快速变压吸附制氢工艺的模拟与分析

doi:10.11949/0438-1157.20201393

摘要/Abstract

摘要：

目前工业上主要通过变压吸附技术从蒸汽甲烷重整气中制取氢产品气。然而，能源需求量的快速增加使得传统变压吸附技术在产量方面的不足越发明显。为此，进行了快速变压吸附从蒸汽甲烷重整气中制取氢气的模拟研究。采用活性炭和5A分子筛作为吸附剂，并以测得的原料气中各组分在两种吸附剂上的吸附数据为基础，进行了六塔快速变压吸附工艺的数值模拟与分析。在分析了塔内温度、压力和固相的浓度分布后，探究了进料流量、双层吸附剂高度比以及冲洗进料比三个操作参数对于快速变压吸附工艺性能的影响，结果表明：原料气组成为H₂/CH₄/CO/CO₂=76%/3.5%/0.5%/20%，吸附压力为22 bar（1 bar=10⁵ Pa），解吸吹扫压力为1.0 bar，处理量为0.8875 mol·s^-1，吸附剂床层高度比为0.5∶0.5，冲洗进料比为22.37%时，可获得H₂纯度99.90%，回收率69.88%，此时H₂产量为0.4713 mol·s^-1。相比之下，氢气纯度为99.90%时，尽管PSA工艺回收率为83.40%，但处理量只有0.39 mol·s^-1，因此H₂产量仅为0.2472 mol·s^-1。

关键词: 快速变压吸附, 双层吸附剂, 蒸汽甲烷重整, 制氢, 数值模拟

Abstract:

At present, pressure swing adsorption is the main technology to produce hydrogen product gas from steam methane reformed gas in the industry. However, the rapid increase in energy demand makes the shortcomings of traditional pressure swing adsorption technology more obvious in terms of productivity. For this reason, a simulation study of hydrogen production from steam methane reformed gas by rapid pressure swing adsorption was carried out. The activated carbon and 5A zeolite were used as adsorbents and the numerical simulation and analysis of six bed rapid pressure swing adsorption process were carried out based on the measured adsorption data of each component in the feed gas on the two adsorbents. After analyzing the temperature, pressure and gas and solid concentration distribution in the bed, the three operating parameters of the feed flow rate, the height ratio of the two-layer adsorbent and purge-to-feed ratio have been investigated for the effect of the rapid pressure swing adsorption process performance. When the feed gas composition is H₂/CH₄/CO/CO₂=76%/3.5%/0.5%/20%, the adsorption pressure is 22 bar, the pressure of purge desorption is 1.0 bar, the feed flow rate is 0.8875 mol·s^-1, the adsorbent bed height ratio is 0.5∶0.5, and purge-to-feed ratio is 22.37%, the purity of H₂ is 99.90% and the recovery is 69.88%. At this time, the yield of H₂ is 0.4713 mol·s^-1. In contrast, although the H₂ recovery of the PSA process is 83.40%, the processing capacity is only 0.39 mol·s^-1, so the productivity is only 0.2472 mol·s^-1when the purity is 99.90%.

Key words: rapid pressure swing adsorption, double layer adsorbent, steam methane reforming, hydrogen production, numerical simulation

中图分类号:

TQ 028.1

钮朝阳, 江南, 沈圆辉, 吴统波, 刘冰, 张东辉. 快速变压吸附制氢工艺的模拟与分析[J]. 化工学报, 2021, 72(2): 1036-1046.

NIU Zhaoyang, JIANG Nan, SHEN Yuanhui, WU Tongbo, LIU Bing, ZHANG Donghui. Simulation and analysis of rapid pressure swing adsorption for hydrogen production[J]. CIESC Journal, 2021, 72(2): 1036-1046.

