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Early construction and operation of the highlycontaminated water treatment system in FukushimaDaiichi Nuclear Power Station (III) – a uniquesimulation code to evaluate time-dependent Csadsorption/desorption behavior in column systemKenta Inagakia, Takatoshi Hijikataa, Takeshi Tsukadaa, Tadafumi Koyamaa, Keiji Ishikawab,Shoichi Onob & Shunichi Suzukiba Nuclear Technology Research Laboratory, Central Research Institute of Electric PowerIndustry, 2-11-1 Iwado-kita Komae-shi, Tokyo 201-8511, Japanb Tokyo Electric Power Company, 1-1-3 Uchisaiwai-cho,Chiyoda-ku, Tokyo 100-8560,JapanPublished online: 19 Jun 2014.

To cite this article: Kenta Inagaki, Takatoshi Hijikata, Takeshi Tsukada, Tadafumi Koyama, Keiji Ishikawa, ShoichiOno & Shunichi Suzuki (2014) Early construction and operation of the highly contaminated water treatmentsystem in Fukushima Daiichi Nuclear Power Station (III) – a unique simulation code to evaluate time-dependent Csadsorption/desorption behavior in column system, Journal of Nuclear Science and Technology, 51:7-8, 906-915, DOI:10.1080/00223131.2014.921580

To link to this article: http://dx.doi.org/10.1080/00223131.2014.921580

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Journal of Nuclear Science and Technology, 2014Vol. 51, Nos. 7–8, 906–915, http://dx.doi.org/10.1080/00223131.2014.921580

ARTICLE

Early construction and operation of the highly contaminated water treatment system in FukushimaDaiichi Nuclear Power Station (III) – a unique simulation code to evaluate time-dependent Cs

adsorption/desorption behavior in column system

Kenta Inagakia∗, Takatoshi Hijikataa, Takeshi Tsukadaa, Tadafumi Koyamaa, Keiji Ishikawab, Shoichi Onob andShunichi Suzukib

aNuclear Technology Research Laboratory, Central Research Institute of Electric Power Industry, 2-11-1 Iwado-kita Komae-shi,Tokyo 201-8511, Japan; bTokyo Electric Power Company, 1-1-3 Uchisaiwai-cho,Chiyoda-ku, Tokyo 100-8560, Japan

(Received 13 January 2014; accepted final version for publication 6 April 2014)

A simulation code was developed to evaluate the performance of the cesium adsorption instrument op-erating in Fukushima Daiichi Nuclear Power Station. Since contaminated water contains seawater whosesalinity is not constant, a new model was introduced to the conventional zeolite column simulation codeto deal with the variable salinity of the seawater. Another feature of the cesium adsorption instrument isthat it consists of several columns arranged in both series and parallel. The spent columns are replacedin a unique manner using a merry-go-round system. The code is designed by taking those factors intoaccount. Consequently, it enables the evaluation of the performance characteristics of the cesium adsorp-tion instrument, such as the time history of the decontamination factor, the cesium adsorption amountin each column, and the axial distribution of the adsorbed cesium in the spent columns. The simulationis conducted for different operation patterns and its results are given to Tokyo Electric Power Company(TEPCO) to support the optimization of the operation schedule. The code is also used to investigate thecause of some events that actually occurred in the operation of the cesium adsorption instrument.

Keywords: Fukushima Daiichi Nuclear Power Station; adsorption; simulation; contaminated water; zeolite

1. Introduction

The radioactive wastewater treatment facility inFukushima Daiichi Nuclear Power Station is in service.Cesium in the accumulated water has been treated us-ing the cesium adsorption instrument developed by Ku-rion. The cesium adsorption instrument consists of anumber of zeolite columns. The contaminated water isrun through the columns so that the cesium ions are ad-sorbed on the zeolite. When the amount of adsorbedcesium comes close to its limit, the columns are re-placed with new ones. In the operation of this cesiumadsorption instrument, the operation schedule (flowrate and time to change columns) should be carefullyoptimized because the “decontamination factor (DF)”should never fall below the prescribed value. The DF isthe ratio of the initial concentration of the contaminatedwater to the final concentration resulting from the oper-ation of the cesium adsorption instrument. The DF caneasily be maintained high by replacing columns as of-ten as possible. However, the number of spent columns

