Chapter 6: Results Analysis and Discussion _____________________________________________________________________ Chapter Six: Results Analysis and Discussion Introduction This chapter discusses the results on the moisture effects on pure thermal model, evaluates the evaporation and moisture transport using porous model for spontaneous combustion of wood, and lastly analyses the results of oxygen chemisorption and the ignition temperature of wood chars. 6.1 Heat transfer using thermal model The computational model constructed as a pure thermal model in Section 4.3.2 using Fluent®6.3 provided the heat simulation in the solid slab. The revised analytical model as embodied by Equations (4.24) to (4.29) incorporating moisture-mediated terms, on the other hand, yielded data that contained the effects of moisture. These data were analysed alongside experimental data obtained from Cone Calorimeter for green and preburn wood. This section sought to analyse wood combustion from the point of a thermal problem but also explored the effect of moisture on piloted and spontaneous ignition via changes in thermophysical properties; surface temperatures were compared with that simulated using pure heat conduction model and those calculated by heat transfer analytical model allowing for changes in thermophysical terms. 135 Chapter 6: Results Analysis and Discussion _____________________________________________________________________ 6.1.1 Piloted ignition - surface temperatures in green wood Piloted ignition is defined as the initiation of flaming combustion in the presence of a pilot (Spearpoint and Quintiere 2001). Critical surface temperature criterion was chosen over other criteria such as mass loss rate to determine ignition for engineering analysis, since a number of researches has shown the viability of using critical surface temperature criterion (Thomas, Simms and Theobald 1959, Lawson and Simms 1952, Simms 1960, Simms 1963, Simms and Law 1967, Atreya 1983, Janssens 1991a). In Table 6.1, the measured surface temperatures at ignition for green wood, obtained from Cone Calorimeter, have been discussed in Chapter 4. This section discusses the use of revised analytical model where the effects of moisture on ignition temperature Tig are taken into account through the thermophysical terms. For green wood, the cooling modulus β , as defined in Equation (4.25) ranges from 0.194 to 4.11 (to significant figures) as shown in Table 6.1. The ignition temperature Tig is calculated using Equation (4.24) and tabulated as “calculated surface temperature” in Table 6.1. 136 Chapter 6: Results Analysis and Discussion _____________________________________________________________________ Table 6.1. Calculated surface temperature for green wood in piloted ignition Samples Incident heat flux qe′′ (kW/m2) Time to piloted ignition t (s) Cooling Modulus β = (h / k ) *(α t )1/2 (- ) Calculated surface temperature Tig (°C) Measured surface temperature Tig (°C) G1 G2 G3 G4 G5 G6 G7 G8 50 40 30 25 20 15 11 10 26 54 108 324 764 3222 7990 7554 0.194494 0.392996 0.543835 0.944199 1.452066 3.655498 3.928308 4.115363 287.4 250.1 370.7 (-957.681) (903.9584) 455.4 439.7 400.4 266.5 373.4 374.9 375.9 373.9 460.5 345.4 342.4 The calculated surface temperatures using revised analytical model according to Equations (4.24) and (4.29) were compared against the experimental surface temperatures in Table 6.1. For samples G6 to G8 where β values ranging from 3.65 to 4.11 i.e. β  , the analytical model calculated surface temperatures using Equation (4.24) yielded 455.4°C for sample G6 which is in good agreement with the measured temperature of 460ºC. Samples G7 and G8 showed a bigger variation between calculated (439.7°C and 400°C) and measured surface temperatures (345.4ºC and 342.4ºC). The exceedingly long heating time, which was more than two hours in G7 and G8, probably has caused changing thermal thickness, and hence deviation from thermally thick assumption. For samples G1 to G3 where β ranged from 0.194 to 0.543, i.e. β  , the cooling modulus was computed using the error function erf β as given in Equation (4.28) instead of complimentary error function erfcβ in Equation (4.27). In other words, the surface temperatures for samples G1 to G3 were calculated using Equation (4.29). Good values of surface temperatures were obtained: 266.5°C, 373.4°C and 374.9°C which were in reasonably good fit with the measured 137 Chapter 6: Results Analysis and Discussion _____________________________________________________________________ surface temperatures. For samples G4 and G5 where 0.944 ≤ β ≤ 1.45 , no sensible values of surface temperatures were obtained using either form of cooling modulus. This is because these values of β were either too small to be considered as  , and too close to unity to be taken as  , which probably explained why the mathematical treatment did not work. Consequently, these calculated data for samples G4 and G5 were treated as outliers. Surface temperatures at ignition were also simulated by considering the pure heat conduction model constructed in Section 4.3.2 using Fluent®6.3. The simulated surface temperatures were compared with the calculated surface temperatures using revised analytical model