Reactor simulation and optimization for CO oxidative coupling to dimethyl oxalate reactions

doi:10.11949/0438-1157.20220761

Abstract

Abstract:

The oxidative coupling of CO and methyl nitrite (MN) to produce dimethyl oxalate (DMO) is a key step in the process of synthesis gas to ethylene glycol, and the existing industrial equipment has the problem of low efficiency. A two-dimensional heterogeneous reactor model with a kinetic model including side reactions of dimethyl carbonate and methyl formate was established to simulate and optimize the tubular fixed-bed reactor, with focus on the influences of coolant-flow schemes and operation conditions. The results showed that ∂²T/∂z² at hot spot reflected the potential of thermal runaway sensitively and reliably. The evenness of the temperature distribution indicated co-current coolant-flow was preferred to be employed to achieve a higher conversion, compared with the conventional isothermal and counter-current schemes. Moreover, it was found that MN accelerated reactions, while CO and NO inhibited the reactions by adsorption competition with MN, and the elevated total pressure moderated the reaction and hot spot temperature. Compared with the influence of CO, the hot spot temperature was more sensitive to the contents of MN and NO, which should be strictly controlled. The genetic algorithm was used to optimize the process conditions of the reactor, and found that the annual production capacity of EG by one reactor unit could reach 120000 t.

Key words: dimethyl oxalate, oxidative coupling reaction, fixed-bed reactor, optimization, mathematical modeling

摘要：

CO与亚硝酸甲酯(MN)氧化偶联制草酸二甲酯(DMO)是合成气制乙二醇过程的关键步骤，现有工业装置存在效率低的问题。采用包括副反应(生成碳酸二甲酯和甲酸甲酯)动力学的动力学模型和二维两相反应器模型，对CO氧化偶联的移热式固定床反应器进行建模，研究了换热方式及操作条件对反应器性能和安全性的影响。结果表明，以温度的二阶导数作为飞温的判据是灵敏和可靠的。与常规的逆流和恒温移热方式相比，并流移热使反应器形成更为均匀的温度分布，有利于提高反应器产能。增加入口MN含量会升高反应器MN转化率和热点温度；但是，由于CO、NO和反应物MN之间存在竞争吸附，增加入口CO和NO含量会导致MN转化率和热点温度降低，所以增加入口压力导致MN转化率降低。且热点温度对MN和NO的含量更为敏感，应严格控制入口MN和NO的含量。采用遗传算法进行反应器工况寻优，确定了最优的反应条件，可提高单台反应器对应的乙二醇(EG)年产能至12万吨。

关键词: 草酸二甲酯, 氧化偶联, 固定床反应器, 优化, 数学模拟

CLC Number:

TQ 203.2

Ziyi CHI, Chengwei LIU, Yuling ZHANG, Xuegang LI, Wende XIAO. Reactor simulation and optimization for CO oxidative coupling to dimethyl oxalate reactions[J]. CIESC Journal, 2022, 73(11): 4974-4986.

迟子怡, 刘成伟, 张欲凌, 李学刚, 肖文德. CO氧化偶联反应器模拟与优化[J]. 化工学报, 2022, 73(11): 4974-4986.

Figures/Tables 15

Fig.1 Structure sketch of DMO synthesis industrial reactor

Table 1 Parameters in two-dimensional heterogeneous model

参数	表达式
D_er^[16]	$D e r = u f d p 8.65 1 + 19.4 d p D t$
k_er^[20]	k_er= k_er,0+ k_fRePr / Pe_r
k_fs^[16,21]	k_fsd_p/ D_ij = 2+1.1Sc^1/3Re^0.6
h_fs^[21]	h_fsd_p/ k_f = 2+1.1Pr^1/3Re^0.6
h_w^[20]	h_w= Nu_wk_f/d_p， $N u w = N u w, 0 + 1 / 1 N u w * + 1 N u m$ ， $N u w *$ = 0.3Pr^1/3Re^0.75, Nu_m= 0.054PrRe
h_o^[22]	$h o = λ 0 J H o P r o 1 / 3 φ o ε h 2 / D e$ $J H o = 0.378 R e o 0.554 Z - 15 / 10 + 0.41 R e o 0.5634 25 - Z / 10$
h_ew^[15]	对于并流和逆流： $1 h e w = 1 h w + δ λ w + 1 h o + R d$ 对于恒温换热： $1 h e w = 1 h w + δ λ w + R d$

