• 한국지능시스템학회논문지
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• 제16권6호
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• pp.753-758
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• 2006

본 논문에서는 하이브리드 발전 시스템에서의 최대 전력 추종을 위한 디지털 퍼지 제어기 설계를 목표로 한다. 하이브리드 발전 시스템은 풍력과 태양광, 두 개의 발전 시스템으로 구성된다. 각 발전기에서 전압과 전류는 일반적으로 비선형 관계에 있기 때문에, 퍼지 모델 기반 제어기를 사용하여 비선형성을 효율적으로 제어하게 된다. 또한 마이크로프로세서 기반제어 시스템의 구축을 위하여 최신 디지털 재설계 기법을 사용하며, 디지털 퍼지 제어기를 설계하게 된다. 마지막으로 하이브리드 발전 시스템의 플랜트를 통한 실험으로써 본 제안 기법의 우수성을 입증한다.

• 대한금속재료학회지
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• 제49권12호
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• pp.956-966
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• 2011

Bioleaching studies of metals from a spent catalyst were conducted using both adapted and unadapted bacterial cultures. The bacterium used in this experiment was Acidithiobacillus ferrooxidans. A comparison of the kinetics of leaching was made between the two cultures by varying the leaching parameters, including the pulp density, particle size and temperature. Both cultures showed similar effects with respect to the above parameters, but the leaching rates of all metals were higher with the adapted compared to the unadapted bacterial cultures. The leaching reactions were continued for 240 h in the case of the unadapted bacterial culture, but only for 40 h in the case of the adapted bacterial culture. The leaching reactions followed first order kinetics. In addition, the kinetics of leaching was concluded to be a diffusion control model; therefore, the product layers were impervious.

• Smart Structures and Systems
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• 제24권6호
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• Steel and Composite Structures
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• 제6권3호
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• pp.203-219
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• 2006

One of the most promising ways through which a steel moment frame may attain high energy dissipating capability is to trim off a portion of the beam flanges near the column face. This type of moment connection, known as Reduced Beam Section (RBS) connection, has notable superiority in comparison with other moment connection types. As the result of the advantages of RBS moment connection, it has widely being used in practice. In spite of the good hysteretic behaviour, an RBS beam suffers from an undesirable drawback, which is local and lateral instability of the beam. The instability in the RBS beam reduces beam load-carrying capacity. This paper aims to investigate key issues influencing cyclic behaviour of RBS beams. To this end, a numerical analysis was conducted on a series of steel subassemblies with various geometric properties. The obtained results together with the existing experimental data are used to study the instability of RBS beams. A new slenderness concept is presented to control an RBS beam for combined local and lateral instability. This concept is in good agreement with the numerical and experimental results. Finally, a model is developed for the prediction of the magnitude of moment degradation owing to the instability of an RBS beam.

• 설비공학논문집
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• 제16권7호
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• pp.630-638
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• 2004

Liquid desiccant dehumidification systems have the ability to provide efficient humidity and temperature control while saving the electrical energy requirement for air conditioning as compared to a conventional system. The dehumidifier and the regenerator form the heart of this system. The latent part of the cooling load is overcome using liquid desiccant. The model regenerator has been designed to study the absorption characteristic of the aqueous triethylene glycol (TEG) solution which is in the flow range from 20 to 50 LPM. Also, this system designed that was able to change the height of the regenerator and dehumidifier. Because the effect of performance have different result according the height. The effect of performance factors of the regenerator with inlet solution flow rate, air flow rate, solution concentration, solution temperature, brine temperature, air temperature and inlet air relative humidity have been analyzed. Data obtained are useful for design guidance and performance analysis of the hybrid air conditioning system.

• Nuclear Engineering and Technology
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• 제18권2호
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• pp.71-77
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• 1986

원자로 노심을 축방향으로 일차원 해석을 하고, 가입경수로형원자로의 안전성 해석에 적용할 수 있는 중성자 동특성프로그램 BIK를 개발하였다. BIK프로그램내에서 공간변수에 대해서는 유한차분법이, 시간변수에 대해서는 $\theta$-시간적분법이 채택되었다. 또한 도플러 및 감속재 궤환과 제어봉구동 등을 자세히 묘사하는 모델들이 포함되었다 핵모델의 검증은 ANL검증문제를 통해 이루어졌고, 고리 1호기의 제어봉 인출사고시의 노심출력 변화를 계산하였다. 이상의 계산결과 BIK동특성프로그램이 노심의 중성자 속 변화를 일차원해석의 한계내에서 비교적 정착하게 묘사할 수 있으며, 가압경수로형 원자로의 안전성 해석에 유용하게 사용될 수 있다는 것이 증명되었다.

