Experimental Investigation of the Effects of Temperature, Moisture, and

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An experimental investigation of the effects of temperature, moisture and physical structure variations on the thermal properties of lignite Keji Wan, Jingpeng Chen, Zhenyong Miao, Qiongqiong He, and Jingyu Tian Energy Fuels, Just Accepted Manuscript • Publication Date (Web): 06 Jun 2017 Downloaded from http://pubs.acs.org on June 7, 2017

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An experimental investigation of the effects of temperature, moisture and physical structure variations on the thermal properties of lignite

Keji Wana,b, Jingpeng Chena,b, Zhenyong Miaoa,b,*, Qiongqiong Hea,b, Jingyu Tiana,b

a

School of Chemical Engineering and Technology, China University of Mining and

Technology, Xuzhou 221116, Jiangsu, China b

National Engineering Research Center of Coal Preparation and Purification, China

University of Mining and Technology, Xuzhou 221116, Jiangsu, China

Correspondence information: Zhenyong Miao, School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China, E-mail address: [email protected]; Tel: +86 0516 83884289; fax: +86 0516 83884289.

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Abstract A new laser flash system and micro calorimeter were proposed to measure thermal properties of lignite and determine the influences from temperature, moisture and physical structure variation. It was showed that the thermal diffusivity of lignite ranged from 0.12 mm2/s to 0.23 mm2/s (30~250 oC). The decreasing thermal diffusivity with increasing temperature was attributed to the increasing number of phonon-phonon collisions leading to decrease the mean free path of phonon scattering. Thermal capacity and conductivity of dry lignite were in the range of 1.10 ~1.60 J/K/g and 0.21 ~0.32 W/m/K (30~180 oC), respectively, and both of them had a tendency to increase with temperature. It was showed that thermal capacity was mainly affected by moisture, which can be accurately described by a linear constitutive equation. Meanwhile, the strong interaction between coal and water also increased the thermal capacity of non-freezable water and bound water. Moisture had a greater influence than porosity in variation of thermal conductivity, and the effects of moisture was weakened at low moisture region. Porosity changes as a function of moisture were introduced into the general models for lignite, and the experimental values were almost located in the range between parallel and geometric mean model.

Keywords: Lignite; LFA; C80; thermal properties; temperature; moisture; porosity.

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1. Introduction Lignite is becoming an important fuel resource for many developing countries because of the rapid increase in high-rank coal consumption combined with the wide availability of low-rank coal. Nevertheless, high moisture content (about 30%~65% wet basis) has significantly limited its economic benefits and competitiveness in different industrial utilization such as pyrolysis, gasification and combustion. And hence, drying is playing a more and more important role in lignite upgrading. A better knowledge of the thermal properties of lignite is required to improve on their drying and propose new drying schedules. Meanwhile, that allows using in some numerical models developed in literature to simulate the most reliably coupled processes of the heat and mass exchange and predict the lignite drying. Generally, these thermal properties mainly include the thermal conductivity (λ), which describes the ability of the material to transfer heat, the thermal capacity (Cp), which describes the ability to store heat, and the thermal diffusivity (α) characterizes the velocity at which the heat propagates in the substance. By combining with density (), the relationship of these three parameters can be described by equation (1), = (1) Currently, although there are several methods to determine the thermal properties of materials, such as transient hot wire method [1], transient plane source method [2], etc., it is still hardly to get a reliable determination of the thermal properties for the solids such as minerals or rock materials due to contact thermal resistance and radiative transfer effects [3]. To eliminate the contact resistance of the sample with thermocouples and the heat source and increasing the accuracy of measurements , laser flash method with the accuracy of 2% ~ 3% for thermal diffusivity and 5% for 3