∗Corresponding author. Email: inagaki@criepi.denken.or.jp

should be minimized because they are wastes and theamount of cesium adsorbed in each column should notbe very high because it will result in the high surface ra-diation of the spent columns, which can harm the safetyof the workers. Hence, to find an optimized solution un-der these conditions, a simulation code could be a strongtool to predict the performance of the cesium adsorptioninstrument.

The kinetic behavior of a zeolite column system hasalready been modeled and implemented in simulationcodes such as “versatile reaction-separation model forliquid chromatography (VERSE-LC)” code [1]. How-ever, the cesium adsorption instrument in FukushimaDaiichi Nuclear Power Station is unique in that a num-ber of columns are connected both in parallel andseries, and they are operated in the so-called merry-go-round system. The detailed explanation for themerry-go-round system is given in Section 3.1. Anotherunique feature is that seawater is included in the con-taminated water and its salinity is not constant over the

C© 2014 Atomic Energy Society of Japan. All rights reserved.

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operation period, which varies the adsorption perfor-mance. Therefore, in the present study, the simulationcode for the cesium adsorption instrument is devel-oped by taking the above factors into account. A single-column analysis module is first developed using ourexperience on an engineering-scale zeolite column sys-tem for the decontamination of high-level molten saltwaste from the pyro-reprocessing of the spentmetal fuelsof fast breeder reactor [2]. Several experiments are con-ducted to estimate some physical parameters necessaryfor the simulation code. After the single-column analy-sis module is validated, a simulation code for the cesiumadsorption instrument is developed by allocating severalsingle-column analysis modules so that it simulates theactual system. Then, the simulation is conducted andits results are used to support the operation scheduleoptimization. The simulation code is also used to in-vestigate the cause of some initial events that actuallyoccurred in the cesium adsorption instrument operatedin Fukushima Daiichi Nuclear Power Station.

2. Single-column analysis module

2.1. Physical modelThe physical model used in the single-column anal-

ysis module is based on that adopted in the VERSE-LCcode. A column is filled with zeolite particles with in-ternal macropores as illustrated in Figure 1. The soluteconcentration cb in the interparticle liquid and the con-centration cp in the intraparticle liquid are the variablesto be calculated. The behavior of cb is predominated bythe solute dispersion, the convection in the flow throughthe column, and the solute transportation from the in-terparticle liquid into the intraparticle liquid. The trans-portation process is described on the basis of the filmdiffusion assumption. The resistance against the solutetransportation on the particle surface is modeled by as-suming a thin film around the particle throughwhich thesolute diffuses. The behavior of cp is controlled by the so-lute transportation into the particle, the solute diffusionalong the radial direction within the particle pores, andthe solute adsorption on the internal surface of the solid.

Figure 1. Configuration of the single column and its model.

2.2. Governing equationsGoverning equations are formulated on the basis of

the following assumptions:

– only one type of solute is involved;– there is no radial concentration gradient in a col-

umn;– the volumetric flow rate through a column is

constant;– adsorption solid media have porous particles

and all particles are the same in size;– there is no angular concentration gradient

within a particle;– surface diffusion with Fickian pore diffusion is

negligible;– there is local equilibrium between the solute con-

centration adsorbed on the solid and the soluteconcentration in the liquid, and the adsorptionequilibrium between the liquid and the solid isgiven by the Langmuir equation.

The one-dimensional transport equation for the in-terparticle liquid concentration is given by

∂cb∂t

= Db∂2cb∂x2

− u∂cb∂x

− 3kf (1 − εb)Rεb

(cb − cp|r=R),

(1)

with the following boundary conditions:

x = 0, Db∂cb∂x

= u(cb − c0), (2-a)

x = L,dcbdx

= 0. (2-b)

In Equation (1), the first and second terms on theright-hand side are the dispersion and convection, re-spectively. The third term corresponds to the transportof the solute from the interparticle liquid to the intra-particle liquid. The one-dimensional transport equationfor the intraparticle liquid concentration is given by

∂cp∂t

= εp(εp + (1 − εp)

∂q∂cp

) × Dp

(∂2cp∂r 2

+ 2r

∂cp∂r

).

