A Novel Radial Adsorber with Parallel Layered Beds for

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Industrial & Engineering Chemistry Research

A novel radial adsorber with parallel layered beds for prepurification of large-scale air separation units Qiqi Tian1, Guogeng He*1, Zhiping Wang1, Dehua Cai1, Liping Chen2 1

School of Energy and Power Engineering, Huazhong University of Science and Technology,

Wuhan, China 2

CAD Center, Huazhong University of Science and Technology, Wuhan, China

* Corresponding author. Tel.: +86 2787542718 601; fax: +86 2787540724. E-mail address: [email protected] (Guogeng He) ABSTRACT The scale of cryogenic air separation units (ASUs) has increased continuously in recent years. In order to better meet the requirements of large-scale ASUs in terms of achieving both good prepurification performance and energy-saving effects, a novel radial adsorber with parallel layered adsorbent beds is proposed in the present paper. The main purpose of the novel adsorber is to reduce the pressure drop and increase the adsorption performance with a relatively compact structure, which may gain long-term energy-saving effects for large-scale ASUs as well as other similar applications. The novel adsorber is modelled in the cylindrical coordinate system using the mass conservation equation, energy conservation equation, adsorbing isotherm equation and LDF mass transfer equation. The geometric dimensions of the two-passage and three-passage adsorbers are both calculated using a proposed scheme, indicating the volume reductions of 27.8% and 31.7% and the pressure loss reductions of 10.8% and 56.4%, respectively. Furthermore, the adsorption and desorption simulations of adsorbers with both parallel and single layered beds are performed, and the results show that better adsorbent utilization is achieved by the parallel one than the single one 1

ACS Paragon Plus Environment


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due to reduced feed velocities, increasing the breakthrough time by about 23.1%. Keywords: Radial adsorber; Parallel layered beds; Parallel passages; Large-scale ASUs; Pressure loss; Breakthrough time 1. Introduction At present, the most commonly used approach for producing high-purity gases such as oxygen and nitrogen on an industrial scale is the cryogenic air separation approach1. The rapid growth in demand for industrial gas in steel and chemical industries leads to the capacity expansion of the cryogenic air separation unit (ASU)2, which may adversely affect the performance of the prepurification equipment (i.e., the adsorber) in terms of flow resistance, adsorption performance, the external dimensions, etc. The adsorber, as one of the key equipment of the ASU, is used to purify the feed air to ensure both the product purity and system safety. Before the feed air enters the cold box of the ASU, it should be purified in the adsorber to remove moisture, carbon dioxide and some hydrocarbons3. Otherwise, these impurities may directly go into the main heat exchange equipment of the ASU, i.e. the plate-fin heat exchanger4, and may not only freeze and block the passages of the heat exchanger but also increase the explosion risk due to their flammability. For example, in a reported accident5, the ethylene acted as an igniter and led to the explosion of the aluminum reboiler of the low pressure column. In recent years plentiful attentions and interests have been devoted to air prepurification, adsorption and the relevant issues, achieving important progress. In terms of the adsorbents, Bezerra et al 6, 7performed a series of experiments on the CO2 adsorption with amine-grafted zeolite 13X and amine-grafted activated carbon, respectively, obtaining important adsorption characteristics 2


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under different temperature and pressure conditions; Belmabkhout et al8, 9 experimentally demonstrated that high adsorption rate, stability and selectivity can be achieved by amine-bearing mesoporous silica for CO2 removal from air; Shekhah et al10 proposed a novel isostructural metal-organic framework SIFSIX-3-Cu, which exhibits remarkable ability of CO2 uptake and selectivity in highly diluted gas streams and stable adsorption performance under alternant moisture conditions; Zhang et al 11, 12 experimentally evaluated the polyethyleneimine-silica adsorbent on capturing CO2 from ambient air in fluidized beds, achieving 11 wt% equilibrium capacities for 60 cycles as well as other important characteristics. In terms of the cycle feature, Monereau et al13 employed an accelerated TSA cycle for prepurifying air and obtained satisfied results; Gomes et al applied the PSA cycle to the CO2 removal of exhaust gas and confirmed the suitability of Zeolite 13X14, and demonstrated that VSA is more effective than PSA in removing CO2 for methane recovery15. In terms of the adsorption isotherms research, Petkovska 16shown that discrimination between different adsorption isotherm models and identification of the best one can be performed if the values of the local first, second and third order isotherm derivatives are available. In terms of adsorber structure, Celik et al17 proposed a novel rectangular adsorption bed structure containing several parallel modular compact adsorbent bed units working together in an enclosed housing, which has the advantages of increased adsorbent utilization, lower fabrication costs, lower pressure drop in the adsorbent bed by providing a very large flow area (frontal area) combined with shorter bed depths, etc. At present, different types of adsorbers may be employed in different applications according to the scales of the ASU. As described by Kerry18, for the oxygen production up to 700 tonnes/day (about 20000Nm3/h), the market belongs to the vertical adsorber (axial flow); for that with a 3



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capacity from 700 up to 1500t/d (about 44000 Nm3/h), the designer may choose between the vertical adsorber, horizontal adsorber, or preferably, the radial adsorber; beyond 1500t/d (about 44000Nm3/h) the radial adsorber has a very definite advantage. For the radial adsorber, a lower pressure drop can be achieved due to the relatively large inlet area and the reduced feed velocity 19. It is possible to deal with the large-capacity cases by using the conventional radial adsorber with single airflow passage, but the rapidly growing capacity at present may still lead to the challenge of the obvious increase of feed velocity and bed thickness due to the huge amount of feed air, resulting in the increase of pressure drops and the possible reduction of adsorbent utilization. To make it worse, the pressure drop of the adsorber is positively correlated with the required discharge pressure and energy consumption of the air compressor, which is the main energy consumption equipment of the ASU. From this point of view, the long-term economic benefits of ASUs would be reduced due to the increasing pressure drops of adsorbers. In order to deal with such issue, we propose a novel radial adsorber with parallel layered beds in parallel passages given by Fig. 1, which has a much larger inlet area than the single-passage adsorber. The main purpose by doing so is to further reduce the pressure drop and increase the adsorbent utilization with a relatively compact structure, aiming to provide an alternative adsorber with long-term energy-saving potentials for large-scale ASUs. In the present work, the possibility of applying the novel adsorber to large-scale ASU is theoretically validated. The novel adsorber is modeled in the cylindrical coordinate system. The geometric dimensions is calculated based on a proposed scheme, and the air distribution uniformity inside the adsorber is studied using numerical simulation. The performance evaluation of the novel adsorber is performed and compared with the single-passage radial adsorber in terms of pressure drop, adsorbent utilization and geometric 4


