Post on 05-May-2022
2015 International Nuclear Atlantic Conference - INAC 2015
São Paulo, SP, Brazil, October 4-9, 2015 ASSOCIAÇÃO BRASILEIRA DE ENERGIA NUCLEAR - ABEN
ISBN: 978-85-99141-06-9
COMPUTATIONAL MODEL FOR A HIGH TEMPERATURE
ELECTROLYZER COUPLED TO A HTTR FOR EFFICIENT NUCLEAR
HYDROGEN PRODUCTION
Daniel González 1, Leorlen Rojas 1 , Jesús Rosales1 , Landy Castro1 , Abel Gámez1 ,
Carlos Brayner1 , Lázaro García 2 , Carlos García 2 , Raciel de la Torre 2 and Danny
Sánchez 3
1 Departamento de Energia Nuclear – Universidade Federal de Pernambuco
Ave. Prof. Luiz Freire, 1000
50740-420 Recife, PE
danielgonro@gmail.com
2 Instituto Superior de Tecnologías y Ciencias Aplicadas (InSTEC/ Cuba)
Av. Salvador Allende and Luaces
La Habana, Cuba
lgarcia@instec.cu
3 Universidade Estadual de Santa Cruz, Campus Soane Nazaré de Andrade,
Rodovia Jorge Amado, Km 16, Bairro Salobrinho
45662-900, Ilhéus, BA, Brasil
ABSTRACT
High temperature electrolysis process coupled to a very high temperature reactor (VHTR) is one of the most
promising methods for hydrogen production using a nuclear reactor as the primary heat source. However there
are not references in the scientific publications of a test facility that allow to evaluate the efficiency of the process
and other physical parameters that has to be taken into consideration for its accurate application in the hydrogen
economy as a massive production method. For this lack of experimental facilities, mathematical models are one
of the most used tools to study this process and theirs flowsheets, in which the electrolyzer is the most important
component because of its complexity and importance in the process.
A computational fluid dynamic (CFD) model for the evaluation and optimization of the electrolyzer of a high
temperature electrolysis hydrogen production process flowsheet was developed using ANSYS FLUENT®.
Electrolyzer’s operational and design parameters will be optimized in order to obtain the maximum hydrogen
production and the higher efficiency in the module. This optimized model of the electrolyzer will be incorporated
to a chemical process simulation (CPS) code to study the overall high temperature flowsheet coupled to a high
temperature accelerator driven system (ADS) that offers advantages in the transmutation of the spent fuel.
Keywords: High temperature electrolysis, nuclear hydrogen, electrolyzer efficiency, computational
fluid dynamic.
1. INTRODUCTION
Hydrogen economy is one of the most innovative energy concepts since the big oil time in the
20´s [1]. It proposes the substitution of fossils fuels as the baseline of the global energy system
for another energy carrier, hydrogen [2]. The difference between a fuel and an energy carrier
is that the energy carrier needs to be produced since it is not in pure state in nature and the fuel
need only be extracted.
INAC 2015, São Paulo, SP, Brazil.
Hydrogen production currently relies heavily on fossils fuels, since 90% of production comes
from steam reforming or low parameters conventional electrolysis [3]. Nuclear energy is
considered by many scientists as the main primary energy source to be used for a large-scale
hydrogen production. Two processes have the greater expectations of development, high-
temperature electrolysis and thermochemical water splitting cycles [4].
The study of the high temperature nuclear energy for hydrogen production has been increased
in recent years, has been created multinational projects such as EUROPAIRS (End-User
Requirements for industrial Process heat Applications with Innovative nuclear Reactors
for Sustainable energy supply) with the participations of 27 countries under the auspices of
the European Community [5]. Most of very high temperature reactor projects have been
assessed for determinate their capability to be used in the large-scale hydrogen production [6]–
[9].
2. HIGH TEMPERATURE ELECTROLYSIS. TADSEA.
Solid Oxide Electrolyzers (SOEC) have been studied especially in experimental research
focused, searching resistant materials according to high temperature and oxidation-reduction
environments [10]–[12]. However experimental investigations of these electrochemical
devices, which requires materials with special characteristics, are extremely expensive. Besides
these studies are complicated due to the difficulty of conductive extensive parametric analysis
to evaluate deeply the performance of the SOEC in response to the change in operating
conditions and design parameters, which has influence on the devices efficiency [13].
Physical-mathematical models can supply the challenges presented by experimental studies
and complement them so that can obtain a better understanding of the physical phenomena
occurring in the high temperature electrolysis process. That´s why in recent years have been
focused efforts on developing models that reproduce the operating conditions of the SOEC to
have a tool to characterize them with high levels of details and with less costs and limitations
[10], [14]–[18].
