Evaluation and application of pyrolysis kinetic model of Wucaiwan coal and Tulufan coal

doi:10.11949/0438-1157.20190441

Abstract

Abstract:

To clarify the differences in parameters selection of different pyrolysis models and evaluate the adaptability of different models to pyrolysis reaction, the segmented single scanning rate method, iso-conversion kinetic method and the 3-stage Gaussian distribution activation energy model (3-DAEM) were applied to analyze the thermogravimetric experimental data of two low-rank coal. The results show that the kinetic parameters obtained by single scanning rate method cannot reveal the pyrolysis reaction mechanism well. The iso-conversion kinetic method can better obtain the activation energy and pre-exponential factor distribution. The data simulated by 3-DAEM fits best with experimental data, and only one TGA curve is needed to obtain the kinetic parameters suitable for the TGA curve at other heating rates. According to the activation energy distribution, coal pyrolysis can be divided into three stages corresponding to the three classes of dominant chemical bonds.

Key words: coal, pyrolysis, thermogravimetry analysis, distributed activation energy, kinetic, model

摘要：

煤热解是煤热加工利用的基础反应，热解动力学模型有助于预测煤在热解过程中挥发分脱除规律，当前文献中已报道了多种热解动力学模型，厘清不同热解模型参数选择的差异，评估不同模型对煤种及热解反应适应性可为热解工艺设计提供参考。采用¹³C NMR核磁共振测量了五彩湾煤和吐鲁番煤的碳化学结构，并使用热重法测量了不同加热速率下的两种低阶煤失重曲线，结合分段式单一速率扫描法、等转化率法和3段式高斯分布活化能模型（3-DAEM）分析热重实验数据。结果表明单一速率扫描法得出的动力学参数难以准确揭示热解反应机理；等转化率法可以较好地得出热解活化能及指前因子分布图；将等转化率方法获得的指前因子赋值给分布活化能模型，可以避免分布活化能模型指前因子选择的盲目性；3-DAEM模型仅需要一条TGA曲线便可获得适用于整个加热速率的动力学参数，其预测结果与实验数据吻合最好，且模拟得出的活化能分布图很好地反映了煤热解三个阶段特征。

关键词: 煤, 热解, 热重分析, 分布活化能, 动力学, 模型

CLC Number:

TQ 530.2

Liping WEI,Guodong JIANG,Yukuan GU,Haipeng TENG. Evaluation and application of pyrolysis kinetic model of Wucaiwan coal and Tulufan coal[J]. CIESC Journal, 2019, 70(S2): 275-286.

魏利平,江国栋,古玉宽,滕海鹏. 五彩湾煤和吐鲁番煤热解动力学模型评估与应用[J]. 化工学报, 2019, 70(S2): 275-286.

Figures/Tables 15

Table 1 Proximate and ultimate analyses of raw coals

Coal type	Proximate analysis/%				Ultimate analysis/%
Coal type	M_ad	A_ad	V_ad	FC_ad	C_daf	H_daf	O_daf	N_daf	S_daf
WCW	9.97	3.67	27.86	58.5	78.94	3.78	16.26	0.54	0.48
TLF	5.25	11.80	40.69	42.26	78.79	5.81	13.01	2.02	0.37

Fig.1 ?13C?NMR(CP/MAS) spectra of two coal samples

Fig.2 TG curves of coal samples during pyrolysis at different heating rates

Fig.3 DTG curves of coal samples during pyrolysis at different heating rates

Table 2 Pyrolysis characteristic values of two coal samples

Coal	$β / (℃ / m i n)$	$T 0 / K$	$T p / K$	$R ∞ / (% / m i n)$	$V f / %$
WCW	10	527.27	722.94	0.78	38.49
	20	542.15	736.09	1.47	37.57
	30	543.20	742.95	2.10	38.01
	50	546.86	777.05	3.74	35.98
TLF	10	457.18	714.67	3.48	41.49
	20	473.42	730.73	6.61	46.65
	30	499.54	734.35	10.01	45.58
	50	518.65	747.02	17.73	45.52

Table 2 Pyrolysis characteristic values of two coal samples

Coal	$β / (℃ / m i n)$	$T 0 / K$	$T p / K$	$R ∞ / (% / m i n)$	$V f / %$
WCW	10	527.27	722.94	0.78	38.49
	20	542.15	736.09	1.47	37.57
	30	543.20	742.95	2.10	38.01
	50	546.86	777.05	3.74	35.98
TLF	10	457.18	714.67	3.48	41.49
	20	473.42	730.73	6.61	46.65
	30	499.54	734.35	10.01	45.58
	50	518.65	747.02	17.73	45.52

