 2, the four-probe method was adopted to measure the longitudinal resistance of the CNFP samples under ambient temperature conditions (− 30 to 300 °C) in a refrigerator or in a temperature-controllable oven. A DC current, Iout, was applied at the two outer contacts, and the two inner contacts were used for measuring the voltage Uinner. A DC circuit developed by Li et al.,(2008) was used to measure the resistance of the CNFP sample as follows: R¼

U inner  Rref U inner ¼ ; U out Iout

ð1Þ

where Rref is the standard reference resistor, as shown in Fig. 2, Uout is the voltage applied to Rout, R and Uinner are the resistance and voltage of the two inner contacts of the CNFP sample and Iout is the current flowing through Rref. Iout and Uinner were measured simultaneously to calculate R in series in the circuit. Based on Ohm's law, the longitudinal resistivity of each CNFP specimen was calculated as follows: ′

RS U  Rref S U inner Δh ¼ ρ ¼ ⋅ ¼ inner ; l l U out Iout n

ð2Þ

24

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

Fig. 2. The schematic of the DC circuit for the temperature-dependent resistivity measurement based on the four-probe method with n equal to 1:1, 1:2 and 1:3.

where S and l are the cross-sectional area and the distance between the inner contacts of the CNFP sample, as shown in Fig. 1 (b), Δh and a are the thickness and width of the sample, and n = l/a is the ratio of l to the width a, which was n = 1:1, 1:2 and 1:3 in this study. It is well known that the material microstructure is the critical factor dominating the physical performance of the material, including the mechanical, thermal and electrical properties. To investigate the effect of the micro-fiber distribution in CNFP on the electro-thermal properties, a micro- morphology image of the CNFP micro-structure was obtained with a scanning electron microscope (SEM), as shown in Fig. 3. 2.1.2. Results and discussion The increase in the temperature of the CNFP with time and an applied voltage of 4 V under various ambient temperatures is shown in Fig. 4. It can be seen from Fig. 4 (a) that the electro-thermal property of CNFP is dependent on temperature. The temperature dramatically increases with time over the first 10 sec and then approaches a stable temperature. This stable temperature is dependent on the surrounding temperature, whereas the increase in the relative temperature is not

strongly dependent and is focused primarily on the temperature interval of 40–50 °C. For example, the stable temperature is 12 °C for an ambient temperature of −30 °C; it is approximately 36 °C for an ambient temperature of −20 and −10 °C and is approximately 45 °C for 0 °C. When the ambient temperature is higher than 0 °C, the stable temperature becomes approximately 85 °C for a surrounding temperature of 20 and 40 °C, 100–110 °C for a surrounding temperature of 60 and 80 °C, and approximately 140 °C for a surrounding temperature of 100 °C. The temperature dependence of the electro-thermal property of CNFP can be attributed to the quantized transition of electronic energy, which determines electron transport activity in CNFs. Furthermore, CNFP can reach the same stable temperature at an ambient temperature of −30 to 0 °C, which indicates that CNFP is a good candidate for the highly efficient thermal source required for deicing in winter (below 0 °C). Fig. 4 (b) presents the increase in temperature with time for various applied voltages (4, 6, 8 and 10 V) at room temperature. The results in Fig. 4(b) indicate that the temperature of CNFP increases rapidly in a short period of time, implying that, like the individual CNFs, CNFP naturally displays excellent electro-thermal properties. Due to the unique electron transport mechanism of a single CNF and the microtopography of CNFP, as shown by the SEM picture in Fig. 3, electron transport in the material can be highly efficient, which leads to the high efficiency of the electro-thermal property of CNFP. The temperature-dependent resistivity of CNFP is shown in Fig. 5. The resistivity of CNFP exhibits distinctly temperature-dependent characteristics. The curve of the resistivity of CNFP and the surrounding temperature can be categorized into three regions. In region 1 (over the range of −30 to −0 °C), the resistivity remains constant (0.72 Ω ⋅ mm). In region 2 (over the range of 0–280 °C), the resistivity of CNFP decreases linearly with an increase in temperature, exhibiting strongly temperature-dependent characteristics. It is well known that the resistivity of isolated CNT or CNF is dependent on temperature because of the increase in activity of phonon and hot electrons with an increase in temperature (Kane et al., 1998). Similarly, as a macro-mass of individual CNFs, the resistivity of CNFP decreases linearly as the temperature increases from 0 to 280 °C because of the activity of hot electrons, even with a slight deformation in the micro-structure of CNFP based on temperature change, which corresponds to an improvement in the

Fig. 3. SEM image of CNFP (a) 1 mm, (b) 100 um, (c) 50 um, (d) a node, (e) fiber in node (1 μm,) and (f) fiber connection in a node (3 μm).

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

-30

Temperature (°C)

200 150

0

(b) 350

60°C

-20

20

80°C

-10

40

100°C

100 50 0 -50

4V

300

Temperature (°C)

(a) 250

25

6V 8V

250

10V

200 150 100 50

0

100

200

300

0

0

200

Time (sec)

400

600

800

1000

Time (s)

Fig. 4. The temperature versus time curves of CNFP (a) at various ambient temperatures with an applied voltage of 4 V and (b) with applied voltage of 4, 6, 8 and 10 V at room temperature.

electrical properties of CNFP. In region 3 (above 280 °C), the resistivity of CNFP remains constant (0.6 Ω ⋅ mm) and is again independent of the surrounding temperature. Statistically, the resistivity of CNFP is independent of the specimen size. Based on the temperature dependence of the resistivity as shown in Fig. 5, a piecewise linear model of the resistivity of CFNP was proposed in the following form (units are Ω ⋅ mm):