High temperature electrolysis (Fig. 1) unlike of low parameters electrolysis, requires an
external source of high parameters heat (over 900 oC) besides electricity, in this case is
proposed a pebbled bed very high temperature nuclear system (TADSEA) [19], [20].
Figure 1: Flowsheet diagram for a HTE process coupled to TADSEA.
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To assess the reliability of the TADSEA for hydrogen production by high temperature
electrolysis process is proposed a computational model using a chemical process simulation
software (CPS) Aspen HYSYS® [21]. However, the electrolyzer is not a standard component
of these chemical processes simulators [21], in addition to this the electrolyzer is the most vital
component in the HTE flowsheet, it is proposes to construct a detailed model of the SOEC
employing a CFD software (ANSYS FLUENT®) to optimized the SOEC and then incorporate
it to the CPS flowsheet as an add-on component.
3. HIGH TEMPERATURE SOLID OXIDE ELECTROLYZER.
High temperature electrolysis is a variant of the conventional one, in which rupture of the water
molecule is carried out on heated steam to 750oC-900oC reaching superior levels of efficiency
than low parameters electrolysis. The increased efficiency is due to the molar Gibbs energy of
the reaction (ΔG) decreases from 1,23 V at 25 oC to ~ 0,9 V at 900 oC [22].
Water splitting electrochemical reaction takes place in electrolytic cell or electrolyzer. A high
temperature solid oxide electrolytic cell is composed of an electrolyte, both electrodes (anode
and cathode) and two connectors [23]. Water is turned into steam, by an external heat source
(TADSEA) before entering the electrolyzer, this steam is supplied to the electrode where
decomposes into hydrogen and oxygen according to reaction 1:
𝐻2𝑂 + 2𝑒− → 𝐻2 + 𝑂2− (1)
Oxygen ions are recovered on the other electrode as molecular oxygen following the equation
2:
𝑂2− →1
2𝑂2 + 2𝑒− (2)
During operation of the SOEC voltage can be expressed by Nernst equations (3) and (4):
𝑉 = 𝐸 + 𝜂𝑎𝑐𝑡,𝑐 + 𝜂𝑎𝑐𝑡,𝑎 + 𝜂𝑜ℎ𝑚𝑖𝑐 (3)
𝐸 = 𝐸0 +𝑅𝑇
2𝐹𝑙𝑛 (
𝑃𝐻2𝐼 (𝑃𝑂2
𝐼 )0,5
𝑃𝐻2𝑂𝐼 ) (4)
Where E0, is the equilibrium potential, 𝜂𝑜ℎ𝑚𝑖𝑐 the ohmics losses, 𝜂𝑎𝑐𝑡,𝑎 y 𝜂𝑎𝑐𝑡,𝑐 overpotentials
losses at the electrodes, 𝑃𝐻2𝑂𝐼 partial pressure at the interface electrode-electrolyte, R (8,3145
J/molK) universal gas constant, F (96,485 C/mol) Faraday´s constant and T local temperature
[15].
3.1 CFD Model for HTE Electrolyzer.
For a detailed description of the physical phenomena occurring in the process of high-
temperature electrolysis is necessary to solve the governing equations of fluid dynamics as well
as expressions that define the electrochemistry of the problem. So the computational tool used
must be able to integrate, in an iterative process, the results of the fluid dynamic and
electrochemical calculations to obtain a full description of the problem [14].
3.1.1. Computational fluid dynamic model for the HTE electrolyzer. Equations.
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Development of the computational model for the SOEC is performed using the fluid dynamic
software ANSYS FLUENT®, which in addition to solving the equations of mass and energy
transfer has an additional module which allows to simulate electrolysis and fuel cells [24].
Heat and mass transfer in a SOEC.