according to Equations (4.24) and (4.29) as well as the experimental surface temperatures in Table 6.2. The simulation produced the lowest surface temperatures at ignition at 300°C and the highest at 470°C. This simulated temperature range was consistent with results obtained from other heat conduction thermal models (Lawson and Simms 1952). These surface temperatures at ignition Tig simulated from pure heat conduction however were larger than the thermocouplemeasured values for green wood. At high heat fluxes≥ 20kW/m 2, these simulated surface temperatures Tig were, in average, one hundred degree Celsius larger in magnitude than the measured surface ignition temperatures Tig. 138 Chapter 6: Results Analysis and Discussion _____________________________________________________________________ Table 6.2. Comparison of surface temperatures for green wood in piloted ignition Samples Incident heat flux qe′′ (kW/m2) Time to piloted ignition t (s) Simulated surface temperature Tig (°C) Measured surface temperature Tig (°C) Calculated surface temperature Tig (°C) G1 G2 G3 G4 G5 G6 G7 G8 50 40 30 25 20 15 11 10 26 54 108 324 764 3222 7990 7554 463.01 465.70 431.06 436.06 402.16 367.60 315.26 298.38 266.5 373.4 374.9 375.9 373.9 460.5 345.4 342.4 287.4 250.1 370.7 (-957.681) (903.9584) 455.4 439.7 400.4 In comparison, the calculated surface temperatures were in better agreement with the measured surface temperatures. For higher heat fluxes ≥ 30kW/m2, the calculated and the measured temperatures were both in the range of 260°C to 370°C. The simulated temperatures were consistently higher, showing temperatures ranging from 430°C to 465°C for incident heat fluxes ≥ 30kW/m2. Figure 6.1 illustrates the discrepancy in surface temperatures obtained from the three different methods, with large variations indicated from the longer error bars shown between the simulated and the calculated values, and relatively closer fit of surface temperatures between those calculated and measured data. 139 Chapter 6: Results Analysis and Discussion _____________________________________________________________________ Figure 6.1. Comparison of surface temperatures for green wood in piloted ignition Surface temperatures (°C) 500 400 300 200 Measured surface temperature θF (°C) Calculated surface temperature θF (°C) 100 Simulated surface temperature θF (°C) 50 40 30 25 20 15 11 10 Radiant heat flux (kW/m ) The comparison of surface temperatures obtained from the pure conduction computational model constructed in Section 4.3.2 using Fluent®6.3 and that of revised analytical model calculated using Equations (4.24) and (4.29) allowing for moisturemediated thermophysical terms suggests that moisture, inter alia, affects the heat transfer in oven-dry wood. Because both the computational and analytical models assumed wood to be inert, the closer fit of calculated values with the measured results strongly point towards the sole interplay of moisture effects on wood ignition, downplaying other factors such as endothermicity and pyrolysis in the scope of analysis. The effects of moisture on thermophysical properties produce a significantly better agreement of results between measured and calculated values, suggesting the importance of moisture in the heating of oven-dry green wood. 140 Chapter 6: Results Analysis and Discussion _____________________________________________________________________ 6.1.2 Piloted ignition - surface temperatures in preburn wood Preburn wood has been preheated in oven resulting in 52% mass loss. The partially charred wood has a smaller moisture content of 6.65% as compared to 13.83% of oven-dry green wood, and reduced specific heat capacity and thermal conductivity when compared to green wood, as shown in Chapter 4. Heat transfer in preburn wood could be increased by reduced thermal inertia because of the reduced density (Cuzzillo 1997); and that conductivity strongly correlates with reduced density and moisture content (Janssens 1991b). When solved using the revised analytical model according to Equations (4.24) and (4.29), samples with β  yielded feasible surface temperatures using erfcβ . For samples with β  , it was found that their surface temperatures at ignition were successfully solved by using erf β . Both calculated and measured surface temperatures were tabulated in Table 6.3. Table 6.3. Calculated surface temperature for preburn wood in piloted ignition Samples Incident heat flux qe′′ (kW/m2) Time to piloted ignition t (s) Cooling modulus β = (h / k ) *(α t )1/2 (- ) Calculated surface temperature Tig (°C) Measured surface temperature Tig (°C) P1 P2 P3 P4 P5 P6 50 40 30 20 15 12 33 56 142 372 1056 2594 0.254693 0.473433 0.789939 1.191651 1.955786 4.170185 526.5 555.7 300.0 328.0 479.3 357.1 429.6 436.7 437.5 366.2 400.7 421.9 141 Chapter 6: Results Analysis and Discussion _____________________________________________________________________ For preburn wood, the surface temperatures at ignition Tig obtained from simulations using pure heat conduction model and that calculated from analytical heat balance were very similar; the computed surface temperatures from both methods were in relatively good agreement with the experimental surface temperatures. The minimised