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thermal conductivity [3] was first proposed by Parker and Jenkins [4]. This technique entails heating the front side of a thin disk-shaped plane-parallel sample by a short laser pulse, and then the temperature rise on the rear surface is measured versus time using an infrared detector [5], and its application has been extended into many fields [6-8]. But it should be noticed that when determining the thermal capacity, compared to the laser flash method, differential scanning calorimetry (DSC) can present more reliable data[3]. The thermal properties of materials are the resultants of compositions, structure and temperature. For thermal diffusivity in materials, temperature plays an important role among various influence factors [9,10], and a theoretically based correlation for the thermal diffusivity of substance requires the known temperature behavior of the microscopic parameters (average phonon speed, mean-free path et al.) [11, 12]. A series of good reviews of correlations for the thermal capacity of coal have been carried out by Clendenin et al. [13], Agroskin [14], Kirov [15] and LEŚNIAK et al. [16]. Generally, the thermal capacity of coal depends on temperature and composition, and in most cases, the thermal capacity increases with temperature and moisture content. Heat is transferred through a medium by phonons. Scattering of the phonons causes a decrease in the thermal conductivity and the conductivity is thus sensitive to the structure of the materials. The thermal conductivity of a porous medium is always described by geometric structure models [17]. Specifically, if the structure and orientation of the porous medium is such that the heat conduction takes place in series, with all of the heat flux passing through both solid and fluid (in Fig. 1. b [18]), then the overall conductivity ( ) is the weighted harmonic mean of solid conductivity ( ), liquid conductivity ( ) and gas conductivity ( ),

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=

1 (2) 1 (1 )

where and was water saturation and porosity, respectively. On the other hand, if the heat conduction in the solid and fluid phases occurs in parallel (in Fig. 1. c [18]), then the overall conductivity ( ) is the weighted arithmetic mean of solid conductivity ( ), liquid conductivity ( ) and gas conductivity ( ), namely = (1 ) (1 ) (3)

Fig. 1. Simplified geometric structure of porous media used to calculate the thermal conductivity [18]

Actually, and provides the upper and lower bounds of the actual overall conductivity, respectively [17]. For practical purposes, a rough and ready estimate is provided by the weighted geometric mean ( ) of solid conductivity, liquid conductivity and gas conductivity,

=

( )

(4)

Many authors used this model to predict effective thermal conductivity in a wetted porous media: Carson [19] in porous food, Bal et al. [20] in laterite based bricks, etc. 5


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There are two important variables, and , in equation (2) ~ (4), and their accuracy would play a vital role in model prediction. However, experimental evidence on the thermal properties of lignite is still meager and incomplete, not to mention the relative influence factors, and some researchers don’t have too much choice but to directly reference the data from the literature about bituminous or sub-bituminous when simulating the drying process [21, 22]. More importantly, due to the colloidal properties of lignite, with moisture decreasing, the volume of lignite starts to shrink, and the structure changes would result in different heat transfer properties. The macropore volume, the main storage space for water can decrease sharply from about 1.5mL/g to 0.5mL/g in drying [23], and the pore structure such as porosity, , cannot be maintained as a constant. Thus, for wet lignite, neglecting the change of pore structure in drying and directly applying these models (described in equation (2) ~ (4)) to calculate the thermal conductivity would result in large error. Therefore, the objectives of this study are to (1) propose an appropriate method to measure the intrinsic thermal properties of lignite to meet the urgent demand for the data in industry and research, (2) to analyze the effects of temperature, moisture and physical structure on thermal properties, and (3) to modify the common geometric structure models of thermal conductivity by considering the deformation of lignite

2. Experimental 2.1. Sample preparation Four lignites from different regions of China were used in this study, which were named as Zhaotong (ZT), Xiao Longtan (XLT), Shengli (SL) and Mengdong (MD), 6


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respectively, and could reflect the properties of most lignites in China. Basic analysis of four samples was shown in Table 1. Before testing, raw coals were cut by a diamond saw into thin (1∼2 mm thick), square flat pieces (10mm×10mm) as shown in Fig. 2. The samples, which occurred as randomly oriented aggregates, with the best mechanical properties were selected (with small amounts of visible cracks) for further investigations. By using a halogen moisture detector to remove different quantity of water from raw lignite, a series of samples with expected value of moisture content could be obtained. The pore structure information of lignite was measured by mercury intrusion method (in Table 2). Table 1. Proximate analysis and elemental analysis of lignite samples.

XLT lignite Moisture (wt%, as received basis)

29.98

SL lignite 28.18

ZT lignite

MD lignite

61.61

27.20

Proximate analysis (wt %, dry basis) Volatile matter

44.41

35.72

50.58

23.18

Fixed carbon

36.01

42.95

28.78

27.68

Ash

19.58

21.33

20.64

49.14

Ultimate analysis (wt %, dry ash free basis) C

68.18

65.71

65.74

72.21

H

3.47

4.92

3.59

4.24

N

1.89

1.26

1.98

1.17

S

3.08

2.42

2.75

1.42

O

23.38

25.69

25.94

20.96

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Fig. 2. Samples cut by a diamond saw

Table 2. Basic information of pore structure of dry lignites from mercury injection apparatus.

