• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.2
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• pp.1184-1187
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• 2003

Electrochemical capacitors are becoming attractive energy storage systems particularly for applications involving high power requirements such as hybrid systems consisting of batteries and electrochemical capacitors for electric vehicle propulsion. A new type electric double layer capacitor (EDLC) was constructed by using carbon nanofibers (CNFs) and DAAQ(1,5-diaminoanthraquinone) electrode. Carbonaceous materials are found in variety forms such as graphite, diamond, carbon fibers etc. While all the carbon nanofibers include impurities such as amorphous carbon, nanoparticles, catalytic metals and incompletely grown carbons. We have eliminated of Ni particles and some carbonaceous particles in nitric acid. Nitric acid treated CNFs could be covered with very thin DAAQ oligomer from the results of CV and TG analyses and SEM images. DAAQ oligomer film exhibited a specific capacity as 45-50 Ah/kg in 4M $H_2SO_4$. We established Process Parameters of the technique for the formation of nano-structured materials. Furthermore, improved the capacitive properties of the nano structured CNFs electrodes using controlled solution chemistry. As a result, CNFs coated by DAAQ composite electrode showed relatively good electrochemical behaviors in acidic electrolyte system with respect to specific capacity and scan rate dependency.

• 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.

• 한국기계가공학회지
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• 제20권2호
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• pp.14-22
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• 2021

A plan for the development of reliability-based ROK amphibious assault vehicles is proposed. By analyzing the development case of the U.S. EFV, considerations for the successful development of the next-generation Korea Forces amphibious assault vehicle are presented. If the vehicle reliability can be improved to the level of the fourth highest priority electric unit for power units, suspensions, decelerators, and body groups, which have the highest priority among fault frequency items, a system level MTBF of 36.4%↑ can be achieved, and the operational availability can be increased by 3.5%↑. The next-generation amphibious assault vehicles must fulfill certain operating and performance requirements, the underlying systems must be built, and sequencing of the hybrid engine and the modular concept should be considered. Along with big-data- and machine-learning-based failure prediction, machine maintenance based on augmented reality/virtual reality and remote maintenance should be used to improve the ability to maintain combat readiness and reduce lifecycle costs.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2013년도 추계학술발표대회
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• pp.180-183
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• 2013

근래의 프로세서는 하나의 다이 위에 여러 개의 코어를 배치한 멀티코어 형태를 띠고 있다. 최근에는 프로세서의 에너지 소비량을 줄이기 위해 비대칭 멀티코어를 활용하여 동일한 성능을 유지하며 소비전력을 낮추는 방법에 대한 연구가 활발히 진행되고 있다. 비대칭 멀티코어의 장점을 최대한 활용하기 위해서는 대칭형 멀티코어와는 달리 실행해야 할 프로세스와 상이한 코어간의 작동 특성을 고려해야 한다. 본 논문에서는 전력 소비 효율 향상을 위해 프로세스 스케줄링 알고리즘에 하이브리드 인공지능 기술인 Adaptive Neuro Fuzzy Inference System (ANFIS)를 적용하여 각 프로세스에 적합한 코어를 찾아 할당하는 방법을 제안한다. 시뮬레이션 결과 제안하는 프로세스 스케줄러는 리눅스의 CFS 대비 평균 35.4% 낮은 Energy Delay Product (EDP)를 보였으며 이를 통해 하이브리드 인공지능을 적용한 프로세스 스케줄링 알고리즘의 유효성을 입증하였다.

• 한국지열·수열에너지학회논문집
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• 제16권4호
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• pp.31-38
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• 2020

The investment in the technology of using a combined heat source is insufficient, which utilizes the advantages of various heat sources to maximize the potential energy and at the same time increases the performance of the heat pump. In this study, as basic data for the development of a high-efficiency hybrid heat pump system that actively connects and uses various heat sources, simulations were conducted for the heat pumps in two cases where geothermal and hydrothermal heat were applied respectively. In May, COP increased by about 27.3% compared to geothermal heat. In February, the COP percentage decrease of hydrothermal heat compared to geothermal heat is -6.9%. In May, total energy consumption can be reduced by 21.1% when hydrothermal is applied compared to geothermal heat. In February, the total energy consumption increases by 3.4%.

• 소성∙가공
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• 제32권3호
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• pp.122-128
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• 2023

As electric vehicles (EV) have increasingly replaced the conventional vehicles with internal combustion engines (ICE), most of automotive makers are actively devoting to the technology development of EV parts. Accordingly, the manufacturing process for power source has been also shifting from engine/transmission to EV motor/reducer system. However, lack of experience in developing the EV motor still remains as a technical challenge. In this paper, we employed the forming simulation based on finite element modeling to solve this problem. In particular, in order to increase the accuracy of the forming simulation, we introduced the elastic-plastic constitutive model parameters for polymer-copper hybrid wire by investigating the individual strain-stress curves, and elastic modulus of polymer and copper. Then, the reliability of modeling procedure was confirmed by comparing the simulated results with experiments. Finally, the identified mechanical properties and finite element modeling were applied to a hairpin forming process, which involves multiple deformation paths such as bending, pressing, widening, and twisting. The proposed numerical approach can replace common experience or experiment based trials by reducing production time and cost in the future.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2020년도 전력전자학술대회
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• pp.109-111
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• 2020