(3)

The right-hand side of Equation (3) is the diffusionequation in the polar coordinate multiplied by the coef-ficient that corresponds to the reduction of the solute inthe intraparticle liquid due to the adsorption. Boundaryconditions are given by

r = 0 :∂cp∂r

= 0, (4-a)

r = R : εpDP∂cp∂r

= kf(cb − cp|r=R

). (4-b)

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The amount of solute q (mol/g) adsorbed in the zeo-lite can be estimated by substituting cp into the followingLangmuir adsorption equation:

q = acp(1 + bcp

) . (5)

2.3. Estimation of the parametersThe coefficients a and b in Equation (5) depend on

both the type of zeolite and the salinity of the water csw(%). In the cesium adsorption instrument, Herschelitezeolite (H), silver impregnated engineered Herschelite(AGH), and surfactant modified zeolite (SMZ) are used.Langmuir coefficients for H are estimated from the re-sults of batch equilibrium tests conducted for differentsalinity of water in Central Research Institute of Elec-tric Power Industry (CRIEPI) [3]. An artificial sea saltwas used to control the salinity of the water in the tests.Consequently, the relationships between the Langmuircoefficients for H and csw are given by interpolating thediscretely measured data as

a = (1803 − 513csw) × 10−6, (6-a)

b = (1138 − 356csw) × 10−3, (6-b)

which are valid in the range 1.0 ≤ csw ≤ 2.0 (%). AGH isa herschelite impregnated with silver and its adsorptioncapacity was proved to be similar to that of H [4]. There-fore, the same formulations are used for AGH. The coef-ficients for SMZ are measured only for csw = 3.0, wherea = 0.00011 and b = 0.307. Coefficients for SMZ forother salinity are not necessary in this study becauseSMZ zeolite was used only in the beginning of the opera-tion of the cesium adsorption instrument, where salinityof the contaminated water was around 3.0%.

The values of the kinetic parameters Db and kf inEquation (1) and Dp in Equation (3) are estimated us-ing the models cited in the literature. Chung and Wen’smodel [5] is used for estimating the axial dispersion co-efficient Db expressed as

Db = 2Ruεb0.2 + 0.011Re0.48

. (7)

The Reynolds number Re in Equation (7) is givenby

Re = 2Ruεbν

. (8)

The model of Wilson and Geankoplis [6] is adoptedfor the estimation of the film mass transfer coefficient kfgiven by

[kfuεb

]Sc2/3 = 1.09

εbRe−2/3. (9)

The Schmidt number Sc in Equation (9) is definedby

Sc = ν

D∞, (10)

where D∞ is the diffusivity of the ion in the free streamin the water.

The effective intraparticle diffusivity Dp is consid-ered to be lower than D∞ owing to the bends along thepore paths, and its value is estimated by

Dp = D∞5

, (11)

as suggested by Smith [7].The values obtained from Equations (7)–(11) are

only rough estimates because these kinetic parametersare also affected by other factors such as the type of ad-sorption medium, the configuration of the system, thepresence of other types of cations, and so on. Therefore,it is necessary to modify the values for each column sys-tem to precisely evaluate those parameters. In this study,the values of the parameters for each configuration arefirst estimated using the above-mentioned models, andthen adjusted by fitting the simulation results to themea-sured DF as described in Section 2.7.

