Pelletizing Properties of Wheat Straw Blending with Rice Straw

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Pelletizing Properties of Wheat Straw Blending with Rice Straw Yu Wang, Kai Wu,* and Yu Sun School of Mechanical Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei, Nanjing, Jiangsu 210094, People’s Republic of China ABSTRACT: Mixing different types of biomass materials to achieve better pelletizing properties is a potential method to improve the biomass pelletizing process. In this study, experiments were carried out with a single pellet unit to obtain the pelletizing properties of wheat straw blending with rice straw. The effects of the temperature, pressure, moisture content, blending proportion, and particle size on specific energy consumption, pellet density, and compressive strength were investigated. The experimental data were processed by the methods of regression analysis and variance analysis, and regression models were finally built. On the basis of these models, effects of each factor on specific energy consumption, pellet density, and compressive strength were studied considering the interaction between other factors. Finally, optimal conditions for the pelletizing process presented in this study were obtained. heating value of rice straw pellets. Serrano et al.11 found that adding small quantities of pine sawdust could improve the durability of barley straw pellets. Ståhl et al.12 made pellets from a raw material mix, including sawdust and rapeseed cake. Results showed that adding sawdust to the pelletizing process of rapeseed cake would increase the pellet durability. Liu et al.13 discovered that pellet properties were improved through mixing bamboo particles and rice straw particles. The inorganic ash content and gross calorific value of the pellets would meet the stand when the mixing ratio of bamboo and rice straw was no less than 3:2. Lu et al.,14 Stasiak et al.,15 and Rahaman et al.16 investigated the pelletizing properties of straw blending with wood saw dust. Results showed that the saw dust could act as a good binder to reduce the energy consumption and improve the product quality. Larsson et al.17 investigated the pelletizing properties of a sawdust blend of Scots pine and Norwegian spruce with additives including cassava stem powder and starch. Results showed that the cassava stem powder could act as a good natural binder to improve the pellet durability. Rajaseenivasan et al.18 investigated the performance of sawdust briquette blending with neem powder and found that the sawdust with neem powder as a binding agent had a considerable increase in pellet mechanical strength but a little reduction in the burning rate. Although these studies have proven that blending with woody biomass materials can achieve lower energy consumption and better pellet quality during the pelletizing process of crop straw, it is still not a good method for agricultural developing countries, which are rich in crop straw rather than wood. Instead, mixing different types of crop straw is a potential way to improve the crop straw pelletizing process. Wheat and rice are two global important crops, and the straw appears frequently in related studies. As a large agricultural developing country, China is rich in crop straw resources. According to the newest data obtained from the National Bureau of Statistics of the People’s Republic of

1. INTRODUCTION With the population growth, the surging demand for food has forced us to pay more attention to the reuse of agricultural wastes, such as crop straw.1 The most direct and simple way to use the energy from crop straw is to densify the loose material into pellets (or briquettes) with regular shape, higher density, and higher strength. The densified biomass pellets can be used for household heating, cooking, and electricity generation. As a kind of agricultural byproduct, crop straw does not occupy any extra fields. Besides, the carbon dioxide released during the combustion process of crop straw pellets is counterbalanced by the amount absorbed when the crop grows.1 Therefore, crop straw is a potential biomass material for pelletizing. However, several problems, including high energy consumption, serious wear of the mold, low heating value, and low mechanical strength, have seriously hindered the development of crop straw pelletizing technology.2 In recent years, various studies have been carried out to find solutions to these problems. The solutions include optimal design of the device, pretreatment of the raw material, adding fossil additives, and mixing different types of biomass materials.3−7 There is no doubt that mixing different types of biomass materials is the most simple and green way to solve these problems. Factors affecting the biomass pelletizing process mainly include types of the material, raw material particle size and its distribution, raw material moisture content, compression pressure, and temperature.8 Most related studies take one or several types of biomass materials as the raw material and investigate the effects of these factors on the pelletizing process based on experiments. As a result of the good performance in the pelletizing process, woody biomass materials are chosen as additives frequently to improve the pelletizing process of crop straw. Demirbaş et al.9 made pellets with a mixture of wheat straw and waste paper. They discovered that, in comparison to wheat straw, the optimal moisture content for a 20.0% by weight of waste paper and straw mixture was reduced from 22 to 18% and the optimal pressure was increased from 22.4 to 32 MPa. Chou et al.10 found that adding in rice bran could improve the compressive strength and © XXXX American Chemical Society

