• 한국전산유체공학회:학술대회논문집
• /
• 2004.10a
• /
• pp.187-191
• /
• 2004

The conventional reliability based design optimization(RBDO) methods require high computational cost compared with the deterministic design optimization(DO) methods. To overcome the computational inefficiency of RBDO, single loop methods have been proposed. These need less function calls than that of RBDO but much more than that of DO. In this study, the approximate reliability method is proposed that the computational requirement is nearly the same as DO and the reliability accuracy is good compared with that of RBDO. Using this method, the 3-D viscous aerodynamic shape design optimization with uncertainty is performed very efficiently.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.19 no.5
• /
• pp.589-595
• /
• 2010

This paper presents a reliability-based shape optimization (RBSO) using the evolutionary structural optimization (ESO). An actual design involves uncertain conditions such as material property, operational load, poisson's ratio and dimensional variation. The deterministic optimization (DO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBSO 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-based shape design optimization method is proposed by utilization the reliability index approach (RIA), performance measure approach (PMA), single-loop single-vector (SLSV), adaptive-loop (ADL) are adopted to evaluate the probabilistic constraint. In order to apply the ESO method to the RBSO, a sensitivity number is defined as the change of strain energy in the displacement constraint. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization.

• International Journal of Quality Innovation
• /
• v.5 no.1
• /
• pp.43-51
• /
• 2004

During process design or process optimization, it is quite common for experimenters to find optimum operating conditions for several responses simultaneously. The traditional multiresponse surfaces optimization methods do not consider the uncertain relationship among these responses sufficiently. For this reason, the authors propose an optimization method based on evidential reasoning theory by Dempster and Shafer. By maximizing the basic probability assignment function, which indicates the degree of belief that certain operating condition is the solution of this multiresponse surfaces optimization problem, the desirable operating condition can be found.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.34 no.7
• /
• pp.18-27
• /
• 2006

The conventional reliability based design optimization(RBDO) methods require high computational cost compared with the deterministic design optimization(DO) methods, therefore it is hard to apply directly to large-scaled problems such as an aerodynamic shape design optimization. In this study, to overcome this computational limitation the efficient RBDO procedure with the two-point approximation(TPA) and adjoint sensitivity analysis is proposed, that the computational requirement is nearly the same as DO and the reliability accuracy is good compared with that of RBDO. Using this, the 3-D aerodynamic shape design optimization is performed very efficiently.

• Nuclear Engineering and Technology
• /
• v.52 no.5
• /
• pp.956-963
• /
• 2020

Dose optimization for Radioactive Occupational Personal (ROP) is an important subject in nuclear and radiation safety field. The geometric environment of a nuclear facility is complex and the work area is radioactive, so traditional navigation model and radioactive data field cannot form an effective environment model for dose assessment and dose optimization. The environment model directly affects dose assessment and indirectly affects dose optimization, this is an urgent problem needed to be solved. Therefore, this paper focuses on an environment model used for Dose Assessment and Dose Optimization (DA&DO). We designed a multi-layer radiation field coupling modeling method, and then explored the influence of the environment model to DA&DO by virtual simulation. Then, a simulation test is done, the multi-layer radiation field coupling model for nuclear facilities is demonstrated to be effective for dose assessment and dose optimization through the experiments and analysis.

• Journal of the Korea Safety Management & Science
• /
• v.8 no.3
• /
• pp.125-141
• /
• 2006

If do not become whole optimization because enterprise's individual enterprise internal determinate improvement effort is associated with activity in enterprise SCM, competitive power can not but be extremely limited the result. Therefore, to spur in hidden cost's discovery and logistics' optimization is actuality. In this paper, as long as it is by logistics cost except empty driving if reverse logistics happens in distribution channel progressing, logistics reverse logistics' hidden cost through model that do minimization profit of logistics to look for plan that can do maximization try. Finally, is based on dual of distribution cost and profit of logistics and reverse logistics and achieves Pull, optimal system modeling that use Push system and gropes method of effective logistics cost.