图/表 18

图1 六塔RPSA和PSA整体工艺结构图

Fig.1 Configuration diagram of the six-bed RPSA and PSA process

图2 RPSA和PSA循环工艺示意图

Fig.2 Process schematic diagram of RPSA and PSA

表1 六塔RPSA时序

Table 1 The schedule of six-bed RPSA

时间/s	塔1	塔2	塔3	塔4	塔5	塔6
10	AD1	ER1	ER3	BD	ED3	ED1
15	AD2	PR	ER2	PUR	COD	ED2
10	ED1	AD1	ER1	ER3	BD	ED3
15	ED2	AD2	PR	ER2	PUR	COD
10	ED3	ED1	AD1	ER1	ER3	BD
15	COD	ED2	AD2	PR	ER2	PUR
10	BD	ED3	ED1	AD1	ER1	ER3
15	PUR	COD	ED2	AD2	PR	ER2
10	ER3	BD	ED3	ED1	AD1	ER1
15	ER2	PUR	COD	ED2	AD2	PR
10	ER1	ER3	BD	ED3	ED1	AD1
15	PR	ER2	PUR	COD	ED2	AD2

表2 六塔PSA时序

Table 2 The schedule of six-bed PSA

时间/s	塔1	塔2	塔3	塔4	塔5	塔6
40	AD1	ER1	ER3	BD	ED3	ED1
50	AD2	PR	ER2	PUR	COD	ED2
40	ED1	AD1	ER1	ER3	BD	ED3
50	ED2	AD2	PR	ER2	PUR	COD
40	ED3	ED1	AD1	ER1	ER3	BD
50	COD	ED2	AD2	PR	ER2	PUR
40	BD	ED3	ED1	AD1	ER1	ER3
50	PUR	COD	ED2	AD2	PR	ER2
40	ER3	BD	ED3	ED1	AD1	ER1
50	ER2	PUR	COD	ED2	AD2	PR
40	ER1	ER3	BD	ED3	ED1	AD1
50	PR	ER2	PUR	COD	ED2	AD2

表3 吸附塔数学模型

Table 3 Mathematical model of adsorption bed

	数学模型
质量守恒	$- ε b D a x, i ? 2 c i ? z 2 + ε b ? (v g c i) ? z + (ε b + (1 - ε b) ε p) ? c i ? t + ρ s (1 - ε b) ? q i ? t = 0$	(1)
	$ε b ? (v g c) ? z + (ε b + (1 - ε b) ε p) ? c ? t + ρ s (1 - ε b) ∑ i = 1 n ? q i ? t = 0$	(2)
	$D a x, i = 0.73 D m, i + v g r p ε b 1 + 9.49 ε b D m, i 2 v g r p$	(3)
能量守恒	$- ε b k g ? 2 T g ? z 2 + C v g v g ρ g ? T g ? z + ε b C v g ρ g ? T g ? t + P ? v g ? z + h f a p (T g - T s) + 4 h w D b (T g - T 0) = 0$	(4)
	$- k s ? 2 T s ? z 2 + C p s ρ s ? T s ? t + ρ s ∑ i = 1 n (C p a, i q i) ? T s ? t + ρ s ∑ i = 1 n Δ H i ? q i ? t - h f a p (T g - T s) = 0$	(5)
	$k w ? 2 T w ? z 2 + C p w ρ w ? T w ? z - h w 4 D b (D b + W t) 2 - D b 2 (T g - T w) + h a m b 4 (D b + W t) 2 (D b + W t) 2 - D b 2 (T w - T a m b) = 0$	(6)
动量守恒	$- ? P ? z = 150 μ (1 - ε b) 2 ε b 3 (2 r p ψ) 2 v g + 1.75 (1 - ε b) ρ g 2 r p ψ ε b 3 \| v g \| v g$	(7)
吸附等温式	$q i * = (I P 1, i + I P 2, i T s) I P 3, i e x p (I P 4, i / T s) P i 1 + ∑ i = 1 n (I P 3, i e x p (I P 4, i / T s) P i)$	(8)
线性推动力方程	$? q i ? t = k L D F, i (q i * - q i)$	(9)