discrepancy among the three types of surface temperatures could be seen from the reduced high-low bars indicated on Figure 6.2. Table 6.4 listed all the surface temperatures obtained from the three different methods for preburn wood. When compared to green wood, the preburn wood samples showed a good agreement between the calculated and simulated temperatures, and these two types of “theoretical” temperatures also agreed well with measured temperatures. The good agreement between the calculated temperatures with the measured temperatures suggests that piloted ignition problem for preburn wood is more strongly a thermal case, as compared to that of the oven-dry green wood. For partially charred wood, the reduced pyrolysable content, indicated by lower heat of release rates for fire modelling (Moghtaderi and Kennedy 1998, Chow and Han 2006), validates the underlying assumption of negligible chemical effects that is adopted in the formulation of a thermal model. In preburn wood, ignitability at a given heat flux is related to the thermal properties of the material, in particular the thermal inertia, kρc (Cuzzillo and Pagni 1999). The reduced kρc as a result of pre-burning produced higher surface ignition temperatures in preburn wood as compared to that of green wood. The same deduction is purported by Cuzzillo and Pagni (1999). 142 Chapter 6: Results Analysis and Discussion _____________________________________________________________________ Table 6.4. Comparison of surface temperatures for preburn wood in piloted ignition Samples Incident heat flux qe′′ (kW/m2) Time to piloted ignition t (s) Simulated surface temperature Tig (°C) Measured surface temperature Tig (°C) Calculated surface temperature Tig (°C) P1 P2 P3 P4 P5 P6 50 40 30 20 15 12 33 56 142 372 1056 2594 526.32 475.53 441.49 369.80 353.31 327.34 429.6 436.7 437.5 366.2 400.7 421.9 526.5 555.7 300.0 328.0 479.3 357.1 Figure 6.2. Comparison of surface temperatures for preburn wood in piloted ignition Surface temperatures (°C) 600 500 400 300 Measured surface temperature θF (°C) 200 Calculated surface temperature θF (°C) 100 Simulated surface temperature θF (°C) 50 40 30 20 15 12 Radiant heat flux (kW/m ) On the other hand, the good agreement between the simulated and the calculated surface temperatures in preburn wood re-instated the role of moisture in heat transfer, where the reduced moisture content in preburn wood simply minimised the impact of moisture on the thermophysical terms and hence the heat balance on preburn samples. 143 Chapter 6: Results Analysis and Discussion _____________________________________________________________________ 6.1.3 Spontaneous ignition - surface temperatures in green wood The spontaneous ignition of wood can also be calculated using the revised analytical model assuming a critical surface temperature criterion. Spontaneous ignition is defined as the initiation of flaming combustion without a pilot (Janssens 1991a). Only sustained ignition i.e. the initiation of flaming combustion that persists after the external heat source is removed, was considered in this analysis. Experimentally, spontaneous ignition to direct flaming was noted only at high incident heat fluxes of 50 kW/m2 and 40 kW/m2. Ignition at lower heat fluxes occurred via glowing ignition is not considered in this discussion. For green wood, two sustained flaming combustion were noted and the surface temperatures were found to be 448°C and 457°C respectively. These surface temperatures at ignition Tig were much higher than that for green wood in piloted mode. The results suggested that the presence of moisture increased the surface temperature of ignition for green wood. For piloted ignition, ignition occurred more readily as pilot provided the energy to ignite the combustible-gas mixture. For spontaneous ignition, flaming occurred entirely upon the attainment of sufficient surface temperature (Martin 1964). It was interesting to see the interplay of moisture on ignition of green wood by comparing the two different ignition modes. For spontaneous ignition in green wood, given that the values of β  , the surface temperatures were therefore calculated using erf β . The calculation yielded surface temperatures of 558.2°C to 786.2°C, which were higher as compared to the surface temperatures of 448°C and 457°C measured at 50kWm-2 and 40kWm-2 respectively, 144 Chapter 6: Results and Analysis ________________________________________________________________________ 380mmHg partial pressure of oxygen (Teng et al 1999) and brown coal chars were examined at 760mmHg partial pressures of oxygen (Allardice 1966). Despite the different partial pressures of oxygen, these chars have remarkably similar values of a, except for brown coal char tested at elevated temperature of 155°C. The similar reactivity further endorsed the earlier research findings that the initial rate of a was well correlated with temperature but was independent of pressure. In other words, the changes in oxygen partial pressures did not significantly affect the rate of chemisorption as temperature does. This finding suggested the ambient temperature has a far more important and direct impact on chemisorption of cellulosic materials than its indirect