ð3Þ

2.2. Thermo-conductive properties of MWCNT/cement-based composite 2.2.1. Materials and methods As another component of a self-deicing road system, the thermal conduction layer embedded in the road should have high thermal conductivity to achieve the expected heat transfer efficiency during the deicing process. Although the Portland cement concrete has been proven to have thermal conductivity (Yang et al., 2012), for further improving the heat transfer efficiency of concrete, a developed concrete with much higher thermal conductivity should be developed in this paper. Previous studies have indicated that the electrical properties of cement-based composites can be enhanced greatly by filling them with a highly conductive admixture, such as carbon fiber, carbon black, and steel fibers (Chen and Chung, 1995; Chung, 2001, 2004). To efficiently enhance the thermal conductivity, a cement-based

0.75

Resistivity (Ω∗mm)

Resistivity (Ω∗mm)

1.0

0.8

0.70

slope=-4.28*10-4

0.65 B(280,0.6)

0.60

Average resistivity Piecewise Linear Fit 0

100

200

300

Temperature (°C)

1:1

1%

10

A(0,0.72)

0.55

3% 5%•

8

5

6 4

0

4 3

1%

1:3

0.6

Expeimental Study Theory prediction

2

2

1:2

-50

2.2.1.1. Results and discussion. Based on the Fourier heat conduction equation, the thermal conductivity of the MWCNT/cement-based composite was studied as a thermal steady-state problem with an infinite plate (Karlekar and Desmond, 1977). The temperature was monitored using two K-type thermocouples. One was embedded at 7.5 mm above the bottom surface, and the other was at 7.5 mm below the upper surface of the specimen; the thermocouples were 10 mm apart. DC power supplied the heat flux to the CNFP layer.

λ (Wm-1K-1)

ρCNFP ¼

T b 0BC o 0:72 0BC ≤ T ≤ 280 C o 0:72−4:28  10−4 T T ≥ 280 C:

Temperature gap (°C)



composite containing MWCNT was fabricated in this study to take advantage of the excellent thermal and electrical properties of MWCNTs (~6000 W/(m·K)). MWCNTs (b 50 nm, > 95%), which were purchased from the Chengdu Institute of Organic Chemistry Academia Sinica (Chengdu, China), were mixed with cement to fabricate material for the thermal conduction layer. With 0.1% by cement weight sodium dodecyl sulfate (SDS) as the dispersing agent, 1%, 3% and 5% by cement weight MWCNTs were first dispersed in a water solution of SDS and stirred at a speed of 3,000 rpm for 1 h. An ultrasound dispersing instrument was used to disperse the MWCNTs in the water at a power of 400 W for 2 h and to ensure the uniformity of the mixture. Then 350 g of cement was poured into the prepared mixture of water and MWCNTs in a water-cement ratio of 0.4 and stirred mechanically at a speed of 2,000 rpm for 10 min using an agitator to create a uniform MWCNT/ cement-based composite. Finally, the composite was poured into molds to form specimens with a size of 100×100×25 mm; the specimens were demoded after 24 h and then cured in a moisture room for 7 days.

50

100

150

200

250

300

Temperature (°C) Fig. 5. The temperature-dependent resistivity of CNFP. Outer figure: resistivity with three n ratios equal to 1:1, 1:2 and 1:3; Inner figure: the average resistivity and linear curve-fit.

0

0

1000

2000

3%

Wt. of MWCNT (%) 3000 4000

5%

5000

Time (s) Fig. 6. The thermal conductivity of the MWCNT/cement-based composite. Outer figure: temperature gap between two measurement points vs. time; inner figure: theoretical and experimental thermal conductivity.

26

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

Fig. 7. The configuration of the CNFP-based self-deicing road system.

The heat flux is defined as the product of inputting a voltage and causing a corresponding current to flow through the CNFP layer. Then the mathematical formula for the thermal conductivity coefficient derived from the Fourier laws is given as λc ¼ −

Q dx ; A dT

ð4Þ

where λc is the thermal conductivity coefficient of the material, Q is the heat flux flowing into the bottom of the specimen, which is negative for inflow and positive for outflow, A is the bottom surface area of the experimental specimen, and dT is the temperature gradient along the dx height of the specimen and is given by the ratio of the stable temperature gap and the distance (10 mm) between the two measuring points. The temperature gap converges after approximately 4000 sec, as shown in Fig. 6. The stable temperature gap between two measurement points was extracted. The thermal conductivity coefficients of the three types of samples are all higher than that of normal concrete (1.58 W/ (m·K)), indicating that the thermal properties of cementbased composites containing MWCNTs are significantly improved. Consequently, cement-based composites containing MWCNTs can be incorporated into a self-deicing road system as the thermal conduction layer. It should be noted that as the amount of MWCNTs increases, it becomes more difficult to disperse the MWCNTs uniformly in the cement because of the large specific surface area. Generally, heat conduction in MWCNT/cement-based composites is dominated by the transportation of phonon and electrons and is extremely sensitive

to micro-defects and weak interfaces because phonon and electrons will frequently scatter at the locations of such defects. These negative effects are caused by the aggregation of MWCNTs in the composite. Therefore, the enhancement of heat conduction is not only dependent on the quantity of filled MWCNTs but is also determined by the status of the dispersion of MWCNTs in the composite. As presented in Fig. 6, the thermal conductivity cannot be further improved by increasing the amount of MWCNTs after the proportion of MWCNTs exceeds 3%. Therefore, in this study, the optimal percentage of MWCNTs for improving the thermal conductivity of cement-based composites filled with MWCNTs is 3%; the thermal conductivity coefficient corresponding to this percentage is 2.83 W/(m·K). Cement-based composites filled with MWCNTs would be qualified for incorporation into the CNFP-based self-deicing road system. 3. Integration of the CNFP-based self-deicing road system and its deicing performance in a refrigerator 3.1. Integration of the CNFP-based self-deicing road system A CNFP-based self-deicing road system should include a heating source, a thermal transfer layer, an electro-insulated layer and a thermally insulated substrate. The configuration of the CNFP-based selfdeicing road system that was designed in this study is shown in Fig. 7. CNFP was selected as the heat source. To prevent the heat energy from flowing down into the soil below the road, epoxy was chosen as the thermal insulation substrate and placed between the soil and the CNFP layer. In terms of the mechanical requirements of a road, the cement-

Fig. 8. The schematic of the integrated controllable self-deicing road system consisting of a CNFP-based road component, a DC power supply, and monitoring and control modules.

