이익진 교수
Lee, Ikjin
KAIST 기계공학과 · 의사결정과학
연구실 소개
이 교수의 연구실은 신뢰성 기반 최적화(RBDO) 및 비정상적 불확실성 하에서의 설계 최적화를 핵심으로 하며, 특히 첫째도 신뢰도 분석의 정확도를 향상시키기 위한 고차수 신뢰도 방법(SORM) 개발과, 둘째로 설계 변수에 대한 민감도 분석 및 최적화 후처리 기법을 통해 기존의 근사 기반 방법의 오차를 보정하는 데 초점을 맞추고 있습니다. 차용된 차량 역학 모델과 함께 Monte Carlo 기반의 정확한 대체모델을 활용한 신뢰도 및 민감도 분석 기법도 개발 중이며, 실제 도로 설계 및 차량 안정성 분석에 적용 가능한 실용적 응용을 추구하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15This 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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