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dimensions. 2. Adsorption model In the cryogenic ASU, the layered beds of the adsorber generally include two beds: the activated alumina bed and the 13X zeolite molecular sieve bed. The activated alumina bed has strong adsorbability over moisture, and the 13X zeolite molecular sieve bed is able to adsorb both moisture and carbon dioxide. Usually the moisture and carbon dioxide in the feed air should be removed to be less than 0.1ppm and 1.0ppm3, respectively. In the present work, a novel radial adsorber is proposed with parallel layered adsorbent beds in parallel airflow passages, and the structure of it as well as the conventional single-passage adsorber is shown in Fig. 1. Due to the parallel structure, a much larger inlet area can be achieved by the novel adsorber, contributing to the reduction of the inlet velocity of the feed air. Since excessive amount of air may pass through the beds at the section near the bottom, cone distributors are employed to improve the airflow distribution uniformity20, 21. Fig. 1 The adsorption model of parallel beds is built in cylindrical coordinate systems. In order to simplify the analysis, the following assumptions are made similar to the previous research 19, 22, 23: (1) The processed air follows an ideal gas law. (2) The density and porosity of activated alumina and 13X molecular sieve are fixed. (3) The thermal conductivity along the axial and circumference directions is neglected. (4) The fluid flows along the radial direction. (5) The concentration gradients along the axial and circumferential directions are neglected. 2.1 Mass conservation equation 5



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The mass conservation equation is given by19, 24 ∂yi ∂ ( yi u ) ρ p (1 − ε ) ∂qi + + = 0, i = 1, 2 , ε ∂t ∂r ∂t

(1)

where yi is the mole concentration of component i; t is the time (s); u is the interstitial velocity of −3 the gas phase ( m ⋅ s −1 ); r is the radius (m); ρ p is the particle density of adsorbents ( kg ⋅ m ); ε −1 is the voidage of adsorbent beds; qi is the adsorbing quantity of adsorbents ( mol ⋅ kg ). The

dispersion term is not involved in the mass conservation equation, while it is considered in the modified LDF model 25.

2.2 Energy conservation equation The energy conservation equation of the gas phase is given by23, 24 ∂Tg ∂t

−

KL

（

c p,g ρ p

∂ 2 Tg ∂r

2

+

∂T a (1 − ε ) 2( Do + L ) hw 1 ∂Tg (Tg − Ts ) + (Tg − Tw ) = 0 , ）+u g + hs s r ∂r ∂r c p,g ρ gε Do L c p , g ρ g ε

(2)

where KL is the thermal dispersion coefficient ( W ⋅ m−2 ⋅ K −1 ); c p , g is the specific heat capacity −1 −1 of gas phase( J ⋅ kg ⋅ K ); Tg , Ts and Tw denote the temperature of gas, layered beds and

adsorber wall, respectively; hs is the convective heat transfer coefficient between gas and beds, and hw is that between gas and the adsorber wall ( W ⋅ m −2 ⋅ K −1 ); as is the surface area per volume of the adsorbent particle ( m2 ⋅ m−3 ); Do and L denote the external diameter and axial height of the adsorber, respectively (m). As the feed air flows pass through the adsorbent beds, the heat transfer coefficients are not fixed. The mean heat transfer coefficient is usually obtained by experiments26, 27:

Nu =

hs Dp kg

= 2 + 1.1(

Dp G

µ

)0.6 (

c p,g µ kg

1

) 3,

(3)

6


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where Nu is the Nusselt number; Dp is the particle diameter (m); kg is the heat conductivity of the gas stream; G is the mass flow rate of the stream ( kg ⋅ m−2 ⋅ s −1 ); and µ is the dynamic viscosity of the gas stream ( Pa ⋅ s ). In Equation (2), hw can be determined by28:

hw = 3.404

kg ρ g uDp 0.9 −6 Dp Di ( ) e , (4) Di µ

where Di is the internal diameter of the adsorber. In Equation (2), KL can be determined by JH factor method29:

JH = (

KL ) pr 2/3 , Gc p , g

(5)

thus obtaining29:

KL =

J H Gc p , g pr 2/3

.

(6)

The dimensionless quantity Prandtl number is given by

pr = c p , g µ / k g .

(7)

J H is a function of Reynolds number given by29 J H = 2.26 Re −0.51 , 0.06 < Re < 300 J H = 1.28 Re −0.41 , 300 < Re < 6000

.

(8)

The energy conservation equation of the adsorbates is given by23, 24 2 ∂Ts ha ∆H i ∂qi − s s (Tg − Ts ) + ∑ =0, ∂t c p , s ρ p i =1 c p , s ∂t

(9)

−1 −1 where c p , s is the specific heat capacity of the adsorbents ( J ⋅ kg ⋅ K ); and ∆Hi represents the

adsorption heat ( J ⋅ kg −1 ). The energy conservation equation of the adsorber wall is given by23, 24

7



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∂Tw hw hair − (Tg − Tw ) + (Tw − Tair ) = 0 , ∂t c p , w ∆X w c p , w ∆X w ρ w

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(10)

−1 −1 where c p , w denotes the specific heat capacity of the adsorber wall ( J ⋅ kg ⋅ K ); ∆X w denotes

the thickness of the adsorber wall (m); hair denotes the free convection heat transfer coefficient (

W ⋅ m−2 ⋅ K −1 ); ρw represents the density of the adsorber wall ( kg ⋅ m − 3 ); Tair represents the ambient temperature (K). hair is given by28:

hair = 1.294(Tw − Tair )1/3 ,

(11)

where Tair denotes the ambient air temperature in the adsorber.

