• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.11
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• pp.1151-1157
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• 2009

Ensuring both product quality and reducing material cost are important issue for the design of the piping system of an air conditioner outdoor unit. This paper describes a shape optimization that achieves mass reduction of an air conditioner piping system while satisfying two design constraints on resonance avoidance and the maximum stress in the pipes. In order to obtain optimized design results with various analysis fields considered simultaneously, an automated multidisciplinary analysis system was constructed using PIAnO v.2.4, a commercial process integration and design optimization(PIDO) tool. As the first step of the automated analysis system, a finite element model is automatically generated corresponding to the specified shape of the pipes using a morphing technique included in HyperMesh. Then, the performance indices representing various design requirements (e.g. natural frequency, maximum stress and pipe mass) are obtained from the finite element analyses using appropriate computer-aided engineering(CAE) tools. A sequential approximate optimization(SAO) method was employed to effectively obtain the optimum design. As a result, the pipe mass was reduced by 18 % compared with that of an initial design while all the constraints were satisfied.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.72-81
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• 2014

In this study, we perform the optimization of trailing arm bush in a vehicle rear suspension to improve the ride and handling performance. A design problem was formulated considering 2 objective functions and 7 constraints related to vehicle ride and handling performance. PIAnO, one of the PIDO (Process Integration and Design Optimization) tool, was used to automate analysis procedures and perform a design optimization. In order to assess relation between performances and design variables, we perform the DOE (Design of Experiments). To find the optimal solution, we used Progressive quadratic response surface method (PQRSM), one of the design optimization techniques equipped in PIAnO. As an optimization result, we got an optimal solution and could improve lateral force steer off-center by 43.0% while decreasing brake compliance at wheel center by 8.1%.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.1
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• pp.124-130
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• 2012

An injection mold cooling circuit for an automotive front bumper was optimally designed in order to simultaneously minimize the average of the standard deviations of the temperature and the difference in mean temperatures of the upper and lower molds for uniform cooling. The temperature distribution for a specified design was evaluated by Moldflow Insight 2010, a commercial injection molding analysis tool. For efficient design, PIAnO (Process Integration, Automation and Optimization), a commercial PIDO tool, was used to integrate and automate injection molding analysis procedure. The weighted-sum method was used to handle the multi-objective optimization problem and PQRSM, a function-based sequential approximate optimizer equipped in PIAnO, to handle numerically noisy responses with respect to the variation of design variables. The optimal average of the standard deviations and difference in mean temperatures were found to be reduced by 9.2% and 56.52%, respectively, compared to the initial ones.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.5
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• pp.62-67
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• 2010

Exhausting fossil fuel and increasing concern of air pollution have brought on the change of the focus of developing new vehicles from performance to fuel economy and emission. The gasoline engines adopting the naturally aspirated way use the throttle-body for engine load control. Therefore, its pumping loss increases more than that of the diesel engine, and also mostly operating in a partial load condition has bad influence on fuel economy and emission. In these days, the continuous variable valve timing system and variable induction system are adopted in order to improve fuel consumption and emission. In this study, we optimize the runner length and operate region of variable induction system to simulataneously improve the performance, fuel economy, and emission of gasoline engine with employing GT-Power as a CAE tool for engine analysis and PIAnO as PIDO tool for process integration and design optimization.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.4
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• pp.325-329
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• 2011

Floating, production, storage and offloading (FPSO) is a production facility that refines and saves the drilled crude oil from a drilling facility in the ocean. The flare system in the FPSO is a major part of the pressure relieving system for hydrocarbon processing plants. The flare system consists of a number of pipes and complicated connection systems. Decision of pipe support types is important since the load on the support and the stress in the pipe are influenced by the pipe support type. In this study, we optimally determined the pipe support types that minimized the support cost while satisfying the design constraints on maximum support load, maximum nozzle load and maximum pipe stress ratio. Performance indices included in the design constraints for a specified design were evaluated by pipe structural analysis using CAESAR II. Since pipe support types were all discrete design variables, an evolutionary algorithm (EA) was used as an optimizer. We successfully obtained the optimal solution that reduced the support cost by 27.2% compared to the initial support cost while all the design requirements were satisfied.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.8-14
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• 2013

In this study, we propose the method of optimally selecting material of front pillar (A-pillar) and package tray for minimizing weight while satisfying vehicle requirements on static stiffness and dynamic stiffness. First, we formulate a material selection optimization problem. Next, we establish the CAE procedure of evaluating static stiffness and dynamic stiffness. Then, to enhance the efficiency of design work, we integrate and automate the established CAE procedure using a commercial process integration and design optimization (PIDO) tool, PIAnO. For effective optimization, we adopt the approach of metamodel based approximate optimization. As a sampling method, an orthogonal array (OA) is used for selecting sampling points. The response values are evaluated at the sampling points and then these response values are used to generate a metamodel of each response using the radial basis function regression (RBFr). Using the RBFr models, optimization is carried out an evolutionary algorithm that can handle discrete design variables. Material optimization result reveals that the weight is reduced by 49.8% while satisfying all the design constraints.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.4
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• pp.16-22
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• 2013

In this study, we propose the method of optimally changing material of BIW for minimizing weight while satisfying vehicle requirements on static stiffness. First, we formulate a material selection optimization problem. Next, we establish the CAE procedure of evaluating static stiffness. Then, to enhance the efficiency of design work, we integrate and automate the established CAE procedure using a commercial process integration and design optimization (PIDO) tool, PIAnO. For effective optimization, we adopt the approach of metamodel based approximate optimization. As a sampling method, an orthogonal array (OA) is used for selecting sampling points. The response values are evaluated at the sampling points and then these response values are used to generate a metamodel of each response using the linear polynomial regression (PR) model. Using the linear PR model, optimization is carried out an evolutionary algorithm (EA) that can handle discrete design variables. Material optimization result reveals that the weight is reduced by 44.8% while satisfying all the design constraints.