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Automotive fuel tank is generally divided into two parts: main frame and assembly parts. While the car is running, valves are used to prevent liquid carry over and to discharge evaporated gas from the fuel tank. However, current fuel tank designs focus on the gas ventilation or secured location. In this study, the location of the parts used to prevent liquid carry over within the fuel tank is evaluated during an optimal design process. To develop this design process, an approximate optimization is applied. Through the optimal design process, the optimal valve location in fuel tank is determined and the approximate optimization is validated by the Taguchi method. Finally, the optimized valve location is used to reduce the development cost and time and to contribute toward improved automobile quality owing to enhanced reliability.

In order to improve the efficiency of the branch-and-bound method for mixed-discrete nonlinear programming, a nonuniform convergence tolerance scheme is proposed for the continuous subproblem optimizations. The suggested scheme assigns the convergence tolerances for each continuous subproblem optimization according to the maximum constraint violation obtained from the first iteration of each subproblem optimization in order to reduce the total number of function evaluations needed to reach the discrete optimal solution. The proposed tolerance scheme is integrated with five branching order options. The comparative performance test results using the ten combinations of the five branching orders and two convergence tolerance schemes show that the suggested non-uniform convergence tolerance scheme is obviously superior to the uniform one. The results also show that the branching order option using the minimum clearance difference method performed best among the five branching order options. Therefore, we recommend using the "minimum clearance difference method" for branching and the "non-uniform convergence tolerance scheme" for solving discrete optimization problems.

A cleaning blade is an attachment installed in the toner cartridge of a laser printer for removing the residual toner from an organic photo-conductive drum. There have been many studies on the performance and life of the rubber blade. We focus on optimally designing the blade shape parameters to minimize the maximum stress of the blade while satisfying design constraints on the cleaning performance and part interference. The blade is optimally designed using a design of experiments, meta-models and an optimization algorithm implemented in PIAnO (process integration, automation, and optimization), a commercial PIDO (process integration and design optimization) tool. We integrate the CAE tools necessary for the structural analysis of the cleaning blade, automate the analysis procedure, and optimize the solution using PIAnO. We decreased the maximum stress by 32.6% in comparison with that of the initial design.

We present a new dual sequential approximate optimization (SAO) algorithm called SD-TDQAO (sequential dual two-point diagonal quadratic approximate optimization). This algorithm solves engineering optimization problems with a nonlinear objective and nonlinear inequality constraints. The two-point diagonal quadratic approximation (TDQA) was originally non-convex and inseparable quadratic approximation in the primal design variable space. To use the dual method, SD-TDQAO uses diagonal quadratic explicit separable approximation; this can easily ensure convexity and separability. An important feature is that the second-derivative terms of the quadratic approximation are approximated by TDQA, which uses only information on the function and the derivative values at two consecutive iteration points. The algorithm will be illustrated using mathematical and topological test problems, and its performance will be compared with that of the MMA algorithm.

As the number of mobile subscribers has increased recently, the demand for more number of base stations hasincreased. However, because of the shortage of sites for constructing base stations, a mobile communication module needsto be small in size. To minimize the size of the module, the size of the heat sink attached to the outside of the moduleshould be minimized. Furthermore, the temperature of each electronic component of the module should be lower than theallowable temperature so that thermal stability can be maintained. A commercial PIDO (process integration and designoptimization) tool PIAnO and a commercial CFD (computational fluid dynamics) tool FLOTHERM are used to minimizethe size of the module while the constraints on the temperatures of the twelve electronic components are satisfied. As aresult of design optimization, the volume of the heat sink is reduced by 41.9% while all the constraints on the temperatureof the twelve electronic components of the module are satisfied.

유압 브레이커는 굴착기의 암 끝에 장착되어 파쇄작업을 하는 부착작업기이다. 그러나 굴착기의 성능에 치명적인 영향을 미치는 유압 브레이커의 중량에 대한 연구는 아직 없었다. 따라서 본 연구에서는 유압 브레이커에서 대부분의 중량을 차지하고 있는 하우징에 대한 최적설계를 수행하였다. 유압 브레이커 하우징의 설계 요구사항은 정상 운전상태에서 파손없이 중량을 최소화하는 것이다. 직교배열표를 이용하여 실험점을 선정하였고, 실험점에서의 결과를 바탕으로 근사모델을 생성하여 최적 설계안을 도출하였다. 그 결과, 모든 구속조건을 만족하면서 유압 브레이커 하우징의 중량을 4.8% 감소시켰다.