2.3 Adsorption isotherm Langmuir adsorption isotherm equation is widely used for the modeling of moisture and carbon dioxide adsorption. Considering the interactive influences of moisture adsorption and carbon dioxide adsorption, the Langmuir adsorption isotherm equation has been improved in order to obtain more accurate results30: qi =

qmi bi pi e di pi psi , i = 1, 2 j = 1, 2 and i ≠ j 1 + bi pi + b j p j

(12)

where qmi , bi and di are the model parameters, respectively; pi is the partial pressure; and ps is the saturated pressure. Compared with the traditional two-component A-D model, the model expressed by Equation (12) retains the advantage of the A-D model and avoids the occurrence of singular points when the pressure equals the saturated pressure.

qmi , bi and di are determined by the adsorption equilibrium data

24, 31, 32

. The adsorption heat

∆Hi in Equation (9) can be determined by 23: −∆H ∂ ln pi =[ ]N , 2 RT ∂T

(13)

8


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−∆H =

Rqm qB ( A2 + B2 − i 2 ) . qm qm

(14)

In Equation (14), the involved parameters for moisture and CO2 are shown in Tables 1 and 2, respectively.

Tables 1 and 2 2.4 Mass transfer model The modified LDF model is used to describe the mass transfer33

∂qi = kci (qi* − qi ) , ∂t

(15)

where kci is the modified mass transfer coefficient ( s −1 ), and qi* is the mean adsorption quantity ( mol ⋅ kg −1 ). The effect of dispersion term is considered 34

1 ρb DL 1 = + , (16) kc ε u 2 kc0 where kc is the modified heat transfer coefficient ( m2 ⋅ s −1 ); ρ b is the bulk density of the adsorbents ( kg ⋅ m 3 ); DL is the dispersion coefficient of mass transfer given by34

DL R S = γ 1 + γ 2 e c . (17) Dm ε Dm is the molecular dispersion coefficient ( m2 ⋅ s−1 ); Sc =µ / ( ρ Dm ) is the Schmidt number;

γ 1 and γ 2 are related parameters as shown in Table 3, respectively, where the Koch and Brady’s correlation is used35-38.

Table 3 The molecular dispersion coefficient is determined by the typical Chapman-Enskog correlation33:

9



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1 1 12 + ) MA MB , (18) pσ AB Ω D 3

0.001858T 2 ( Dm =

where M A and M B are the relative molecular mass of A and B, respectively; σ AB = (σ A + σ B ) 2 is the Lennard-Jones potential function, and the reference values of potential function are shown in Table S1 39.

Table S1 In Equation (18), ΩD is the collision integral between molecules as a function of TN = kT / ε AB , where ε AB = (

εA εB k k

)1/2 . ΩD can be determined from Table S2 according to the

value of TN 39, or determined by

ΩD =

1.06036 0.19300 1.03587 1.7647 + + + 0.15610 TN exp(0.47635TN ) exp(1.52996TN ) exp(3.89411TN )

(19)

Table S2 In equation (16), the mass transfer coefficient before modification ( kc0 ) is determined by 34: Rp Rp 2 1 = + kc0 3k f 15ε p Dk

(20)

where R p is the adsorbent particle diameter; ε p is the porosity of adsorbent particles; and k f is given by28, 40 k f = (2.0 + 1.1S c1/3 R e 0.6 )

Dm ,3 < R e < 10000 Dp

(21)

The porous diffusivity Dk in Equation (20) is given by34 Dk =

1

τp

[

3 π M 1/2 1 −1 ( ) + ] 4 rp 2 RT Dm

(22)

where rp is the micropore radius of adsorbent particles; R =3.8145J kg-1 is the gas constant; τ p is the bending factor of the adsorbent micropore given by Suzuki-Smith correlation34:

τ p = ε p + 1.5(1 − ε p )

(23) 10


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The partial differential equations should be discretized before being solved. Second-order and first-order partial derivatives are discretized by using central difference and backward difference, respectively. The initial conditions and boundary conditions should be determined in order to solve the model. For the adsorption process, the condition after desorption can be regarded as the initial condition, and the inlet condition of the feed air can be regarded as the boundary condition. For the desorption process, the condition after complete adsorption can be regarded as the initial condition. During the desorption process of the cryogenic ASUs, the adsorbents is usually purged by waste nitrogen, and hence the inlet condition of the waste nitrogen can be regarded as the boundary condition. The accuracy of the numerical model is critical to the reliability of the simulation results. In the present work, the adsorption model is based on mainly the work of Zhang et al

24, 30

, where the

adsorption model is verified with the experimental results of Kim31, Lee32 and Rege3. Zhang et al 24, 30

compared the adsorption isotherms of CO2 and H2O on activated alumina and 13X zeolite,

respectively, covering the temperatures of 293K, 313K, 333K, 353K with the pressure ranges of roughly 0-2.5kPa (H2O adsorption) and 0-101kPa (CO2 adsorption). The comparison indicates that the simulation results fit well with the experimental results.

3. Geometric dimension 3.1 Calculation scheme In this section, a scheme is proposed for calculating the geometric dimension of the adsorber. Some principles are followed to develop a computer program, which are listed below: (1) The sum of air flow rate of individual passages should equal to the total flow rate of feed air. 11



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(2) The adsorption time, desorption time and axial heights of layered beds in different passage should be about the same. (3) Pressure losses of layered beds in different passages should be close to each other and in a proper range, a reference range is about 0.23kPa m-1 to 70kPa m-1 for the adsorber of the ASU 41. (4) A reference range of the inlet velocity is about 0.05-0.2m s-1 for the adsorber of the ASU42. (5) The diameter-height ratio should be in a reasonable range.

Fig. 2 Based on the above principles, a calculation scheme is proposed, as shown in Fig. 2. Here a case study is performed for a large-scale ASU with an oxygen production of 120,000Nm3/h, which corresponds to an approximate air processing rate of 600,000 Nm3/h. The calculation results of both the parallel-passage and the single-passage radial adsorbers are shown in Table 4. According to Table 4, the adsorber volume can be determined, as shown in Fig. 3.

Table 4 The pressure loss of different adsorbers can be calculated by using the semi-empirical correlation43:

∆p (1 − ε ) 2 µ (1 − ε ) = 150 3 2 + 1.75 3 ρ u2 , L ε Dp ε Dp g

(24)

where ∆p is the pressure loss (Pa); L is the thickness of the adsorbent beds (m); The average pressure losses are shown in Fig. 4. It can be concluded from Equation (24) that a smaller particle diameter will correspond to a larger pressure drop of the bed layer.

Figs. 3 and 4 Figs. 3 and 4 show that the volume reductions of 27.8%, 31.7%, 32.9% and the pressure loss reductions of 10.8%, 56.4%, 78.4% can be achieved by using the two-passage, three-passage and 12


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four-passage structures, respectively. From this point of view, it is possible to reduce the pressure drop by using the novel adsorber for large-scale ASU, and the required pressure of the air compressor can thus be reduced, contributing to the energy consumption reduction of the whole ASU.