impact on moisture variations which linked to fluctuations in oxygen partial pressure found in the interstitial atmosphere of substrate. Table 6.11: Comparison of Elovich constants for oxygen chemisorption on cellulosic chars and coal chars Type of chars Temperature (°C) a (mg/g min) b (mg/g) -1 Cellulosic char 139 104.45 0.038 a Resin char 150 99 0.50 Brown coal char 110 101 1.09 (1)b Brown coal char 155 292 1.01 (2)b a Resin char tested in Teng HH et al (1999) was derived from phenol-formaldehyde resins pyrolysed in a helium environment at 950°C for hours. b Brown coal chars used in Allardice’s work (1966) were obtained from Yallourn brown coal I-type briquette carbonised at 1000°C. 188 Chapter 6: Results and Analysis ________________________________________________________________________ 6.3.1.2 Activation energy and variation of chemisorption rates with oxygen uptake The parameter b derived from cellulosic chars in this study did not show a dependence on temperature. The activation energy may have not have a distributed range of values but a single value independent of surface coverage. Consider that activation energy can be expressed by the familiar Arrhenius equation in logarithmic form as ln = r ln A − E RT (6.5) where r is the reaction rate constant, A is the pre-exponential factor, E is the activation energy and R is the universal gas constant. Differentiating Equations (6.5) with respect to T gives d (ln r ) E = − d (1 T ) R (6.6) Recalling from Chapter 5, Section 5.1.1 where Equation (5.6) can be rearranged and expressed as E d (ln r ) d (b) = − c −q d (1/ T ) R d (1/ T ) (6.7) Thus, equating Equations (6.6) and (6.7) yields 189 Chapter 6: Results and Analysis ________________________________________________________________________ − E E d (b) = − c −q R R d (1 T ) (6.8) For b which is independent of adsorption temperature, then q d (b) d (1 T ) = . Therefore, = E / R E= Ec . The activation energy has a single value independent of surface c / R coverage. To evaluate the activation energy, the values of a at different temperatures were plotted on an Arrhenius scale (see Figure 6.24); the slope of the plot yielded a single activation energy of 16 kcal/mol. Figure 6.24: Arrhenius plot of of Log a on Arrhenius scale of Kapur char pyrolysed in nitrogen in air chemisorption 190 Chapter 6: Results and Analysis ________________________________________________________________________ This apparent activation energy of 16 kcal/mol was in good agreement with the range of activation energies found for cellulosic chars, of which 12.6kcal/mol was the lowest limit of the reported range (Bradbury and Shafizadeh 1980b). The activation energy of 16 kcal/mol was higher than the range of 3.1 to 12.4 kcal/mol of activation energies found for the chemisorption on an ultraclean carbon (Bansal, Vastola and Walker 1970). The apparent activation energy in wood chars therefore showed that there were different types of active sites responsible for chemisorption in wood chars and that of the more mature and graphitic carbon chars. Hshieh F.Y., et al (1989) has suggested that these low activation energies of this order indicated that the chemisorption process in both the compact solid wood char and the comparatively fibrous cellulose chars was a diffusion controlled process. However, diffusion control phenomenon rarely influenced the kinetics of combustion at temperatures below 650°C (Teng and Hsieh 1999), much less on the even slower chemisorption process at the low temperatures investigated here. The more probable reason for the low activation energies for zero-order gas-solid reaction in which desorption was negligible is due to rate control by surface re-arrangement of adsorbed species (Walker, Ruskinko and Austin 1959), just as the case of wood chars examined here. 191 Chapter 6: Results and Analysis ________________________________________________________________________ 6.3.2 Chemisorption for samples preheated in air For samples preheated in air, there was no immediate weight gain due to surface adsorption of gases. The already formation of surface oxides during the preheating treatment at 140°C and 150°C for 50 days and 30 days respectively in air possibly blocked the surface for gases adsorption. Chemisorption however occurred after some periods of isothermal heating in TGA [Figures 6.25 and 6.26] – the occurrence of chemisorption proved that continued heating removed the surface oxides, and re-exposed surface active sites for further chemisorption. Since the desorption of surface oxides was temperature-dependent, the chemisorption was more marked in both air preheated samples of K150 and K140 at 109°C, as compared to the lower chemisorption temperature of 74°C. For chemisorption temperature at 109°C, K150 showed a remarkable weight gain due to gases adsorption, and ensued by a precipitous weight loss thereafter, indicating ignition. For K140, chemisorption occurred after some period of isothermal heating, leading to rapid gasification at the end of the chemisorption run. The weight variations of K140 and K150 were shown in Figures 6.25(a) and 6.25(b). The same pattern was also observed at chemisorption runs conducted at 74°C, albeit to a less magnitude in both the mass gain and the duration for which it occurred, as seen in the weight variations graphs in Figure 6.26(a) and 6.26(b). 