表3 吸附塔数学模型

Table 3 Mathematical model of adsorption bed

	数学模型
质量守恒	$- ε b D a x, i ? 2 c i ? z 2 + ε b ? (v g c i) ? z + (ε b + (1 - ε b) ε p) ? c i ? t + ρ s (1 - ε b) ? q i ? t = 0$	(1)
	$ε b ? (v g c) ? z + (ε b + (1 - ε b) ε p) ? c ? t + ρ s (1 - ε b) ∑ i = 1 n ? q i ? t = 0$	(2)
	$D a x, i = 0.73 D m, i + v g r p ε b 1 + 9.49 ε b D m, i 2 v g r p$	(3)
能量守恒	$- ε b k g ? 2 T g ? z 2 + C v g v g ρ g ? T g ? z + ε b C v g ρ g ? T g ? t + P ? v g ? z + h f a p (T g - T s) + 4 h w D b (T g - T 0) = 0$	(4)
	$- k s ? 2 T s ? z 2 + C p s ρ s ? T s ? t + ρ s ∑ i = 1 n (C p a, i q i) ? T s ? t + ρ s ∑ i = 1 n Δ H i ? q i ? t - h f a p (T g - T s) = 0$	(5)
	$k w ? 2 T w ? z 2 + C p w ρ w ? T w ? z - h w 4 D b (D b + W t) 2 - D b 2 (T g - T w) + h a m b 4 (D b + W t) 2 (D b + W t) 2 - D b 2 (T w - T a m b) = 0$	(6)
动量守恒	$- ? P ? z = 150 μ (1 - ε b) 2 ε b 3 (2 r p ψ) 2 v g + 1.75 (1 - ε b) ρ g 2 r p ψ ε b 3 \| v g \| v g$	(7)
吸附等温式	$q i * = (I P 1, i + I P 2, i T s) I P 3, i e x p (I P 4, i / T s) P i 1 + ∑ i = 1 n (I P 3, i e x p (I P 4, i / T s) P i)$	(8)
线性推动力方程	$? q i ? t = k L D F, i (q i * - q i)$	(9)

表4 辅助设备数学模型

Table 4 Mathematical model of auxiliary equipment

设备	数学模型
压缩机	$? d W = P c i n V i n η p γ γ - 1 P c o u t P c i n γ - 1 γ - 1$ $W c y c l e = ∫ 0 t c y c l e d W, ? γ = C p C v$	(10)
缓冲罐	$? T (∑ i = 1 n n i C p g, i) ? t = ∑ b i n = 1 N i n F b i n T b i n y i C p g, i - F b o u t T b o u t y i C p g, i$	(11)
缓冲罐	$? n i ? t = ∑ b i n = 1 N i n F b i n y i - ∑ b o u t = 1 N o u t F b o u t y i$	(11)
线性阀门	$F = C V (P v i n ? - ? P v o u t)$	(12)

表4 辅助设备数学模型

Table 4 Mathematical model of auxiliary equipment

设备	数学模型
压缩机	$? d W = P c i n V i n η p γ γ - 1 P c o u t P c i n γ - 1 γ - 1$ $W c y c l e = ∫ 0 t c y c l e d W, ? γ = C p C v$	(10)
缓冲罐	$? T (∑ i = 1 n n i C p g, i) ? t = ∑ b i n = 1 N i n F b i n T b i n y i C p g, i - F b o u t T b o u t y i C p g, i$	(11)
缓冲罐	$? n i ? t = ∑ b i n = 1 N i n F b i n y i - ∑ b o u t = 1 N o u t F b o u t y i$	(11)
线性阀门	$F = C V (P v i n ? - ? P v o u t)$	(12)

表5 工艺性能评价指标

Table 5 Process performance indicator

指标	数学模型
纯度	$p u r i t y H 2 = ∫ 0 t a d F o u t y o u t, H 2 d t ∫ 0 t a d F o u t d t$	(13)
回收率	$r e c o v e r y H 2 = ∫ 0 t a d F o u t y o u t, H 2 d t ∫ 0 t a d F i n y i n, H 2 d t$	(14)
生产量	$p r o d u c t i v i t y H 2 = 60 R T s t a n ∫ 0 t a d F o u t y o u t, H 2 d t P s t a n t c y c l e$	(15)