1.1 사출성형 사출성형(injection molding)이란 용융된 가소성 수지를 가압 플런저를 사용하여 사출금형(injection mold) 내부에 압입하는 성형법이다. 사출성형공정은 자동화가 쉽고 생산성이 우수하기 때문에 자동차와 가전, 생필품 등과 같은 다양한 제품의 생산에 이용된다. 과거에는 사출성형에 필요한 공정조건이 작업자의 경험과 직관에 의존하여 주로 결정되었다. 하지만 제품의 특성 저하와 성형불량과 같은 문제를 사전에 예측할 수 없으므로 제품 개발과 생산에 추가적인 비용이 요구되고 이는 곧 제품 생산 원가에 영향을 주게 된다. 따라서 사출성형품의 품질과 다양성에 대한 소Key Words : Injection Molding(사출성형), Injection Pressure(사출압력), Warping Deformation(휨 변형), Weldline (웰드라인), Design of Experiments(실험계획법), Meta-model(근사모델), Design Optimization(최적설계) 초록: 사출성형에서 사출압력은 제품의 특성을 결정하는 주요인자이므로 성형품의 품질 향상을 위해 사출압력은 최소화 되어야 한다. 또한 휨 변형과 웰드라인은 사출성형에서의 대표적인 불량요인으로 사출성형품의 품질 향상을 위해 방지되어야 한다. 본 논문에서는 사출성형품의 품질 향상을 위해 설계 절차를 2단계로 나눈다. 첫 번째 설계에서는 공정조건을 제어하여 사출압력과 휨 변형을 최소화 하기 위해 직교배열표를 이용한 전산실험을 수행하고 이를 이용하여 근사모델을 생성한 후 최적설계를 수행한다. 두 번째 설계에서는 유동경로 개선을 통한 웰드라인의 발생을 방지하기 위해 해석모델의 두께를 변경하고 웰드라인 발생 유무를 평가한다. 이러한 설계절차를 통해 사출압력과 휨 변형을 최소화하면서 웰드라인을 방지하여 본 논문에서 제안한 설계방법의 유효성을 보이고자 한다. Abstract: Injection pressure, an important factor in the filling procedure, should be minimized to enhance injection molding quality. In addition, warping deformation and weld lines, which are representative failures, should be avoided to enhance injection molding quality. To improve injection molding quality, the design procedure for an automotive fog blank cover is divided into two stages. In the first stage, we optimally obtain injection molding process variables that minimize injection pressure and warping deformation by using design of experiments, approximation and optimization techniques equipped in PIAnO (Process Integration, Automation and Optimization), a commercial PIDO (Process Integration and Design Optimization) tool. Then, we determine the thickness of the automotive fog blank cover that enables us to avoid generating weld lines. The design results we obtain in this study are found far better than those of the initial design, which demonstrates the effectiveness of our design method.

RBDO approach based on a sampling method with the Kriging metamodel and Constraint Boundary Sampling (CBS), which is sequential sampling method to generate metamodels is proposed. The major advantage of the proposed RBDO approach is that it does not require Most Probable failure Point (MPP) which is essential for First-Order Reliability Method (FORM)-based RBDO approach. The Monte Carlo Sampling (MCS), most well-known method of the sampling methods for the reliability analysis is used to assess the reliability of constraints. In addition, a Cumulative Distribution Function (CDF) of the constraints is approximated using Moving Least Square (MLS) method from empirical distribution function. It is possible to acquire a probability of failure and its analytic sensitivities by using an approximate function of the CDF for the constraints. Moreover, a concept of inactive design is adapted to improve a numerical efficiency of the proposed approach. Computational accuracy and efficiency of the proposed RBDO approach are demonstrated by numerical and engineering problems.

This study provides how the Dimension Reduction (DR) method as an efficient technique for reliability analysis can acquire its increased efficiency when it is applied to highly nonlinear problems. In the highly nonlinear engineering systems, 4N+1 (N: number of random variables) sampling is generally recognized to be appropriate. However, there exists uncertainty concerning the standard for judgment of non-linearity of the system as well as possibility of diverse degrees of non-linearity according to each of the random variables. In this regard, this study judged the linearity individually on each random variable after 2N+1 sampling. If high non-linearity appeared, 2 additional sampling was administered on each random variable to apply the DR method. The applications of the proposed sampling to the examples produced the constant results with increased efficiency.

Among many kinds of parts for Liquid Crystal Display (LCD), a Back Light Unit (BLU) that changes the path of the light from light source to screen is the most important part to improve optical performances such as uniformity and average value of brightness. Up to recently, design process of BLU has been carried out by depending on the experience of design engineer. Using this approach, however, is proven that it is hard to effectively deal with difficulties in a process of the LCD development such as frequent design modifications, various design requirements, and short-term development. To cope with this situation, we applied a Process Integration and Design Optimization (PIDO) based design environment. PIDO is a software package to integrate multiple simulation processes and find a better solution using various design techniques. In this research, we found a design solution satisfying all design requirements by using the PIDO.

