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학위논문
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이영헌 (부산대학교, 부산대학교 대학원)

지도교수
강범수
발행연도
2020
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부산대학교 논문은 저작권에 의해 보호받습니다.

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이 논문의 연구 히스토리 (2)

초록· 키워드

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본 연구에서는 수소연료전지 시스템에서 연료를 저장하는 2, 3 및 6 리터 용량의 수소저장용기에 대하여 최적설계를 수행하였다. 최적설계 조건은 67.5 MPa의 파열압력에서 파손이 발생하지 않으며, 이때 수소 저장용기의 무게가 최소가 되도록 설정하였다. 최적화 방법은 전역적 최적화에 보다 적합한 메커니즘을 가지고 있는 유전자 알고리즘을 사용하였으며, 설계변수로 복합재료의 헬리컬 층과 후프 층의 적층 각도와 두께를 사용하였다. 파손은 Tsai-Wu 파손이론을 이용한 유한요소해석을 통해 검증하였다. 그리고 최적화된 수소저장용기와 상용 제품의 중량을 비교하였으며, 6 리터 용량의 수소저장용
기에서 약 12.59%의 중량이 감소됨을 확인하였다. 추가로 수소저장용기의 중량 감소에 따른 비행성능 향상을 확인하기 위해 제자리 비행시간을 계산하였으며, 6 리터 용량의 최적화한 수소저장용기를 적용한 경우 상용 제품과 비교하여 제자리 비행시간이 약 17.69% 증가함을 확인하였다.

목차

1. 서론 ·········································································································································· 1
2. 유한요소법을 이용한 수치해석 ······························································································· 4
2.1. 저장용기 설계 ··················································································································· 4
2.2. 저장용기의 타입 ··············································································································· 4
2.3. 사이징 ································································································································ 5
2.4. 복합재료 파단 기준 ········································································································· 5
2.4.1. 최대 응력 파손기준 ···························································································· 6
2.4.2. 최대 변형률 파손 기준 ······················································································ 8
2.4.3. Tsai-Hill 파손기준 ····························································································· 9
2.4.4. Tsai-Wu 파손기준 ··························································································· 10
2.4.5. Hashin 파손기준 ······························································································ 11
2.4.6. Puck 파손기준 ································································································· 12
3. 유전자 알고리즘 ······················································································································ 15
3.1. 초기 개체군 생성 ··········································································································· 16
3.2. 적합도 평가 ····················································································································· 16
3.3. 선택 연산 ························································································································ 17
3.4. 교차 연산 ························································································································ 18
3.5. 변이 연산 ························································································································ 18
4. 비행성능 예측 ·························································································································· 19
5. 결과 ············································································································································ 21
5.1. 최적화 결과 ····················································································································· 21
5.2. 비행성능 예측 결과 ······································································································· 22
6. 결론 ············································································································································ 24

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