3.2 Uniformity of airflow distribution The uniformity of airflow distribution inside the adsorber should be ensured, since a poor uniformity may reduce the adsorbent utilization and the switching time, and may even lead to safety problems 20. In practical operation of the large-scale ASU, the adsorption pressure is about 0.54MPa and the desorption pressure is about 0.11MPa. In the present work, only the airflow distribution of the desorption process is studied, since it has higher uniformity requirement than the adsorption process21. Fig. 5 shows the airflow directions for both the single-passage adsorber and parallel-passage adsorber.

Fig. 5 There are static pressure differences between the inlet and outlet of layered beds. For the purpose of ensuring the airflow distribution uniformity, the variation of the static pressure differences along the axial direction should be small enough, which can be evaluated by 44

η p = 1−

max ∆p − min ∆p max ∆p

(25)

where max ∆p and min ∆p are the maximum and minimum pressure losses along the axial direction, respectively. Due to the inconvenience of measuring the static pressure and determining the maximum and minimum pressure differences, a velocity-based evaluating method is proposed

13



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to describe the airflow distribution uniformity45:

ηv = 1 −

∑ (ωϕ / υ − 1)

2

/ ( n − 1)

(26)

where ω is the inlet velocity of beds at different axial positions; ϕ is the voidage ratio at the inlet of bed; υ is the average velocity at the axial position. It can be found that Equation (25) emphasizes the pressure loss uniformity along the axial direction, and Equation (26) emphasizes the uniformity of inlet velocity of beds along the axial direction. In the present paper, pressure contours and velocity contours are both obtained by numerical simulation. Structured quadrilateral grids are employed to discretize the airflow passages, and porous media model is utilized to describe the layered beds.

Fig. 6 Fig. 6 shows the pressure contours of both single-passage and two-passage adsorbers. It shows that the two-passage adsorber has a smaller pressure drop, whereas it has a relatively low uniformity than the single-passage adsorber. The reason may be that the airflow passage is relatively narrow, especially at the bottom of the cone distributor. At that position, airflow velocity as well as the frictional losses will increase obviously, thus reducing the pressure. For the “Z” style airflow path, i.e. identical airflow inlet and outlet directions, the sectional area ratio of the inlet passage and the outlet passage is suggested to be 1.0 to 1.846. In this case, the structure of the two-passage adsorber is improved, as shown in Table 5. After improvement, the adsorber volume is about 359.4m3, which is 20.4% smaller than the single-passage adsorber (not considering the head cover).

Table 5 Figs. 7 and 8 show the pressure contour and velocity contour of the two-passage adsorber after improvement. The two figures indicate that the pressure losses and velocity along the axial direction 14


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are more uniform.

Figs. 7 and 8 4. Simulation and discussions In order to evaluate the adsorption and desorption performance of the parallel-passage adsorber, the simulation is carried out and the results is compared with those of the single-passage adsorbers. Similar to the practical operation of general ASUs, different flowing directions are followed by adsorption and desorption process, respectively. In the adsorption process, the feed air passes through the activated alumina layer first and then the 13X zeolite layer. In contrast, in the desorption process the purge gas is sent into the outlet of the adsorber and therefore passes through the 13X zeolite layer first and then the activated alumina layer. In the present work, the low-purity waste nitrogen extracting from the upper part of the low-pressure column is chosen as the purge gas, which is also similar to the practical operation of ASUs.

4.1 Adsorption simulation Most parameters involved in simulation are given directly or by correlations. The physical parameters of 13X and activated alumina as well as the adsorber can be obtained from previous research24, 28, and is shown in Table S3. The involved thermophysical properties of air is available from other research47, 48, and is given by Fig. S1.

Table S3 Figure S1 In the simulation, the temperature, pressure and air processing rate are set as 293.15K, 0.54MPa and 600,000 Nm3 ⋅ h −1 , respectively. The CO2 concentration is set as 450ppm. The moisture amount can be calculated using saturated condition, since the feed air is cooled in the precooler of the ASU 15



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by the cooling medium water before going into the adsorber, where the feed air becomes saturated moist air. It turns out to be about 2.7g/(kg dry air). As mentioned in Section 2.2, the spatial discretization is conducted for adsorbent beds. A number of 13 nodes and 18 nodes are respectively employed for the activated alumina bed and the 13X zeolite bed. The adsorption simulation for single-passage adsorber is carried out first. Fig. 9 shows the mole fraction variation of the carbon dioxide and moisture at the outlet of the single-passage adsorber with the simulation time of 72000s (20h). Fig. 9 shows that at the outlet of the adsorber the mole fraction of H2O is much lower than that of CO2, since the 13X zeolite and activated alumina have stronger adsorbability on H2O than CO2. In practical design of the ASU, it is generally considered that once the removal of CO2 meets the demands, the removal of H2O can also be ensured. In this case, we only consider the adsorption of CO2 here.

Fig. 9 The adsorption simulation for the two-passage adsorber is also conducted. Figs. 10 and 11 show the mole fraction variation of CO2 in airflow at different nodes of the 13X zeolite beds of two passages with the simulation time of 72000s (20h). It can be found that the two beds in different passages show similar concentration profiles, which is important to ensure the overall adsorption performance. Moreover, in practical operation of ASUs, 4 hours (14,400s) breakthrough time is generally needed to be ensured at present 21. The two figures show that at 14,400s the CO2 concentration is below 1ppm, meeting the prepurification requirement.

