• Journal of Power Electronics
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• 제18권1호
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• pp.92-102
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• 2018

A sliding mode control (SMC) for servo motors based on the differential evolution (DE) algorithm, called DE-SMC, is proposed in this study. The parameters of SMC should be designed exactly to improve the robustness, realize the precision positioning, and reduce the steady-state speed error of the servo drive. The main parameters of SMC are optimized using the DE algorithm according to the speed feedback information of the servo motor. The most significant influence factor of the DE algorithm is optimization iteration. A suitable iteration can be achieved by the tested optimization process profile of the main parameters of SMC. Once the parameters of SMC are optimized under a convergent iteration, the system realizes the given performance indices within the shortest time. The experiment indicates that the robustness of the system is improved, and the dynamic and steady performance achieves the given performance indices under a convergent iteration when motor parameters mismatch and load disturbance is added. Moreover, the suitable iteration effectively mitigates the low-speed crawling phenomenon in the system. The correctness and effectiveness of DE-SMC are verified through the experiment.

• 국제초고층학회논문집
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• 제12권1호
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• pp.35-47
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• 2023

The transport system and its infrastructure are not only the fundamental means of sustaining the operation of contemporary cities, but also important drivers for the evolution of urban form. Rail transit, critical to improving the operational efficiency and optimizing the spatial layout in cities, is one of the critical conditions for high-density areas with limited land and concentrated resources to be compact to take on complex challenges. As a node element of infrastructure, rail transit entrances are the most important points connecting the rail transit system with urban space. Although influenced by urban form, their quantity and location also influence and shape the evolution of urban space form. Based on the development gap of high-density areas in various contexts, focusing on various rail transit stations in Asia, this research analyzes the correlation between rail transit entrances and peripheral high-density urban form in a delicate, dynamic and granular way. The research considers both horizontal and vertical perspectives, in combination with the urban evolution process in time series, to explore the development trend of high-density urban form in Asia from the aspect of correlation, and building a new foundation for research on urban form, suitable for different types of cities.

• 한국세라믹학회지
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• 제42권8호
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• pp.537-541
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• 2005

Silicon nitride is one of the most successful engineering ceramics, owing to a favorable combination of properties, including high strength, high hardness, low thermal expansion coefficient, and high fracture toughness. However, the impact damage behavior of $Si_3N_4$ ceramics has not been widely characterized. In this study, sphere and explosive indentations were used to characterize the static and dynamic damage behavior of $Si_3N_4$ ceramics with different microstructures. Three grades of $Si_3N_4$ with different grain size and shape, fine-equiaxed, medium, and coarse-elongated, were prepared. In order to observe the subsurface damaged zone, a bonded-interface technique was adopted. Subsurface damage evolution of the specimens was then characterized extensively using optical and electron microscopy. It was found that the damage response depends strongly on the microstructure of the ceramics, particularly on the glassy grain boundary phase. In the case of static indentation, examination of subsurface damage revealed competition between brittle and ductile damage modes. In contrast to static indentation results, dynamic indentation induces a massive subsurface yield zone that contains severe micro-failures. In this study, it is suggested that the weak glassy grain boundary phase plays an important role in the resistance to dynamic fracture.

• Geomechanics and Engineering
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• 제16권5호
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• pp.483-493
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• 2018

Experimental study of the deterioration of high-temperature rock subjected to rapid cooling is essential for thermal engineering applications. To evaluate the influence of thermal shock on heated granite with different temperatures, laboratory tests were conducted to record the changes in the physical properties of granite specimens and the dynamic mechanical characteristics of granite after rapid cooling were experimentally investigated by using a split Hopkinson pressure bar (SHPB). The results indicate that there are threshold temperatures ($500-600^{\circ}C$) for variations in density, porosity, and P-wave velocity of granite with increasing treatment temperature. The stress-strain curves of $500-1000^{\circ}C$ show the brittle-plastic transition of tested granite specimens. It was also found that in the temperature range of $200-400^{\circ}C$, the through-cracks induced by rapid cooling have a decisive influence on the failure pattern of rock specimens under dynamic load. Moreover, the increase of crack density due to higher treatment temperature will result in the dilution of thermal shock effect for the rocks at temperatures above $500^{\circ}C$. Eventually, a fitting formula was established to relate the dynamic peak strength of pretreated granite to the crack density, which is the exponential function.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권1호
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• pp.31-36
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• 2008

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the enviromuent. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.1114-1116
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• 2005

Shop floor control systems (SFCS) are used to make real-time planning and scheduling decisions to optimize the efficiency of manufacturing shops. These shops exhibit a non-linear, dynamic evolution caused by 1) the concurrent flows of disparate parts following complex routings, 2) a variety of machines that breakdown at random times, 3) stochastic arrivals of new parts with different priorities, and 4) jobs that have probabilistic processing times and transportation times. Because of their ability to capture that evolution faithfully, simulation models are often used in the aforementioned decisions. In this paper, various types of decision-making problems encountered in a shop floor have been investigated and categorized into process related problems and resource related problems for shop floor simulation.

• 대한기계학회논문집B
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• 제23권9호
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• pp.1185-1191
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• 1999

Radiation-induced oscillatory instability in diffusion flames is numerically investigated with nonlinear dynamics considered. As the simplest flame model, a diffusion flame established in the stagnant mixing layer is employed with optically thin gas-phase radiation and unity Lewis numbers for all species. Attention is focused on the radiation-induced extinction regime, which occurs at large $Damk\ddot{o}hler$ number. Once the steady flame structure is obtained for a prescribed value of the initial $Damk\ddot{o}hler$ number, transient solution of the flame is calculated after a finite amount of the $Damk\ddot{o}hler$-number perturbation is imposed on the steady flame. Transient evolution of the flame exhibits three types of flame-evolution behaviors, namely decaying oscillatory solution, diverging solution to extinction and stable limit-cycle solution. A dynamic extinction boundary is identified for laminar flamelet library.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.920-924
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• 2005

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the environment. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• Carbon letters
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• 제14권4호
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• pp.228-233
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• 2013

In this work, we report in-situ observations of changes in catalyst morphology, and of growth termination of individual carbon nanotubes (CNTs), by complete loss of the catalyst particle attached to it. The observations strongly support the growth-termination mechanism of CNT forests or carpets by dynamic morphological evolution of catalyst particles induced by Ostwald ripening, and sub-surface diffusion. We show that in the tip-growth mode, as well as in the base-growth mode, the growth termination of CNT by dissolution of catalyst particles is plausible. This may allow the growth termination mechanism by evolution of catalyst morphology to be applicable to not only CNT forest growth, but also to other growth methods (for example, floating-catalyst chemical vapor deposition), which do not use any supporting layer or substrate beneath a catalyst layer.

• 대한기계학회논문집B
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• 제25권1호
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• pp.29-35
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• 2001

Radiation-induced oscillatory instability in CH$_4$/Air diffusion flames is numerically investigated by adopting detailed chemistry. Counterflow diffusion flame is employed as a model flamelet and optically thin gas-phase radiation is assumed. Attention is focused on the extinction regime induced by radiative heat loss, which occurs at low strain rate. Once a steady flame structure is obtained for a prescribed value of initial strain rate, transient solution of the flame is calculated after a finite amount of strain-rate perturbation is imposed on the steady flame. Depending on the initial strain rate and the amount of perturbed strain rate, transient evolution of the flame exhibits various types of flame-evolution behaviors. Basically, the dynamic behaviors can be classified into two types, namely oscillatory decaying solution and diverging solution leading to extinction.