Ikjin Lee
Korea Advanced Institute of Science and Technology 기계공학과 · Decision Sciences
이 교수의 연구실은 신뢰성 기반 설계 최적화(RBDO)와 신뢰성 분석 기법의 정밀도 향상을 핵심으로 하며, 특히 1차 신뢰성 방법(FORM)과 2차 신뢰성 방법(SORM)의 정확성 개선에 초점을 맞추고 있습니다. 차원 감소법(DRM)과 몽테카를로 시뮬레이션 기반의 민감도 분석, 그리고 관련된 성능 함수의 해석적 도함수 유도 등 신뢰성 기반 최적화의 정밀성과 효율성을 동시에 확보하는 데 기여하고 있습니다. 특히 차량 역학 기반 도로 설계 최적화 및 부정확한 최적해 보정 기법 개발을 통해 실용적 응용 가능성까지 확장하고 있습니다.
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This paper proposes a novel second-order reliability method (SORM) using noncentral or general chi-squared distribution to improve the accuracy of reliability analysis in existing SORM. Conventional SORM contains three types of errors: (1) error due to approximating a general nonlinear limit state function by a quadratic function at most probable point in standard normal U-space, (2) error due to approximating the quadratic function in U-space by a parabolic surface, and (3) error due to calcula
This study presents a methodology for computing stochastic sensitivities with respect to the design variables, which are the mean values of the input correlated random variables. Assuming that an accurate surrogate model is available, the proposed method calculates the component reliability, system reliability, or statistical moments and their sensitivities by applying Monte Carlo simulation to the accurate surrogate model. Since the surrogate model is used, the computational cost for the stocha
Abstract In gradient‐based design optimization, the sensitivities of the constraint with respect to the design variables are required. In reliability‐based design optimization (RBDO), the probabilistic constraint is evaluated at the most probable point (MPP), and thus the sensitivities of the probabilistic constraints at MPP are required. This paper presents the rigorous analytic derivation of the sensitivities of the probabilistic constraint at MPP for both first‐order reliability method (FORM)
This article presents reliability analysis and reliability-based optimization of roadway minimum radius design based on vehicle dynamics, mainly focusing on exit ramps and interchanges. The performance functions are formulated as failure modes of vehicle rollover and sideslip. To accurately describe the failure modes, analytical models for rollover and sideslip are derived considering nonlinear characteristics of vehicle behaviour using the commercial software TruckSim. The probability of an acc
Summary In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a perfo
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