192 Chapter 6: Results and Analysis ________________________________________________________________________ Figure 6.25: Weight change in air-preheated wood chars at chemisorption temperature of 109°C for (a) wood char heated at 150°C for 30days; (b) wood char heated at 140°C for 50days Figure 6.26: Weight change in air-preheated wood chars at chemisorption temperature of 74°C for (c) wood char heated at 150°C for 30days; (d) wood char heated at 140°C for 50days 193 Chapter 6: Results and Analysis ________________________________________________________________________ There was no conclusive evidence in this study to predict when chemisorption might occur in air-preheated samples, and if ignition might take place at all, unlike inert-heated samples where chemisorption was immediate upon exposure to oxygen and in certain cases, the heat flux generated by the rapid initial oxygen chemisorption was sufficient to induc e ignition at low temperature. Nonetheless, this study provided a significant experimental evidence to suggest that air-preheated samples at temperatures as low as 140°C and 150°C for extended heating were capable of chemisorption, and they might lead to possible ignition at low temperature when the rate of heat generation exceeded the rate of heat loss. 6.3.3 Variation in functional groups using Fourier-transform Infra-red (FTIR) Spectroscopy The relationship between oxygen chemisorption and the chemisorption temperature (CST) has been discussed at length in foregoing sections. When the propensity of spontaneous ignition of low temperature wood char was concerned, it was an issue as how the heat treatment temperature may affect the subsequent chemisorption activity of these wood chars (Hshieh and Richards 1989a). This study used low heat treatment temperatures (HTT) not exceeding 200°C, unlike graphitic carbon involving HTT as high as 1000°C (Bansal, Vastola and Walker 1970, Waters, Squires and Laurendeau 1986, Suuberg, Wojtowicz and Calo 1989). It would be of interest the extent these low heat treatment temperatures have brought upon chemical changes in virgin wood, and how the chemical changes have enhanced propensity of self-heating in 194 Chapter 6: Results and Analysis ________________________________________________________________________ preheated wood chars, when the ignition temperature and pyrolysis kinetics were discussed in the next section. Fourier-transform Infra-red Spectroscopy (FTIR) was carried out for fresh wood (KF) and wood chars created at 140°C (K140), 150°C (K150) to elucidate the changes in the functional groups. From the elemental analysis (see Tables 5.1 to 5.4), fresh wood has an empirical formula of C3.9H6.5O2.9. Following heat treatment, K140 became C3.9H6.0O2.9 and K150 attained C3.9H5.8O2.9. The changes in elemental composition of carbon and hydrogen were minimal in air-preheated wood chars. Increasing aromaticity and increased fusion of aromatic rings have been associated with decreased reactivity in wood chars as the reactive sites in chars were maintained by the presence of more mobile aliphatic structures (Calemma, Vansa, Margarit and Girardi 1988). It would be too superficial to conclude just from elemental analysis that wood chars remained just as reactive because carbon ratio has not increased. FTIR spectra must be examined to expound chemical changes that might have not been detected by elemental analysis. Figure 6.27 shows the spectra of untreated wood and wood chars respectively. Wood chars created at 200°C (K200) were also analysed alongside K140 and K150. As shown in Figure 6.27, K140 has similar spectra pattern as KF. However, the intensities of some functional groups varied. In the absorbance spectra, the peak showed up at 2900 cm-1 was associated with aliphatic –CH2 groups. This peak was very clear for KF and K140, but diminished at K150 and was totally eliminated in treated sample K200. The disappearing of aliphatic –CH2 groups signified an increased aromatisation as charring temperature 195 Chapter 6: Results and Analysis ________________________________________________________________________ intensified (Shafizadeh and Sekiguchi 1983). Bands of medium intensities spanning between 550 cm-1 and 700 cm-1 weakened in K150 and disappeared in K200. In other words, the bands spanning from 550 cm-1 and 700 cm-1 were only observable in spectra of low temperature chars. Figure 6.27 Spectra of different wood samples: fresh wood (KF), wood char 140oC (K140) , wood char 150oC(K150) and wood char 200oC(K200) 1,3 3348 KF K140 K150 K200 1049 1,2 1,1 1,0 2930 Absorbance 0,9 1460 0,8 604 0,7 1736 0,6 0,5 0,4 0,3 0,2 0,1 0,0 4000 3500 3000 2500 2000 1500 1000 500 wavenumbers The absorption intensity of hydroxyl groups (bands at 3600-3200 cm-1) decreased dramatically when the samples were treated at higher temperature at both 150oC and 200oC. Higher heat treatment temperature caused dehydration and thermal degradation that contributed to this decrease in hydroxyl groups. The decrease in the intensity of the 196 Chapter 6: Results and Analysis ________________________________________________________________________ OH stretching band at 3600-3200 cm-1 was also accompanied by a decrease in the H2O deformation band near 1600 cm-1 further endorsed the proposition. In contrary, the aromatic stretching band near 1600 cm-1 increased. However, Hshieh and Richards (1991) pointed out that as the intensity of the aromatic stretching band could be influence greatly by the existence of oxygen in chars, and also by the size of fused ring structures, it could not be concluded at this point that carbon aromaticity has been enhanced. There has always been an issue of the degree of heat treatment temperatures that might create just the right pyrophoric wood chars. Wood chars were therefore created at 200°C (K200) to examine changes in aromaticity. The various bands between 1300 and 1030 cm-1 contain carboxylic acids, esters, alcohol, anhydrides were commonly found in cellulose and wood. In K140 and K150 spectra, these bands were still clear but have weaker intensities. Interestingly, there was a shift of the peaks from 1100-1030 cm-1 to 1300-1200 cm -1 in K200 sample’s spectra. This might be due to the formation of the stable char corresponded with complete degradation of the glycosyl units as shown by the virtual disappearance of the glycosidic band at 900-1200 cm-1 in addition to the predominance of COC group at 1250 cm-1. Besides, the carbonyl C=O absorption between 1800-1700 cm-1 slightly increased in K200 sample. The aromatic bands at 1600 cm-1 attributed to the absorption of the carbon-carbon double bond decreased in all wood char samples. In general, the spectra obtained with the present study show that heating at 200oC in air for extended hours led to surface oxides formation judging from the existence of ether and carbonyl group absorption bands at 1250 and 1700 cm-1, respectively. 197 Chapter 6: Results and Analysis ________________________________________________________________________ The FTIR therefore demonstrated the progressive development of C=O groups and the disappearance of the carbohydrate hydroxyl groups on heating cellulose at 200°C in air for several hours and days. Furthermore, the decline in the intensity of the -CH2 deformation band suggested that the primary hydroxyl group was preferentially oxidized. The changes in functional groups showed that HTT at 200°C rendered wood chars less reactive than those created at 140°C and 150°C. An earlier study conducted by US Forest Products Laboratory has selected HTT at 107°C, 120°C, 140°C and 150°C for heating of wood sticks (3mm x 6mm) for 16 days to 1050 days (McNaughton 1945). However, in the study, only the loss of weight and transverse shrinkage were measured to examine the charring temperatures on ignition. This study provided a chemical explanation to the choice of heat treatment temperatures. 6.3.3.1 Concluding remarks on Fourier-transform Infra-red (FTIR) Spectroscopy The low temperature chars prepared at 140°C and 150°C for woods in general have very similar chemical composition with the fresh wood samples, except that these char samples seemed to possess higher concentration of carbonyl groups at around 1700 cm-1. There were obvious changes in functional groups in as heat treatment temperature increased, particularly noted in K200 sample. On the whole, K200 have oxide formation of ether linkages, carbonyl with absorption bands at 1250 and 1700 cm-1. Besides, the aliphatic groups at 2900 cm-1 fully disappeared. This study showed that the longer the duration of heating, more hydroxyl groups (3600-3300 cm-1) can be eliminated. In other words, the longer the period of heat treatment temperature, the stronger was the oxidation 198 Chapter 6: Results and Analysis ________________________________________________________________________ of hydroxyl groups to form carbonyl and carboxyl compositions. The FTIR analysis strongly suggested that 200°C was the upper limit for creating pyrophoric wood chars for extended period in ambience. The findings granted a chemical justification to the range of heat treatment temperatures for further research investigation of preheated wood chars. 6.3.4 Ignition temperature and pyrolysis kinetics Chemisorption was noted to occur in both air-preheated and nitrogen-preheated wood chars. The fact that chemisorption is exothermic could lead to ignition at a lower than expected temperature, since thermal runaway occurred when the heat generated by chemisorption in the sample exceeded heat loss. Lower ignition temperatures have been found for the long-term air-preheated wood char samples in this study [Table 6.12]. The air-preheated wood chars have reported lower ignition temperatures in the range of 414.9°C to 421°C, as compared to the untreated fresh wood powder of 430°C found in Hshieh F.Y. et al work (1989b). Table 6.12: Effect of long-term preheating in air of wood on the ignition temperature in air Sample Preheating time (days) 30 50 30 Weight loss (%)a Ignition temperature (°C)b 414.9 418.1 421.0 K150 20.5 K140 21.0 CW150c a Air-dry basis b Heat from 25°C at 5°C/min in air c Cotton wood disc preheated in air -data taken from Hshieh F.Y. et al (1989) 199 Chapter 6: Results and Analysis ________________________________________________________________________ The impact of a