http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
유전자 알고리즘을 이용한 로커암 축의 최적설계에 관한 연구
안용수(Y. S. An),이수진(S. J. Lee),이동우(D. W. Lee),홍순혁(S. H. Hong),조석수(S. S. Cho),주원식(W. S. Joo) 한국정밀공학회 2004 한국정밀공학회 학술발표대회 논문집 Vol.2004 No.10월
This study proposes a new optimization algorithm which is combined with genetic algorithm and ANOM. This improved genetic algorithm is not only faster than the simple genetic algorithm, but also gives a more accurate solution. The optimizing ability and convergence rate of a new optimization algorithm is identified by using a test function which have several local optimum and an optimum design of rocker arm shaft. The calculation results are compared with the simple genetic algorithm.
역전파 신경회로망을 이용한 피로손상 모델링에 관한 연구
김민철(M.C.Kim),주원식(W.S.Joo),장득열(D.Y.Jang),조석수(S.S.Cho),김순호(S.H.Kim) 한국자동차공학회 1998 한국자동차공학회 춘 추계 학술대회 논문집 Vol.1998 No.11_2
Back-propagation neural networks performs computer simulations that have the potential to find the same patterns that fatigue practitioners recognize to relate experimental results to fatigue life prediction. This potential was used to construct neural networks to recognize the relation between da/dN, N/Nf, X-ray diffraction half-value breadth ratio B/Bo, fractal dimension D_f and fracture mechanical parameters for Al 2024-T3 alloy. Learning and generalization of neural networks was optimized by floating rate method. This study shows that neural networks has ability to predict fatigue crack growth rate and life on data of unlearned experimental condition.<br/>
KSAE 대학생 Formula 차량의 롤 케이지 구조 설계 및 제작
강호진(Ho-Jin Kang),조석수(Seok-Swoo CHO),민종식(Jong-Sik MIN),박재성(Jae-Sung PARK),박형도(Hyung-Do PARK),김덕주(Deok-Joo KIM),한창훈(Chang-Hoon HAN),강동웅(Dong-Woong KANG),김종범(Jong-Bum KIM),윤영환(Young-Hwan YOON),이범석(Beom-S 대한기계학회 2016 대한기계학회 춘추학술대회 Vol.2016 No.12
The study of this research is to design and manufacture the roll cage frame for Kangwon National University KSAE Student Team in The KSAE Formula 2016 Competition. The objective value of the stress and the displacement at roll cage frame are 305 MPa and 25mm respectively. Structural analysis and structural optimization are performed by ANSYS Workbench 15 and Minitab 17. Structural optimized roll cage has bending stiffness of 23,833N/mm and torsional stiffness of 1,408N·m/deg. The results are compared with the roll cage manufactured by the other university teams. The roll cage for 2016 KNU KSAE student formula team has maximum stress of 146.68MPa and maximum displacement of 7.93mm which accomplish the requirements of the roll cage.