表5 工艺性能评价指标

Table 5 Process performance indicator

指标	数学模型
纯度	$p u r i t y H 2 = ∫ 0 t a d F o u t y o u t, H 2 d t ∫ 0 t a d F o u t d t$	(13)
回收率	$r e c o v e r y H 2 = ∫ 0 t a d F o u t y o u t, H 2 d t ∫ 0 t a d F i n y i n, H 2 d t$	(14)
生产量	$p r o d u c t i v i t y H 2 = 60 R T s t a n ∫ 0 t a d F o u t y o u t, H 2 d t P s t a n t c y c l e$	(15)

表6 活性炭和5A分子筛吸附剂参数

Table 6 Parameter of activate carbon and 5A zeolite adsorbent

物性参数	活性炭	5A分子筛
$ρ b$ /(kg·m^-3)	522.0	698.0
C_p_s/(kJ·kg^-1·K^-1)	1.047	0.92
r_p/m	0.00115	0.00157
$ε b$	0.433	0.357
$ε p$	0.61	0.65
$Ψ$	0.9	1.0
$k L D F, C H 4$ /s^-1	0.195	0.147
k_LDF_,_CO/s^-1	0.15	0.063
$k L D F, C O 2$ /s^-1	0.0355	0.0135
$k L D F, H 2$ /s^-1	0.7	0.7

表6 活性炭和5A分子筛吸附剂参数

Table 6 Parameter of activate carbon and 5A zeolite adsorbent

物性参数	活性炭	5A分子筛
$ρ b$ /(kg·m^-3)	522.0	698.0
C_p_s/(kJ·kg^-1·K^-1)	1.047	0.92
r_p/m	0.00115	0.00157
$ε b$	0.433	0.357
$ε p$	0.61	0.65
$Ψ$	0.9	1.0
$k L D F, C H 4$ /s^-1	0.195	0.147
k_LDF_,_CO/s^-1	0.15	0.063
$k L D F, C O 2$ /s^-1	0.0355	0.0135
$k L D F, H 2$ /s^-1	0.7	0.7

表7 吸附床参数

Table 7 Parameters of adsorption bed

参数	数值
H_b/m	1.0
W_t/m	0.002
D_b/m	0.2
$ρ w$ /(kg·m^-3)	7800
C_p_w/(kJ·kg^-1·K^-1)	0.5024
h_w/(W·m^-2·K^-1)	94.0
T_amb/K	298.15

表7 吸附床参数

Table 7 Parameters of adsorption bed

参数	数值
H_b/m	1.0
W_t/m	0.002
D_b/m	0.2
$ρ w$ /(kg·m^-3)	7800
C_p_w/(kJ·kg^-1·K^-1)	0.5024
h_w/(W·m^-2·K^-1)	94.0
T_amb/K	298.15

图3 四种组分在5A分子筛和活性炭上的吸附等温线

Fig.3 Adsorption isotherms of four components on 5A zeolite and activated carbon

表8 扩展型Langmuir吸附模型拟合参数

Table 8 Extended Langmuir adsorption model fitting parameters

参数	活性炭				5A分子筛
参数	CH₄	CO	CO₂	H₂	CH₄	CO	CO₂	H₂
IP₁/(mol·kg^-1·bar^-1)	0.02386	0.03385	0.02880	0.01694	0.005833	0.01185	0.01003	0.004314
IP₂/K	5.62×10^-5	9.07×10^-5	7.00×10^-5	2.10×10^-5	1.19×10^-5	3.13×10^-5	1.86×10^-5	1.06×10^-5
IP₃/bar^-1	3.48×10^-3	2.31×10^-4	0.0100	6.25×10^-5	6.05×10^-4	0.02020	1.5781	0.002515
IP₄/K	1159	1751	1030	1229	1731	763.0	207.0	458.0
R	0.9998	0.9999	0.9998	1.0000	0.9917	0.9988	0.9919	0.9984
ΔH/(kJ·mol^-1)	-22.70	-22.58	-29.08	-12.84	-20.64	-29.77	-35.97	-9.23