The governing equations of CFD software [25] that will be solved in the problem domain are:
- Continuity: 𝜕(𝜌𝑈)
𝜕𝑥+
𝜕(𝜌𝑉)
𝜕𝑦+
𝜕(𝜌𝑊)
𝜕𝑧= 𝑆𝑚 (5)
-Momentum: 𝜕𝑢
𝜕𝑡+ 𝑢
𝜕𝑢
𝜕𝑥+ 𝑣
𝜕𝑢
𝜕𝑦+ 𝑤
𝜕𝑢
𝜕𝑧= −
1
𝜌
𝜕𝑝
𝜕𝑥+ 𝑢
𝜕2𝑢
𝜕𝑥2 + 𝑢𝜕2𝑢
𝜕𝑦2 + 𝑢𝜕2𝑢
𝜕𝑧2 (6)
𝜕𝑢
𝜕𝑡+ 𝑢
𝜕𝑣
𝜕𝑥+ 𝑣
𝜕𝑣
𝜕𝑦+ 𝑤
𝜕𝑣
𝜕𝑧= −
1
𝜌
𝜕𝑝
𝜕𝑦+ 𝑣
𝜕2𝑣
𝜕𝑥2 + 𝑣𝜕2𝑣
𝜕𝑦2 + 𝑣𝜕2𝑣
𝜕𝑧2 (7)
𝜕𝑢
𝜕𝑡+ 𝑢
𝜕𝑤
𝜕𝑥+ 𝑣
𝜕𝑤
𝜕𝑦+ 𝑤
𝜕𝑤
𝜕𝑧= −
1
𝜌
𝜕𝑝
𝜕𝑧+ 𝑣
𝜕2𝑤
𝜕𝑥2 + 𝑣𝜕2𝑤
𝜕𝑦2 + 𝑣𝜕2𝑤
𝜕𝑧2 (8)
-Energy: 𝐷𝐸
𝐷𝑡=
𝜕(𝑢𝜎𝑥𝑥)
𝜕𝑥+
𝜕(𝑣𝜎𝑦𝑦)
𝜕𝑦+
𝜕(𝑤𝜎𝑧𝑧)
𝜕𝑧+
𝜕(𝑢𝜏𝑦𝑥)
𝜕𝑦+
𝜕(𝑢𝜏𝑧𝑥)
𝜕𝑧+
𝜕(𝑣𝜏𝑥𝑦)
𝜕𝑥+
𝜕(𝑣𝜏𝑧𝑦)
𝜕𝑧+
𝜕(𝑤𝜏𝑧𝑦)
𝜕𝑧+
𝜕(𝑤𝜏𝑥𝑧)
𝜕𝑥+ +
𝜕(𝑤𝜏𝑦𝑧)
𝜕𝑦−
𝜕𝑞𝑥
𝜕𝑥−
𝜕𝑞𝑦
𝜕𝑦−
𝜕𝑞𝑧
𝜕𝑧 (9)
These equations (5-9) will provide the fluid dynamics of the electrochemical cell, but no
description of electrochemical parameters, so should be solved other expressions that
characterize the electrochemistry of the models domain.
Electrochemistry in a SOEC.
FLUENT´s electrochemical model solve two Equations (10-11), one that takes into
consideration the electron transport through the conductor materials and other for the ions
transport trough the electrolyte [24]:
∇(𝜎𝑠𝑜𝑙∇𝜙𝑠𝑜𝑙) + 𝑅𝑠𝑜𝑙 = 0 (10)
∇(𝜎𝑚𝑒𝑚∇𝜙𝑚𝑒𝑚) + 𝑅𝑚𝑒𝑚 = 0 (11)
Consumption ratios and total production of chemical species are calculated as:
𝑆𝐻2=
𝑀𝑤,𝐻2
2𝐹 𝐼 (12)
𝑆𝑂2=
𝑀𝑤,𝑂2
4𝐹 𝐼 (13)
𝑆𝐻2𝑂 = −𝑀𝑤,𝐻2𝑂
2𝐹 𝐼 (14)
Voltage and current density are calculated by the code using the Nernst equation, variables that
characterize the device operation. Also, it uses the Butler-Volmer expression (Eq. 15 and 16)
for calculate the lost potential due to lower reaction rate at the electrodes [26]:
𝑖 = 𝑖0 [𝑒𝑥𝑝 (𝛼𝑐𝜂𝑎𝑐𝑡𝐹
𝑅𝑇) − 𝑒𝑥𝑝 (−
𝛼𝑐𝜂𝑎𝑐𝑡𝐹
𝑅𝑇)] (15)
𝑖0 = 𝑎𝑖0,𝑟𝑒𝑓(𝑌𝑗)ϒ (16)
Integrating these equations to the governing equations of CFD the code will return a detailed
description of all phenomena that occur during high-temperature electrolysis in the
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computational domain, resulting in a powerful tool to evaluate the influence of several
operating and design parameters on the SOEC´s efficiency.
3.2 Computational Domain for SOEC Using ANSYS FLUENT.
Several geometries are possible for SOEC electrolyzers, however planar configurations are the
most studied, a typical geometry of planar SOEC is shown in Figure 2:
Figure 2: Typical planar crossflow SOEC configuration.
Planar configuration may change considering variations in the shape of the flow channels and
gas flow direction. In this work, it is considered a planar crossflow geometry with the
dimensions that are summarized in Figure 3:
Figure 3: Main dimensions of the SOEC electrolyzer simulated.
Several materials are being studied for the production of SOEC [11], [27]–[29], for the
development of this model are used the materials listed in Table 1.
Table 1: SOEC materials and properties.