본 논문에서는 ESS용 전류원 Dual-Active-Bridge 컨버터의 저 부하 및 고 부하에서의 효율 향상을 위한 하이브리드 스위칭 알고리즘을 제안하고자 한다. 전류원 DAB 컨버터는 인터리브 구조를 이용하여 배터리 단의 입력 전류 리플을 저감할 수 있고, 전력 변환 효율 개선을 위한 다양한 제어 변수를 도입할 수 있는 등의 장점으로 인해 DC 마이크로그리드에서 ESS용 절연형 양방향 DC/DC 컨버터로 주목받고 있다. 그러나 전류원 DAB에서 종래의 전력 제어 방법인 펄스폭 변조 방식과 위상천이가 결합된 방법 (PWM plus Phase Shift, PPS)의 경우 저 부하 조건에서 높은 피크 전류로 인해 도통 손실이 크며, 펄스폭 변조 방식과 이중 위상천이가 결합된 방법(PWM plus Dual Phase Shift, PPDPS)의 경우 고 부하 조건에서 영전압 스위치 영역이 좁아져 효과적이지 않다. 따라서 본 논문에서는 2차 측의 펄스폭과 위상천이를 독립적으로 제어하는 하이브리드 스위칭 알고리즘을 통해 순환전류를 감소시키고 영전압 스위치 영역을 확장시켜 저 부하 및 고 부하 모두에서 효율을 향상시키고자 한다. 1-kW급 전류원 DAB 컨버터 시작품을 통해 제안된 하이브리드 스위칭 알고리즘의 효율성과 타당성을 검증한다.

• Nuclear Engineering and Technology
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• 제55권7호
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• pp.2516-2533
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• 2023

Several practical methods for accelerating the depletion calculation in a GPU-based Monte Carlo (MC) code PRAGMA are presented including the multilevel spectral collapse method and the vectorized Chebyshev rational approximation method (CRAM). Since the generation of microscopic reaction rates for each nuclide needed for the construction of the depletion matrix of the Bateman equation requires either enormous memory access or tremendous physical memory, both of which are quite burdensome on GPUs, a new method called multilevel spectral collapse is proposed which combines two types of spectra to generate microscopic reaction rates: an ultrafine spectrum for an entire fuel pin and coarser spectra for each depletion region. Errors in reaction rates introduced by this method are mitigated by a hybrid usage of direct online reaction rate tallies for several important fissile nuclides. The linear system to appear in the solution process adopting the CRAM is solved by the Gauss-Seidel method which can be easily vectorized on GPUs. With the accelerated depletion methods, only about 10% of MC calculation time is consumed for depletion, so an accurate full core cycle depletion calculation for a commercial power reactor (BEAVRS) can be done in 16 h with 24 consumer-grade GPUs.

• 전기전자학회논문지
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• 제21권4호
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• pp.388-396
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• 2017

얼굴 검출에는 다양한 포즈, 빛의 세기, 얼굴이 가려지는 현상 등의 많은 변수가 존재하므로, 높은 성능의 검출 시스템이 요구된다. 이에 영상 분류에 뛰어난 Convolutional Neural Network (CNN)이 적절하나, CNN의 많은 연산은 고성능 하드웨어 자원을 필요로한다. 그러나 얼굴 검출을 위한 소형, 모바일 시스템의 개발에는 저가의 저전력 환경이 필수적이고, 이를 위해 본 논문에서는 소형의 FPGA를 타겟으로, 얼굴 검출에 적절한 3-Stage Cascade CNN 구조를 기반으로하는 CPU-FPGA 통합 시스템을 설계 구현한다. 가속을 위해 알고리즘 단계에서 Adaptive Region of Interest (ROI)를 적용했으며, Adaptive ROI는 이전 프레임에 검출된 얼굴 영역 정보를 활용하여 CNN이 동작해야 할 횟수를 줄인다. CNN 연산 자체를 가속하기 위해서는 FPGA Accelerator를 이용한다. 가속기는 Bottleneck에 해당하는 Convolution 연산의 가속을 위해 FPGA 상에 다수의 FeatureMap을 한번에 읽어오고, Multiply-Accumulate (MAC) 연산을 병렬로 수행한다. 본 시스템은 Terasic사의 DE1-SoC 보드에서 ARM Cortex A-9와 Cyclone V FPGA를 이용하여 구현되었으며, HD ($1280{\times}720$)급 입력영상에 대해 30FPS로 실시간 동작하였다. CPU-FPGA 통합 시스템은 CPU만을 이용한 시스템 대비 8.5배의 전력 효율성을 보였다.

• 한국수소및신에너지학회논문집
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• 제31권5호
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• pp.405-410
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• 2020

In this literature, we are introduce a basic design of multi energy hub based on natural gas governor station. Multi energy hub consists of turbo expender generator, phosphoric acid fuel cell, pressure swing adsorption, H₂ charging station, utilities and etc. We design a hybrid energy hub system that provides energy using these complex energies, and calculates the amount of electricity that can be produced and the amount of hydrogen charged through the process analysis. TEG and phosphoric acid fuel cell produce 2,290 to 2,380 kW and can supply electricity to 500 houses. In addition, By-product H₂ gas is refined to H₂ vehicle fuel. This will help maximize the balance of energy demand and supply and improve national energy efficiency by integrating unused decompression energy power generation technology and various power generation/heat source technologies.