Table 1 Parameters in two-dimensional heterogeneous model

参数	表达式
D_er^[16]	$D e r = u f d p 8.65 1 + 19.4 d p D t$
k_er^[20]	k_er= k_er,0+ k_fRePr / Pe_r
k_fs^[16,21]	k_fsd_p/ D_ij = 2+1.1Sc^1/3Re^0.6
h_fs^[21]	h_fsd_p/ k_f = 2+1.1Pr^1/3Re^0.6
h_w^[20]	h_w= Nu_wk_f/d_p， $N u w = N u w, 0 + 1 / 1 N u w * + 1 N u m$ ， $N u w *$ = 0.3Pr^1/3Re^0.75, Nu_m= 0.054PrRe
h_o^[22]	$h o = λ 0 J H o P r o 1 / 3 φ o ε h 2 / D e$ $J H o = 0.378 R e o 0.554 Z - 15 / 10 + 0.41 R e o 0.5634 25 - Z / 10$
h_ew^[15]	对于并流和逆流： $1 h e w = 1 h w + δ λ w + 1 h o + R d$ 对于恒温换热： $1 h e w = 1 h w + δ λ w + R d$

Table 2 Kinetic parameters

A_k	A_k,ref	B_k/(kJ/mol)
K_CO·	0.13	-103.23
K_NO·	0.32	-92.91
$K C H 3 C O O ·$	3.22	-31.25
K_H·	1.01	-60.90
k_DMO	2.19	-62.12
k_DMC	0.42	-5.54
k_MF	0.24	49.13

Table 2 Kinetic parameters

A_k	A_k,ref	B_k/(kJ/mol)
K_CO·	0.13	-103.23
K_NO·	0.32	-92.91
$K C H 3 C O O ·$	3.22	-31.25
K_H·	1.01	-60.90
k_DMO	2.19	-62.12
k_DMC	0.42	-5.54
k_MF	0.24	49.13

Fig.2 Effect of coolant flow and direction on reactor performance

Fig.3 Effect of inlet temperature on reactor performance

Table 3 Effect of pressure on reactor performance

P_in/kPa	X_MN/%	S_DMO/%	S_DMC/%	S_MF/%	T_max/^oC	ΔP/kPa	STY/(kg/h)
450	90.20	95.70	3.41	0.88	158.04	159.74	2.92
500	85.64	96.43	2.95	0.62	152.60	137.08	2.79
550	80.43	96.93	2.62	0.45	148.23	120.79	2.64
600	75.08	97.28	2.37	0.35	145.11	108.30	2.47
650	69.90	97.54	2.17	0.28	143.00	98.34	2.31

Fig.4 Effect of species content on reactor performance

Table 4 Effect of GHSV on reactor performance

GHSV/h^-1	X_MN/%	S_DMO/%	S_DMC/%	S_MF/%	T_max/^oC	ΔP/kPa	STY/(kg/h)
3000	69.90	97.54	2.17	0.28	143.00	98.34	2.31
3500	65.86	97.44	2.26	0.30	145.16	133.92	2.53
4000	62.61	97.29	2.38	0.34	147.62	177.03	2.75
4500	60.18	97.08	2.53	0.39	150.13	229.80	2.97
5000	58.65	96.77	2.75	0.48	152.82	296.35	3.20

Fig.5 Effect of GHSV on axial temperature profile

Fig.6 Effect of gas inlet temperature on axial temperature and its second-order partial derivative

Fig.7 Effect of inlet pressure on axial temperature and its second-order partial derivative

Fig.8 Effect of feed contents on axial temperature and its second-order partial derivative

Table 5 Optimized conditions

No.	y_MN,in/%	y_CO,in/%	y_NO,in/%	T_in/℃	P_in/kPa	GHSV/h^-1	w_c/ (kg/s)	η	ε_b
1	12.57	40.00	7.94	130.55	535.32	3179.78	0.011	0.35	0.45
2	13.94	39.98	7.60	136.24	590.47	3744.12	0.013	0.25	0.50
3	13.79	40.00	5.29	137.32	505.30	4554.93	0.014	0.21	0.55
4	12.61	30.00	8.46	128.23	582.70	3375.64	0.013	0.38	0.45
5	12.63	30.00	5.70	126.36	578.14	3907.57	0.014	0.35	0.50
6	14.52	29.98	8.66	129.62	586.35	4999.46	0.020	0.36	0.55

Table 6 Optimized results

No.	X_MN/%	S_DMO/%	S_DMC/%	S_MF/%	T_max/^oC	ΔP/kPa	STY/(kg/h)
1	76.84	97.28	2.19	0.53	157.71	149.40	2.91
2	76.42	96.16	2.97	0.87	167.25	116.31	3.73
3	77.87	95.16	3.54	1.30	170.09	133.94	4.53
4	75.18	96.83	2.63	0.54	154.33	149.92	3.01
5	74.97	96.94	2.55	0.51	154.50	124.45	3.49
6	70.41	95.98	3.31	0.71	159.04	130.72	4.77

Fig.9 Reactor performance under optimized conditions

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