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

27

Fig. 9. The schematic of the integration process of the deicing system.

based thermal conduction layer were integrated into a self-deicing road system, as shown in Fig. 7. The operation of the CNFP-based self-deicing road system is shown in Fig. 8. An external DC power source was applied at the CNFP layer; in this study, the power source was solar energy-based and could be automatically controlled. An anemoscope, temperature sensors and K-type thermocouples were used to measure the wind, ambient temperature and the temperature in the deicing system. These analogue signals were collected by sensors and were transformed to a digital signal by DA/AD boards and then transported to a PC to determine the optimal heat flux density input. 3.2. Preparation of specimens

Fig. 10. The setup for the deicing experiment in a refrigerator.

based composite containing the MWCNTs was designed to be the thermal conduction layer and was placed over the CNFP thermal source. In practice, the cement-based composite filled with MWCNTs is typically covered by ice or snow. An AlN ceramic wafer was placed between the CNFP thermal source layer and the thermal conduction layer to guarantee electrical insulation and to simultaneously ensure efficient heat transfer up to the thermal conduction layer. In summary, an epoxy thermal insulation substrate, a CNFP thermal source, an AlN ceramic wafer insulated-encapsulation layer, and a MWCNT/cement-

(b)

0 1800 W/m2 2

1400 W/m

-5

1000 W/m2 600 W/m2

-10 0

2000

4000

6000

Time (sec)

8000 10000

Temperature(°C)

Temperature(°C)

5

(c) 5

5

0 1800 W/m2 2

1400 W/m

-5

1000 W/m2 600 W/m2

-10 0

3000

6000

9000

Time (sec)

12000 15000

Temperature(°C)

(a)

As shown in Fig. 9, the integrated deicing system consisted of an epoxy thermal insulation substrate, a CNFP high-efficiency thermal source, an AlN ceramic wafer insulated capsulation layer and a MWCNT/cementbased highly thermally conductive layer. As the essential components of the whole deicing system, CNFP and the cement-based composite filled with MWCNTs were fabricated individually as described above. The epoxy substrate with a thickness of 2 mm was coated directly onto the bottom of the system at room temperature to prevent the heat from flowing downwards, and then the prepared CNFP sample (100 × 100 × 0.38 mm) as the thermal source was attached to the thermally insulated substrate. Next, an AlN ceramic wafer with a thickness of 0.5 mm was layered onto the CNFP thermal source as an electro-insulated layer. This wafer displays a remarkable capacity for electrical insulation and heat conduction (1.5× 1013 Ω·cm

0 1800 W/m2 1400 W/m2

-5

1000 W/m2 600 W/m2

-10 0

4000

8000

12000

16000

Time (sec)

Fig. 11. The temperature distribution at the interface between the ice layer and the cement-based thermal conduction layer at an ambient temperature of −10 °C and for an ice thickness of (a) 10 mm, (b) 15 mm, and (c) 20 mm.

28

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

Table 1 Times of initiation and completion of deicing. Temperature, °C

Thickness, mm

Time, sec 600 W/m2

−10

10 15 20 10 15 20 10 15 20

−20

−30

1000 W/m2 Finish

Start

Finish

Start

Finish

Start

Finish

3240 3810 4800 4830 5160 5490 6180 6630 7200

8970 13020 16500 14460 15750 17130 16880 20100 22920

2460 2670 2880 2730 3330 3660 4410 4920 5580

6450 8970 10230 7500 9930 11130 8670 11250 14010

1920 2190 2700 2580 2760 2970 2880 3540 3990

5130 5820 7650 6750 7590 8130 7230 9120 10080

1230 1530 1650 1830 2550 3000 2670 3180 4110

3360 4830 5820 5430 6750 7500 6120 8190 9300

were selected as the three critical factors to be investigated in this experiment. The heat flux densities used in this experiment were 600, 1000, 1400 and 1800 W/m2. The ice was formed in a refrigerator with sizes of 100×100×10 mm, 100×100×15 mm and 100 × 100 × 20 mm. The ambient temperatures were −30, −20 and −10 °C. The temperature distribution in the system was monitored by the embedded K-type thermocouples. The corresponding comprehensive deicing efficiency was evaluated using the proposed indices, which are described later in this paper. It should be noted that the heat convection coefficient is affected by the ambient wind speed. However, it is hard to simulate the wind speed in a refrigerator, so this factor is ignored in the deicing test.

Temperature Ice thickness Energy / kJ /°C /mm 600 W/m2 1000 W/m2 1400 W/m2 1800 W/m2

−20

−30

10 15 20 10 15 20 10 15 20

53.82 78.12 99 86.76 94.5 102.78 101.28 120.6 137.52

64.5 89.7 102.3 75 99.3 111.3 86.7 112.5 140.1

1800 W/m2

Start

Table 2 Energy consumption for deicing.

−10

1400 W/m2

71.82 81.48 107.1 94.5 106.26 113.82 101.22 127.68 141.12

60.48 86.94 104.76 97.74 121.5 135 110.16 147.42 167.4

3.3. Results and discussion and 175 W/m·K), which ensures normal performance of the CNFPbased thermal source during the deicing process. The MWCNT/cementbased thermo-conductive layer (100×100×25 mm) was then placed over the AlN ceramic wafer layer. All of the different components were glued together and firmly connected to guarantee perfect thermal contact and effective heat transfer. Fig. 9 presents the deicing system integration procedure. To monitor the temperature change during the deicing process, four K-type thermocouples (Center 309 thermometer) were used in the system. Two of them were embedded at the interface between the thermal conduction layer and the ice layer; at the upper surface of the ice layer, a third one was embedded at 12.5 mm above the bottom of the thermal conduction layer, and the last one was placed on the side wall of the system to monitor the surrounding temperature. The anemoscope and caliper were fixed at the experiment site for measuring the wind and the ice thickness. DC power was then applied to the specimen to supply the energy for the deicing system. The intelligent control equipment (PC, data acquisition system) was assembled with the other modules to complete the system integration and was used to investigate the deicing performance of the system in this study. The setup for the deicing experiment in a refrigerator is shown in Fig. 10. The heat flux density, ice thickness and ambient temperature