2.4. Model for the variable salinityIn the contaminated water accumulated in the

Fukushima Daiichi Nuclear Power Station, the salinitycsw is not constant over the operation period because ad-ditional cooling water is continuously supplied. On theother hand, the model explained in Section 2.1 is basedon the assumption that the Langmuir constants a andb in Equation (5) are not variables. Hence, the modelshould be modified to take variable Langmuir constantsinto account. If the Langmuir isotherm constants arechanged from a and b to aʹ and bʹ, for example, owingto the salinity change, Equation (5) does not hold any-more. This is solved by considering a new equilibriumstate where a certain amount of solute is transferred be-tween the intraparticle liquid and the solid surface. Theamount� to be transferred for the new equilibrium statecan be determined by solving

q + �

m= a′(cp − �/v)

1.0 + b′(cp − �/v)(12)

where m is the mass of the adsorbent solid and v is thevolume of the fluid. In the simulation code, the valuesof q and cp are revised by solving Equation (12) at everytime step when the value of csw changes.

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2.5. FlushingDuring the operation of the cesium adsorption in-

strument in the Fukushima Daiichi site, the injection ofthe contaminated water is temporarily stopped and thewater without contamination (pure water or seawater) ispassed through the columns to reduce the surface radi-ation of the pipes. This process is called flushing. In ourcalculation, flushing can be simulated by setting c0 = 0during such a period of operation. However, we mustpay attention to the treatment of desorption that canoccur during flushing. When the column is flushed withseawater, cesium ions move back from the intraparticleliquid to the interparticle liquid because the cesium con-centration in the interparticle liquid decreases as cb < cp.This occurs because adsorbed cesium ions are replacedwith other cations, such as Na ions, contained in the sea-water. This behavior is automatically taken into accountby solving Equation (1). On the other hand, if pure wateris used for flushing, desorption may not occur owing tothe absence of replacing cations. Hence, desorptionmustbe inhibited during pure water flushing. In our simula-tion code, this was performed by setting kf = 0 temporar-ily during the period of pure water flushing.

2.6. Numerical methodA single column filled with zeolite is spatially dis-

cretized into one-dimensional Nb grids using a particlemodel that corresponds to a zeolite solid, as shown inFigure 1. The particle model consists of Np polar coor-dinate grids. On the basis of this model, Equations (1)and (3) are discretized into Equations (13) and (14), re-spectively.

cn+1b,i − cnb,i

�t= Db

cn+1b,i+1 − 2cn+1

b,i + cn+1b,i−1

�x2

− ucn+1b,i − cn+1

b,i−1

�x− 3kf (1 − εb)

Rεb

×(cn+1b,i − cn+1

p,i, j=1

), (13)

cn+1p,i, j − cnp,i, j

�t= MDp

(cn+1p,i, j+1 − 2cn+1

p,i, j + cn+1p,i, j−1

�r 2

+ 2r

cn+1p,i, j+1 − cn+1

p,i, j

�r

), (14)

M= εp(εp + (1 − εp)

∂q∂cnp,i, j

) . (15)

Here, the upper index n is the time index, the lowerindex i corresponds to the axial position along the col-umn, and the lower index j corresponds to the radial po-sition in the particle. The backward difference approxi-mation is used for time dimension derivatives. The valueof the term ∂q/∂cp in Equation (3) is approximated us-ing the value calculated in the previous time step to ex-

clude nonlinearity. Equations (13) and (14) are relocatedso that the unknown terms are placed on the left-handside and the known terms on the right-hand side.

(−Db�t�x2

)cn+1b,i+1

+(1.0 + 2Db�t

�x2+ u�t

�x+ 3kf (1 − εb)�t

Rεb

)cn+1b,i

+(−Db�t

�x2− u

�t�x

)cn+1b,i−1

−(3kf (1 − εb)�t

Rεb

)cn+1p,i, j=1 = cnb,i , (13’)

−MDp

(�t�r 2

+ 2�tr�r

)cn+1p,i, j+1

+(1.0 + MDp

(2�t�r 2

+ 2�tr�r

))cn+1p,i, j

−MDp�t�r 2

cn+1p,i, j−1 = cnp,i, j . (14’)

Equations (13ʹ) and (14ʹ) hold for the number of col-umn grids, Nb, and the number of particle grids, Nb

∗Np,respectively. Consequently, the discretized equations re-duce to sets of linear simultaneous equations and can bewritten in the matrix form as

