• Applied Chemistry for Engineering
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• v.29 no.6
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• pp.789-798
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• 2018

The role of empirical equation to predict the performance of polymer electrolyte membrane fuel cell is important. The activation, ohmic and mass transfer losses were separated in a polarization curve, and the curve fitting according to each region was performed using Kim's model and Hao's model. Changes of each loss were compared according to operation variables of the temperature, pressure, oxygen concentration and membrane thickness. The existing model showed a good fitting convergence, but less fitting accuracy in the separated loss region. A new model using the convergence coefficient was suggested to improve the accuracy of performance prediction of fuel cells of which results were demonstrated.

• Corrosion Science and Technology
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• v.20 no.2
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• pp.62-68
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• 2021

Artificial neural network techniques show an excellent ability to predict the data (output) for various complex characteristics (input). It is primarily specialized to solve nonlinear relationship problems. This study is an experimental investigation that applies artificial neural network techniques and an experimental design to predict the cyclic polarization curves of the super-austenitic stainless steel AL-6XN alloy with sensitization. A cyclic polarization test was conducted in a 3.5% NaCl solution based on an experimental design matrix with various factors (degree of sensitization, temperature, pH) and their levels, and a total of 36 cyclic polarization data were acquired. The 36 cyclic polarization patterns were used as training data for the artificial neural network model. As a result, the supervised learning algorithms with back-propagation showed high learning and prediction performances. The model showed an excellent training performance (R²=0.998) and a considerable prediction performance (R²=0.812) for the conditions that were not included in the training data.

• Corrosion Science and Technology
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• v.19 no.6
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• pp.302-309
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• 2020

This study aimed to predict the pitting corrosion characteristics of AL-6XN super-austenitic steel using multiple linear regression. The variables used in the model are degree of sensitization, temperature, and pH. Experiments were designed and cyclic polarization curve tests were conducted accordingly. The data obtained from the cyclic polarization curve tests were used as training data for the multiple linear regression model. The significance of each factor in the response (critical pitting potential, repassivation potential) was analyzed. The multiple linear regression model was validated using experimental conditions that were not included in the training data. As a result, the degree of sensitization showed a greater effect than the other variables. Multiple linear regression showed poor performance for prediction of repassivation potential. On the other hand, the model showed a considerable degree of predictive performance for critical pitting potential. The coefficient of determination (R2) was 0.7745. The possibility for pitting potential prediction was confirmed using multiple linear regression.

• Journal of the Korean Ceramic Society
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• v.42 no.12 s.283
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• pp.854-859
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• 2005

Performance of micro scale intermediate temperature solid oxide fuel cell system has been successfully evaluated by computer simulation based on macro modeling. Two systems were studied in this work. The one is designed that the ceria-based electrolyte placed between composite electrodes and the other is designed that electrodes alternately placed on the electrolyte. The injected gas was composed of hydrogen and air. The polarization curve was obtained through a series of calculations for ohmic loss, activation loss and concentration loss. The calculation of each loss was based on the solving of mathematical model of multi physical-phenomena such as ion conduction, fluid dynamics and diffusion and convection by Finite Element Method (FEM). The performance characteristics of SOFC were quantitatively investigated for various structural parameters such as distance between electrodes and thickness of electrolyte.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.887.1_888.1
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• 2009

This paper proposes a core loss analysis method to obtain high accuracy prediction by using Multi-curve representing magnetic properties of a electrical steel in Finite Element Analysis (FEA). Generally, the magnetic prosperities of the electrical steel are measured by Epstein Method based on the international standards that are not good sufficient to predict motor performances. The method only aims to grade products in steel companies The magnetic properties of actual stator core is highly different to those given by steel companies due to the fact that stacking effect, shearing stress, nature anisotropy of electrical steels are not taken into account. In this paper, the magnetic properties are variously measured by three measuring devices, and then the several BH curves and BW curves obtained are used to analyze the core loss of a IPM. The BH curve in the high magnetic field are extrapolated using the mathematical formulation with the maximum saturation magnetic polarization measured

• Bulletin of the Korean Chemical Society
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• v.18 no.12
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• pp.1274-1280
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• 1997

The photodissociation dynamics of CH2I2 has been studied at 304 nm by state-selective photofragment translational spectroscopy. Velocity distributions, anisotropy parameters, and relative quantum yields are obtained for the ground I(2P3/2) and spin-orbit excited state I*(2P1/2) iodine atoms, which are produced from photodissociation of CH2I2 at this wavelength. These processes are found to occur via B1 ← A1 type electronic transitions. The quantum yield of I*(2P1/2) is determined to be 0.25, indicating that the formation of ground state iodine is clearly the favored dissociation channel in the 304 nm wavelength region. From the angular distribution of dissociation products, the anisotropy parameters are determined to be β(I)=0.4 for the I(2P3/2) and β(I*)=0.55 for the I*(2P1/2) which substantially differ from the limiting value of 1.13. The positive values of anisotropy parameter, however, show that the primary processes for I and I* formation channels proceed dominantly via a transition which is parallel to I-I axis. The above results are interpreted in terms of dual path formation of iodine atoms from two different excited states, i.e., a direct and an indirect dissociation via curve crossing between these states. The translational energy distributions of recoil fragments reveal that a large fraction of the available energy goes into the internal excitation of the CH2I photofragment; < Eint > /Eavl=0.80 and 0.82 for the I and I* formation channels, respectively. The quantitative analysis for the energy partitioning of available energy into the photofragments is used to compare the experimental results with the prediction of direct impulsive model for photodissociation dynamics.

• Journal of the Korean Electrochemical Society
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• v.14 no.4
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• pp.231-238
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• 2011

In this work, the numerical analysis for the zincate behavior at a zinc electrode with an electrolyte flow was carried out for a ZAFC. The Nernst-Planck equation with a boundary condition of Butler-Volmer type was adopted to describe electrochemical effects of mass transfer, migration, kinetics of electrode. The Navier-Stokes equation, coupling to the Nernst-Planck equation, is also applied to describe the internal electrolyte flow fields. The validity of the numerical model is proved through the comparative analysis between numerical and experimental results. The concentration of zincate and the current density were also investigated at a zinc anode according to various electrolyte velocities. We have found the concentration of zincate decreased and the current density increased with an increase in the electrolyte velocity.