• 한국전산유체공학회:학술대회논문집
• /
• 2005.10a
• /
• pp.99-104
• /
• 2005

For the efficient reliability analysis, Bi-direction two-point approximation(BTPA) method is developed which solves shortcomings of conventional two-point approximation(TPA) methods that generate an approximate surface with low accuracy or sometimes do an unstable approximate surface. The conventional reliability based design optimization(RBDO) methods require high computational cost compared with the deterministic design optimization(DO) methods. To overcome the computational inefficiency of RBDO, the approximate reliability analysis approaches on the TPA surface are proposed. Using these FORM and SORM analysis strategies, multi-point aerodynamic-structure interacted shape design optimizations with uncertainty are performed very efficiently.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.01a
• /
• pp.257-260
• /
• 2021

본 논문에서는 카메라의 포커싱과 아웃포커싱에 의해 이미지에서 뿌옇게 표현되는 DoF(Depth of field, 피사계 심도) 영역을 쿼드트리(Quadtree) 기반의 합성곱 신경망을 통해 빠르게 찾는 방법을 제안한다. 우리의 접근 방식은 RGB채널기반의 상호-상관 필터를 이용하여 DoF영역을 이미지로부터 효율적으로 분류하고, 적응형 트리인 쿼드트리를 기반으로 유의미한 영역만을 분류한다. 이 과정에서 손실 없이 온전하게 DoF영역을 추출하기 위한 필터링 과정을 거친다. 이러한 과정에서 얻어진 이미지 패치들은 전체 이미지에 비해 적은 영역으로 나타나며, 이 적은 개수의 패치들을 이용하여 네트워크 단계에서 사용할 이미지-DoF가중치 맵 데이터 쌍을 설정한다. 네트워크 과정에서 학습할 때 사용되는 데이터는 이미지와 상호-상관 필터 기반으로 추출된 DoF 가중치 맵을 이용한다. 본 논문에서 제안하는 쿼드트리 기반 합성곱 신경망은 이미지로부터 포커싱과 아웃포커싱된 DoF영역을 자동으로 추출하는 과정을 학습시키기 위해 사용된다. 결과적으로 학습에 필요한 데이터 영역이 줄어듦으로써 학습 시간과 메모리를 절약했으며, 테스트 결과로 얻은 DoF 가중치 이미지는 입력 이미지에서 DoF영역을 더욱더 빠른 시간 내에 찾아낸다.

• Journal of computational fluids engineering
• /
• v.9 no.1
• /
• pp.34-40
• /
• 2004

Recently with growth in the capability of super computers and Parallel computers, shape design optimization is becoming easible for real problems. Also, Computational Fluid Dynamics(CFD) techniques have been improved for higher reliability and higher accuracy. In the shape design optimization, analysis solvers and optimization schemes are essential. In this work, the Roe's 2nd-order Upwind TVD scheme and DADI time march with multigrid were used for the flow solution with the Euler equation and FDM(Finite Differenciation Method), GA(Genetic Algorithm) and Kriging were used for the design optimization. Kriging were applied to 2-D airfoil design optimization and compared with FDM and GA's results. When Kriging is applied to the nonlinear problems, satisfactory results were obtained. From the result design optimization by Kriging method appeared as good as other methods.

• Journal of the Korea Institute of Building Construction
• /
• v.8 no.6
• /
• pp.91-98
• /
• 2008

It is time-consuming and difficulty to solve the time-cost trade-off problems, as there are trade-offs between time and cost to complete the activities in construction projects and this problems do not have unique solutions. Typically, heuristic methods, mathematical models and GA models has been used to solve this problems. As heuristic methods and mathematical models are have weakness in solving the time-cost trade-off problems, GA based model has been studied widely in recent. This paper suggests the time-cost trade-off optimization algorithm using particle swarm optimization. The traditional particle swarm optimization model is modified to generate optimal tradeoffs among construction time and cost efficiently. An application example is analyzed to illustrate the use of the suggested algorithm and demonstrate its capabilities in generating optimal tradeoffs among construction time and cost. Future applications of the model are suggested in the conclusion.