(a)

From a practical point of view, the most important points for this system are the deicing time and the energy consumption. Therefore, the time cost and energy consumption were proposed as the relevant performance indices and were used to evaluate the deicing efficiency. First, the temperature distribution was obtained from the embedded thermocouples. The temperature recorded at the interface of the cement-based thermal conduction layer, and the ice is shown in Fig. 11 for an ambient temperature of − 10 °C; ice thicknesses of 10, 15 and 20 mm; and four heat flux densities. Fig. 11 shows that the temperature versus time curves can be divided into three stages, i.e., an ice-specific heat stage (b 0 °C), an ice-phase change stage (≈0 °C) and a water-specific heat stage (>0 °C). During the ice specific heat stage, the temperature rapidly increases up to 0 °C, the phase change begins, the ice begins to melt, and the temperature is fixed until the completion of ice melting. The total duration of these two stages is referred to as the time cost for ice deicing. After the ice phase change is completed, the temperature at the upper surface of the ice layer has reached the freezing point, as the third region in Fig. 11 shows. The results show that a higher heat flux density corresponds to a steeper heating gradient and a lower time cost for deicing. However, for the same heat flux density and ambient temperature, thicker ice

(b) L-H-I S-H-S

84.81%~86.8%

S-H-I 10.6%~10.9%

2.3%~4.6%

(c) L-H-I S-H-S

73.6%~76.7%

S-H-I 18.5%~19.2%

L-H-I S-H-S

65%~68.6%

S-H-I 24.5%~25.8%

5.5%~10.5%

Fig. 12. The proportion of the three effective energy components for various conditions: (a) −10 °C, (b) −20 °C, and (c) −30 °C.

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

10

15

20

-20C° -30C°

10

Thickness of ice (mm) Time(sec*103)

-20C°

-30C°

20 15 10 10

15

14

-10C°

12

-30C°

120 100 80 60

20

10

-20C°

8 6 10

Thickness of ice (mm)

15

15

180 160 140 120 100 80 60

20

20

11 10 9 8 7 6 5 4

-10C°

-20C°

-30C°

10

Thickness of ice (mm)

15

-10C°

-20C°

-30C°

10

Thickness of ice (mm)

10

20

-20C°

-30C°

Thickness of ice (mm) Time(sec*103)

-10C°

25

15

-10C°

140

Energy (kJ)

-30C°

-10C°

Energy (kJ)

-20C°

(d)

160

Time(sec*103)

-10C°

(c)

160 140 120 100 80 60

15

20

Thickness of ice (mm) Time(sec*103)

(b)

160 140 120 100 80 60 40

Energy (kJ)

Energy (kJ)

(a)

29

-20C°

-30C°

8 6 4 2

20

-10C°

10

Thickness of ice (mm)

10

15

20

Thickness of ice (mm)

Fig. 13. The effect of ice thickness on the energy and time required to deice a certain amount of ice under specified conditions (heat flux density and ambient temperature): (a) 600 W/m2, (b) 1000 W/m2, (c) 1400 W/m2, and (d) 1800 W/m2.

12 8 -30

-20

12 10 8 6

-10

-30

Ambient temperature (oC)

Energy (kJ)

120 100 80 60 -30

-20

-10

Ambient temperature (oC)

-20

160

8 6 -30

-10

10mm 15mm 20mm

140 120 100 80

60

-30

-20

-10

Ambient temperature (oC)

10mm 15mm 20mm

10

-20

8 6 4 -30

-10

10mm 15mm 20mm

140 120 100 80 -30

-20

-10

Ambient temperature (oC)

10mm 15mm 20mm

10

-20

-10

Ambient temperature (oC)

Ambient temperature (oC)

Ambient temperature (oC)

Energy (kJ)

10mm 15mm 20mm

140

(d) Time (sec)

16

10mm 15mm 20mm

14

Time (sec)

20

16

ð5Þ

where Eeffective is defined as the effective energy used for deicing, Eice is the energy consumed by ice heating and phase change, Esystem is the energy used for system heating, cice is the specific heat of ice (2.1 kJ/ (kg·°C)), ΔT is the temperature difference between the ice and the surroundings up to 0 °C, L is the latent heat of the phase change of ice to water (335 kJ/ kg), ρice is the density of ice (970 kg/m 3), A is the cross-sectional area of heat flow (100× 100 mm), and d is the thickness of the ice.

Energy (kJ)

10mm 15mm 20mm

24

Eeffective ¼ Eice þ Esystem ¼ L⋅mice þ cice mice ΔT þ Esystem ¼ ðL þ cice ΔT Þ⋅A⋅ρice ⋅d þ Esystem ;

(c)

(b) Time (sec*103)

3

Time (sec*10 )

(a)

3.3.1. The effect of ice thickness The total input energy can be categorized as either the effective energy or the waste energy, which is dissipated to the surroundings. The effective energy is defined as the energy used for the phase change of ice (L-H-I), for ice heating (S-H-I) and for system heating (S-H-S):

Energy (kJ)

requires more time for deicing. The first stage of the curve represents many of the characteristics associated with the heat flux density, such as the start of deicing and the speed of the temperature rise. The time consumption and energy expenditure related to the latent heat of the ice (335 kJ/kg) for deicing can be obtained from the second stage. For the other ambient temperatures of − 20 and − 30 °C, the times of the initiation and completion of deicing in the temperature curves are listed in Table 1. The energy consumption was calculated by multiplying the heat flux density qw (W/m 2) by the time required to finish the deicing process (E = qwt); the results are listed in Table 2. The effect of the heat flux density and ice thickness on the deicing time is the same as for an ambient temperature of −10 °C. Additionally, a lower ambient temperature corresponds to a longer deicing time. Of most interest is that, for most of the cases listed in Table 1, the energy consumption for deicing is lower with a smaller heat flux density, whereas the time for deicing is longer.