lower ignition temperature on the pyrolysis kinetics on wood chars however remained unknown. There was a question whether lower ignition temperature means a change in the pyrolysis kinetics of wood chars, and hence an alteration in the pyrolysis pathways. Alternatively, it was also a question if the different ignition temperatures between subsequent extension of preheating duration and/or change in heat treatment temperature were kinetically significant, thereby providing a clue as to how chemisorption has affected the combustion behaviour of solid. The Semenov model of thermal ignition was applied to investigate the results where R (T ) S h exp [ E / RT ] = e E V σ QA (6.9) Assuming S,V,σ and Q dis not differ much between samples, as porosity did not increase significantly for heat treatment below 500°C (Bradbury and Shafizadeh 1980c), and h remained unchanged between experiments, applying Equation (6.9) between two samples of two different ignition temperatures could be re-written as (T1 ) E1 A1 exp [ E1 / RT1 ] (T ) = E2 A2 exp [ E2 / RT2 ] (6.10) Equation (6.10) was linearised by applying natural logarithm to both sides, where E1 (T ) / RT + ln 1 E1 A1 = E2 / RT2 (T ) + ln E2 A2 (6.11) 200 Chapter 6: Results and Analysis ________________________________________________________________________ Each side of the Equation (6.11) represented a linear graph. Given that both graphs were identical, equating the constants terms and re-arranging yielded E1 A1 E2 A2 T  =   T2  (6.12) To examine if the effect of heat treatment and/or preheating duration which lowered the ignition temperature affects was kinetically significant, Equation (6.12) was applied to analyse the temperature difference in ignition temperatures [Table 6.12] observed between K140 preheated for 50 days and K150 preheated for 30 days. By substituting T1 = 414.9°C and T2 = 418.1°C into Equation (6.12), it was found that E1A1 = 0.984 E2A2. The analysis showed that the different ignition temperatures, which arised from a combination of different preheating duration and heat treatment temperature were almost kinetically comparable. In another case where ignition temperature changed as a consequence of preheating duration as found in Hshieh and Richards’ work (1989b), the analysis showed for T1 = 430°C and T2 = 441°C for wood discs preheated in air between and hours, E1A1 =0.969E2A2. In this case, neither was the effect of preheating duration kinetically significant. Equation (6.12) also indicated the scope of variation of E and A between the two samples. Using the case of a temperature difference as varied as 11°C, the permitted ratio between two groups of A and E is 0.969. Non-conformance firstly indicated that the pair of A and E were significantly different in kinetics, and secondly the resulting change in A and E implied a changing kinetics pathway altogether, depending on the value of the parameters. Tinney (1965) has suggested that the reasonable estimate for the pyrolysis of wood in the 201 Chapter 6: Results and Analysis ________________________________________________________________________ temperature interval of 220°C to 400°C is E = 30kcal/mol, and A spanned the range of 6E07 s-1- 7E08 s-1. Using E2 = 33.26 kcal/mol and A2 =7.738E07 s-1 found for Balau hardwood in temperature interval of 210°C to 300°C from S.M. Lim’s work (2002), and assuming E1 = 30 kcal/mol, numerical analysis showed that for the ratio of 0.969, A1 works out to be 8.31E07 s-1. This value of A conformed to the span suggested by Tinney (1965). Therefore, with the change in temperature variation as much as 11°C, the activation energies ranged between 30 kcal/mol to 33.26 kcal/mol, the values of which were typical for dehydration pathway. A switch in pathway to depolymerisation would require a leap in E to the range of 37-43 kcal/mol with A in the span of 4E08 s-1- 2E09 s-1. The numerical analysis illustrated that chemisorption may lower the ignition temperatures of wood due to exothermicity of the reaction, but for the reported range of temperature variation, chemisorption did not seem to impact on the pyrolysis kinetics. 6.3.4.1 Concluding remarks for oxygen chemisorption The results of Elovich kinetics parameters strongly indicated that low temperature wood chars possessed altogether a different type of active sites responsible for chemisorption activities, which were remarkably different from the more carbonized and mature graphitic carbon polymers. In addition, chemisorption also occurred in long-term airpreheated wood chars. As a result, lower ignition temperatures have been subsequently noted. The experiments indicated that wood chars were reactive, especially when preheated at temperatures below 200°C. However, the observed range of lowered ignition temperatures was not shown to be kinetically significant on wood pyrolysis, neither did 202 Chapter 6: Results and Analysis ________________________________________________________________________ the change in ignition temperature suggest a switch in pyrolysis pathway in wood decomposition. The schematic analysis of propensity of wood chars from chemical viewpoint and the findings were summarised below. PROPENSITY FOR SELF-IGNITION PREHEATED WOOD CHARS ELEMENTAL ANALYSIS CHEMISORPTION EXPERIMENTS FTIR EXPERIMENTS PROXIMATE ANALYSIS OXYGEN ADSORPTION • INERT WOOD CHARS • AIR-PREHEATED WOOD CHARS CHARACTERISATION OF FUNCTIONAL GROUPS PROPENSITY FOR SELF-IGNITION DID IGNITION TEMPERATURE REDUCE? A LOWER IGNITION TEMPERATURE  No indication of increase in aromaticity  Inert chars showed similar reactivity as coals  air-preheated wood chars chemisorbed  Different reactive sites from coal  primary –CH2 was preferentially oxidized  Higher heating led to thermal annealing  mobile aliphatic groups responsible for char reactivity SEMENOV MODEL NO CHANGE IN PYROLYSIS PATHWAYS Figure 6.28: Schematic analysis and findings on propensity of self-ignition in wood chars 203 [...]