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황승민,박재용,임민규,오영규,한석영 한국공작기계학회 2009 한국공작기계학회 춘계학술대회논문집 Vol.2009 No.-
This paper presents a reliability-based topology optimization (RBTO) using bi-directional evolutionary structural optimization (BESO). Topology optimization is formulated as volume minimization problem with probabilistic displacement constraint. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., RIA, PMA, SLSV and ADL(adaptive-loop), are used. Reliability-based topology optimization design process is conducted to obtain optimal topology satisfying displacement and reliability index constraints with the above four methods, and then each result is compared with respect to numerical stability and computing time.
황승민(Seung-min Hwang),박재용(Jae-yong Park),임민규(Min-gyu Im),오영규(Young-kyu Oh),박재용(Jae-yong Park),한석영(Seog-young Han) 한국생산제조학회 2009 한국생산제조시스템학회 학술발표대회 논문집 Vol.2009 No.5
This paper presents a reliability-based topology optimization (RBTO) using bi-directional evolutionary structural optimization (BESO). Topology optimization is formulated as volume minimization problem with probabilistic displacement constraint. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., RIA, PMA, SLSV and ADL(adaptive-loop), are used. Reliability-based topology optimization design process is conducted to obtain optimal topology satisfying displacement and reliability index constraints with the above four methods, and then each result is compared with respect to numerical stability and computing time.
박재용(Jae-Yong Park),황승민(Seung-Min Hwang),임민규(Min-Kyu Lim),오영규(Young-Kyu Oh),박재용(Jae-Yong Park),한석영(Seog-Young Han) 한국생산제조학회 2009 한국생산제조시스템학회 학술발표대회 논문집 Vol.2009 No.5
This paper presents a reliability-based topology optimization (RBTO) using bi-directional evolutionary structural optimization (BESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic topology optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints. In this paper, the reliability index approach (RIA) is adopted to evaluate the probabilistic constraint. RBTO based on BESO starting from various design domains produces a similar optimal topology each other. Numerical examples are presented to compare the DTO with the RBTO.
ESO 기법을 이용한 외팔보의 신뢰성 기반 위상최적설계
김상락,박재용,이원구,유진식,한석영 한국공작기계학회 2008 한국공작기계학회 춘계학술대회논문집 Vol.2008 No.-
This paper presents a Reliability-Based Topology Optimization (RBTO) using the Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. The Deterministic Topology Optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints, In order to determine whether the probabilistic constraint is satisfied or not, simulation techniques and approximation methods are developed, In this paper, the reliability index approach (RIA) is adopted to evaluate the probabilistic constraint, In order to apply the ESO method to the RBTO, a sensitivity number is defined as the change in the reliability index due to the removal of ith element. Numerical examples are presented to compare the DTO with the RBTO.
박재용,황승민,임민규,오영규,박재용,한석영 한국공작기계학회 2009 한국공작기계학회 춘계학술대회논문집 Vol.2009 No.-
This paper presents a reliability-based topology optimization (RBTO) using bi-directional evolutionary structural optimization (BESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic topology optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints. In this paper, the reliability index approach (RIA) is adopted to evaluate the probabilistic constraint. RBTO based on BESO starting from various design domains produces a similar optimal topology each other. Numerical examples are presented to compare the DTO with the RBTO.
김상락,박재용,이원구,유진식,한석영 한국공작기계학회 2007 한국공작기계학회 추계학술대회논문집 Vol.2007 No.-
This paper presents a Reliability-Based Topology Optimization (RBTO) using Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic Topology Optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, RBTO involves evaluation of probabilistic constraints, which can be done in two different ways, the reliability index approach (RIA) and the performance measure approach (PMA). Limit state function is approximated using Monte Carlo Simulation and Central Composite Design for reliability analysis. ESO, one of the topology optimization techniques, is adopted for topology optimization. Numerical examples are presented to compare the DTO with RBTO.
ESO 기법을 이용한 외팔보의 신뢰성 기반 위상최적설계
김상락(Sang-Rak Kim),박재용(Jea-Yong Park),이원구(Won-Goo Lee),유진식(Jin-Shik Yu),한석영(Seog-Young Han) 한국생산제조학회 2008 한국생산제조시스템학회 학술발표대회 논문집 Vol.2008 No.5
This paper presents a Reliability-Based Topology Optimization (RBTO) using the Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. The Deterministic Topology Optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraint is satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability index approach (RIA) is adopted to evaluate the probabilistic constraint. In order to apply the ESO method to the RBTO, a sensitivity number is defined as the change in the reliability index due to the removal of ith element. Numerical examples are presented to compare the DTO with the RBTO.
김상락(Sang-Rak Kim),박재용(Jea-Yong Park),이원구(Won-Goo Lee),유진식(Jin-Shik Yu),한석영(Seog-Young Han) 한국생산제조학회 2007 한국생산제조시스템학회 학술발표대회 논문집 Vol.2007 No.10
This paper presents a Reliability-Based Topology Optimization (RBTO) using Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic Topology Optimization (DTO) is obtained without considering of uncertainties related to the uncertainty parameters. However, RBTO involves evaluation of probabilistic constraints, which can be done in two different ways, the reliability index approach (RIA) and the performance measure approach (PMA). Limit state function is approximated using Monte Carlo Simulation and Central Composite Design for reliability analysis. ESO, one of the topology optimization techniques, is adopted for topology optimization. Numerical examples are presented to compare the DTO with RBTO.