180 160 140 120 100 80 60

10mm 15mm 20mm

-30

-20

-10

Ambient temperature (oC)

Fig. 14. The effect of ambient temperature on the energy and time required to deice a certain amount of ice with applied heat flux densities of (a) 600 W/m2, (b) 1000 W/m2, (c) 1400 W/m2, and (d) 1800 W/m2.

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

(b) 10mm 15mm 20mm

15 12 9 6

Time (sec*103)

Time (sec*103)

(c) 18

18

10mm 15mm 20mm

15 12 9

600 800 1000 1200 1400 1600 1800

Heat flux density (W/m2)

Heat flux density (W/m2)

80

180

10mm 15mm 20mm

120

Energy (kJ)

Energy (kJ)

140

100

12

600 800 1000 1200 1400 1600 1800

Heat flux density (W/m2) 10mm 15mm 20mm

16

8

3

600 800 1000 1200 1400 1600 1800

10mm 15mm 20mm

20

6

3

120

24

160

Energy (kJ)

(a)

Time (sec)

30

100 80

60

140

10mm 15mm 20mm

120 100 80

60

600 800 1000 1200 1400 1600 1800

600 800 1000 1200 1400 1600 1800

600 800 1000 1200 1400 1600 1800

Heat flux density (W/m2)

Heat flux density (W/m2)

Heat flux density (W/m2)

Fig. 15. The effect of heat flux density on the energy and time required to deice a certain amount of ice at ambient temperatures of (a) −10 °C, (b) −20 °C, and (c) −30 °C.

Table 3 Comprehensive index of time-energy for the evaluation of deicing efficiency. Temperature, °C

Ice thickness, mm

600 W/m2

1000 W/m2

1400 W/m2

1800 W/m2

−10

10 15 20 10 15 20 10 15 20

1.749 1.871 1.924 1.888 1.778 1.761 1.919 1.818 1.822

1.617 1.689 1.575 1.286 1.448 1.474 1.301 1.323 1.448

1.572 1.355 1.464 1.434 1.356 1.318 1.347 1.320 1.283

1.217 1.340 1.331 1.376 1.429 1.438 1.363 1.407 1.406

−30

The energy consumption for each of the three components of the effective energy was calculated using Eq. (5) and is shown in Fig. 12. The results in Fig. 12 indicate that the majority of the energy is utilized for the phase change of the ice (> 65%), whereas only a small portion is used for system heating (b10%). The proportion is affected by the ambient temperature, i.e., more energy is needed for ice heating and system heating at lower ambient temperatures. The results show that the energy consumed by ice heating and phase change accounts for more than 90% of the effective energy.

(b)

(a) 10mm 15mm 20mm

1.6 1.4 1.2 600 800 1000 1200 1400 1600 1800

Heat flux density (W/m2)

Time-Energy index

Time-Energy index

(c)

2.0

2.0 1.8

3.3.2. The effect of ambient temperature For a certain amount of ice, the latent heat expenditure is fixed, and the specific heat energy consumption is a linear function of the ambient temperature. Moreover, a lower ambient temperature results in a higher temperature gradient and increased energy transfer between the system and the surroundings. Therefore, the energy and time required to deice a certain amount of ice for heat flux densities of 600, 1000, 1400 and 1800 W/m 2 reduce with the increase in ambient temperature, as shown in Fig. 14. Based on the effective insulation measurements for the surrounding system and the bottom layer (PVC insulated plates, >0.14 W/m·K, purchased

1.8

10mm 15mm 20mm

1.6 1.4 1.2

600 800 1000 1200 1400 1600 1800

Heat flux density (W/m2)

2.0

Time-Energy index

−20

The data in Tables 1 and 2 are depicted in Fig. 13. At a specific ambient temperature, the energy and time required to deice a certain amount of ice both increase approximately linearly with the ice thickness for heat flux densities of 600, 1000, 1400 and 1800 W/m 2 . This trend occurs because the energy consumed by ice heating and phase change are linear functions of ice thickness and account for more than 90% of the effective energy, as shown in Fig. 12. Other energy expenditures, such as dissipation and system heating, are independent of the thickness of the ice at the same ambient temperature. Therefore, the approximate linear relationship between both deicing time and energy consumption and ice thickness is acceptable and reasonable.

10mm 15mm 20mm

1.8 1.6 1.4 1.2

600 800 1000 1200 1400 1600 1800

Heat flux density (W/m2)

Fig. 16. Index of time-energy in deicing for ambient temperatures of (a) −10 °C, (b) −20 °C, and (c) −30 °C.

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

4

12

54 2

12

106

10

104

8

102

75

6

100

70

4

90

10

85

8

80

6 4

600 800 1000 1200 1400 1600 1800

600 800 1000 1200 1400 1600 1800

2

Time(sec*103)

60

14

112 Time-20mm 110 Energy-20mm 108

16

Energy (kJ)

66

6

18

Time-15mm Energy-15mm 95

14

Time(sec*103)

8

78 Time-10mm Energy-10mm 72

100

Energy (kJ)

Time(sec*103)

(c)

(b)

10

600 800 10001200140016001800

98

2

2

Heat flux density (W/m )

Energy (kJ)

(a)

31

Heat flux density (W/m )

Heat flux density (W/m )

Fig. 17. The evaluation of the prior options for time and energy consumption on deicing efficiency at an ambient temperature of −10 °C for ice thicknesses of (a) 10 mm, (b) 15 mm, and (c) 20 mm.