... validity of the IDP model 164 Chapter 6: Results Analysis and Discussion _ Figure 6. 10: Velocity and temperature contours on the mid-plane (z = 0mm) for longitudinal flow using IDP Model Velocity contour Temperature contour Figure 6. 11: Velocity and temperature contours on z = 20mm from the mid-plane for longitudinal flow using IDP Model Velocity contour Temperature contour... Temperature contour Figure 6. 12: Velocity and temperature contours near wall from the mid-plane for longitudinal flow using IDP Model Velocity contour Temperature contour 165 Chapter 6: Results and Analysis 6. 2.3 Velocity and temperature contours of moisture movement in Extended Drying Phase (EDP) Model To examine the velocity and temperature contours of moisture movement... Velocity contour Temperature contour Figure 6. 15: Velocity and temperature contours near wall from mid-plane for longitudinal flow using EDP Model Velocity contour Temperature contour 168 Chapter 6: Results and Analysis 6. 2.4 Progression of self -heating in porous wood slab This section discusses the development of temperature field and how the influence of induced water... Figure 6. 5 shows the linear regression  ′′  ′′ of qe / tig vs qe Table 6. 7: Ignition data of green wood Density ρ (kg/m3) ′ Incident heat flux q e′ 2 (kW/m ) Time to flaming ignition tig (hr:min:s) 64 4 50 62 4 40 64 0 30 64 0 25 63 6 20 62 4 15 708 11 65 2 10* 62 8 9 66 4 8 * Only one out of three samples tested at 10kW/m2 ignited after than 2 hours a,b No ignition was observed up to 6 hours duration 0:0: 26. .. wood slab that would be discussed in the next section 167 Chapter 6: Results and Analysis Figure 6. 13: Velocity and temperature contours on the mid-plane (z = 0mm) for longitudinal flow using EDP Model Velocity contour Temperature contour Figure 6. 14: Velocity and temperature contours on z = 20mm from mid-plane for longitudinal flow using EDP Model Velocity contour... spontaneous combustion of wood was studied using wood cube of critical size exposed to low- temperature, long- term heating in an isothermal oven as described in Chapter 4 The temperature field and progression of self -heating was tracked by thermocouples The modified Darcy’s law porous model developed in Chapter 3, which was formulated with surface evaporation and that of an internal evaporation, was used to. .. period of wood drying where the temperature in the material was almost uniform, the temperature fields in the wood cube would not be uniform because of more pronounced combined moisture convection The temperature profiles measured in wood cube, as shown in Figures 6. 16( a) and 6. 17(a) agreed with the simulations The lowest plot (t = 30mins) in both Figures 6. 16( b) and 6. 17(b) showed a 169 Chapter 6: Results... effect of the different treatments of evaporation in a drying model of wood The temperature profiles were shown in Figure 6. 9 The different numerical approach and treatment of evaporation generated very different temperature profiles in Figure 6. 9 Model 1 has a depressed curve while the temperature profiles of Model 2 and modified Darcy’s law Model were rather linear The linear temperature profiles of. .. high -temperature drying model which normally ignored the free water as it vaporises too quickly to allow any tangible impact Spontaneous combustion of wood was then considered within the framework of moisture migration and thermophysical properties of wood, of which experiments on wood cube heating were analysed for its thermal runaway behaviour An analysis of the progression of temperature profiles... progression of self -heating in 89mm wood cubes These wood cubes have been fitted with thermocouples to measure the temperature histories and were heated in an isothermal oven at 200°C until thermal runaway occurred, in order to study the influence of moisture movement and size effect on spontaneous ignition of wood The experiment set up was described in Chapter 4 6. 2.4.1 S temperature- distance curve When a wood . 463 .01 266 .5 287.4 G2 40 54 465 .70 373.4 250.1 G3 30 108 431. 06 374.9 370.7 G4 25 324 4 36. 06 375.9 (-957 .68 1) G5 20 764 402. 16 373.9 (903.9584) G6 15 3222 367 .60 460 .5. smaller moisture content of 6. 65% as compared to 13.83% of oven-dry green wood, and reduced specific heat capacity and thermal conductivity when compared to green wood, as shown in Chapter. 50 33 0.25 469 3 5 26. 5 429 .6 P2 40 56 0.473433 555.7 4 36. 7 P3 30 142 0.789939 300.0 437.5 P4 20 372 1.19 165 1 328.0 366 .2 P5 15 10 56 1.9557 86 479.3 400.7 P6 12 2594