图4 RPSA和PSA气相温度分布

Fig.4 Gas temperature distribution of RPSA and PSA

图5 RPSA和PSA压力分布

Fig.5 Pressure distribution of RPSA and PSA

图6 CO、CO2、CH4和H2在轴向上的固相浓度分布

Fig.6 Solid phase concentration profiles of CO, CO2, CH4 and H2

图7 进料流量对于RPSA性能的影响

Fig.7 Effect of feed flow rate on RPSA performance

图8 活性炭/5A分子筛床层填充比对于RPSA性能的影响

Fig.8 Effect of layer ratio of AC/5A zeolite on RPSA performance

图9 冲洗进料比对于RPSA性能的影响

Fig.9 Effect of purge-to-feed ratio on RPSA performance

图10 两种工艺的H2产量和H2回收率对比

Fig.10 Comparison of H2 yield and recovery of the two processes

参考文献 30

1	陈思晗, 张珂, 常丽萍, 等. 传统和新型制氢方法概述[J]. 天然气化工(C₁化学与化工), 2019, 44(2): 122-127.
	Chen S H, Zhang K, Chang L P, et al. Overview of traditional and new hydrogen production methods[J]. Natural Gas Chemical Industry, 2019, 44(2): 122-127.
2	朱晓宇, 刘则渊. 国际氢能研究的文献计量学分析[J]. 情报杂志, 2011, 30(6): 65-69.
	Zhu X Y, Liu Z Y. Biliometrics analysis of international research on hydrogen energy[J]. Journal of Intelligence, 2011, 30(6): 65-69.
3	Delgado J A, Águeda V I, Uguina M A, et al. Adsorption and diffusion of H₂, CO, CH₄, and CO₂ in BPL activated carbon and 13X zeolite: evaluation of performance in pressure swing adsorption hydrogen purification by simulation[J]. Industrial & Engineering Chemistry Research, 2014, 53(40): 15414-15426.
4	Sircar S, Golden T C. Purification of hydrogen by pressure swing adsorption[J]. Fuel & Energy Abstracts, 2000, 35(5): 667-687.
5	何东荣, 周向辉, 张东辉. 利用ASPEN-ADSIM模拟变压吸附分离过程[J]. 天然气化工(C₁化学与化工), 2009, 34(3): 11-15.
	He D R, Zhou X H, Zhang D H. Simulation of PSA separation process by ASPEN-ADSIM[J]. Natural Gas Chemical Industry, 2009, 34(3): 11-15.
6	冯孝庭. 吸附分离技术[M]. 北京: 化学工业出版社, 2000: 32-39.
	Feng X T. Adsorption Separation Technology[M]. Beijing: Chemical Industry Press, 2000: 32-39.
7	Sircar S, Waldron W E, Rao M B, et al. Hydrogen production by hybrid SMR-PSA-SSF membrane system[J]. Separation and Purification Technology, 1999, 17(1): 11-20.
8	Lopes F V S, Grande C A, Alírio E R. Activated carbon for hydrogen purification by pressure swing adsorption: multicomponent breakthrough curves and PSA performance[J]. Chemical Engineering Science, 2011, 66(3): 303-317.
9	Golmakani A, Nabavi S A, Vasilije M. Effect of impurities on ultra-pure hydrogen production by pressure vacuum swing adsorption[J]. Journal of Industrial and Engineering Chemistry, 2020, 82: 278-289.
10	Golmakani A, Fatemi S, Tamnanloo J. Investigating PSA, VSA, and TSA methods in SMR unit of refineries for hydrogen production with fuel cell specification[J]. Separation and Purification Technology, 2017, 176: 73-91.
11	Shi W R, Yang H W, Shen Y H, et al. Two-stage PSA/VSA to produce H₂ with CO₂ capture via steam methane reforming (SMR)[J]. International Journal of Hydrogen Energy, 2018, 43(41): 19057-19074.
12	田涛, 刘冰, 石梅生, 等. 双塔微型变压吸附制氧机实验和模拟[J]. 化工学报, 2019, 70(3): 969-978.
	Tian T, Liu B, Shi M S, et al. Experiment and simulation of PSA process for small oxygen generator with two adsorption beds[J]. CIESC Journal, 2019, 70(3): 969-978.
13	Chai S W, Kothare M V, Sircar S. Numerical study of nitrogen desorption by rapid oxygen purge for a medical oxygen concentrator[J]. Adsorption-Journal of the International Adsorption Society, 2012, 18(2): 87-102.
14	Rao V R, Kothare M V, Sircar S. Novel design and performance of a medical oxygen concentrator using a rapid pressure swing adsorption concept[J]. AIChE Journal, 2014, 60(9): 3330-3335.