3.4. The evaluation of deicing efficiency based on the priority of time and energy options Considering the time and energy consumption efficiency associated with deicing, the optimal heat flux density option may not coincide with the other parameters being specified, which require that the least energy and the shortest time expenditure be used to deice a certain amount of ice. However, it is impossible to optimize both time

(a)

  β ¼ ðT=T max Þ þ Ec =Ec;max ;

where T and Ec are the time and energy used for deicing, Tmax and Ec,max are the longest time and maximum energy required for deicing a certain amount of ice with varying heat flux density under the same ambient conditions. To minimize the confusion regarding the equation working conditions, the heat flux cannot be zero and should be in a reasonable range to ensure that the deicing process is finished in a finite time period. The second index considers only the energy concerned, i.e., the requirement of minimum power consumption. The last index considers only the shortest time expenditure for an emergency case. As shown in Table 3 and Fig. 16, at an ambient temperature of −10 °C the optimal heat flux densities were 1800, 1400/1800 and 1800 W/m2 for ice with thicknesses of 10, 15 and 20 mm, where the minimum time-energy indices are 1.217, 1.34 and 1.331, respectively. These optimal values were reasonable because for the heat flux density of 1800 W/m2 the time efficiency was much higher than the increase in energy consumption. At an ambient temperature of −20 °C, the most appropriate heat flux densities were 1000, 1000 and 1400 W/m 2 for ice with thicknesses of 10, 15 and 20 mm, where the minimum time-energy indices of 1.286, 1.356 and 1.318, respectively, represent the optimal balance between the time efficiency and the energy consumption. Furthermore, 1000 and 1400 W/m 2 could be the best choices for ice thicknesses of 10 and 20 mm. There were two acceptable heat flux densities, 1000 and 1400 W/m2, for deicing 15-mm-thick ice because of their similar indices

(b)

10 8 6 4

Heat flux density (W/m2)

16

Time-15mm 130 Energy-15mm

14

120

12 110

10 8

100

6 4

600 800 1000 1200 1400 1600 1800

Heat flux density (W/m2)

90

Energy (kJ)

12

18

Time(sec*103)

14

110 Time-10mm 105 Energy-10mm 100 95 90 85 80 75 70 600 800 1000 1200 1400 1600 1800

Energy (kJ)

16

ð6Þ

(c)18

150

16

Time-20mm Energy-20mm 140

14

130

12 120

10

110

8 6

Energy (kJ)

3.3.3. The effect of heat flux density For fixed conditions (ice thickness and ambient temperature), the energy and time requirements for the deicing process are constant. The heat flux density refers to the energy input to a unit area per unit time and essentially dictates the heating rate and temperature gradient, as shown in Fig. 11. A higher heat flux density results in a faster heating rate and a smaller time expenditure for deicing. As shown in Fig. 15, the deicing time decreases with the increase in heat flux density, with a very fast decay at the beginning followed by a relatively slower decay. The results indicate that increasing the heat flux density is effective for deicing in the range of 600–1000 W/m 2 but that the effectiveness increases little when the heat flux density exceeds 1000 W/m2. The energy is the product of the heat flux density and the time used for deicing; the higher the heat flux density, the less the expenditure of time, so a minimum energy consumption value (optimal value) should exist, as shown in Fig. 15. For example, 1000 W/m2 is the optimal heat flux density for ice with a thickness of 10 mm at an ambient temperature of −20 °C.

and energy because the shortest time cost does not usually accompany the most economic energy requirement. Therefore, three evaluation indices could be used to determine the expected options for the heat flux density for a certain amount of ice. The first choice is defined as a comprehensive index, β, which accounts for the optimal time and energy efficiency as follows (a balance between time and energy consumption):

Time(sec*103)

in Harbin, China), the energy that dissipates to the environment is only a small portion of the entire energy. Consequently, it is reasonable to conclude that the consumptions of time and energy for deicing are approximately linear functions of the ambient temperature.

600 800 10001200140016001800

100

Heat flux density (W/m2)

Fig. 18. The evaluation of the prior options for time and energy consumption on deicing efficiency at an ambient temperature of −20 °C for ice thicknesses of (a) 10 mm, (b) 15 mm, and (c) 20 mm.

32

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

(b)

(a)

90 6

12 100 9 90

80

600 800 1000 1200 1400 1600 1800

2

18

130 12

6

80

2

Heat flux density (W/m )

140

15

120

9

6 600 800 1000 1200 1400 1600 1800

160 Time-15mm Energy-15mm 150

Energy (kJ)

9

110

21

Time(sec*103)

100

Time(sec*103

12

Energy (kJ)

110

Time-10mm 120 Energy-10mm

15

Energy (kJ)

Time-10mm 120 Energy-10mm

15

Time(sec*103

(c)

18

18

110 600 800 1000 1200 1400 1600 1800

100

2

Heat flux density (W/m )

Heat flux density (W/m )

Fig. 19. The evaluation of the prior options for time and energy consumption on deicing efficiency at an ambient temperature of −30 °C with ice thicknesses of (a) 10 mm, (b) 15 mm, and (c) 20 mm.

of 1.323 and 1.320, but when the efficiency of time is also considered, 1400 W/m2 should be the first choice. When a single index is considered, i.e., the least energy consumption or the shortest time expenditure at an ambient temperature of −10 °C, as shown in Fig. 17 and Tables 1 and 2, a heat flux density of 600 W/m 2 is the optimal choice for the 10-mm-thick ice by virtue of having the lowest energy consumption (53.82 kJ). However, in an emergency situation, 1800 W/m2 could be selected because it requires the least time. For ice of thicknesses of either 15 mm or 20 mm, a heat flux density of 600 W/m 2 is a reasonable choice if time is not a limitation because it has the lowest energy requirement. In an emergency situation, 1800 W/m2 must be applied to meet the minimum time requirement, although more energy is consumed. Fig. 18 presents the time and energy consumption for deicing a certain amount of ice at an ambient temperature of −20 °C. The trends in the curves shown in Fig. 18 imply the existence of the critical phenomenon, which is that the second optimal solution is more practical than the absolute optimal solution. For ice with thicknesses of 10 mm, 15 mm and 20 mm, although the time was slightly longer when the heat flux density was 1000, 1400 and 1400 W/m2 than when it was 1800 W/m2, the energy consumption was much smaller at these heat flux densities than at 1800 W/m2. These values are consistent with the time-energy index shown in Fig. 16. Therefore, the optimal solution was that the regular heat flux density (1000–1400 W/m 2) would be offered for ambient temperatures of −20 to −10 °C with the anticipated associated good energy and time efficiency. Similar to the results shown in Fig. 18, the second optimal point was more practical for the ambient temperature of −30 °C, as shown in Fig. 19. The optimal heat flux density for an ice thickness of 10 mm was 1000 W/m2 (smallest energy requirement with a relatively short time requirement); the optimal heat flux densities for ice thicknesses of 15 mm and 20 mm were 1000 and 1400 W/m 2. Moreover, for 20-mm-thick ice at − 30 °C, the energy requirement increased slightly with the increase of heat flux density from 600 to Table 4 Economic expenditure per unit area for deicing a certain thickness of ice. Ambient temperature, °C