Received: January 9, 2017 Revised: March 13, 2017 Published: March 30, 2017 A

DOI: 10.1021/acs.energyfuels.7b00097 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels China, the country produced 208.25 million tons of rice straw and 130.19 million tons of wheat straw in 2015. However, pelletizing properties of wheat straw blending with rice straw have yet to be determined. Effects of each factor on the pelletizing process considering the interaction between each factor have yet to be cleared. This work investigated the pelletizing properties of wheat straw blending with rice straw based on a response surface experimental design. Effects of several factors on specific energy consumption, pellet density, and pellet compressive strength were studied. These factors included the temperature, compression pressure, moisture content, wheat straw percentage, and particle size. The experimental data were processed by variance analysis and regression analysis, and regression models were finally built. On the basis of these models, effects of each factor on specific energy consumption, pellet density, and pellet compressive strength were analyzed considering the interaction between the factors. Finally, in combination with Design Expert, the optimal conditions for the pelletizing process presented in this study were obtained.

Table 1. Factor Level Codes Zj

temperature, F1 (°C)

compression pressure, F2(MPa)

moisture content, F3 (%)

wheat straw percentage, F4 (%)

particle size, F5 (mm)

+1 0 −1

120 100 80

40 30 20

25 15 5

100 50 0

0.685 0.485 0.285

tagged sealed bags for 24 h before use. Each tag number corresponds to the test number shown in Table 2. In Table 1, Z1 = (F1 − 100)/20, Z2 = (F2 − 30)/10, Z3 = (F3 − 15)/ 10, Z4 = (F4 − 50)/50, Z5 = (F5 − 0.485)/0.2, and Zj ∈ [−1, 1] (j = 1, 2, ..., 5). 2.2. Devices. An apparatus (Figure 2) including a universal testing machine (HRJ Company Jinan, China) and a self-designed single pellet unit (Figure 3) was developed previously.20 The diameter of the mold used in this study was 10 mm. During the test, the mold was heated to the target temperature with several heating devices and a temperature controller first. Then, materials were placed in the heated mold and compressed by the pressing shaft at the speed of 10 mm/min until the compression pressure reached the target. The pressure was held for 1 min before the biomass was extruded from the mold. Forces on the biomass during the process were recorded. 2.3. Methods. The experiment is carried out based on the Box− Behnken design (BBD). The factor level codes are shown in Table 1, and the test scheme is shown in Table 2. Levels of the factors are chosen based on the results of related published papers. 2.4. Specific Energy Consumption. High energy consumption is one of the problems that needs to be solved urgently in the crop straw pelletizing process, and the specific energy consumption obtained from the experiment can present the energy consumption in a real production process. Specific energy consumption is the energy consumption of producing unit weight products. Because the energy is mainly used to compress the biomass and overcome the friction between the biomass and mold, the energy consumption is defined as the work performed by the compression force during a single pelletizing process. The specific energy consumption is given by14

2. EXPERIMENTAL SECTION 2.1. Materials. Wheat straw and rice straw were collected in Yangzhou, China, in June 2016 and October 2015, respectively. The raw materials were stored in several sealed bags after they were naturally air-dried for 24 h. The wheat straw and rice straw were crushed into pieces with a lab-scale crusher. The particle size of the crushed wheat straw was determined by sieving based on ANSI/ASAE S319.4 FEB2008 (R2012),19 and the geometric mean diameter (dgw) of the sample turned out to be 0.485 mm. The mass fraction distribution is shown in Figure 1 (blue line marked with circles). This line was shifted to left and

E=

W 1 = m m

∫0

l

F(x) dx =

v m

∫0

tB

F(t ) dt

(2)

where E (J/g) is the specific energy consumption, m (g) is the weight of the single pellet, v (m/s) is the compression velocity, tB (s) is the compression time, and F (N) is the compression force. 2.5. Density. The pellet density can be calculated by eq 3.21 The mass and size of the pellet are measured by an electronic scale and a vernier caliper, respectively Figure 1. Particle size distribution of the crushed wheat straw.