Acn+1 = cn, (16)

where the vectors cn + 1 and cn are defined as

cn+1 = [cn+1p,i=1, j=1, ...c

n+1p,i=1, j=Np

...cn+1p,i=Nb, j=Np

,

cn+1b,i=1...c

n+1b,i=Nb

]T, (17)

cn = [cnp,i=1, j=1, · · · cnp,i=1, j=Np

· · · cnp,i=Nb, j=Np,

cnb,i=1 · · · cnb,i=Nb

]T. (18)

Matrix A in Equation (16) is the [(Np + 1)∗Nb] ×[(Np + 1)∗Nb] matrix, the component of which consistsof the coefficients in Equations (13ʹ) and (14ʹ). The solu-tion for cn + 1 is determined by calculating the inverse ofmatrix A by iteration methods. In the present code, theconjugate gradient method [8] is adopted.

2.7. Verification of the single-column analysismodule

Small-column tests were conducted by CRIEPI [9]to compare experimental results with our simulationresults. In these tests, the cesium-containing water ispassed through a small column (6 cm in axial lengthand 3 cm in diameter) filled with mordenite. The cesiumconcentration of the effluent is measured to evaluate thebreakthrough curve. The concentration of cesium in theinflowwater is 20, 50, or 200 ppm. The value of 20 ppm ischosen because it is high enough compared to the lower

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Figure 2. Numerical and experimental results for break-through curve in the small-column test.

measurement limit of the atomic absorption analyzerused in the test. Other initial concentration cases (50 and200 ppm) are conducted to investigate their influence onthe kinetic parameters. The simulation is performedwiththe following values of parameters: �x = 0.0015, �r =0.00005, Nb = 40, Np = 10, and �t = 0.2. The calcu-lations are conducted for several times by changing thevalues of kinetic parameters (Db,Dp, and kf), so that thesimulation results fit reasonably with the experimentallyobtained breakthrough curve. Consequently, the simula-tion results are in good agreement with the experimentalresults, as shown in Figure 2. The adjusted values of thekinetic parameters are shown inTable 1. It turns out thatthe behavior of the breakthrough curve strongly dependson the values of kf andDp, whereas it is almost indepen-dent of Db. The values adjusted by data fitting are com-pared with those estimated using the model described inSection 2.2, as shown in Table 1. Although the estimatedvalue ofDb could be used without adjustment, the othertwo adjusted parameters show large deviations from theestimated values. It is confirmed that the single-columnanalysis module is suitable for the simulation of actualzeolite columns as long as the values of kinetic parame-ters are appropriately determined.

3. Simulation of the cesium adsorption instrument

3.1. Development of the simulation code for thecesium adsorption instrument

In the cesium adsorption instrument in theFukushima Daiichi site, contaminated water is passed

through four lines running in parallel and each lineconsists of one S column and three H columns arrangedin series followed by one AGH column, as illustrated inFigure 3. The S and H columns are filled with silica sandand H, respectively. This system is designed so that oilis removed by the S column, cesium is adsorbed by theH columns, and iodine and the remaining cesium areremoved by the AGH column. Although the S columncontains SMZ in the beginning, it is replaced with silicasand as explained in detail in Section 4.3.

In the actual operation of the cesium adsorption in-strument, themerry-go-round system is adopted, i.e., af-ter a certain period of operation, the first H column inH1-1 is detached from the line, then the columns in H1-2 and H1-3 are transferred to the positions of H1-1 andH1-2, respectively, and a new column is installed in H1-3. The same process is performed for lines 2, 3, and 4.AGH columns are also replaced with new ones when theamount of cesium adsorbed becomes high.