−10

−20

−30

Ice thickness, /mm

10 15 20 10 15 20 10 15 20

1400 W/m 2, but the time was significantly reduced. If there was no limitation for time cost, the 600, 1000 and 1400 W/m2 heat flux densities could be used, but the optimal density was 1400 W/m2 because of the combined efficiency of time and energy, with a minimum time-energy index of 1.283 as presented in Table 3. Generally, 1400 W/m 2 was an appropriate option that could be widely applied in severely harsh weather for deicing.

3.5. The evaluation of economic expense The price for electric power in China is currently USD$ 0.083 per kW·h. The cost of deicing per unit area using the proposed technology was calculated and is listed in Table 4. For the low temperature case (− 10 to 0 °C), 0.11–0.22 $/m 2 is sufficient for deicing ice in the thickness range of 10–20 mm. For lower temperature conditions (−20 to −10 °C), the cost is 0.15–0.28 USD$/m2, which is much lower than the other current techniques listed in Table 5 (George and Charles, 2011; Harnick et al., 1980; Lee et al., 2000; Litvan, 1976; Wang et al., 2006). The cost was calculated based on the present economic costs and the operating efficiency of various deicing methods. The estimated expense of each mechanical method includes the labor costs (>11.00 /h in China, http://finace.sina.com.cn/g/20100809/07058444689.shtml) and the work efficiency. For the chemical methods, the cost is dependent on the market price (NaCl, 0.31USD$/kg; CMA, 3.1USD$/kg) and the amount consumed (NaCl, 0.3–0.6 kg/m2; CMA, 0.56–1.13 kg/m2). As shown in Table 5, for similar situations the cost of using conductive concrete to deice the same amount of ice (Yehia et al., 2000) is almost 4 times the cost of the approach proposed in this paper. Common salt (sodium chloride) is not recommended due to the severe environmental pollution and corrosion of reinforced concrete associated with its use, even though it is only half the cost of the approach proposed in this study (George and Charles, 2011; Harnick et al., 1980; Lee et al., 2000; Litvan, 1976; Wang et al., 2006). Moreover, the application of some non-polluting chemical salts, e.g., calcium chloride and acetic acid calcium magnesium, is also limited because of their much higher cost (0.26–0.7 USD$/m2, 1.75–3.51 USD$/m2). The proposed deicing technique is an excellent option, especially for the extremely

Economic expenditure USD$/m2 600 W/m2

1000 W/m2

1400 W/m2

1800 W/m2

0.11 0.15 0.21 0.18 0.20 0.22 0.22 0.25 0.29

0.14 0.18 0.22 0.15 0.20 0.23 0.18 0.23 0.29

0.15 0.17 0.22 0.20 0.22 0.23 0.22 0.26 0.29

0.12 0.18 0.22 0.20 0.25 0.28 0.23 0.31 0.35

Table 5 Cost of deicing using different approaches at an ambient temperature of −20 °C. Ice thickness /mm

10 15 20

Economic expenditure USD $/m2 NaCl

CaCl

CMA

Conductive concrete

Mechanical

CNFP

0.09 0.13 0.18

0.26–0.35 0.40–0.53 0.53–0.70

1.75 2.65 3.51

>0.56 >0.56 >0.73

>0.1 >0.1 >0.1

0.15–0.2 0.2–0.25 0.22–0.28

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

initial temperature of −12 °C, the gray line for a snow thickness of 30 mm has a steeper gradient, and snow melting began earlier. This result is the same as that of the black line and the black dashed line for the 40- and 50-mm-thick snow at an initial temperature of − 22 °C. Although melting the thicker snow requires more energy, because of the lower thermal conductivity of snow (approximately 0.1 W/(m*K) for new snow), the thicker snow layer actually played a more active role in heat preservation as a porous media and prevented heat loss into the surrounding air. A similar phenomenon also presented in other cases, as shown in Fig. 21, except for the cases with 40- and 50mm-thick snow at an initial temperature of − 23 °C, as shown in Fig. 21 (b). The results for these cases are different because of the relatively lower heat flux density input and the extremely low surrounding temperature exceeding the heat preservation capability of the specimen. Therefore, the time cost for melting the snow is determined by a combination of the energy requirement and the heat preservation effect. As shown in Fig. 22, with a heat flux density of 600 W/m 2, it took approximately 6,000, 6,500, 7,500 and 6,800 sec to melt snow with thicknesses of 20, 30, 40 and 50 mm at a surrounding temperature of − 9.1, − 9.2, − 9.7 and − 10 °C, respectively; the corresponding energy consumption for these cases is 1.0, 1.12, 1.28 and 1.10 kWh/m 2. In contrast with the other results, a heat flux density of 600 W/m 2 is most efficient and profitable for 30-mm-thick snow at a normal low temperature (−10 °C), with a minimum consumption of time and energy that results from the joint effect of heat preservation and dissipation under similar surrounding conditions. Similarly, because of the previously mentioned heat preservation effect, 800 W/m 2 is more efficient and preferable for thicker snow (30 mm) at extreme ambient temperature condition (−17 °C). Overall, it makes sense that the time and energy cost increases as the snow thickness increases for similar ambient conditions. In contrast to the lower heat flux densities, 1000 W/m 2 is more efficient and preferable for thicker snow (40 mm) at the extreme ambient temperature condition (− 23 °C) because of the relatively longer melting time but higher efficiency, which is also a result of the heat preservation effect associated with thicker snow. The cost of the self-deicing technique (0.05–0.11 $/m 2) proposed in this study was approximately half that of the snow-melting method developed by Hou et al. (2002) based on conductive concrete filled with CF (1.85%). The technique proposed in this study was also verified as being only 1/10–1/6 of the cost calculated by Yehia et al. (2000) in the bridge snow-melting study based on conductive concrete filled with steel fiber. In summary, the investigations of deicing and snow melting verified that the self-deicing/snow-melting technique proposed in this study offers the advantages of less time, lower energy consumption, feasible