Fig.4 α-T curves of coal samples during pyrolysis at different heating rates

Coal	T/K	Method	$E$ /( $k J / m o l$ )	$k$ / $s - 1$	$R 2$
WCW	543—560	C-R	297.0	$1.50 × 1016$	0.87
		Doyle	291.1	$7.91 × 1023$	0.88
		A-B-S-W	14.4	$3.45 × 10 - 3$	0.99
	560—740	C-R	55.0	$2.27 × 10 - 6$	0.99
		Doyle	62.5	142.49	0.99
		A-B-S-W	48.1	3.78	0.98
	>740	C-R	22.3	$2.98 × 10 - 8$	0.99
		Doyle	37.0	3.13	0.99
		A-B-S-W	30.5	0.13	0.76
TLF	473—500	C-R	168.1	$1.06 × 106$	0.78
		Doyle	148.5	$3.41 × 1011$	0.77
		A-B-S-W	13.3	$9.81 × 10 - 4$	0.99
	560—746	C-R	53.4	$1.87 × 10 - 6$	0.95
		Doyle	60.6	108.81	0.96
		A-B-S-W	66.55	1271.17	0.90
	>746	C-R	9.4	$1.98 × 10 - 8$	0.92
		Doyle	23.95	1.21	0.99
		A-B-S-W	18.81	0.25	0.35

Coal	T/K	Method	$E$ /( $k J / m o l$ )	$k$ / $s - 1$	$R 2$
WCW	543—560	C-R	297.0	$1.50 × 1016$	0.87
		Doyle	291.1	$7.91 × 1023$	0.88
		A-B-S-W	14.4	$3.45 × 10 - 3$	0.99
	560—740	C-R	55.0	$2.27 × 10 - 6$	0.99
		Doyle	62.5	142.49	0.99
		A-B-S-W	48.1	3.78	0.98
	>740	C-R	22.3	$2.98 × 10 - 8$	0.99
		Doyle	37.0	3.13	0.99
		A-B-S-W	30.5	0.13	0.76
TLF	473—500	C-R	168.1	$1.06 × 106$	0.78
		Doyle	148.5	$3.41 × 1011$	0.77
		A-B-S-W	13.3	$9.81 × 10 - 4$	0.99
	560—746	C-R	53.4	$1.87 × 10 - 6$	0.95
		Doyle	60.6	108.81	0.96
		A-B-S-W	66.55	1271.17	0.90
	>746	C-R	9.4	$1.98 × 10 - 8$	0.92
		Doyle	23.95	1.21	0.99
		A-B-S-W	18.81	0.25	0.35

Fig.5 Comparison of data simulated by Doyle method and experimental data

Fig.6 Plots oflnβversusT-1 at various α for FWO model

Fig.7 Pyrolysis activation energy distributions f(E) based on FWO model for two coals

Fig.8 Pyrolysis pre-exponential factor distributions f(k) based on FWO model for two coals

Fig.9 Comparison of experimental data and simulated data with FWO method

Table 4 Kinetic parameters of 3-DAEM for pyrolysis of coal samples at heating rate of 20?K/min

Coal	$E 1 / k J / m o l$	$σ 1 / k J / m o l$	$E 2 / k J / m o l$	$σ 2 / k J / m o l$	$E 3 / k J / m o l$	$σ 2 / k J / m o l$	$ω 1$	$ω 2$	n	OF
WCW	279.06	9.90	348.08	74.43	355.20	52.77	0.200	0.334	3.820	0.0005
TLF	176.13	118.51	208.05	3.62	233.95	35.65	0.265	0.365	2.336	0.0008

Table 4 Kinetic parameters of 3-DAEM for pyrolysis of coal samples at heating rate of 20?K/min

Coal	$E 1 / k J / m o l$	$σ 1 / k J / m o l$	$E 2 / k J / m o l$	$σ 2 / k J / m o l$	$E 3 / k J / m o l$	$σ 2 / k J / m o l$	$ω 1$	$ω 2$	n	OF
WCW	279.06	9.90	348.08	74.43	355.20	52.77	0.200	0.334	3.820	0.0005
TLF	176.13	118.51	208.05	3.62	233.95	35.65	0.265	0.365	2.336	0.0008

Fig.10 Distribution activation energy curves as a function of activation energy for 3-DAEM with Gaussian distribution functions

Fig.11 Comparison of experimental data and simulated data at various heating rate with 3-DAEM

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