In the extended code to simulate the cesium adsorp-tion instrument, 20 single-column analysis modules arerun in parallel, where 4modules are for S columns, 12 forH and 4 for AGH. The way of the calculation for eachcolumn is similar to the single-column analysis men-tioned in Section 2, except that the inflow cesium con-centration c0 is determined based on the concentrationof the outflow from the upper columns. For example,the value of cesium concentration of the output liquidof H1-1 is given to the module for H1-2, as c0 at eachtime step. In this extended code, a data-set calculatedin one module corresponds to an actual column. There-fore, merry-go-round system can be simulated by trans-ferring the data-sets according to the actual movementof columns. For example, when the column exchange isconducted in H1 line, data-set from H1-1 module is pre-served as a spent column data. Data-sets fromH1-2 andH1-3 are transferred to H1-1 and H1-2 modules, respec-tively. All the variables in H1-3 module are set to zerobecause new column is located there.

The whole operation period is divided into severalsubperiods assuming that all parameters are constantwithin each subperiod. The following parameters aregiven as inputs for each subperiod:

– start and end times of the normal operation;– start and end times of flushing;– flow rate in each line;– column exchange time for lines 1–4;

Table 1. Estimated and adjusted values of kinetic parameters obtained in the small-column test equipped with mordenite.

Adjusted values

Kinetic parameters Estimated values 20 ppm 50 ppm 200 ppm

Db 1.21× 10−5 1.21× 10−5 1.21× 10−5 1.21× 10−5

Dp 5.88× 10−10 4.70× 10−9 1.89× 10−9 9.41× 10−10

kf 6.89× 10−5 4.70× 10−5 2.57× 10−5 1.61× 10−5

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Journal of Nuclear Science and Technology, Volume 51, Nos. 7–8, July–August 2014 911

Figure 3. Allocation of the single-column analysis modules for the cesium adsorption instrument simulation.

– salinity of the contaminated water csw; and– inflow cesium concentration c0.

Consequently, the simulation of cesium adsorptioninstrument is enabled. This code is also useful for casestudies for unusual operations of the instrument, e.g.,reutilization of a spent column in the cesium adsorptioninstrument can be easily simulated by giving the data setfor the spent column to the corresponding module.

3.2. Verification of the simulation codeThe simulation of the cesium adsorption instrument

is done for the operation from June to August 2011,where the values of kinetic parameters Dp, Db, andkf are estimated from Equations (7)–(11). The calcu-lated DF is compared with that measured as shown inFigure 4. They are in good agreement. On the otherhand, as already discussed in Section 2.7, there is apossibility that the values of the kinetic parametersDp and kf should be modified to obtain appropri-

Figure 4. Time history of DF measured in the cesium ad-sorption instrument during actual operation and simulationresult.

ate results. To confirm the validity of the estimatedvalues for kinetic parameters, the same calculation isconducted with making values for Dp and/or kf twotimes larger or smaller. The results of those calcula-tions are in less agreement compared to the originalone. This indicates the validity of the estimated val-ues for kinetic parameters. Consequently, it is con-firmed that the simulation code can be used for theprediction of the system performance with adequateaccuracy.

4. Application

4.1. Optimization of the operation scheduleThe DF value must be maintained higher than the

target value to prevent the contaminated water fromleaking. The behavior of the DF is mainly affected bythe flow rate and column exchange interval. It is ap-parent that the DF value can be maintained well byreducing the flow rate or changing the columns as of-ten as possible. On the other hand, less frequent col-umn change is desired to reduce the number of spentcolumns and the amount of manual labor. It is also re-quired that the amount of cesium accumulated in a col-umn should not be very high because the surface radi-ation of columns can harm the safety of the workers.Therefore, fictitious calculations for one month opera-tion of the cesium adsorption instrument are conductedwith different flow rates and column change frequen-cies. The obtained results are compared to find the bestoperation pattern where the DF value never falls belowthe target value while each column is optimally used. Inthis evaluation, the target DF value is set to 1.0× 105.The DF behavior of each operation pattern is shown inFigure 5. When the flow rate is 12 m3/h and the inter-val of column change is two days, the DF value becomeslower than the target value. On the other hand, when theflow rate is 6 or 8m3/h and the interval of column changeis two days, theDFbecomes stable at valuesmuch higherthan the target value. However, under such conditions,

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Figure 5. Calculated time dependence of DF with differentflow rate and column exchange intervals.

the throughput of the system is not sufficiently efficient.Consequently, it is verified that the flow rate should be10 m3/h if the interval of column change is fixed to twodays. It is also observed that the DF is higher when thevalues of (flow rate)× (time to change) are lower. Fromthese results, the optimal flow rate for each target DFvalue and the interval of column change can be esti-mated. The information obtained from these calcula-tions is continuously used in the determination of theactual operation schedule of the cesium adsorption in-strument operated in FukushimaDaiichiNuclear PowerStation.