ρ=

(3)

where ρ (g/cm ) is the product density, m (g) is the mass of the pellet, D (cm) is the diameter of the pellet, and L (cm) is the length of the pellet. 2.6. Compressive Strength. The pellet compressive strength is tested by the universal testing machine. Put the sample on the test platform horizontally and then press it at the speed of 5 mm/min until the sample is broken. Record the maximum force during the process, and the compressive strength is defined as14 3

right with Excel, and another two lines with similar distribution were finally obtained, whose dgw was 0.285 and 0.685 mm, respectively. On the basis of Figure 1, the crushed wheat straw and rice straw were sieved and mixed to obtain the special-sized wheat straw and rice straw, of which dgw was 0.285, 0.485, and 0.685 mm. The three different sized materials were stored in sealed bags. Initial moisture contents of these materials were tested with a moisture meter and turned out to be 5 ± 1%. With an electronic scale, the moisture content was adjusted to the target (±1%) by adding water.20 The weight of the added water is given by m (w − w0) mw = 0 1 100 − w1

m 4m = V πD 2 L

σt =

2F πDL

(4)

where σt (MPa) is the compressive strength, F (N) is the maximum force, D (mm) is the diameter of the sample, and L (mm) is the length of the sample.

(1)

where mw (g) is the weight of added water, m0 (g) is the weight of initial material, w0 (%) is the initial moisture content, and w1 (%) is the target moisture content. According to the factor level codes shown in Table 1, and the test scheme shown in Table 2, test materials were prepared and then kept in

3. RESULTS AND DISCUSSION 3.1. Results of the Experiment. Samples of the pellets are shown in Figure 4. Test results are shown in Table 2. B


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Energy & Fuels Table 2. Test Scheme and Results factors

responses

test number

Z1

Z2

Z3

Z4

Z5

specific energy consumption (J/g)

density (g/cm3)

compressive strength (MPa)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45

−1 0 0 0 −1 1 −1 −1 0 0 0 0 1 0 0 −1 −1 0 1 0 0 1 0 1 0 0 0 0 −1 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0

0 0 −1 1 0 0 1 0 0 1 0 0 0 1 0 0 −1 0 1 0 1 0 0 0 0 −1 −1 1 0 1 0 0 0 0 0 0 0 0 −1 −1 0 −1 0 −1 0

0 −1 0 0 0 −1 0 0 −1 1 1 0 0 0 0 −1 0 0 0 0 0 0 0 1 1 0 −1 −1 1 0 0 0 −1 0 1 0 −1 0 0 0 0 1 0 0 1

0 0 0 1 1 0 0 −1 0 0 0 −1 −1 0 0 0 0 0 0 0 0 1 0 0 −1 −1 0 0 0 −1 0 −1 1 0 1 1 −1 1 1 0 0 0 0 0 0

1 −1 1 0 0 0 0 0 1 0 −1 −1 0 −1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 −1 0 1 0 0 −1 0 1 −1 1

9.752 9.798 6.760 8.919 9.528 10.018 9.178 6.683 11.369 5.428 3.568 5.515 5.970 7.458 7.049 11.337 6.362 8.001 8.126 7.457 9.222 8.729 8.030 5.302 4.109 4.577 7.568 12.263 5.468 6.443 7.068 7.010 11.408 7.256 5.548 7.262 8.512 8.883 6.807 6.006 6.836 4.007 7.860 5.031 5.366

0.799 0.922 0.818 0.810 0.745 0.978 0.908 1.010 0.937 0.773 0.763 0.996 1.022 0.984 0.907 0.889 0.832 0.889 1.009 0.948 0.883 0.929 0.912 0.886 0.947 0.998 0.877 1.018 0.631 1.057 0.967 0.957 0.950 0.937 0.552 0.853 1.019 0.849 0.841 0.909 1.019 0.826 0.946 0.901 0.822

1.035 1.809 1.423 1.568 0.642 2.579 1.761 2.404 1.540 0.924 0.173 2.537 3.532 1.916 1.755 1.293 1.192 1.971 2.555 2.039 2.355 1.686 2.044 1.909 1.672 2.175 1.408 2.704 0.536 2.729 1.920 1.758 1.201 2.405 0.353 0.775 2.364 1.268 1.094 2.830 3.107 0.896 2.301 1.807 1.159