Fig. 10 and 11 Furthermore, Figs. 10 and 11 also show that the CO2 concentration in the airflow is even larger than 450ppm on the right side. A possible reason is that the concentration wave of moisture moves 16


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forward continuously during the adsorption process, and the adsorbed CO2 in adsorbents may be partly replaced by the moisture due to the stronger absorbability of adsorbents on moisture, thus yielding a concentration larger than original 450ppm. To demonstrate the analysis, the quantity of the adsorbed CO2 in the adsorbents is obtained and shown in Fig. 12, from which it can be found that the quantity of the adsorbed CO2 decreases after reaching the maximum value, confirming the above analysis. The roll-up of CO2 concentration brings adverse effect on the prepurification performance. First, it results in an unsteady CO2 adsorption capacity during an adsorption cycle. In other words, the adsorption capacity is reduced gradually during the process. In this case, it should take into consideration the capacity reduction when designing the bed thickness, and the most direct mean is to increase the designed bed thickness for safety, thus increasing the capital investment and the pressure drop. Furthermore, in the case of large-scale air feeds, which is the focus of the present study, the total quantity of the replaced CO2 released by all the upstream adsorbent may be relatively large, as can be seen from Figs. 10 and 11 that the final steady concentrations of downstream airflow nodes are increasing gradually. Therefore, in the case of large-scale air feeds, it may be a challenge for the downstream adsorbent to deal with airflow with an increasing CO2 concentration. In such case the reasonable bed design requires accurate experiment evaluation of the whole adsorption characteristics, making the issue rather complicated. There exists a promising material free of such adverse effect which is mentioned in Section 1: the isostructural metal-organic framework SIFSIX-3-Cu10, and rigorous experiments indicates that it is an excellent recyclable and moisture stable MOFs (metal-organic framework) after at least four cycles of CO2 adsorption and breakthrough runs under dry and humid conditions (74% RH). More importantly, the SIFSIX-3-Cu exhibits unprecedented CO2 uptake at trace CO2 concentration, 17



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which is highly consistent with the application condition of air prepurification (roughly 400ppm under 5 - 6 bar). According to the experimental results of Shekhah et al10, under the pressure of 500Pa and the temperature of 298K, the SIFSIX-3-Cu exhibits a CO2 uptake of 2.26 ∙ , which is the highest among the most promising MOFs and amine-supported materials10, 49. Here we give a comparison between the SIFSIX-3-Cu and the zeolite 13X mainly responsible for CO2 removal in the adsorber of the ASU. Giving the above temperature and pressure, we can easily calculate the CO2 uptake of zeolite as 0.28 ∙ by using the Equation (12). That is to say, the CO2 uptake of SIFSIX-3-Cu is about eight times as large as that of zeolite 13X. Furthermore, the SIFSIX-3-Cu shows extremely steep adsorption isotherms at very low pressure10, thus its CO2 removing ability will be even more powerful than the conventional zeolite adsorbent in case of highly diluted CO2 streams such as feed air. Considering the above fact, it is not difficult to image that if the SIFSIX-3-Cu is applied to the air prepurification, it will bring about great changes on the adsorber, especially in the case of large-scale ASU. The adsorber dimension and the bed thickness will be remarkably reduced, and those issues of air prepurification caused by the scaling up of the ASU, which are discussed in Section 1, will be completely solved. Although the SIFSIX-3-Cu is still costly at present, it is a kind of very promising alternative adsorbent due to the significant performance advantages, and it is worthy of more research efforts to promote its application in air prepurification of the ASUs.

Fig. 12 The concentration of CO2 in the airflow at the outlet is an important parameter, since it determines the breakthrough time of the bed. Fig. 13 shows the mole fraction variation of CO2 in the airflow for both single-passage and two-passage adsorbers. It can be found that the two beds of 18


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the two-passage adsorber have similar variation curves, thereby indicating similar adsorption performance and breakthrough time. Fig. 13 also shows that the two-passage adsorber has lower CO2 concentration than the single-passage adsorber. Therefore, the two-passage adsorber achieves a breakthrough time of about 24,000s, which is 23.1% larger than the single-passage adsorber (about 19,500s). A possible reason is that the novel adsorber enables a larger inlet area and a lower velocity of the feed air, thus increasing the contact time and the adsorbent utilization.

Fig. 13 Fig. 14 shows the temperature variation of the airflow at the inlet and outlet of the beds for both single-passage and two-passage adsorbers. Fig. 14 shows that the outlet temperature is higher than the inlet temperature due to the released adsorption heat, and at 72,000s (20h) the temperature difference is about 0.41oC for the two-passage adsorber and 0.18 oC for the single-passage adsorber.

Fig. 14 4.2 Desorption simulation In practical ASU, the adsorption process and the desorption process occur simultaneously in two adsorbers, and are switched about every 4 hours. Incomplete desorption of the adsorber may directly increase the residual impurity quantity in adsorbents and reduce the breakthrough time of the adsorption process. The desorption process usually includes the steps of depressurization, hot blow, cold blow and pressurization, of which hot blow and cold blow are the key steps for desorption. In the hot blow step, a waste nitrogen stream, which is usually heated to the temperature of about 200℃, is fed into the adsorber in a reversed flowing direction for about 1.5 hours to desorb the impurities. Subsequently, the adsorber is purged with a cold nitrogen stream for about 1.5 hours to reduce the 19



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bed temperature to recover the adsorption capacity. The simulation of the two key steps is performed here with the flow rate of 200,000 Nm3 ⋅ h−1 , the temperature of 200oC and the initial adsorbent temperature of 20 oC. Since the cone distributors are used to increase the airflow distribution uniformity in adsorption process, it is therefore difficult to ensure the uniformity in desorption process due to the reversed airflow direction which is commonly adopted by ASUs. Hence, it is really a challenge in heating the layer homogeneously considering the whole TSA cycle, thus affecting the quality of the desorption process. However, from another perspective, the adverse effect on the desorption performance may not be so obvious. In the depressurization step, the pressure throughout the adsorber will be reduced to roughly ambient pressure, accelerating the desorption process. This step will not be affected by the airflow distribution. For the second step, the adsorbent will be heated by the hot waste nitrogen with the temperature of about 200oC. This hot blow step will last about 1.5hours. It is really true that the temperature rising of the adsorbent will be inhomogeneous in the adsorber caused by the airflow distribution nonuniformity. However, considering that the heating process is sufficiently long and the purging gas amount is large enough, it is therefore possible that the adsorbent at different locations will finally achieve similar temperature by both hot airflow heating and heat conduction in the adsorbent. The cold blow step which also lasted for about 1.5hours can also exhibit similar performance like the cold blow effect. In summary, it is possible that the adverse effect of heating or cooling on the desorption process may not be very obvious. A relatively high outlet temperature is important to ensure the desorption effects. Figs. 15 and 16 show the outlet temperature of the purging gas (waste nitrogen) and the adsorbents for both 20


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single-passage and two-passage adsorbers. It can be found that after about 5000s of hot blow, the gas and bed temperature are all above 150℃, which is important for the thorough desorption. Fig. 16 indicates that the desorption performance of the two beds in the two-passage adsorber is similar. There is a sharp decrease of the purging gas temperature at the beginning of the simulation from 200oC, since it takes a short time for the cold beds to cool the initial hot purging gas.