Part Anode Cathode Electrolyte Current Collectors Catalyst
Material Ni-YSZa LSMb YSZc Stainless-steel Ni-YSZ
Density (kg/m3) 6500 5620 5480 3000 6500
CP (J/kgK) 500 450 500 500 500
Thermal Cond (W/mK) 13,1 9,6 2,16 27 13,1
Porosity 0,37 0,375 - 0 0,37
Electrical Cond (1/ohm m) 112919 7045 2 850000 112919 aNi-YSZ: Nickel oxide+yttria-stabilized zirconia. bLSM: Strontium-lanthanum-manganite. cYSZ: Yttria-stabilized zirconia
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3.3 Volume Discretization and Boundary Conditions.
In Figure 4 is shown the computational domain of the SOEC discretized and meshed to solve
the mathematical equations of HTE process using the finite volume method. Whereas the
geometry is planar and has no appreciable complexity is used a hexahedral elements meshing
method with an orthogonal quality 0,999 [30]. Due to the small dimensions of the electrodes
catalyst layers it is necessary to use a small minimum element size in these areas to have at
least two elements in each zone to avoid numerical converge problems [31].
Figure 4: SOEC mesh properties.
Electrolyzers operating parameters and input conditions were obtained from literature and are
summarized in Table 2 [32], [33].
Table 2: Parameters used in the 3D CFD modelling analysis of a planar SOEC.
Q (kg/s) V (m/s) T (K) H2 H2O O2 N2
Anode inlet 5.00E-06 0.2638 1103 0 0.6 0 0.4
Cathode inlet 5.00E-06 0.193 1103 0 0 0.2 0.8
Operating Temperature (K) 1103 Operating Voltage (V) 1.32
Electrode Porosity 0.37 Open Circuit Voltage (V) 0.82
Because some of these parameters as the speed of inlet gas, its composition, the porosity of the
electrodes among others, are relevant to the model optimization are just shown the initial
values, as these will be varied in further analyzes.
4. RESULTS AND DISCUSSION.
For validation of the physical-mathematical model built in ANSYS FLUENT®, were
reproduced operating conditions of a numerical model for a SOEC published by Ni (2009)
using a two-dimensional formulation [15]. Operating and inputs conditions reported by [15] to
the proposed model were applied and the results obtained are shown in the Table 3:
Table 3: Comparison between some parameters of the SOEC model proposed by Ni
(2009) and the proposed model at the same operation conditions.
Ni (2009) Proposed Model
H2 Mass Fraction at Anode Outlet 0.373 0.375
Average SOEC Temperature at Outlet 1181.5 K 1181.9 K
Elements 141204
Nodes 149940
Quality 0,99919256
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Although both models differ in several numerical aspects, such as numerical solving
methodology employed and geometrical aspects (the proposed model is 3D) there is a good
agreement for the H2 mass fraction at the anode outlet and the average cell temperature of both
models as can be observed in Table 3. Other hydrodynamic aspects such as velocity profiles
and flow lines also presented strong similarity. Considering that the results reported by [15]
were obtained from a numerical model and these, at the same time, were verified by
experimental parametric studies and compared with theoretical curves. The proposed model in
this work have a notable coincidence with the reported by [15], which represents a validation
criteria for the model developed.
4.1 Model Analysis.
Initial model shown in Table 2 will be analyzed hydrodynamic and electrochemically and then
perform an optimization of some operation and design parameters, in order to increase the
device efficiency. In Table 4 are shown the results of chemical species distribution,
thermodynamics and electrochemical parameters obtained for initial conditions, notice the
variation of H2 mass fraction at the anode outlet, where a value of 0.1442 is obtained. Likewise
a decrease in the mass fraction of H2O corresponding to water consumption in the process can
be observed.
Table 4: Results of the SOEC proposed model for initial conditions.
Q (kg/s) V (m/s) T (K) H2 H2O O2 N2
Anode Outlet 2.33E-06 0.3272 1145.41 0.1442 1.04E-06 0 0.8557
Cathode Outlet 7.67E-06 0.3524 1145.63 0 0 0.4784 0.5215
Cell Temperature (K) 1145.14 Current (A) 32.1987
Current Density (A/cm2) 0.504 Electric Potential (V) 1.26403
Contours of chemical species in the flow channels at the SOEC are also obtained, seeking that
there is a growing behavior of hydrogen mass fraction with the channel length, as expected
theoretically and it is reported by experimental studies and other HTE simulation studies
[15][34]–[36]. Figure 5 shows the mass fraction in both flow channels, anode and cathode, as
well as the mass fraction variation profiles along the flow direction.
(a) (b)
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(c) (d)
Figure 5: Chemical species at the flows channels of the SOEC proposed model.