3.2. Specific Energy Consumption. Test results of specific energy consumption are shown in Table 2. Variance analysis and regression analysis show that a quadratic model fit the experimental data well. With significant terms, the regression equation is expressed as eq 5. The multiple correlation coefficient (R) equals 0.9818, which suggests that this model can provide good predictions.22 The F test indicates that the model is highly statistically significant (p < 0.0001). The lack of fit test shows that the model fits well with the experimental data (p = 0.9183)

E = 7.55 − 0.41Z1 + 1.24Z 2 − 2.72Z3 + 1.14Z4 + 0.86Z5 + 0.29Z1Z3 − 0.42Z1Z5 − 0.82Z 2Z3 − 0.36Z3Z4 + 0.39Z12 − 0.44Z 2 2 − 0.30Z4 2

(5)

where E is the specific energy consumption and Zj (j = 1, 2, ..., 5) is the code of the temperature, compression pressure, moisture content, wheat straw percentage, and particle size, respectively. Considering the interaction between the factors, effects of each factor on specific energy consumption are analyzed on the basis C


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Energy & Fuels

Figure 2. Test device.

Figure 4. Samples of the pellets made in this experiment.

where CE11 = −0.41 − 0.42Z5 + 0.29Z3, CE21 = 1.24 − 0.82Z3, CE31 = −2.72 + 0.29Z1 − 0.82Z2 − 0.36Z4, CE41 = 1.14 − 0.36Z3, CE51 = 0.86 − 0.42Z1, and CE12, CE22, CE32, CE42, and CE52 are integration constants for each sub-equation, respectively. Each CEji (j = 1, 2, ..., 5; i = 1 and 2) is a polynomial consisting of Zk (k = 1, 2, ..., 5; k ≠ j). As a result, CEji can be regarded as dynamic constants in each sub-equation. With the abscissa of Zj, the ordinate of CEj1, the specific energy consumption is plotted in Figure 5. As shown in Figure 5a, when CE11 reached the maximum (corresponding to the smallest particle and largest moisture content), specific energy consumption decreased first and then increased with the increase of the temperature, and when CE11 reached the minimum (corresponding to the largest particle and smallest moisture content), specific energy consumption decreased with the increase of the temperature. For the rest of the factors (panels b−e of Figure 5), specific energy consumption increased with the increase of the compression pressure,23 wheat straw percentage, and particle size22,24 and decreased with the increase of the moisture content. The interaction only affected the rate at which the specific energy consumption varied with each factor. 3.3. Density. Test results of the pellet density are shown in Table 2. With significant terms, the regression equation is expressed as eq 8. The multiple correlation coefficient (R) equals 0.9017, which suggests that the model can provide good predictions. The F test indicates that the model is highly statistically significant (p < 0.0001). The lack of fit test shows that the model fits well with the experimental data (p = 0.3063)

Figure 3. Details of the self-designed single pellet unit.

of eq 5. The partial derivative of specific energy consumption with respect to each Zj (j = 1, 2, ..., 5) reads ⎧ ∂E ⎪ ⎪ ∂Z1 ⎪ ∂E ⎪ ⎪ ∂Z 2 ⎪ ⎪ ∂E ⎨ ⎪ ∂Z3 ⎪ ⎪ ∂E ⎪ ∂Z4 ⎪ ⎪ ∂E ⎪ ∂Z ⎩ 5

= 0.78Z1 + ( −0.41 − 0.42Z5 + 0.29Z3) = −0.88Z 2 + (1.24 − 0.82Z3) = ( −2.72 + 0.29Z1 − 0.82Z 2 − 0.36Z4) = −0.60Z4 + (1.14 − 0.36Z3) = (0.86 − 0.42Z1) (6)

ρ = 0.92 + 0.059Z1 + 0.028Z 2 − 0.087Z3 − 0.092Z4

On the basis of eq 6, the equation of specific energy consumption is rewritten as ⎧ E = 0.39Z 2 + C Z + C 1 E11 1 E12 ⎪ 1 ⎪ E = −0.44Z 2 + C Z + C 2 2 E 21 2 E 22 ⎪ ⎪ ⎨ E3 = CE31Z3 + CE32 ⎪ ⎪ E4 = −0.30Z4 2 + CE 41Z1 + CE 42 ⎪ ⎪E = C Z + C ⎩ 5 E 51 5 E 52