Fig. 20. The test setup for melting snow in a natural environment.

low temperature case (−30 °C), because at a maximum cost of no more than 0.29 USD$/m 2 the deicing cost is much lower. The solar energy used as the power source in this study is an abundant source of energy, increasing the feasibility of this proposed deicing system for practical applications. Currently, the price of CNFP is relatively expensive as a new material, it must decrease with the mature of manufacture process in the future, then the installation cost will also accordingly significantly drop. 4. Investigation of the snow-melting capabilities of the CNFP-based self-deicing road system in a natural environment The performance of the CNFP-based self-deicing road system for melting snow in a natural environment was also investigated. The applied heat flux densities were 600, 800 and 1000 W/m 2 with snow thicknesses of 20, 30, 40 and 50 mm. The surrounding temperature and wind speed were monitored by the Center 309 thermometer and anemoscope. The snow-melting process was affected by multiple factors, such as wind speed, ambient temperature, heat flux density and snow thickness. The test setup for the system is shown in Fig. 20 and the temperature distribution measured in the test is shown in Fig. 21. As shown in Fig. 21, at the beginning the temperature increased rapidly from the initial state to the freezing point (0 °C). The snow then absorbed enough energy to achieve its latent heat, then began to melt and formed a moving interface between the melted water and the rest of the snow; the temperature at the melting interface was stable at 0 °C until the snow vanished. As shown in Fig. 21 (a), for the same

10

10

0 -10 20mm 30mm 40mm 50mm

-20 0

1000

2000

3000

Time(sec)

4000

5000

Temeprature (oC)

Temperature(oC)

(c)

(b) 10

5 0 -5 -10

20mm 30mm 40mm 50mm

-15 -20 -25

0

1500

3000

4500

Time (sec)

6000

7500

Temperature(oC)

(a)

33

5 0 20mm 30mm 40mm 50mm

-5

-10

0

1500

3000

4500

6000

7500

Time(sec)

Fig. 21. The change in temperature with time at the interface between the thermal conductive layer and the snow layer for four different snow thicknesses and heat flux densities of (a) 1000 W/m2, (b) 800 W/m2 and (c) 600 W/m2.

H. Li et al. / Cold Regions Science and Technology 86 (2013) 22–35

(a)

(b)

9000

2

Time (sec)

8000 7000

Temperature (oC)

600 W/m 2 800 W/m 2 1000 W/m

6000 5000 4000 3000 2000

20

25

30

35

40

45

Snow thickness (mm)

50

(c)

0

2

Energy (Kwh/m2)

34

-6 -12 -18 2

600 W/m 2 800 W/m 2 1000 W/m

-24 -30

20

25

30

600 W/m 2 800 W/m 2 1000 W/m

1.3 1.2 1.1 1.0 0.9

35

40

45

50

Snow thickness (mm)

20

25

30

35

40

45

50

Snow thickness (mm)

Fig. 22. Effect of multiple factors on the snow-melting process: (a) time cost, (b) the corresponding surrounding temperature and (c) energy expenditure per unit area (kWh/m2).

operation, intelligent control and environmental protection. This system can be widely used in roads, pavement, highways and bridges. In addition, the integration of a self-energy harvesting system with this self-deicing/ snow-melting system will be competitive in the future.

5. Conclusion A self-deicing road system based on a CNFP electro-thermal source was proposed. The feasibility and efficiency of the self-deicing road system were validated through experiments. This study resulted in the following conclusions: CNFP provides good electro-thermal properties at ambient temperatures below 0 °C, with a rapid heating reaction and stable resistivity (0.72 Ω·mm). These properties indicate that CNFP can be employed as a highly efficient thermal source to generate a stable heat flux density for a self-deicing road system. For example, a stable heat flux density of 1000 W/m 2 can be generated by CNFP with an applied current of 2.3 A. A cement-based composite filled with 3% by weight MWCNTs shows much better thermal conductivity (2.83 W/m·K) than cement-based composites filled with other conductive materials such as carbon fibers (1.3–2.0 W/m·K, 1% MWCNT 2.5 W/m·K) and than common cementbased composites (1.58 W/m·K). This composite can be incorporated into the self-deicing road system as a thermal conduction layer. The high deicing efficiency and low energy consumption of the proposed self-deicing road system with electro-thermal materials has been validated. The deicing performance was affected by the thickness of the ice layer, the surrounding temperature, the heat flux density and the wind speed. The experimental results indicate that the deicing time and energy consumption increase with an increase in ice thickness but decrease with an increase in the surrounding temperature. As another essential factor affecting the deicing performance, a larger heat flux density results in a decreased time cost as a hyperbolic function but has an uncertain influence on energy consumption. Therefore, the optimal option for the heat flux density was determined by an evaluation of the time-energy index, β, as the most rational power affordance. For example, with an ambient temperature of −10 °C, the optimal heat flux density is 1800, 1400/1800 and 1800 W/m2 for ice with thicknesses of 10, 15 and 20 mm, which corresponds to minimum indices of 1.217, 1.34 and 1.331, respectively. The high performance of the CNFP-based self-deicing road system for snow melting was also validated through an experimental study. In terms of the evaluation criteria of efficiency, time, energy supply, cost and environmental impacts, the deicing and snow melting investigation verified that the proposed self-deicing road system is a competitive and promising deicing/snow-melting technique. It may have the

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