• 한국재료학회지
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• 제31권6호
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• pp.367-374
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• 2021

This paper presents the characteristics of gentamicin-loaded into cetyl trimethyl ammonium intercalated montmorillonite (GtM/CTMA/Mt) as a hybrid composite for a slow-released antibacterial delivery systems. The work describes the successful immobilization of gentamicin into the interlayers of surfactant-modified montmorillonite. Physicochemical characterization of the material is carried out by means of X-ray diffraction, scanning electron microscopy, transmission electron microscopy, and Fourier transform infrared spectroscopy. The kinetics of the gentamicin release is investigated by in vitro study and analyzed based on UV-Vis spectrometry. In addition, antibacterial study is performed towards Klebsiella pneumoniae Staphylococcus aureus, Escherichia coli, and Streptococcus pyogenes. The results show that the gentamicin loading into CTMA/Mt increases the effectiveness of the antibacterial activity, as shown by the higher inhibition zone for all tested bacteria, compared to gentamicin as a positive control. The kinetics study suggests that the gentamicin release obeys the modified Korsmeyer-Peppas model. The physicochemical study and activity test demonstrate the feasibility of the GtM/CTMA/Mt for practical applications.

• Advances in concrete construction
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• 제10권6호
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• pp.489-498
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• 2020

This paper investigates mechanical properties of roller compacted concrete (RCC) involving reclaimed asphalt pavement (RAP). In this way, a set of 276 cylindrical RCC specimens were prepared with different RAP sizes (i.e., fine, coarse & total) at various ratios (i.e., 10%, 20%, and 40%). Results reveal that incorporation of RAP decreases unconfined compressive strength (UCS), modulus of elasticity (E), and indirect tensile (IDT) strength of RCC. For each RAP size, a regression model was used to maximize RAP content while satisfying the UCS lower limit (27.6 Mpa) mentioned by ACI as a minimum requirement for RCC used in pavement construction. Moreover, UCS of RAP incorporated mixes, dissimilar to that of control mixes, was found to be sensitive and insensitive to the testing temperature and curing time after 7 days, respectively. The results also demonstrate that the higher amounts of RAP, the more flexibility in RCC is. This issue was also proved by the results of modulus of elasticity test. In addition, the toughness index (TI) shows that increase in RAP content leads to up to 43% increase in energy absorbance capacity of RCC.

• 스마트미디어저널
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• 제11권3호
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• pp.18-25
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• 2022

뉴로모픽 컴퓨팅은 일반적으로 CPU와 GPU를 이용하여 신경망 연산을 하는 것보다 전력, 면적, 속도 측면에서 매우 뛰어난 성능을 보여준다. 이러한 특성은 에너지 사용량이 중요시되는 자원 제약적인 IoT 환경에 매우 적합하다. 하지만 뉴로모픽 컴퓨팅을 지원하는 이기종 IoT 기기에 따라 환경설정 및 응용 프로그램 동작을 위한 소스코드의 수정이 필요하다는 문제점을 가지고 있다. 이러한 문제점을 해결하고자 본 논문에서는 NAAL을 제안하고 구현하였다. NAAL은 공통의 API를 기반으로 다양한 이기종 IoT 기기 환경에서 IoT 기기의 제어와 뉴로모픽 아키텍처의 추상화 및 추론 모델 동작에 필요한 기능을 제공한다. NAAL은 향후 새로운 이기종 IoT 기기 및 뉴로모픽 아키텍처와 컴퓨팅 장치의 추가적인 지원이 가능하다는 장점을 가진다.

• 대한임베디드공학회논문지
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• 제18권4호
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• pp.165-172
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• 2023

Heterogeneous computing is a technology that utilizes different types of processors to perform parallel processing. It maximizes task processing and energy efficiency by leveraging various computing resources such as CPUs, GPUs, and FPGAs. On the other hand, edge computing has developed with IoT and 5G technologies. It is a distributed computing that utilizes computing resources close to clients, thereby offloading the central server. It has evolved to intelligent edge computing combined with artificial intelligence. Intelligent edge computing enables total data processing, such as context awareness, prediction, control, and simple processing for the data collected on the edge. If heterogeneous computing can be successfully applied in the edge, it is expected to maximize job processing efficiency while minimizing dependence on the central server. In this paper, experiments were conducted to verify the feasibility of various parallel programming models on high-end and low-end edge devices by using benchmark applications. We analyzed the performance of five parallel programming models on the Raspberry Pi 4 and Jetson Orin Nano as low-end and high-end devices, respectively. In the experiment, OpenACC showed the best performance on the low-end edge device and OpenSYCL on the high-end device due to the stability and optimization of system libraries.