Samples

Bulk density (g/cm3)

Total porosity (%)

Specific intruded volume (mL/g)

Ture density (g/cm3)

ZT

1.04

32.13

0.308

1.53

XLT

1.36

14.74

0.109

1.60

SL

1.24

17.41

0.141

1.50

MD

1.13

19.57

0.172

1.40

2.2. Measurements of thermal properties by light flash apparatus Thermal diffusivity and capacity of lignite was determined by using the Light Flash Apparatus (Netzsch LFA-467). About 0.25 g sample, the prepared square flat pieces, was spray-coated with a thin layer of graphite to improve the absorption of the laser light. Measurements were conducted under the flow of argon (20 cm3/min). Three laser shots with a pulse length of 0.5 ms were applied to each sample at a given temperature. The specific measurement procesure was as follows: (1) The thermal properties of wet lignites with different moisture were measured at 30 °C to study the effects from moisture contents; (2) Dry lignites were heated from 30 °C to 250 °C at a 8


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heating rate of 5 °C/min, and the corresponding measured points were selected at 30 °C, 50 °C, 70 °C, 90 °C, 100 °C, 120 °C, 150 °C, 180 °C, 200 °C and 250 °C. The final result for each parameter was presented as the average value of three partial measurements, and each datum point was measured more than three times. 2.3. Measurements of thermal properties by micro calorimeter The Setaram C80 micro calorimeter, a more accurate DSC instrument with the 0.1% of calorimetric precision, was used to measure thermal capacity of lignite. About 5 g sample was used in each experiment, and the sampling process was operated in the glove box filled up with pure argon, and then the vessels were sealed by poly tetra fluoro ethylene gasket (PTFE) and fastening piece to avoid air oxidation at high temperature. Specific temperature procedure was as follows: (1) Thermal capacities of lignites with different moisture contents were measured over the temperature range from 30 °C to 60 °C at a heating rate of 0.2 °C/min to investigate the interaction between coal and water; (2) Dry lignite was heated from 30 °C to 180 °C at a heating rate of 0.2°C/min to study the variation of thermal capacity with temperature.

3. Results and discussion 3.1. Thermal diffusivity of lignite Although there are few literatures involved in the study about the thermal diffusivity of lignite, Wen [9] and Gosset [24] did some comprehensive researches about that of bituminous or sub-bituminous coal, and the results were shown in Fig. 3. The temperature dependence of the thermal diffusivity of lignite was measured for the temperature range from 30 oC to 250 oC (in Fig. 4). Taken as a whole, the thermal diffusivities of dry lignite were in the range of 0.12~0.23 mm2/s, which were larger 9


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than those of bituminous and sub-bituminous coals (0.06~0.13 mm2/s). The effects of temperature on thermal diffusivity were not exactly same for lignite and subbituminous (or bituminous) coals. For sub-bituminous, bituminous and MD lignite, it showed that the thermal diffusivity decreased with an increasing temperature and could be fitted to the model proposed by Wen [9] (in equation (5)),

=

1 (5) #

%$where A and B were the fitting parameters and T was temperature, oC. Thermal diffusivity is connected with the mean free path of the phonon for nonmetals [9], and the fall in thermal diffusivity can be explained by that the rising temperature increases the number of phonon and phonon-phonon collisions leading to decrease the mean free path of the phonon-phonon scattering in coal. But for ZT, XLT and SL, prior to the similar declining trend appearing, the thermal diffusivity slightly increased firstly, and the transition temperature was at around 80 oC. This may be because that the higher ratio of amorphous phase (organic substances as shown in Table 1) in these samples affects the heat transfer properties in low temperature range. Thus, the general model, equation (5), provided bad fitting results for ZT, XLT and SL, and the actual relationship between thermal diffusivity and temperature can be described by a second-order polynomial wich was not shown in this paper.