15	Vemula R R, Kothare M V, Sircar S. Anatomy of a rapid pressure swing adsorption process performance[J]. AIChE Journal, 2015, 61(6): 2008-2015.
16	刘应书, 祝显强, 杨雄, 等. 快速真空变压吸附制氧实验研究[J]. 医用气体工程, 2016, 1(1): 21-24.
	Liu Y S, Zhu X Q, Yang X, et al. An experimental study of rapid vacuum pressure swing adsorption for producing oxygen[J]. Medical Gases Engineering, 2016, 1(1): 21-24.
17	祝显强, 刘应书, 杨雄, 等. 中间气两步充压对快速真空变压吸附制氧的影响[J]. 化工学报, 2016, 67(10): 4264-4272.
	Zhu X Q, Liu Y S, Yang X, et al. Effect of two-step pressurization with intermediate gas on rapid vacuum pressure swing adsorption process for oxygen generation[J]. CIESC Journal, 2016, 67(10): 4264-4272.
18	Vemula R R, Kothare M V, Sircar S. Performance of a medical oxygen concentrator using rapid pressure swing adsorption process: effect of feed air pressure[J]. AIChE Journal, 2016, 62(4): 1212-1215.
19	Wu C W, Vemula R R, Kothare M V, et al. Experimental study of a novel rapid pressure swing adsorption (RPSA) based medical oxygen concentrator (MOC): effect of adsorbent selectivity of N₂ over O₂[J]. Industrial & Engineering Chemistry Research, 2016, 55(16): 4676-4681.
20	Chai S W, Kothare M V, Sircar S. Rapid pressure swing adsorption for reduction of bed size factor of a medical oxygen concentrator[J]. Industrial & Engineering Chemistry Research, 2011, 50(14): 8703-8710.
21	Urich M D, Rama R V, Kothare M V. Multivariable model predictive control of a novel rapid pressure swing adsorption system[J]. AIChE Journal, 2018, 64(4): 1234-1245.
22	Vemula R R, Sircar S. Comments on the reliability of model simulation of a rapid pressure swing adsorption process for high-purity product[J]. Industrial & Engineering Chemistry Research, 2017, 56(31): 8991-8994.
23	Lopes F V S, Grande C A, Alírio E R. Fast-cycling VPSA for hydrogen purification[J]. Fuel, 2012, 93(1): 510-523.
24	Sharma I, Friedrich D, Golden T C, et al. Monolithic adsorbent-based rapid-cycle vacuum pressure swing adsorption process for carbon capture from small-scale steam methane reforming[J]. Industrial & Engineering Chemistry Research, 2020, 59(15): 7109-7120.
25	Yang H W, Yin C B, Jiang B, et al. Optimization and analysis of a VPSA process for N₂/CH₄ separation[J]. Separation and Purification Technology, 2014, 134(1): 232-240.
26	Sun W N, Shen Y H, Zhang D H, et al. A systematic simulation and proposed optimization of the pressure swing adsorption process for N₂/CH₄ separation under external disturbances[J]. Industrial & Engineering Chemistry Research, 2015, 54(30): 7489-7501.
27	Ding Z Y, Han Z Y, Fu Q, et al. Optimization and analysis of the VPSA process for industrial-scale oxygen production[J]. Adsorption-Journal of the International Adsorption Society, 2018, 24(5): 499-516.
28	Wang Y Y, An Y X, Ding Z Y, et al. Integrated VPSA processes for air separation based on dual reflux configuration[J]. Industrial & Engineering Chemistry Research, 2019, 58(16): 6562-6575.
29	Wu T B, Shen Y H, Feng L, et al. Adsorption properties of N₂O on zeolite 5A, 13X, activated carbon, ZSM-5, and silica gel[J]. Journal of Chemical & Engineering Data, 2019, 64(8): 3473-3482.
30	Chen S R, Shen Y H, Guan Z B, et al. Adsorption properties of SF₆ on zeolite NaY, 13X, activated carbon, and silica gel[J]. Journal of Chemical & Engineering Data, 2020, 65(8): 4044-4051.