As observed in Figures 5 (a) and (b), the mass fractions of H2 and H2O vary linearly with the
channel length and homogeneously in the entire area of the electrolytic cell as reported in other
studies [15],[37], which has benefits for device durability for being more desirable
mechanically and economically [38]. In Figures 5 (c) and (d) are shown the variation of the
mass fraction of N2 and O2, whose behavior corresponds to expected, increasing amount of O2
due to water molecule dissociation and the diffusion of molecular oxygen through electrolyte,
which results in a decrease in the mole fraction of N2. Inhomogeneity in the diffusion of O2
through the electrolyte occurs due to the crossflow configuration channels. As observed in
Figure 5 (b), for initial conditions, the H2O feed into the electrolytic cell is consumed totally,
because by the 70 mm the mass fraction is almost zero.
4.2 Effect of the Operational Voltage.
Figure 6 presents a graph of cell voltage versus current density known as activation curve. To
obtain this graph the current density of the electrolytic cell is varied to obtain the operating
voltage of the cell, obtaining the characteristic voltage increase when increasing the current
density [39].
Figure 6: Activation curve for the initial conditions for the SOEC model.
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The curve obtained besides having the behavior predicted by the theory, has a high coincidence
with the expected values and those reported by other authors in experimental work and
numerical simulations as works [10], [15], [40]. As expected, the variation of the operating
voltage of the electrolytic cell influences other operating parameters which in turn will
influence the production of H2 and device efficiency. In Figure 7 (a) the variation of the
chemical species with the operating voltage for the initial conditions is shown. As shown in
Figure 7 for 1.32 V mass fractions of H2 (0.1442) and O2 (0.4784) reach the maximum values
for the other initial conditions, for this reason this voltage will be assumed hereinafter as the
operating parameter of the SOEC.
Figure 7: Species mass fractions and cell temperature for different operational voltages
of the SOEC model proposed.
The variation of average temperature in SOEC with the operating voltage is shown in Figure
7, as reported by most authors, the temperature decrease to values of voltage near to the open
circuit voltage (OCV= 0.82 V) and then begin to grow according to Nernst equation [33], [40],
[41].
4.3 Effect of the Inlet Mass Flow Rates.
For the model with initial operating conditions the water mass fraction at anode outlet is near
to zero (2.42e-12 kg/s), even before the channels end, which influences the production of
hydrogen. For this reason was performed an analysis to evaluate the influence of the initial
water mass flow into the electrolyzer in other cells parameters. The study was performed
without varying the species mass fractions (H2O/N2= 0.6/0.4). Thus they were obtained the
results shown in Figure 8.
Figure 8: Species mass fractions and cell temperature for different inlet mass flows at
anode channel of the SOEC model proposed.
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Increasing the amount of mixture H2O/N2 at anode inlet causes an increase in the amount of
hydrogen produced, as shown in Figure 8 (a). However the consumed water mass fraction
decrease from almost 1.0 in the case with 5.0e-6 kg/s flow to 0.2 in the case of 1.0e-5kg/s. This
effect can be explained because of the decrease in the average cell temperature (Figure 8 (b))
and increased velocity and turbulence in the flow channels, which is unfavorable to the
occurrence of the electrochemical reaction [15], [40].
4.4 Effect of the Anode Gas Composition.
Inlet gas composition has a marked influence on the SOEC electrochemistry, because affects
important parameters such as current density and area specific resistance (ASR). To evaluate
this was conducted a parametric analysis varying the inlet gas composition from baseline
obtaining the results shown in Figure 9.
(a) (b)
(c) (d)
Figure 9: Influence of the composition at the anode mass flow inlet in the SOEC model
proposed. (a) Current density. (b) ASR. (c) Components mass flows. (d) Temperature.
Increasing the mass fraction of water in the inlet flow to the electrolyzer, it produced an
increase in the hydrogen mass fraction obtained as shows the Figure 9 (c). The effect of
increasing water mass fraction also results in a decrease of the area specific resistance (ASR),
thereby decrease the average cell temperature and the current density. These two effects have
opposite influence on the hydrogen production, because decreasing the operating temperature
is unfavorable, while increasing the current density it is not, however better overall
performance and increase in the hydrogen mass flow is obtained. Because of this results, is
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assumed as the nominal value of water mass fraction H2O/N2=0.9/0.1 due to the improvements
obtained in the hydrogen production.
4.5 Optimized Model of the SOEC.
Once analyzed the influence of several operating parameters were established as nominal the
most favorable for hydrogen production, which is the most important parameter for assess the
device efficiency. They were also considered other electrochemical parameters as the ASR and
the current density so the SOEC efficiency is maximized. A comparison between the initial
model and the optimized is shown in Table 5.
Table 5: Comparison between the initial model and the optimized model.