Nowadays, it is performed actively to optimize by using an approximate model. This is called the approximate optimization. In addition, the sequential approximate optimization (SAO) is the repetitive method to find an optimum by considering the convergence of an approximate optimum. In some recent studies, it is proposed to increase the fidelity of approximate models by applying the sequential sampling. However, because the accuracy and efficiency of an approximate model is directly connected with the design area and the termination criteria are not clear, sequential sampling method has the disadvantages that could support an unreasonable approximate optimum. In this study, the SAO is executed by using trust region, Kriging model and Optimal Latin Hypercube design (OLHD). Trust region is used to guarantee the convergence and Kriging model and OLHD are suitable for computer experiment. finally, this SAO method is applied to various optimization problems of highly nonlinear mathematical functions. As a result, each approximate optimum is acquired and the accuracy and efficiency of this method is verified by comparing with the result by established method.

Viscous-driven pumping is a very promising type in microscale applications. However, there exist a few disadvantages such as low efficiency and small volume flow rate. In the present study, a pump with tandem rotating cylinders and its optimum synthesis are proposed fur enhancing pumping performance. First, using an unstructured grid CFD method, we investigate the effects of geometrical parameters and then the performance of the pump with tandem cylinders is evaluated. Next, an optimum design synthesis tool is constructed by combining the aforementioned CFD analysis model with the mathematical optimization model, namely, Modified Method of Feasible Directions (MMFD). This technique is used to optimize the geometrical parameters of the pump, fur maximizing pumping efficiency. From the optimization results, it is believed that the present optimum synthesis is robust and has a potential fur other microfluidic device design.

Function approximation is one of the most important and active research fields in design optimization. Accurate function approximations can reduce the repetitive computational effort fur system analysis. So this study presents an enhanced two-point diagonal quadratic approximation method. The proposed method is based on the Two-point Diagonal Quadratic Approximation method. But unlike TDQA, the suggested method has two quadratic terms, the diagonal term and the correction term. Therefore this method overcomes the disadvantage of TDQA when the derivatives of two design points are same signed values. And in the proposed method, both the approximate function and derivative values at two design points are equal to the exact counterparts whether the signs of derivatives at two design points are the same or not. Several numerical examples are presented to show the merits of the proposed method compared to the other forms used in the literature.

In the microfluidic applications, viscous-driven pumping mechanism is a promising one since the viscous effect increases significantly as the size of device decreases, relative to the inertial effect. However, there exist a few drawbacks we have to improve such as low efficiency and small volume flow rate. In the present study, an optimum design synthesis is proposed to enhance the performance characteristics of the micropump with single rotating cylinder. First, the unstructured grid CFD method is described and validated by comparing its results to the previous results. Next, an automated optimum design synthesis tool is constructed by combining the aforementioned CFD analysis model with the mathematical optimization model. This technique is used to improve the performance characteristics of newly designed viscous-driven pump. The presented results show that the fluid dynamic optimization tool is robust and may be applied to other microfluidic device design applications.

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to determine the best order of the processes within these subcycles to reduce design cycle time and cost. This is accomplished by decomposing large multidisciplinary problems into several sub design structure matrices (DSMs) and processing them in parallel This paper proposes a new method for parallel decomposition of multidisciplinary problems to improve design efficiency by using the multi-objective genetic algorithm and two sample test cases are presented to show the effect of the suggested decomposition method.

In this study, optimum designs of the air-bearing surface (ABS) are achieved using the reduced basis concept which can effectively reduce the number of design variables without cutting down on the design space. Even though the optimization method is easier and more applicable to handle than the trial-and-error method, its efficiency is largely dependent on the number of the design variables. Hence, the reduced basis concept is applied, by which the desired design can be defined as a linear combination of basis designs. The simulation results show the effectiveness of the proposed approach by obtaining the optimum solutions of the sliders whose target flying heights are 25, 20, and 15nm.

This study presents an efficient method for robust optimal design. In order to avoid the excessive evaluations of the exact performance functions, two-point diagonal quadratic approximation method is employed for approximating them during optimization process. This approximation method is one of the two point approximation methods. Therefore, the second order sensitivity information of the approximated performance functions are calculated by an analytical method. As a result, this enables one to avoid the expensive evaluations of the exact derivatives of the performance functions unlike the conventional robust optimal design methods based on the gradient information. Finally, in order to show the numerical performance of the proposed method, one mathematical problem and two mechanical design problems are solved and their results are compared with those of the conventional methods.

In a micro-scale contact, capillary force and van der Waals interaction significantly influence the contact between asperities of rough surfaces. Little is, however, known about the variation of these surface forces as a function of chemical property of the surface (wet angle), relative humidity and deformation of asperities in the real area of contact. A better understanding of these surface forces is of great necessity in order to find a solution for reducing friction and adhesion of micro surfaces. The objective of this study is to investigate the surface forces in micro-scale rough surface contact. We proposed an effective method to analyze capillary and van der Waals forces in micro-scale contact. In this method, Winkler spring model was employed to analyze the contact of rough surfaces that were obtained from atomic force microscopy (AFM) height images. Self-mated contact of DLC(diamond like carbon) coatings was analyzed, as an example, by the proposed model. It was shown that the capillary force was significantly influenced by relative humidity and wet angle of the DLC surface. The deformation of asperities to a critical magnitude by external loading led to a considerable increase of both capillary and van der Waals forces.