[1]	宋嘉豪, 王文. 斯特林发动机与高温热管耦合运行特性研究[J]. 化工学报, 2023, 74(S1): 287-294.
[2]	张思雨, 殷勇高, 贾鹏琦, 叶威. 双U型地埋管群跨季节蓄热特性研究[J]. 化工学报, 2023, 74(S1): 295-301.
[3]	黄琮琪, 吴一梅, 陈建业, 邵双全. 碱性电解水制氢装置热管理系统仿真研究[J]. 化工学报, 2023, 74(S1): 320-328.
[4]	叶展羽, 山訸, 徐震原. 用于太阳能蒸发的折纸式蒸发器性能仿真[J]. 化工学报, 2023, 74(S1): 132-140.
[5]	张义飞, 刘舫辰, 张双星, 杜文静. 超临界二氧化碳用印刷电路板式换热器性能分析[J]. 化工学报, 2023, 74(S1): 183-190.
[6]	王志国, 薛孟, 董芋双, 张田震, 秦晓凯, 韩强. 基于裂隙粗糙性表征方法的地热岩体热流耦合数值模拟与分析[J]. 化工学报, 2023, 74(S1): 223-234.
[7]	何松, 刘乔迈, 谢广烁, 王斯民, 肖娟. 高浓度水煤浆管道气膜减阻两相流模拟及代理辅助优化[J]. 化工学报, 2023, 74(9): 3766-3774.
[8]	邢雷, 苗春雨, 蒋明虎, 赵立新, 李新亚. 井下微型气液旋流分离器优化设计与性能分析[J]. 化工学报, 2023, 74(8): 3394-3406.
[9]	韩晨, 司徒友珉, 朱斌, 许建良, 郭晓镭, 刘海峰. 协同处理废液的多喷嘴粉煤气化炉内反应流动研究[J]. 化工学报, 2023, 74(8): 3266-3278.
[10]	程小松, 殷勇高, 车春文. 不同工质在溶液除湿真空再生系统中的性能对比[J]. 化工学报, 2023, 74(8): 3494-3501.
[11]	刘文竹, 云和明, 王宝雪, 胡明哲, 仲崇龙. 基于场协同和耗散的微通道拓扑优化研究[J]. 化工学报, 2023, 74(8): 3329-3341.
[12]	洪瑞, 袁宝强, 杜文静. 垂直上升管内超临界二氧化碳传热恶化机理分析[J]. 化工学报, 2023, 74(8): 3309-3319.
[13]	黄可欣, 李彤, 李桉琦, 林梅. 加装旋转叶轮T型通道流场的模态分解[J]. 化工学报, 2023, 74(7): 2848-2857.
[14]	史方哲, 甘云华. 超薄热管启动特性和传热性能数值模拟[J]. 化工学报, 2023, 74(7): 2814-2823.
[15]	周小文, 杜杰, 张战国, 许光文. 基于甲烷脉冲法的Fe₂O₃-Al₂O₃载氧体还原特性研究[J]. 化工学报, 2023, 74(6): 2611-2623.