− 0.023Z5 + 0.042Z1Z3 + 0.043Z1Z4 − 0.048Z 2Z3 − 0.081Z3Z4 − 0.057Z32

(8)

where ρ is the pellet density and Zj (j = 1, 2, ..., 5) is the code of the temperature, compression force, moisture content, wheat straw percentage, and particle size, respectively. Considering the interaction between the factors, effects of each factor on the pellet density are analyzed on the basis of eq 8. The partial derivative of the pellet density with respect to each Zj (j = 1, 2, ..., 5) reads

(7) D


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Energy & Fuels

Figure 5. Effects of each factor on the specific energy consumption. ⎧ ∂ρ ⎪ ⎪ ∂Z1 ⎪ ∂ρ ⎪ ⎪ ∂Z 2 ⎪ ∂ρ ⎪ ⎪ ⎨ ∂Z3 ⎪ ⎪ ⎪ ∂ρ ⎪ ⎪ ∂Z4 ⎪ ⎪ ∂ρ ⎪ ∂Z ⎩ 5

where Cρ11 = 0.059 + 0.042Z3 + 0.043Z4, Cρ21 = 0.028 − 0.048Z3, Cρ31 = −0.087 + 0.042Z1 − 0.048Z2 + 0.081Z4, Cρ41 = −0.092 + 0.043Z1 − 0.081Z3, Cρ51 = −0.023, and Cρ12, Cρ22, Cρ32, Cρ42, and Cρ52 are integration constants for each sub-equation, respectively. Each Cρji (j = 1, 2, ..., 5; i = 1 and 2) is a polynomial consisting of Zk (k = 1, 2, ..., 5; k ≠ j). As a result, Cρji can be regarded as dynamic constants in each sub-equation. With the abscissa of Zj, the ordinate of Cρj1, the pellet density is plotted in Figure 6. As shown in Figure 6a, a higher temperature resulted in a higher pellet density,25 when Cρ11 reached the maximum (corresponding to the highest moisture content and wheat straw percentage), but the temperature had few effects on the pellet density when Cρ11 reached the minimum. Compression pressure had similar effects on pellet density (Figure 6b). For the highest Cρ21 (corresponding to the highest wheat straw percentage), the pellet density increased with the increase of the compression pressure; however, when Cρ11 reached the minimum, the pellet density did not change significantly with the compression pressure.25,26 As a result, for wheat straw pellets, the temperature

= (0.042Z3 + 0.043Z4 + 0.059) = (0.028 − 0.048Z3) = − 0.114Z3 + (− 0.087 + 0.042Z1 − 0.048Z 2 + 0.081Z4) = (− 0.092 + 0.043Z1 − 0.081Z3) = (− 0.023)

(9)

On the basis of eq 9, the equation of the pellet density is rewritten as ⎧ ρ1 = Cρ11Z1 + Cρ12 ⎪ ⎪ ρ2 = Cρ21Z 2 + Cρ22 ⎪ ⎪ ⎨ ρ3 = 0.057Z32 + Cρ31Z3 + Cρ32 ⎪ ⎪ ρ4 = Cρ41Z1 + Cρ42 ⎪ ⎪ ρ = Cρ51Z5 + Cρ52 ⎩ 5

(10) E


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Figure 6. Effects of each factor on the pellet density.

3.4. Compressive Strength. Test results of the pellet compressive strength are shown in Table 2. With significant terms, the regression equation is expressed as eq 11. The multiple correlation coefficient (R) equals 0.9017, which suggests that the model can provide good predictions. The F test indicates that the model is highly statistically significant (p < 0.0001). The lack of fit test shows that the model fits well with the experimental data (p = 0.3063)

has more of an effect on the pellet density compared to the compression pressure. However, it is just the opposite for rice straw pellets. As shown in Figure 6c, the pellet density increased first and then decreased with the increase of the moisture content. There was a maximum when the moisture content was within 5 and 15%.25−27 The specific location of the maximum was determined by the interactions between the factors. As for the wheat straw percentage, it interacted with the temperature and compression pressure (Figure 6d). For the largest Cρ41 (corresponding to the highest temperature and the lowest moisture content), the wheat straw percentage had a minor effect on the pellet density, and for the lowest Cρ41 (corresponding to the lowest temperature and the highest moisture content), the pellet density decreased with the increase of the wheat straw percentage. Different biomass materials have different pelletizing properties,28 but effects of the raw material types can be weakened by adjusting the ranges of technological parameters. The particle size had a minor effect on the pellet density.28 There were no significant interactions between the particle size and the other factors, and pellet density decreased slightly with the increase of the particle size (Figure 6e).