4.2. Estimation of the amount of cesium adsorbedand its axial distribution in the spent columns

The absolute amount of cesiumadsorbed in each col-umn is also evaluated using the developed simulationcode and used to estimate the operation efficiency andpredict the radiation intensity on the column surfaceduring the operation. In Figure 6, the amount of cesiumadsorbed in columns in line 1 from July toAugust 2011 isshown as an example. The salinity of each subperiod isestimated from the concentration of Cl− ion measuredon the water after treatment. The horizontal axis indi-cates the date. The vertical dashed lines in Figure 6 cor-respond to the times of column change. In the earlierperiod (2 July to 3 August), most cesium is adsorbed inthe first column. Hence, the amount of cesium adsorbedin the second and third columns is small. In this period,such an amount is not sufficient from the viewpoint ofwaste minimization because the spent columns detachedfrom H1-1 still have some room to adsorb more cesium.In the latter period (3 August to 19 August), the flowrate and column change interval are altered so that alarger amount of contaminated water is passed beforechanging the columns. During this period, it can be ob-served that the second column starts to adsorb cesiumwhen the amount of cesium adsorbed in the first col-umn comes close to the adsorption capacity of the firstcolumn. It can be considered that the efficiency is im-proved in this period because cesium is adsorbed at anamount as high as the adsorption capacity of the firstcolumn when the column is detached. It should also benoted that a severely large decrease inDF is not observedduring this period, as shown in Figure 4. This is be-cause the third column works as a guard column. These

Figure 6. The amount of cesium adsorbed in the H columns in line 1 in the cesium adsorption instrument during actual operation.

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Figure 7. Axial distribution of the local cesium adsorption amount in the spent columns.

calculation results have been used to support the deter-mination of the optimum operation schedule of the ce-sium adsorption instrument.

The storage of the spent columns is also an impor-tant issue. In designing the storage facility for the spentcolumns, it is necessary to evaluate the axial distribu-tion of cesium in the columns because it affects both thesurface radiation of the spent columns and the behav-ior of the heat generation inside the column. Therefore,the axial distribution of the adsorbed cesium is calcu-lated using the developed code and some of the typicalresults are shown in Figure 7. Columns A, B, and C areselected as examples, which are used in line 1. A hori-zontal dashed line corresponds to the adsorption capac-ity per unit axial length in an equilibrium state for eachcolumn. The adsorption capacity differs in columns A,B, and C because it depends on the salinity of the con-taminatedwater and inflow cesium concentration. Thesecolumns were detached from the cesium adsorption in-strument on 8 July, 25 July, and 6 August, as indicatedin Figure 6. The conditions of the contaminated wa-ter during the operation of each column are shown inTable 2. The notable difference is that flushing was con-ducted before column A was detached. On the otherhand, no flushing was conducted when columns B and Cwere detached. As a result, in column A, the local peakof the adsorption amount is not found at the top edge(x/L = 0) of the column but at the position x/L = 0.2.This can be due to the desorption and dissolution of ce-

sium adsorbed at the top of the column in the flushingwater and its adsorption at a lower position. This be-havior was not observed in columns B and C becauseflushing was not conducted on these columns.When col-umn B was detached, the amount of cesium adsorbedin column B was less than the adsorption capacity ofcolumn B. In this case, it was observed that cesium wasmainly adsorbed in the upper half of the columns, asshown in Figure 7. This implies that the surface radi-ation of the spent columns is higher at the upper side ofthe spent columns. On the other hand, the amount of ce-sium adsorbed in column C is considered to be close tothe adsorption capacity of column C. Consequently, thelocal amount of cesium adsorbed in column C is con-stant along the axial length as shown in Figure 7, whichimplies that column C has high surface radiation at anyaxial position.

