• Progress in Superconductivity and Cryogenics
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• v.20 no.4
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• pp.55-59
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• 2018

Currently, the development of industry makes needs larger electric supply. Providers must consider the efficiency about losses and reliability of the system. In this case, DC power system can save electrical energy; long-distance transmission line losses. Relevance to switch technology with a voltage-source converter (VSC) in AC-DC conversion system have been researched. But, protection device of DC-link against fault current is still needed to study much. VSC DC power system is vulnerable to DC-cable short-circuit and ground faults, because DC-link has a huge size of capacitor filter which releases extremely large current during DC faults. Furthermore, DC has a fatal flaw that current zero crossing is nonexistence. To interrupt the DC, several methods which make a zero crossing is used; parallel connecting self-excited series LC circuit with main switch, LC circuit with power electronic device called hybrid DC circuit breaker. Meanwhile, self-excited oscillator needs a huge size capacitor that produces big oscillation current which makes zero crossing. This capacitor has a quite effective on the price of DCCB. In this paper, hybrid self-excited type superconducting DCCB which are using AC circuit breaker system is studied by simulation tool PSCAD/EMTDC.

• Geomechanics and Engineering
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• v.16 no.5
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• pp.495-501
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• 2018

Geogrid application that has proved to be an effective and economic method of reinforcing particles, is widely used in geotechnical engineering. The discrete element method (DEM) has been used to investigate the micro mechanics of the geogrid deformation and also the interlocking mechanism that cannot be easily studies in laboratory tests. Two types of realistically shaped geogrid models with square and triangle apertures were developed using parallel bonds in PFC3D. The calibration test simulations have demonstrated that the precisely shaped triangular geogrid model is also able to reproduce the deformation and strength characteristics of geogrids. Moreover, the square and triangular geogrid models were also used in DEM pull-out test simulations with idealized shape particle models for validation. The simulation results have been shown to provide good predictions of pullout force as a function of displacement especially for the initial 30 mm displacement. For the granular material of size 40 mm, both the experimental and DEM results demonstrate that the triangular geogrid of size 75 mm outperforms the square geogrid of size 65 mm. Besides, the simulations have given valuable insight into the interaction between particle and geogrid and also revealed similar deformation behavior of geogrids during pullout. Therefore, the DEM provides a tool which enable to model other possible prototype geogrid and investigate their performance before manufacture.

• Journal of Drive and Control
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• v.16 no.1
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• pp.7-13
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• 2019

The objective of this study was to present a damped pneumatic suspension, a bike fork suspension, which can adapt itself to incoming road excitations is presented in this paper. It consists of a hydraulic damper and a pneumatic spring in parallel with a linear spring. The study also proposed a variable and switchable orifice, in the hydraulic damper, to select appropriate damping property. Hydraulic-pneumatic circuit model for the bike fork suspension was established based on AMESim, in order to predict its performance. In addition, elastic-damping characteristics of the fork such as spring constant and viscous damping coefficient were computed and compared, for validation, with those evaluated by experiment using the universal test machine. Through simulation analysis and test, it was established that the hydraulic-pneumatic circuit model is effective and practical for development of future MTB suspensions.

• ETRI Journal
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• v.43 no.3
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• pp.483-510
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• 2021

In computational biology, desired patterns are searched in large text databases, and an exact match is preferable. Classical benchmark algorithms obtain competent solutions for pattern matching in O (N) time, whereas quantum algorithm design is based on Grover's method, which completes the search in $O(\sqrt{N})$ time. This paper briefly explains existing quantum algorithms and defines their processing limitations. Our initial work overcomes existing algorithmic constraints by proposing the quantum-based combined exact (QBCE) algorithm for the pattern-matching problem to process exact patterns. Next, quantum random access memory (QRAM) processing is discussed, and based on it, we propose the QRAM processing-based exact (QPBE) pattern-matching algorithm. We show that to find all t occurrences of a pattern, the best case time complexities of the QBCE and QPBE algorithms are $O(\sqrt{t})$ and $O(\sqrt{N})$, and the exceptional worst case is bounded by O (t) and O (N). Thus, the proposed quantum algorithms achieve computational speedup. Our work is proved mathematically and validated with simulation, and complexity analysis demonstrates that our quantum algorithms are better than existing pattern-matching methods.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.11
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• pp.45-55
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• 2018