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Fig. 3. Thermal diffusivities of bituminous and sub-bituminous coals

Fig. 4. Temperature dependence of thermal diffusivity for lignite 11


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3.2. Thermal capacity of lignite The measurements of thermal capacity of lignite were conducted using micro calorimeter (C80), and deionized water was used to check the accuracy of the instrument. Due to the release of absorpted gases (e.g. CO2, CH4) in lignite and the increasing temperature, the pressure in the sealed vessel of C80 sharply increased, and the maximum temperature allowed was nearly 200 oC. Thus, the final temperature used

Fig. 5. Thermal capacity of lignites determined by LFA [a] and C80 [b] 12


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in this study was 180 oC. Both of thermal diffusivity and thermal capacity of lignite can be measured by LFA at the same time, and the thermal capacities determined by usimg LFA were also used for comparison. Fig. 5 [a] and [b] showed the experimental measurement results of LFA and C80, respectively. Overall, the thermal capacities determined by LFA were higher than those measured by C80, and for the former, the measured values were in the range of 1.40~2.35 J/K/g from 30 oC to 250 oC, and for the latter, the Cp were in the range between 1.10 J/K/g and 1.60 J/K/g over the temperature range from 30 oC to 180 oC, which was closer to results of literature [25]. For both of the two measuring methods, the thermal capacities of lignite had a tendency to increase with temperature, though there was a small fluctuation at around 140oC, which might be due to the energy consumption of the desorption of some gases in pore. Compared to the 0.25 g injected lignite samples of LFA, there are far larger amounts of sample (around 5 g) injected in the sample cell of C80, and thus, the corresponding experiment points should be more typical. Although LFA can provide a larger measurement range (from room temperature to more than 500oC [5]), for lignite drying process, C80 may be a better choice to measure thermal capacity. Due to the large thermal capacity, moisture plays an important role in the variation of thermal capacity for lignite. In most cases, water was always considered as “additive” [26], and then the thermal capacity of porous media with moisture could be simply calculated as the weighted average of the heat capacities of solid skeleton and moisture by researchers [16, 27, 28], which was described by equation (6) = , ( , (1 () (6)

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where , was the thermal capacity of liquid water, J/g/K, , was the thermal capacity of solid skeleton, J/g/K, and w was moisture content, %, wet basis. Then, the measured thermal capacity, Cp, at 30 oC verse calculated values by above model were shown in Fig. 6. It can be seen that all of the experimental values of Cp for lignites with moisture were greater than those predicted values calculated by equation (6), and the maximum deviation can reach nearly 30%. Thus, the total heat capacities of water-filled lignites were larger than the weighting sum of the heat capacities of liquid water and lignite skeleton alone. Actually, this method neglected the complicated interactions between lignite and water as those reported in the literatures [29-31]. According to the intensity of interaction, there are different types of water in lignite, and based on the differences of crystallization temperature, water in lignite can be classified as free water, bound water and non-freezable water [32, 33]. With moisture content increasing, the proportion changes of non-freezable water and bound water were shown in Fig. 7. It is shown that the non-freezable water was the only form of water, when the total moisture content was below 0.18 g/g coal. Bound water started to form from the total moisture content of 0.18 g/g coal and ended at 0.29 g/g coal (bound water content will not change, when free water begin to form [34].). The differences between measured and calculated values of thermal capacity increased firstly and then decreased as shown in Fig. 7. The increasing turning points were at moisture contents of 0.29, 0.26, 0.27 and 0.29 g/g coal for ZT, XLT, SL and MD, respectively. For all of the lignites, differences of thermal capacity were greatly increased with moisture rising in the non-freezable water region (region (a)), and slowly grew in the non-freezable water and bound water region (region (b)). When the free water began to form (region (c))), these differences of thermal capacity started to decline. Therefore, the increase of differences in region (a) and region (b) is due to the 14


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strong interaction between coal surface and water which increased the thermal capacity of non-freezable water and bound water, and the effects on non-freezable water were larger than on bound water. Finally, with moisture increasing, the free water started to form, and the percentage of non-freezable and bound water was decreased and their effects were gradully weakened. The practical relationship of thermal capacity and moisture content (in Fig.8) can be described by a more accurate linear constitutive equation (equation (7)), though the specific interaction between coal and water was not shown in this equation. = 3.372( 1.316 (7)

Fig. 6. Thermal capacities determined by C80 versus the calculated values by equation (6)

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Fig. 7. Changes of differences between measured and calculated thermal capacities with moisture.

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Fig. 8. Variations of thermal capacity of lignite with moisture contents (Dash lines represented the deviation from model).

3.3. Thermal conductivity of lignite 3.3.1. Effects of temperature on thermal conductivity of lignite According to the thermal diffusivity from LFA and thermal capacity from C80, the thermal conductivity of dry lignite were calculated (in Fig.9), which was in the range of 0.21 ~ 0.32 W/m/K over the temperature range from 30 oC to 180 oC. The measured conductivity at 30 oC was in the range from 0.21 W/m/K to 0.26 W/m/K, which was approximate to the value of 0.22 W/m/K at 22 oC from literature [35]. There was a positive relationship between thermal conductivity and temperature of the coal, which is consistent with the results of literature about other coals [25] and can be described by a second-order polynomial. Although the temperature behavior of thermal conductivity is due to microscopic behavior of phonon conduction [36], the macroscopic causes is the increasing thermal capacity with an increasing temperature.