It was clarified that the axial distribution of cesium inthe spent columns differs depending on the conditions.These estimations can be used as reference data in themanagement of the spent columns.

Table 2. Conditions during the operation of columns A, B,and C.

csw (%) c0 (ppm) Flushing

Column A 2.0 0.7 1 hourColumn B 1.8 0.7 No flushingColumn C 1.5 0.5 No flushing

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Figure 8. Amount of cesium adsorbed in SMZ column andH columns in line 1.

4.3. Investigation of the cesium accumulation in Scolumn

The cesium adsorption instrument was activated on17 June 2011 and shortly stopped after several hoursof operation because the surface radiation of the S col-umn increased. One possible reason for this is that ce-sium adsorption occurred in the S column, althoughSMZ was considered to not adsorb cesium. To verifythis, some batch tests were conducted and results re-vealed that SMZ also adsorbs cesium in the presenceof seawater and its adsorption capacity is around 1/10thof that of H. To verify whether the cesium adsorptionof SMZ induced the surface radiation increase, a sim-ulation was conducted again taking SMZ adsorptioninto consideration. As shown in Figure 8, it was demon-strated through the simulation that 0.1 mol of cesiumwas adsorbed in the S column. This amount is relativelysmall compared with that adsorbed in the H columns.However, the shielding wall of the S column was thinnerand its shielding ability was approximately 1% of that ofthe H columns. Since the acceptable amount of cesiumin the H columns was designed to be 3.0 mol, the accept-able amount in the S column can be roughly estimatedto be 0.03 mol. Therefore, the 0.1 mol accumulation inthe S column was sufficiently high to induce the signif-icant increase in surface radiation. Hence, the simula-tion results confirmed that the cesium adsorption in theS column might be the reason for the surface radiationincrease. As a countermeasure, silica sand was placed inthe S column instead of SMZ.

5. Conclusions

A single-column analysis module was first developedwhere the conventionalmodel was improved to deal withthe variable salinity concentration. Some small-columntests were conducted to verify the single-column analy-sis code. Simulation results showed good agreement with

the results of the small-column tests by using appropri-ate values for kinetic parameters. The simulation of thecesium adsorption instrument in the Fukushima Dai-ichi Nuclear Power Station was performed by allocatingsingle-column analysis modules so that the actual col-umn configuration is simulated. The DF of the treatedwater calculated using the developed code showed goodagreement with that measured in the cesium adsorptioninstrument. After the code was validated, fictitious cal-culations were conducted for different flow rates and col-umn change frequencies, the results of which were usedto support the determination of the optimum operationschedule. Then, the cesium amount and its axial distri-bution were estimated in the spent columns. The codewas also used to investigate the cause of an initial eventthat actually occurred in the cesium adsorption instru-ment. The simulation results verified that the increase insurface radiation on the S column was due to the cesiumadsorption of SMZ.

Nomenclaturea: Constants in Langmuir isotherm (m3/g)b: Constants in Langmuir isotherm (m3/mol)c0: Cesium concentration of the inflow (mol/m3)cb: Cesium concentration in interparticle liquid

(mol/m3)cp: Cesium concentration in intraparticle liquid

(mol/m3)csw: Salinity of the contaminated water (%)Db: Axial dispersion coefficient (m2/sec)Dp: Effective intraparticle diffusivity (m2/s)kf: Film mass transfer coefficient (m/sec)L: Length of a column (m)Nb: Axial partition number of a columnNp: Radial partition number of a particleq: Amount of adsorption (mol/g)r: Radial position within a particle (m)R: Radius of a zeolite particle (m)t: Time (s)u: Fluid velocity (m/sec)x: Axial column position (m)εb: Interparticle void fractionεp: Intraparticle void fractionν: Kinematic viscosity (m2/sec)ρ: Mass density of adsorption medium solid (g/m3)

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