• Transactions of the Korean hydrogen and new energy society
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• v.32 no.6
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• pp.489-496
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• 2021

The performandce of polymer electrolyte membrane fuel cell depends on the effective management of heat and product water by the electrochemical reaction. This study is designed to investigate the parametric change of heat management along the channel of polymer electrolyte membrane. The model was developed by an aspen custom modeler that it can solve differential equation with distretization model. The model can simulate water transport through the membrane electrolyte that is coupled with heat generation. In order to verify the model, it is compared with the experimental data. The water transport behavior is then evaluated with the simulation model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4180-4196
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• 2017

In this paper, we analyze average capacity of an amplify-and-forward (AF) cooperative communication system model in multi-relay multiuser networks. In contrast to conventional cooperative networks, relays in the considered network have no embedded energy supply. They need to rely on the energy harvested from the signals broadcasted by the source for their cooperative information transmission. Based on this structure, a two-step selection scheme is proposed considering both channel state information (CSI) and battery status of relays. Assuming each relay has infinite or finite energy storage for accumulating the energy, we use the infinite or finite Markov chain to capture the evolution of relay batteries and certain simplified assumptions to reduce computational complexity of the Markov chain analysis. The approximate closed-form expressions for the average capacity of the proposed scheme are derived. All theoretical results are validated by numerical simulations. The impacts of the system parameters, such as relay or user number, energy harvesting threshold and battery size, on the capacity performance are extensively investigated. Results show that although the performance of our scheme is inferior to the optimal joint selection scheme, it is still a practical scheme because its complexity is much lower than that of the optimal scheme.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.436-443
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• 2007

In this paper, an intelligent method called BELBIC (Brain Emotional Learning Based Intelligent Controller) is used to control of Locally Linear Neuro-Fuzzy Model (LOLIMOT) of Washing Machine. The Locally Linear Neuro-Fuzzy Model of Washing Machine is obtained based on previously extracted data. One of the important issues in using BELBIC is its parameters setting. On the other hand, the controller design for Washing Machine is a multi objective problem. Indeed, the two objectives, energy consumption and effectiveness of washing process, are main issues in this problem, and these two objectives are in contrast. Due to these challenges, a Multi Objective Genetic Algorithm is used for tuning the BELBIC parameters. The algorithm provides a set of non-dominated set points rather than a single point, so the designer has the advantage of selecting the desired set point. With considering the proper parameters after using additional assumptions, the simulation results show that this controller with optimal parameters has very good performance and considerable saving in energy consumption.

• Journal of Astronomy and Space Sciences
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• v.30 no.3
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• pp.141-143
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• 2013

We propose jitter radiation and jitter self-Compton process in this work. We apply our model to the study of GRB prompt emission and GeV-emission. Our results can explain the multi-wavelength spectrum of GRB 100728A very well.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.248-251
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• 2006

Multi-physics problem is considered for the Pitot tube located in uniform freon gas flow with high Mach number and the 3D numerical results of temperature on Pitot tube is given. The model is created by using structural module of ANSYS, the grids are obtained by ICEM, and the problem is solved and the data post-processing is done by CFX.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.81.4-82
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• 2016

Recent analysis on asteroidal thermophysical property revealed that there is a tendency that their thermal inertia decrease with their sizes at least for main belt asteroids. However, little is known about the thermal properties of comet-like bodies. In this work we utilized a simple thermophysical model to calculate the thermal inertia of a bare nucleus of comet P/2006 HR30 (Siding Spring) and an asteroid in comet-like orbit 4015 Wilson-Harrington from AKARI observation data. It is also shown that the determination of their thermal inertia is very sensitive to their spin vector, while the diameter is rather easy to be constrained to a certain range by combining multi-wavelength observational data. Thus, we set diameter and hence the geometric albedo as fixed parameters, and inferred the spin vector and thermal inertia of the targets. Further detailed analyses on these cometary bodies will shed light on our understanding of the detailed surfacial characteristics of them.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.64.3-64.3
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• 2019

A bright post-breakout emission was detected for a Type Ic supernova (SN Ic) LSQ14efd, which was among the first for SNe Ic. To explain the early-time light curve and color evolution, the effects of the circumstellar medium (CSM) are investigated. Four main parameters, CSM mass, CSM radius, nickel distribution, and explosion energy, are systematically explored in multi-group radiation hydrodynamics simulations, STELLA. Matching the model light curves and color evolution with the observation, we could constrain the parameter space and find out the best fit models. Our results imply that the progenitor suffered a strong mass loss shortly before the explosion and had a massive CSM of ~0.1 M_⊙.

• The Journal of the Acoustical Society of Korea
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• v.14 no.4
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• pp.29-37
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• 1995

A resonant frequency of piezoelectric transducer depends remarkably on the electric impedance connected to the vibrator. In this paper, using this effect of frequency controllable two layered PZT ultrasonic transducer is designed and its acoustic characteristics are analyzed by a new transmission model equivalent circuit. The theoretical and the experimental results of the electric impedance effect on the resonant frequency variation were compared and both results showed a good consistency each other. The resonant frequency has been controlled continuously in the wide frequency range of 180kHz~580kHz and the effective attenuations were less than 7dB in the frequency range of 330kHz~470kHz.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.752-762
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• 2021

The Smoothed Particle Hydrodynamics is one of the most widely used mesh-free numerical method for thermo-fluid dynamics. Due to its Lagrangian nature and simplicity, it is recently gaining popularity in simulating complex physics with large deformations. In this study, the 3D single/two-phase numerical simulations are performed on the Liquid Metal Reactor (LMR) centralized sloshing benchmark experiment using the SPH parallelized using a GPU. In order to capture multi-phase flows with a large density ratio more effectively, the original SPH density and continuity equations are re-formulated in terms of the normalized-density. Based upon this approach, maximum sloshing height and arrival time in various experimental cases are calculated by using both single-phase and multi-phase SPH framework and the results are compared with the benchmark results. Overall, the results of SPH simulations show excellent agreement with all the benchmark experiments both in qualitative and quantitative manners. According to the sensitivity study of the particle-size, the prediction accuracy is gradually increasing with decreasing the particle-size leading to a higher resolution. In addition, it is found that the multi-phase SPH model considering both liquid and air provides a better prediction on the experimental results and the reality.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3409-3416
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• 2023

Licensing the next-generation of nuclear reactor designs requires extensive use of Modeling and Simulation (M&S) to investigate system response to many operational conditions, identify possible accidental scenarios and predict their evolution to undesirable consequences that are to be prevented or mitigated via the deployment of adequate safety barriers. Deep Learning (DL) and Artificial Intelligence (AI) can support M&S computationally by providing surrogates of the complex multi-physics high-fidelity models used for design. However, DL and AI are, generally, low-fidelity 'black-box' models that do not assure any structure based on physical laws and constraints, and may, thus, lack interpretability and accuracy of the results. This poses limitations on their credibility and doubts about their adoption for the safety assessment and licensing of novel reactor designs. In this regard, Physics Informed Neural Networks (PINNs) are receiving growing attention for their ability to integrate fundamental physics laws and domain knowledge in the neural networks, thus assuring credible generalization capabilities and credible predictions. This paper presents the use of PINNs as surrogate models for accidental scenarios simulation in Nuclear Power Plants (NPPs). A case study of a Loss of Heat Sink (LOHS) accidental scenario in a Nuclear Battery (NB), a unique class of transportable, plug-and-play microreactors, is considered. A PINN is developed and compared with a Deep Neural Network (DNN). The results show the advantages of PINNs in providing accurate solutions, avoiding overfitting, underfitting and intrinsically ensuring physics-consistent results.