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Fig. 9. Thermal conductivity of lignite at different temperatures

3.3.2 Variations of physical structure with moisture content According to previous study [37], the energy consumption for the removal of different types of water in lignite was shown in Fig. 10. Because the pore structure increased energy consumption of dewatering, the water in pore had higher evaporation heat than pure water. Hence, from Fig.10, it can be seen that for ZT, XLT, SL and MD, the moisture contents in pore were 0.90, 0.68, 0.31 and 0.41 g/g dry coal, respectively. The porosity of water saturated lignite can be calculated by the volume fraction of saturated water, namely,

=

, (8)

, = (. / (1 ) (9) where S was the water saturation, %, S=1, , was the volume fraction of water in lignite, %, (. was moisture content, % dry basis, and / was true density of lignite, g/cm3. Suuberg et al. [38] clearly defined a linear relationship between moisture removed and volumetric shrinkage for lignite, and hence, by assuming that the volumetric shrinkage of lignite in drying was due to the decrease of the pore volume in particles, the variations of porosity of lignite, ((), with moisture can be described by

(() =

1 21 / 2 = (10) 1 21 12

2 = 4((/ () (11) 18


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where / was the porosity of water saturated lignite which can be calculated by above method, 1 and 1 was the volume of pore structure of saturated lignite and corresponding total volume of lignite, respectively, and w0, x and b was the moisture content of water saturated lignite, % wet basis, the ratio of volume shrinkage, %, and proportional coefficient, respectively. Based on the initial porosity (water saturated lignite) and final porosity (dry lignite), b can be obtained, which were 0.81, 1.08, 0.74 and 0.72 for ZT, XLT, SL and MD, respectively, and then the (() can be predicted by the moisture content, as shown in Fig. 11. With moisture content decreasing, the porosity of lignite sharply declined, and it is also showed that the speed of shrink was accelerated in low moisture content region. Hence, variations of physical structure with moisture cannot be neglected, especially at low moisture content region.

Fig. 10. Energy consumption of water evaporation in drying [37].

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Fig.11. Porosity changes of lignite with moisture in drying.

3.3.3 Effects of physical structure and moisture on thermal conductivity of lignite Table 3. Thermal conductivity of dry lignites at 30 oC

Samples

Ash content (% db*)

Carbon +volatiles (% db)

(W/m/K)

Thermal conductivity of dry lignite (W/m/K)

ZT

20.64

79.36

0.336

0.236

XLT

19.58

80.42

0.334

0.136

SL

21.33

78.67

0.338

0.207

MD

49.14

50.86

0.527

0.231

*- dry basis

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The thermal conductivity of lignites could be predicted by a three-component (moisture, ash and organic substances) geometric mean model [35], and thus, for lignite matrix (the mixture of ash, carbon and volatiles), the thermal conductivity ( ) can be simplified as 6

6

7 9 = 5 ∙ (12)

where 5 is the thermal conductivity of ash, 4.65W/m/K [35], is the thermal conductivity of organic substances, 0.23W/m/K [35], and : , :; are the volume fraction of ash and organic substances, respectively, which can be calculated by the data of proximate analysis in Table 1 and the results were shown in Table 3. For the subsequent study, the values used for the thermal conductivity of lignite, water and air were: = , < = 0.58 W/m/K and = 0.026 W/m/K [39], respectively. Finally, introducing the variations of porosity (equation (9) and (10)) into the geometric structure models (equation (2)~(4)), the predicted values can be calculated (in Table 4). Actually, due to the complicated physical properties of lignite, it is hardly to find a quite precise general model to predict thermal conductivity for different lignites, but obtaining its variation range may be more practical. According to Table 4, series model provided a bad fitting results, and most of thermal conductivities determined from experiments were located in the range between parallel model and geometric mean model, even though some points waved around these two models. Therefore, the thermal conductivity of lignite (= ) can be described by combining these two models, and the modified model was expressed as follows, = = 1.254 >? (1 ? ) @ 0.084 (13) = A1 (()B (() (1 )(() (14) 21


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(

Experimental Investigation of the Effects of Temperature, Moisture, and

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