σ = 2.03 + 0.62Z1 + 0.23Z 2 − 0.45Z3 − 0.66Z4 − 0.06Z5 − 0.21Z1Z 2 − 0.32Z 2Z3 + 0.21Z 2Z5 + 0.31Z3Z5 + 0.32Z4Z5 + 0.14Z12 − 0.57Z32 − 0.31Z4 2 − 0.22Z52

(11)

where σ is the compressive strength and Zj (j = 1, 2, ..., 5) is the code of the temperature, compression force, moisture content, wheat straw percentage, and particle size, respectively. Considering the interaction between the factors, effects of each factor on the pellet compressive strength are analyzed on the basis of eq 11. The partial derivative of the pellet compressive strength with respect to each Zj (j = 1, 2, ..., 5) reads F


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Energy & Fuels ⎧ ∂σ ⎪ ⎪ ∂Z1 ⎪ ∂σ ⎪ ⎪ ∂Z 2 ⎪ ⎪ ∂σ ⎪ ∂Z3 ⎨ ⎪ ⎪ ⎪ ∂σ ⎪ ∂Z4 ⎪ ⎪ ∂σ ⎪ ∂Z ⎪ 5 ⎩

wheat straw percentage) but a higher particle size resulted in a lower compressive strength when Cσ51 reached the smallest (corresponding to the lowest temperature, moisture content, and wheat straw percentage). There was a series of the temperature, moisture content, and wheat straw percentage, which could make Cσ51 close to 0. At this time, the compression pressure reached the maximum when the level of the particle size is near 0. 3.5. Optimization. On the basis of the analysis above, optimal conditions for the pelletizing process presented in this study were obtained with the Design Expert software. There were three primary restrictions, including the lowest specific energy consumption, the highest density, and the highest compressive strength. In addition, a lower temperature was set as the secondary restriction to reduce the additional energy consumption. Significant values of the four restrictions were changed 4 times in the software to make one of the restrictions more important than the others for each time, and four conditions were obtained finally. As shown in Table 3, the optimal temperature and moisture content are in the vicinity of the 0 level and the optimal compression pressure, wheat straw percentage, and particle size are in the −1 level. Experiments with a combination of these levels were carried out to verify the optimization results. The experiment was duplicated 5 times. Results showed that the specific energy consumption varied from 3.628 to 3.802 J/g, the density varied from 0.995 to 1.010 g/cm3, and the compressive strength varied from 2.558 to 2.834 MPa. Results of this experiment were in accordance with the optimization results. 3.6. Discussion. An approach of mixing different types of crop straw to achieve better pelletizing properties is proposed for agricultural countries or regions in this study. In comparison to the methods of adding woody or fossil additives, this approach can make full use of the crop straw resource in the region without any extra costs. However, this approach cannot improve the product heating value, which is available by adding woody or fossil additives.5,13,14 Some researchers have proposed other methods to improve the biomass densification process, such as torrefaction,4,24 hydrothermal carbonization,32 and biological pretreatment.33 These methods can improve the densification process but focus more on the increase of the product heating value. Besides, additional devices, techniques, and time are included in these methods, and therefore, more costs are needed in comparison to the approach in this study. Every approach has its advantages and disadvantages. When biological pretreatment is taken as an example, it can deal with large sized materials (50−52.8 mm) with high moisture content (70%) but needs 21−35 days for the pretreatment.33 A combination of several approaches based on an overall consideration of costs and profits is welcome.