Anode
Outlet
Mass flow (kg/s) 2.75E-06 2.33E-06
Velocity (m/s) 0.4491 0.3272
Temperature (K) 1152.1598 1145.41
H2 0.1491 0.1442
H2O 6.32E-01 1.04E-06
O2 0 0
N2 0.2184 0.8557
Cathode
Outlet
Mass flow (kg/s) 9.25E-06 7.67E-06
Velocity (m/s) 0.4272 0.3524
Temperature (K) 1151.991 1145.636
H2 0 0
H2O 0 0
O2 0.4812 0.4784
N2 0.5187 0.5215
Average Temperature (K) 1151.26 1145.14
Current Density (A/cm2) 0.6135 0.5040
Current (A) 39.2395 32.1987
ASR (Ωcm2) 2.0557 2.5044
As shown in Table 5, the optimized SOEC model presents significant improvements in the
fraction of H2 produced due to improved electrochemical process parameters as the current
density and decreasing the ASR, which favors the speed of the electrochemical water splitting
reaction [17].
5. CONCLUSIONS.
A 3D model of a planar electrolytic cell was developed using CFD software. The results of the
simulation model were compared to data reported by other authors, presenting good agreement,
so that the model developed is a convenient tool for the study of these devices. Several
parametric studies to determine the optimum operating parameters of the proposed model were
conducted.
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Contours of H2O and H2 in the anode channel presented a linear behavior, which vary because
of the electrochemical reaction in this part of the cell. For the initial model H2O is consumed
to 70 mm channels length, which decreases the efficiency of the cell. The contours of chemical
species obtained for N2 and O2 have a non-uniform behavior due to the diffusion of O2 anode
channel, it is affected by the direction of the channels (crossflow). For the initial model it was
obtained the activation curve which has a good agreement with data reported by others authors
using mathematical modeling and experimental studies. It was found that for 1.32 V as
operating voltage, the model shown the highest mass fraction of H2 produced, lower ASR
values and higher values of current density are obtained, whereby the speed of the
electrochemical reaction is favored and hence the electrolyzer efficiency. This value was
established as the operating parameter of the SOEC.
It was obtained that increasing the inlet mass flow channel has a slight increase in H2
production, then these values begin to decrease. This can be explained by the decrease of cells
temperature, increasing turbulence and ASR due to variation in the amount of H2O in the anode
channel inlet.
The influence of the composition of the inlet gases was determined by performing a parametric
study, obtaining an improvement in some electrochemical parameters such as current density
and ASR and a decrease in the average cell temperature which entails a slight increase in the
hydrogen produced.
Optimized model was analyzed and it shows huge improvements in the hydrogen mass fraction
produced and other electrochemical variables compared to the initial model. Results obtained
in this work allow a better understanding of physic-chemical phenomena of SOEC and it is a
useful tool for its design optimization. These will be used to build an additional component in
the chemical process simulation software to assess the reliability of TADSEA coupled to an
HTE flowsheet.
ACKNOWLEDGMENTS
The authors would like to acknowledge to CAPES (Coordenação de Aperfeiçoamento de
Pessoal de Nível Superior), to FACEPE (Fundação de Amparo à Ciência e Tecnologia de
Pernambuco) and PROTEN (Programa de Pós-Graduação em Tecnologias Energéticas e
Nucleares) from UFPE (Universidade Federal de Pernambuco) for their support to the
researchers.
REFERENCES
1. J. O. M. Bockris, “The hydrogen economy: Its history,” Int. J. Hydrogen Energy, 38,
no. 6, pp. 2579–2588 (2013).
2. S. S. Penner, “Steps toward the hydrogen economy,” Energy, 31, no. 1 SPEC. ISS., pp.
33–43 (2006).
3. G. F. Naterer, I. Dincer, and C. Zamfirescu, Hydrogen Production from Nuclear Energy.
Springer, Ontario, Canadá, (2013).
4. X. Yan, H. Noguchi, H. Sato, Y. Tachibana, K. Kunitomi, and R. Hino, “A hybrid HTGR
system producing electricity, hydrogen and such other products as water demanded in
the Middle East,” Nucl. Eng. Des., 271, pp. 20–29 (2014).
5. C. Angulo, E. Bogusch, A. Bredimas, N. Delannay, C. Viala, J. Ruer, P. Muguerra, E.
Sibaud, V. Chauvet, D. Hittner, M. A. Fütterer, S. De Groot, W. Von Lensa, K.
INAC 2015, São Paulo, SP, Brazil.
Verfondern, R. Moron, O. Baudrand, G. Griffay, A. Baaten, and J. Segurado-Gimenez,
“EUROPAIRS: The European project on coupling of High Temperature Reactors with
industrial processes,” Nucl. Eng. Des., 251, pp. 30–37 (2012).
