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김상현,장병철,김원기,김남현,조범구,Kim, Sang-Hyeon,Jang, Byeong-Cheol,Kim, Won-Gi,Kim, Nam-Hyeon,Jo, Beom-Gu 대한의용생체공학회 1993 의공학회지 Vol.14 No.2
We developed a ventricular assist device(VAD) to be used as a bridge to heart transplantation or a circulatory assist device for patients with end-stage heart disease or poor myocardial function after cardiac surgery. It is a pneumatic and diaphragm-type VAD and its stroke volume is 90 cc. The upper housing and diaphragm is made of a segmented polyurethane and the lower back plate is made of a polycarbonate. Two Carbomedics$^R$ mechanical valves are used as inlet and outlet valves. It was tested in vitro and the cardiac output of the VAD was 7 L/min at a heart rate of 70 bpm. The line pressure from a pressure transducer inserted in the pneumatic line was recorded and compared with the ideal pressure tracing.
김상현,Kim, Sang-Hyeon 한국과학기술단체총연합회 2003 과학과 기술 Vol.36 No.1
이리 호에 대해 과학자들은 1960년대만 해도 확신에 차 있었다. 이리 호 오염의 원인이 단순했기 때문이다. 그러나 지금은 세 배, 혹은 그 이상으로 복잡하고 다층적이다. 외래 침입종에다 지구 온난화 문제, 거기에 인을 비롯한 독성 화학물질까지 가세해 이리 호 문제 해결을 더욱 어렵게 만들고 있다. 과학자들은 과연 죽어 가는 이리 호를 되살릴 수 있을까?
김상현,정성택,김훈모,Kim, Sang-Hyeon,Jeong, Seong-Taek,Kim, Hun-Mo 대한의용생체공학회 1998 의공학회지 Vol.19 No.1
본 연구에서 복잡한 비선형적 특성을 갖는 공압식 좌심실보조장치의 모델링과 제어에 인공신경망을 제안하였다. 일반적으로 좌심실보조장치는 비선형이 보상되어야 하는데 인공신경망은 학습능력에 의해 비선형 동적 시스템의 제어에 적용될 수 있다. 인공신경망 모델링을 통해 좌심실 보조장치의 동적 모델을 모델링하고 이를 기반으로 하여 인공신경망 제어기가 설계되었다. 제안된 알고리즘을 이용한 좌심실보조장치의 모델링과 제어성능 및 유효성은 컴퓨터 시뮬레이션에 의해 증명되었다. In this paper, we present a neural network identification and a control of highly complicated nonlinear left ventricular assist device(LVAD) system with a pneumatically driven mock circulation system. Generally, the LVAD system needs to compensate for nonlinearities. It is necessary to apply high performance control techniques. Fortunately, the neural network can be applied to control of a nonlinear dynamic system by learning capability. In this study, we identify the LVAD system with neural network identification(NNI). Once the NNI has learned the dynamic model of the LVAD system, the other network, called neural network controller(NNC), is designed for a control of the LVAD system. The ability and effectiveness of identifying and controlling the LVAD system using the proposed algorithm will be demonstrated by computer simulation.
강-소성 유한요소법의 역추적기법을 이용한 정밀정형 쉘 노우징 부품의 성형공정 개발과 실험적 증명
김상현,이진희,임학진,Kim, Sang-Hyeon,Lee, Jin-Hui,Im, Hak-Jin 대한기계학회 1996 大韓機械學會論文集A Vol.20 No.7
A preform is designed by the backward tracing scheme of the rigid-plastic finite element method(FEM) for net-shape shell nosing components without machining after forming. The current process of the shell nosing requires cost-consuming machining to produce final products. Here, the backward tracing scheme of the rigid-plastic FEM, a novel method for preform design of metal forming processes, derives a sound preform for net-shape shell nosing product. The current process is simulated by the rigid-plastic finite element analysis to check the metal flow involved in the forming with a trial preform and its modified preform. The two preforms are found to be inadequate for net-shape shell nosing product. The first application of the back ward tracing scheme derives a preform producing a not-shape shell nosing product. The first application of the backward tracing scheme derives a preform producing a net-shape product numerically, but it is difficult to be formed economically as a preform. Thus an improved preform is designed by the badkward tracing scheme, which is suitable for net-shape manufacturing of the shell nosing components in view of economy of production and forming characteristics of the product. The preform in the current process and a modified preform are confirmed by a series of experiments and the results give the same deformation with the numerical ones. Finally the newly designed preform by the FEM was experimentally proved to be adequate in obtaining net-shape products.