Fig. 15 and 16 The outlet temperature is positively correlated with both the purging gas temperature and the flow rate, as shown in Fig. 17. Although increasing the flow rate of the purging gas is able to accelerate the desorption, it may consume too much processing gas and therefore decrease the production of oxygen and nitrogen of the ASU. Furthermore, more heating power is also consumed to heat the purging gas. Therefore, it should take into consideration the overall economic benefits when determining the amount of the purging gas.

Fig. 17 A relatively low outlet temperature is important to ensure the cold blow effects. The cold blow simulation is carried out with the waste nitrogen flow rate of 100,000 Nm3 ⋅ h−1 , waste nitrogen temperature of 20℃, initial adsorbent bed temperature of 200oC and operation pressure of 0.11MPa. Figs. 18 and 19 show the variation of outlet temperature of the purging gas during the cold blow step. It can be found that after 7000s outlet temperature can be cooled to below 30℃, which is appropriate to recover the adsorption ability. There is a sharp increase of the purging gas temperature at the beginning, since it takes a short time for the initial cold purging gas to be heated.

Figs. 18 and 19 Fig. 20 shows that the outlet temperature is negative correlated with the flow rate of the cold 21



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purging gas and positive correlated with the purging gas temperature. In other words, reducing the temperature and increasing the flow rate of the purging gas can both accelerate the recovery of adsorption ability. Similarly, economic benefits should also be taken into account when determining such parameters.

Fig. 20 4.3 Influences of material properties on adsorption performance The material properties of adsorbent is closely related the adsorption performance, and it is necessary to give an evaluation of some important factors. In terms of the adsorption kinetics, the present work employs the modified LDF model to describe the mass transfer model, as discussed in Section 2.4, where the modified LDF mass transfer coefficient kc is a critical parameter. Here we conduct an adsorption simulation with different kc to see how kc affects the CO2 concentration in airflow inside the bed, which is related to the final breakthrough time. As for the feed air, the CO2 is highly diluted, and the kc value employed in the present work is high enough for adsorption. Further increasing the kc may bring about very limited influence on adsorption, and thus we reduce the present kc of zeolite 13X toward CO2 to 0.1kc and 0.01kc and conduct the simulation, yielding Fig. S2.

Fig. S2 With the variation of the kc, the CO2 mole fraction in the airflow of a node in zeolite 13X bed is monitored. Fig. S2 shows that the CO2 mole fraction is negatively related with the kc. The reason is that a lower mass transfer coefficient is able to hinder the adsorption process, since the CO2 is more difficult to reach the adsorbent surface, resulting in a higher CO2 concentration in the airflow. However, it is also noticed that the curves of kc and 0.1 kc are rather close. A possible reason is that 22


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0.1 kc is large enough to meet the mass transfer requirement in the case of air prepurification since the CO2 concentration is highly diluted, and thus further increasing 0.1kc to kc will not lead to obvious influence on CO2 adsorption. Therefore, too large kc exhibits very limited benefit on the adsorption performance, while it may lead to the obvious increase of the material cost, which should be considered in practical design. The uptake of adsorbent is also an important parameter affecting the adsorption performance. For the air prepurification of the ASU, more attention is usually paid to the CO2 removal than the H2O removal, since the latter is easily to achieve because of the strong adsorption ability of adsorbent toward H2O. Therefore we only consider the CO2 uptake here. In the adsorber, the zeolite 13X is mainly responsible for the removal of CO2. Here we conduct adsorption simulation with five different levels of CO2 uptakes, that is, equaling to 60%, 80%, 100%, 120% and 140% of the present zeolite 13X uptakes, respectively.

Fig. S3 Fig. S3 shows the variation of CO2 mole fraction in the airflow of a node in the zeolite 13X bed, and it indicates that the adsorbent uptakes have great influence on the adsorption performance. Lower uptakes correspond to much steeper curves. The reason is that the adsorbent with higher CO2 uptake is able to adsorb larger amount of CO2 from the airflow in the bed, resulting in the decrease of CO2 mole fraction in the airflow. By comparing Fig. S3 with Fig. S2, we can find that the influence of CO2 uptakes on adsorption performance is more uniform than that of the mass transfer coefficient kc. It means that adsorbent with sufficiently high CO2 uptake will, to a considerable extent, increase the breakthrough time of the adsorber, and can further reduce the adsorbent amount, bed thickness and pressure drop. It is interesting to see that some new materials under research were 23



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reported recently characterized by the unprecedented CO2 uptakes under trace concentration10, 49, as discussed in Section 1 and Section 4.1. The selectivity of adsorbent toward different air component can also affect the adsorption performance. In the adsorber of ASUs, activated alumina layer is mainly responsible for H2O removal and zeolite 13X layer for CO2 removal. Their adsorbability over N2, O2 and Ar, which is the main components of the air, is much smaller than that over H2O and CO2, and are usually neglected in modeling. Meanwhile, the impurities such as some hydrocarbons can also be removed in beds, but their concentration is much lower than H2O and CO2, which is usually also neglected in modeling. In this case, only the removal of H2O and CO2 are considered. Although the zeolite 13X layer is mainly used for CO2 removal, it also has adorability over H2O, resulting in the adsorption competition between CO2 and H2O. This competition is already considered in Equation (12) through the term bjpj, and is also reflected by the simulation results from Fig. 10 to Fig. 12, which is discussed in detail in Section 4.1.

4.4 Adsorption isotherm verification It is important to conduct the experimental verification to ensure the reliability of the model and simulation results. In this section, the simulation results are verified with previous researchers’ experimental results. In terms of the adsorption isotherm data, we give a simple verification here by comparing the simulation results with the experimental results of Lee et al32. Since the main challenge of the adsorber for air prepurification is the CO2 removal by zeolite 13X layer, which is discussed in Section 3, we therefore only validate the adsorption isotherm data for CO2 on zeolite 13X. Fig. S4 shows the detailed comparison results. 24


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Fig. S4 In Fig. S4 the isotherm curves are plotted with the pressure varies from 0 to 120kPa, and two fixed temperatures are chosen: 333.15K and 353.15K. It can be found from Fig. S4 that there exist deviations between the simulation results and the experimental results. However, such deviations can be acceptable from the perspective of engineering calculation.