6. N. Sakaba, S. Kasahara, K. Onuki, and K. Kunitomi, “Conceptual design of hydrogen
production system with thermochemical water-splitting iodine-sulphur process utilizing
heat from the high-temperature gas-cooled reactor HTTR,” Int. J. Hydrogen Energy, 32,
no. 17, pp. 4160–4169 (2007).
7. R. Elder and R. Allen, “Nuclear heat for hydrogen production: Coupling a very
high/high temperature reactor to a hydrogen production plant,” Prog. Nucl. Energy, 51,
no. 3, pp. 500–525 (2009).
8. M. Richards, A. Shenoy, K. Schultz, L. Brown, and G. Atomics, “H2-MHR Conceptual
Designs Based on the SI Process and HTE H2-MHR Conceptual Designs are Being
Developed,” (2005).
9. A. Abánades, C. García, L. García, A. Escrivá, A. Pérez-Navarro, and J. Rosales,
“Application of gas-cooled Accelerator Driven System (ADS) transmutation devices to
sustainable nuclear energy development,” Nucl. Eng. Des., 241, no. 6, pp. 2288–2294
(2011).
10. C. M. Stoots, J. E. O’Brien, K. G. Condie, and J. J. Hartvigsen, “High-temperature
electrolysis for large-scale hydrogen production from nuclear energy - Experimental
investigations,” Int. J. Hydrogen Energy, 35, no. 10, pp. 4861–4870 (2010).
11. X. Zhang, J. E. O’Brien, R. C. O’Brien, J. J. Hartvigsen, G. Tao, and G. K. Housley,
“Improved durability of SOEC stacks for high temperature electrolysis,” Int. J.
Hydrogen Energy, 38, no. 1, pp. 20–28 (2013).
12. W. L. Becker, R. J. Braun, M. Penev, and M. Melaina, “Production of Fischer-Tropsch
liquid fuels from high temperature solid oxide co-electrolysis units,” Energy, 47, no. 1,
pp. 99–115 (2012).
13. J. E. O’Brien, M. G. McKellar, E. A. Harvego, and C. M. Stoots, “High-temperature
electrolysis for large-scale hydrogen and syngas production from nuclear energy -
summary of system simulation and economic analyses,” Int. J. Hydrogen Energy, 35,
no. 10, pp. 4808–4819 (2010).
14. D. Grondin, J. Deseure, A. Brisse, M. Zahid, and P. Ozil, “Simulation of a high
temperature electrolyzer,” J. Appl. Electrochem., 40, no. 5, pp. 933–941 (2010).
15. M. Ni, “Computational fluid dynamics modeling of a solid oxide electrolyzer cell for
hydrogen production,” Int. J. Hydrogen Energy, 34, no. 18, pp. 7795–7806 (2009).
16. L. Mingyi, Y. Bo, X. Jingming, and C. Jing, “Two-dimensional simulation and critical
efficiency analysis of high-temperature steam electrolysis system for hydrogen
production,” J. Power Sources, 183, no. 2, pp. 708–712 (2008).
17. P. Kazempoor and R. J. Braun, “Model validation and performance analysis of
regenerative solid oxide cells: Electrolytic operation,” Int. J. Hydrogen Energy, 39, no.
6, pp. 2669–2684 (2014).
18. J. Stempien, Q. Sun, and S. Chan, “Solid Oxide Electrolyzer Cell Modeling: A Review,”
J. Power Technol., 93, no. 4, pp. 216–246 (2013).
19. C. García, J. Rosales, L. García, A. Pérez-Navarro, A. Escrivá, and A. Abánades,
“Performance of a transmutation advanced device for sustainable energy application,”
Prog. Nucl. Energy, 53, no. 8, pp. 1151–1158 (2011).
20. L. García, J. Pérez, C. García, A. Escrivá, J. Rosales, and A. Abánades, “Calculation of
the packing fraction in a pebble-bed ADS and redesigning of the Transmutation
Advanced Device for Sustainable Energy Applications (TADSEA),” Nucl. Eng. Des.,
253, pp. 142–152 (2012).
INAC 2015, São Paulo, SP, Brazil.
21. Aspen Technology, “Aspen HYSYS User’s Guide,” (2009).
22. A. Brisse, J. Schefold, and M. Zahid, “High temperature water electrolysis in solid oxide
cells,” Int. J. Hydrogen Energy, 33, no. 20, pp. 5375–5382 (2008).
23. S. Fujiwara, S. Kasai, H. Yamauchi, K. Yamada, S. Makino, K. Matsunaga, M. Yoshino,
T. Kameda, T. Ogawa, S. Momma, and E. Hoashi, “Hydrogen production by high
temperature electrolysis with nuclear reactor,” Prog. Nucl. Energy, 50, no. 2–6, pp. 422–
426 (2008).