= 0.28Z1 + (0.62 − 0.21Z 2) = (0.23 − 0.21Z1 − 0.32Z3 + 0.21Z5) = −1.14Z3 + ( −0.45 − 0.32Z 2 + 0.31Z5) = −0.26Z4 + ( −0.66 + 0.32Z5) = −0.44Z5 + ( −0.06 + 0.21Z 2 + 0.31Z3 + 0.32Z4)

(12)

On the basis of eq 12, the equation of the pellet compressive strength is rewritten as ⎧ σ = 0.14Z 2 + C Z + C 1 σ11 1 σ12 ⎪ 1 ⎪ σ2 = Cσ 21Z 2 + Cσ 22 ⎪ ⎪ ⎨ σ3 = −0.57Z32 + Cσ 31Z3 + Cσ 32 ⎪ ⎪ σ4 = −0.13Z4 2 + Cσ 41Z4 + Cσ 42 ⎪ ⎪ σ = −0.22Z 2 + C Z + C ⎩ 5 5 σ 51 5 σ 52

(13)

where Cσ11 = 0.62 − 0.21Z2, Cσ21 = 0.23 − 0.21Z1 − 0.32Z3 + 0.21Z5, Cσ31 = −0.45 − 0.32Z2 + 0.31Z5, Cσ41 = −0.66 + 0.32Z5, Cσ51 = −0.06 + 0.21Z2 + 0.31Z3 + 0.32Z4, and Cσ12, Cσ22, Cσ32, Cσ42, and Cσ52 are integration constants for each sub-equation, respectively. Each Cσji (j = 1, 2, ..., 5; i = 1 and 2) is a polynomial consisting of Zk (k = 1, 2, ..., 5; k ≠ j). As a result, Cσji can be regarded as dynamic constants in each sub-equation. With the abscissa of Zj, the ordinate of Cσj1, the pellet compressive strength is plotted in Figure 7. The pellet compressive strength increased with the increase of the temperature25 (Figure 7a) and decreased with the increase of the wheat straw percentage (Figure 7d). As for the effect of the compression pressure, it was affected a lot by the interactions (Figure 7b). The compressive strength increased with the increase of the compression pressure when Cσ21 reached the maximum (corresponding to the lowest temperature and moisture content and the largest particle size) and decreased with the increase of the compression pressure when Cσ21 reached the minimum (corresponding to the highest temperature and moisture content and the smallest particle size). There was a series of the temperature, moisture content, and particle size, which could make Cσ21 close to 0. At this time, the compression pressure had few effects on the pellet compressive strength. As shown in Figure 7c, the compressive strength increased first and then decreased with the increase of the moisture content and reached the maximum when the moisture content was within 5− 15%.29−31 The specific level of the moisture content corresponding to the maximum strength was affected by the compression pressure and particle size. As shown in Figure 7e, a higher particle size resulted in a higher compressive strength when Cσ51 reached the largest (corresponding to the highest temperature, moisture content, and

4. CONCLUSION The five-factor Box−Behnken experimental design technique with the temperature (°C), compression pressure (MPa), moisture content (%), wheat straw percentage (%), and particle size (mm) as process parameters was used to predict specific energy consumption, pellet density, and compressive strength in the pelletizing process of wheat straw blending with rice straw. The effects of each factor on the responses were obtained. In general, pelletizing properties of rice straw are better than those of wheat straw. Mixing rice straw and wheat straw to make pellets can improve the pelletizing properties of wheat straw. For the experiments presented in this study, the optimal G


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Figure 7. Effects of each factor on the pellet compressive strength.

Table 3. Optimal Conditions factors

responses

F1 (°C)

F2 (MPa)

F3 (%)

F4 (%)

F5 (mm)

specific energy consumption (J/g)

density (g/cm3)

compressive strength (MPa)

1 2

101.71 101.07

20.00 20.00

15.05 15.04

0.00 0.00

0.29 0.29

3.568 3.569

1.008 1.007

2.758 2.730

3

94.60

20.03

15.20

0.00

0.29

3.567

1.003

2.464

4

93.51

20.00

15.24

0.00

0.29

3.568

1.002

2.421

■

temperature and moisture content are at the 0 level and the optimal compression pressure, wheat straw percentage, and particle size are at the −1 level. Interactions between the factors have to be considered in the optimization design of the biomass pelletizing process.

■

REFERENCES

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Yu Wang: 0000-0003-1482-0176 Notes

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Article

Energy & Fuels

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Pelletizing Properties of Wheat Straw Blending with Rice Straw

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