5. Conclusions In the present work, a novel radial adsorber with parallel layered beds in parallel airflow passages is proposed in order to further improve the adsorber performance of the large-scale ASU. The investigated ASU has an oxygen production of 120,000Nm3/h, corresponding to a feed air flow rate of about 600,000 Nm3/h. The evaluation of the novel adsorber is performed in terms of the pressure drop, the geometric dimensions and the adsorption and desorption performance, and the conclusions can be drawn as follows: (1) The airflow distribution uniformity of the novel adsorber can be ensured after improvement. (2) A scheme is proposed for the geometric size calculation of the novel adsorber. It shows the volume reductions of 27.8% and 31.7% by the two-passage and three-passage adsorbers compared with the single-passage one. (3) The novel structure is able to achieve a large inlet area and a relatively low inlet velocity of the beds, thus yielding a low pressure drop. The pressure drop reductions of 10.8%, 56.4% are achieved for compared with the single-passage one, respectively. (4) The two-passage radial adsorber achieves a breakthrough time 23.1% larger than that of the single-passage radial adsorber. It may demonstrate a better adsorbent utilization by the novel adsorber due to a longer contact time caused by a lower velocity. 25



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(5) The adsorption simulation indicates that higher purging gas temperature and flow rate in the hot blow step accelerate the desorption, and lower purging gas temperature and higher flow rate in the cold blow step accelerate the recovery of adsorption ability, while economic benefits should be taken into consideration.

Acknowledgment The authors would like to acknowledge the support provided by the National Basic Research Program of China (No. 2011CB706502).

Supporting Information Available There are additional supporting tables and figures which mentioned in the text. This information is available free of charge via the Internet at http://pubs.acs.org/.

Nomenclature ASU

Air separation unit

LDF

Linear driving force

as

Surface area per volume of the adsorbent particle ( m 2 ⋅ m −3 )

c p,g

Specific heat capacity of gas phase ( J ⋅ kg −1 ⋅ K −1 )

c p,s

Specific heat capacity of the adsorbents ( J ⋅ kg −1 ⋅ K −1 )

c p,w

Specific heat capacity of the adsorber wall ( J ⋅ kg −1 ⋅ K −1 )

Dk

Porous diffusivity

DL

Dispersion coefficient of mass transfer ( s −1 )

Dm

Molecular dispersion coefficient ( s −1 )

Do

External diameter of the adsorber (m)

Dp

Particle diameter (m) 26


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G

Mass flow rate of the stream ( kg ⋅ m −2 ⋅ s −1 )

∆Hi

Adsorption heat of component i ( J ⋅ kg −1 )

hair

Free convection heat transfer coefficient ( W ⋅ m−2 ⋅ K −1 )

hs

Convective heat transfer coefficient between gas and beds ( W ⋅ m−2 ⋅ K −1 )

hw

Convective heat transfer coefficient between gas and adsorber wall ( W ⋅ m−2 ⋅ K −1 )

JH

The JH factor concerning heat transfer

KL

Thermal dispersion coefficient ( W ⋅ m−2 ⋅ K −1 )

kc

Modified LDF mass transfer coefficient ( s −1 )

k c0

Unmodified LDF mass transfer coefficient of component i ( s −1 )

kg

Heat conductivity of the gas stream ( W ⋅ m−1 ⋅ K −1 )

kf

Mass transfer coefficient of flow phase film ( m ⋅ s −1 )

L

Axial height of the adsorber (m)

M

Relative molecular mass

Nu

Nusselt number

pi

Partial pressure of component i (Pa)

ps

Saturated pressure (Pa)

qmi

Parameter of Langmuir equation ( mol ⋅ kg −1 )

qi*

Mean adsorption quantity of component i ( mol ⋅ kg )

qi

Adsorbing quantity of the adsorbents of component i ( mol ⋅ kg )

R

External diameter of the adsorbent beds (m)

Rp

Adsorbent particle radius (m)

Sc

Schmidt number

−1

−1

27



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Tair

Ambient temperature (K)

Tg

Temperature of the gas (K)

Ts

Temperature of the layered bed (K)

Tw

Temperature of the adsorber wall (K)

t

Time(s)

u

Interstitial velocity ( m ⋅ s −1 )

∆X w

Thickness of the adsorber wall (m)

yi

Mole fraction of component i ( mol ⋅ mol −1 )

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Greek symbols −3

ρp

Density of the adsorbent particle ( kg ⋅ m )

ρb

Bulk density of the adsorbents ( kg ⋅ m )

ρg

Molar density of the gas ( mol ⋅ m−3 )

ε

Voidage of adsorbent beds

εp

Porosity of adsorbent particles

µ

Dynamic viscosity of the gas stream ( Pa ⋅ s )

ρw

Density of the adsorber wall ( kg ⋅ m −3 )

σ

Lennard-Jones potential function

ΩD

Collision integral between molecules

τp

Bending factor of the adsorbent micropore

−3

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40. Ahn, H.; Lee, C. H., Adsorption dynamics of water in layered bed for air‐drying TSA process. AICHE J. 2003, 49, 1601-1609. 41. Tang, X.; Gu, F., New questonsn and ansers of oxygen production. Metallurgical Industry Press: Beijing, 2001. 42. Feng, X., Adsorption separation technology. Chemical Industry Press: Beijing, 2000. 43. Pattipati, R. R.; Wen, C., Minimum fluidization velocity at high temperatures. Ind. Eng. Chem. Proc. Des. Dev. 1981, 20, 705-707. 44. Yan, W.; Guiping, L., Modeling and numerical simulation of onboard molecular sieve oxygen generation system. Trans. Nanjing Univ. Aeronaut. Astronaut. 2004, 21, 47-52. 45. Mu, Z.; Wang, J.; Wang, T.; Jin, Y., Optimum design of radial flow moving-bed reactors based on a mathematical hydrodynamic model. Chem. Eng. Process. 2003, 42, 409-417. 46. Kareeri, A.; Zughbi, H.; Al-Ali, H., Simulation of flow distribution in radial flow reactors. Ind. Eng. Chem. Res. 2006, 45, 2862-2874. 47. Lemmon, E. W.; Jacobsen, R. T.; Penoncello, S. G.; Friend, D. G., Thermodynamic Properties of Air and Mixtures of Nitrogen, Argon, and Oxygen From 60 to 2000 K at Pressures to 2000 MPa. J. Phys. Chem. Ref. Data 2000, 29, 331-385. 48. Lemmon, E. W.; Jacobsen, R. T., Viscosity and Thermal Conductivity Equations for Nitrogen, Oxygen, Argon, and Air. Int. J. Thermophys. 2004, 25, 21-69. 49. Nugent, P.; Belmabkhout, Y.; Burd, S. D.; Cairns, A. J.; Luebke, R.; Forrest, K.; Pham, T.; Ma, S.; Space, B.; Wojtas, L.; Eddaoudi, M.; Zaworotko, M. J., Porous materials with optimal adsorption thermodynamics and kinetics for CO2 separation. Nature 2013, 495, 80-84.