24. T. D. Canonsburg, “ANSYS FLUENT Fuel Cell Modules Manual,” Knowl. Creat.
Diffus. Util., 15317, no. October, pp. 724–746 (2012).
25. Z. Qu, P. V. Aravind, S. Z. Boksteen, N. J. J. Dekker, A. H. H. Janssen, N. Woudstra,
and a. H. M. Verkooijen, “Three-dimensional computational fluid dynamics modeling
of anode-supported planar SOFC,” Int. J. Hydrogen Energy, 36, no. 16, pp. 10209–
10220 (2011).
26. M. T. Prinkey, “Solid Oxide Fuel Cell Modeling with FLUENT NETL SOFC Fuel Cell
Modeling Team,” pp. 1–40 (2003).
27. J. Kong, Y. Zhang, C. Deng, and J. Xu, “Synthesis and electrochemical properties of
LSM and LSF perovskites as anode materials for high temperature steam electrolysis,”
J. Power Sources, 186, no. 2, pp. 485–489 (2009).
28. P. Moçoteguy and A. Brisse, “A review and comprehensive analysis of degradation
mechanisms of solid oxide electrolysis cells,” Int. J. Hydrogen Energy, 38, no. 36, pp.
15887–15902 (2013).
29. M. Ni, M. K. H. Leung, and D. Y. C. Leung, “Technological development of hydrogen
production by solid oxide electrolyzer cell (SOEC),” Int. J. Hydrogen Energy, 33, no. 9,
pp. 2337–2354 (2008).
30. I. Ansys, “ANSYS FLUENT theory guide,” Knowl. Creat. Diffus. Util., 15317, no.
November, pp. 724–746 (2009).
31. A. Arvay, A. Ahmed, X.-H. Peng, and A. M. Kannan, “Convergence criteria
establishment for 3D simulation of proton exchange membrane fuel cell,” Int. J.
Hydrogen Energy, 37, no. 3, pp. 2482–2489 (2012).
32. M. Ni, M. K. H. Leung, and D. Y. C. Leung, “Parametric study of solid oxide steam
electrolyzer for hydrogen production,” Int. J. Hydrogen Energy, 32, no. 13, pp. 2305–
2313 (2007).
33. W. J. Sembler and S. Kumar, “Optimization of a Single-Cell Solid-Oxide Fuel Cell
Using Computational Fluid Dynamics,” J. Fuel Cell Sci. Technol., 8, no. 2, p. 021007
(2011).
34. S. D. Kim, J. H. Yu, D. W. Seo, I. S. Han, and S. K. Woo, “Hydrogen production
performance of 3-cell flat-tubular solid oxide electrolysis stack,” Int. J. Hydrogen
Energy, 37, no. 1, pp. 78–83 (2012).
35. J. Leybros, T. Gilardi, A. Saturnin, C. Mansilla, and P. Carles, “Plant sizing and
evaluation of hydrogen production costs from advanced processes coupled to a nuclear
heat source. Part I: Sulphur-iodine cycle,” Int. J. Hydrogen Energy, 35, no. 3, pp. 1008–
1018 (2010).
36. J. Koh, D. Yoon, and C. H. Oh, “Simple Electrolyzer Model Development for High-
Temperature Electrolysis System Analysis Using Solid Oxide Electrolysis Cell,” J.
Nucl. Sci. Technol., 47, no. 7, pp. 599–607 (2010).
37. G. L. Hawkes, J. E. O’Brien, and G. G. Tao, “3D CFD Electrochemical and Heat
Transfer Model of an Internally Manifolded Solid Oxide Electrolysis Cell,” Vol. 4
Energy Syst. Anal. Thermodyn. Sustain. Combust. Sci. Eng. Nanoeng. Energy, Parts A
B, pp. 505–512 (2011).
INAC 2015, São Paulo, SP, Brazil.
38. T. S. Bilge Yildiz, Jeff Smith, “Thermal-fluid and Electrochemical Modeling and
Performance Study of a Planar Solid Oxide Electrolysis Cell : Analysis on SOEC
Resistances , Size , and Inlet Flow Conditions,” .
39. I. EG&G Technical Services, “Fuel Cell Handbook,” Fuel Cell, 7 Edition, no.
November, pp. 1–352 (2004).
40. M. Navasa, J. Yuan, and B. Sundén, “Computational fluid dynamics approach for
performance evaluation of a solid oxide electrolysis cell for hydrogen production,” Appl.
Energy, 137, pp. 867–876 (2014).
41. W. J. Sembler and S. Kumar, “Modification of Results From Computational-Fluid-
Dynamics Simulations of Single-Cell Solid-Oxide Fuel Cells to Estimate Multicell
Stack Performance,” J. Fuel Cell Sci. Technol., 8, no. 2, p. 021008 (2011).