To reduce the energy consumption of HVAC system in buildings, thermally activated building system(TABS) has been applied to low energy building because of energy efficient performance and reduction of peak load. DOAS coupled with a parallel sensible cooling could be promising because TABS handles sensible heat load only. The purpose of this study was to evaluate the indoor thermal environment and cooling operation characteristic of TABS with dedicated outdoor air system(DOAS) in Korea climate. Indoor thermal environment and operation characteristic of TABS integrated with DOAS are investigated at different TABS operation schedules and climate conditions by simulation tests. The result shows that the DOAS is more suitable for hot and humid climates. And also it show that the potential of intermittent operation of TABS.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.2
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• pp.3-12
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• 2001

Currently, the superscalar architecture dominates todays microprocessor marketplase. As, more transistors are integrated onto larger die, however, an on-chip multiprocessor is regarded as a promising alternative to the superscalar microprocessor. This paper examines the behavior of the next generation block encryption algorithms RC6 and Rijndael on the on-chip multiprocessing microprocessor. Based on the simulation results by using a program-driven simulator, the on-chip multiprocessor can exploit thread level parallelism effectively and overcome the limitation of instruction level parallelism in the next generation block encryption algorithms.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.133-144
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• 2021

High-performance computing (HPC) is the underpinning for many of today's most exciting new research areas, to name a few, from big science to new ways of fighting the disease, to artificial intelligence (AI), to big data analytics, to quantum computing. This report captures the summary of a 9-day program of presentations, keynotes, and workshops at the SC20 conference, one of the most prominent events on sharing ideas and results in HPC technology R&D. Because of the exceptional situation caused by COVID-19, the conference was held entirely online from 11/9 to 11/19 2020, and interestingly caught more attention on using HPC to make a breakthrough in the area of vaccine and cure for COVID-19. The program brought together 103 papers from 21 countries, along with 163 presentations in 24 workshop sessions. The event has covered several key areas in HPC technology, including new memory hierarchy and interconnects for different accelerators, evaluation of parallel programming models, as well as simulation and modeling in traditional science applications. Notably, there was increasing interest in AI and Big Data analytics as well. With this summary of the recent HPC trend readers may find useful information to guide the R&D directions for challenging new technologies and applications in the area of HPC.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.73-79
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• 2021

Recently, in the field of computer animation, a method for generating motion using deep learning has been studied away from conventional finite-state machines or graph-based methods. The expressiveness of the network required for learning motions is more influenced by the diversity of motion contained in it than by the simple length of motion to be learned. This study aims to find an efficient network structure when the types of motions to be learned are diverse. In this paper, we train and compare three types of networks: basic fully-connected structure, mixture of experts structure that uses multiple fully-connected layers in parallel, recurrent neural network which is widely used to deal with seq2seq, and transformer structure used for sequence-type data processing in the natural language processing field.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3301-3312
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• 2023

This study incorporates a high-fidelity transient analysis solver based on multigroup CMFD in the MOC code STREAM. Transport modeling with heterogeneous geometries of the reactor core increases computational cost in terms of memory and time, whereas the multigroup CMFD reduces the computational cost. The reactor condition does not change at every time step, which is a vital point for the utilization of CMFD. CMFD correction factors are updated from the transport solution whenever the reactor core condition changes, and the simulation continues until the end. The transport solution is adjusted once CMFD achieves the solution. The flux-weighted method is used for rod decusping to update the partially inserted control rod cell material, which maintains the solution's stability. A smaller time-step size is needed to obtain an accurate solution, which increases the computational cost. The adaptive step-size control algorithm is robust for controlling the time step size. This algorithm is based on local errors and has the potential capability to accept or reject the solution. Several numerical problems are selected to analyze the performance and numerical accuracy of parallel computing, rod decusping, and adaptive time step control. Lastly, a typical pressurized LWR was chosen to study the rod-ejection accident.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.6
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• pp.120-127
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• 1995

A nonlinear empirical state-space model of the Artificial Neural Network(ANN) has been developed. The nonlinear model structure incorporates characteristic, so as to enable identification of the transient response, as well as the steady-state response of a dynamic system. A hybrid feedfoward/feedback neural network, namely a Local Time Delayed Recurrent Multi-layer Perception(RMLP), is the model structure developed in this paper. RMLP is used to identify nonlinear dynamic system in an input/output sense. The feedfoward protion of the network architecture provides with the well-known curve fitting factor, while local recurrent and cross-talk connections provides the dynamics of the system. A dynamic learning algorithm is used to train the proposed network in a supervised manner. The derived dynamic learning algorithm exhibit a computationally desirable characteristic; both network sweep involved in the algorithm are performed forward, enhancing its parallel implementation. RMLP state-space and its associate learning algorithm is demonstrated through a simple examples. The simulation results are very encouraging.