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Table 1 Parameters of adsorption isotherm model for moisture Model

Adsorbent 13X Al2O3 13X Al2O3

Zhang Langmuir

A1 2.296 0.0934 0.854 0.0174

A2 433.92 1030.8 837.31 1977.8

qm (mol / kg ) = A1e A2 /T ;

B1 4.191×10-9 7.504×10-3 3.317×10-5 1.013×10-4

B2 5189.3 490.85 1777.7 726.03

b( Pa −1 ) = B1e B2 /T ;

C1 4778.2 40548.1 — —

C2 -3446 -2987 — —

C1 0 0 — —

C2 0 0 — —

d = C1eC2 /T

Table 2 Parameters of adsorption isotherm model for CO2 Model

Adsorbent A1 13X 0.2202 Al2O3 1.31×10-4 13X 0.2202 Al2O3 1.31×10-4

Zhang Langmuir

A2 820.7 2604.5 820.7 2604.5

qm (mol / kg ) = A1e A2 /T ;

B1 9.169×10-7 5.762×10-3 9.169×10-7 5.762×10-3

B2 1567.1 191.57 1567.1 191.57

b( Pa −1 ) = B1e B2 /T ;

d = C1eC2 /T

Table 3 Correlations for calculating γ 1 and γ 2

γ1

γ2 0.5(1 +

0.73 Nonporous: 0.7 Porous particles: ≤ 20 / ε

13γ 1ε −1 ) Re Sc

Edwards and Richardson, Chem. Eng. Sci.,23,109(1968) Wakao Funazkri, Chem. Eng. Sci.,33,1375(1978)

0.5

3 π 2ε (1 − ε ) ε+ In(Re Sc) 4 6

1 σ v2

0.714

Ref.

+ (1 + σ v 2 ){γ (1 − p ) 2 + γ 2 p (1 − p )3 [e

Koch and Brady, J. Fluid Mech.,154,399(1985) −

1

γ p (1− p )

− 1]} 2 γ = 0.043 Re Sc / (1 − ε ), p = 0.33e( −24/ Re) + 0.17

Gunn, Chem. Eng. Sci., 2, 363 (1987)

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Table 4 Geometric parameters of radial adsorbers with different quantities of passages for air processing capacity of 600,000Nm3/h Thickness Thickness Adsorber Quantities Internal of 13X of Al2O3 Height(m) diameter of Number diameter(m) layer(m) layer(m) (m) passages 2.4 0.61 0.32 24.1 5.2 1 Ⅰ 0.78 0.55 0.23 Ⅰ 21.2 4.71 2 2.69 0.56 0.30 Ⅱ 0.29 0.39 0.14 Ⅰ 3 1.41 0.48 0.22 20.4 4.67 Ⅱ Ⅲ 2.91 0.48 0.25 0.14 0.28 0.10 Ⅰ 0.98 0.37 0.17 Ⅱ 4 20.5 4.62 2.12 0.38 0.20 Ⅲ 3.36 0.37 0.20 Ⅳ Table 5 Geometric parameters of the two-passage adsorber before and after improvement Quantities of passages Before improvement After improvement

2 2

Number

Internal diameter(m)

Ⅰ Ⅱ Ⅰ Ⅱ

1.32 3.47 1.32 3.47

Thicknes s of 13X layer(m) 0.44 0.54 0.44 0.54

Thickness of Al2O3 layer(m) 0.23 0.30 0.23 0.30

Height (m)

Adsorber diameter (m)

17.1

5.42

17.1

5.42

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Fig. 1 Schematic diagram of parallel-passage and single-passage radial adsorbers 1 - Inlet pipe 2 - Adsorbent discharging pipe 3 - Activated alumina 4 - 13X zeolite 5 - Alumina charging pipe 6 - Outlet pipe 7 - 13X zeolite charging pipe 8 - Sealing 9 – External cylinder 10 – Cone distributor 11 - Bottom cover 12 - Head cover

Fig. 2 Calculation scheme for geometric dimension of the parallel-passage adsorber

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Fig. 3 Adsorber volumes with different quantity of passages

Fig. 4 Average pressure losses of adsorbers with different quantity of passages

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Fig. 5 Airflow directions for single-passage and parallel-passage adsorbers in desorption process

Fig. 6 Pressure contours of single-passage and two-passage adsorbers (Pa)

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Fig. 7 Pressure contours of two-passage adsorber after improvement (Pa)

Fig. 8 Velocity contours of two-passage adsorber after improvement (m/s)

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Fig. 9 Mole fraction variation of CO2 and H2O in airflow at the outlet of single-passage adsorber

Fig. 10 Mole fraction variation of CO2 in airflow in the first zeolite 13X bed of two-passage adsorber

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Fig. 11 Mole fraction variation of CO2 in airflow in the second zeolite 13X bed of two-passage adsorber

Fig. 12 Amount of adsorbed CO2 in 13X zeolite beds of two-passage adsorber

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Fig. 13 Mole fraction variation of CO2 in airflow at outlet of both single-passage and two-passage adsorbers

Fig. 14 Temperature variation of airflow at inlet and outlet of beds for both single-passage and two-passage adsorbers 40


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Fig. 15 Outlet temperature of purging gas and beds for single-passage adsorber in hot blow step

Fig. 16 Outlet temperature of purging gas and beds for two-passage adsorber in hot blow step

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Fig. 17 Effects of purging gas temperature and flow rates on outlet temperature in hot blow step

Fig. 18 Outlet temperature of purging gas and beds for single-passage adsorber in cold blow step

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Fig. 19 Outlet temperature of purging gas and beds for two-passage adsorber in cold blow step

Fig. 20 Effects of waste nitrogen temperature and quantity on outlet temperature in cold blow step

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A Novel Radial Adsorber with Parallel Layered Beds for

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