• 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.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.113-116
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• 2008

This work presents numerical optimization for design of staggered arrays of dimples printed on opposite surfaces of a cooling channel with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by three non-dimensional geometric design variables composed of dimpled channel height, dimple print diameter, dimple spacing and dimple depth to maximize heat transfer rate compromising with pressure drop. Twenty designs generated by Latin hypercube sampling were evaluated by Reynolds-averaged Navier-Stokes solver and the evaluated objectives were used to construct Pareto optimal front through hybrid multi-objective evolutionary algorithm. The optimum designs were grouped by k-mean clustering technique and some of the clustered points were evaluated by flow analysis. With increase in dimple depth, heat transfer rate increases and at the same time pressure drop also increases, while opposite behavior is obtained for the dimple spacing. The heat transfer performance is related to the vertical motion of the flow and the reattachment length in the dimple.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.324-333
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• 2013

The purpose of this paper is to improve the efficiency of multi-objective topology optimization using a genetic algorithm (GA) with bar-system representation. We proposed a new GA using an elite initial population obtained from a Solid Isotropic Material with Penalization (SIMP) using a weighted sum method. SIMP with a weighted sum method is one of the most established methods using sensitivity analysis. Although the implementation of the SIMP method is straightforward and computationally effective, it may be difficult to find a complete Pareto-optimal set in a multi-objective optimization problem. In this study, to build a more convergent and diverse global Pareto-optimal set and reduce the GA computational cost, some individuals, with similar topology to the local optimum solution obtained from the SIMP using the weighted sum method, were introduced for the initial population of the GA. The proposed method was applied to a structural topology optimization example and the results of the proposed method were compared with those of the traditional method using standard random initialization for the initial population of the GA.

• International Journal of Air-Conditioning and Refrigeration
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• v.13 no.2
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• pp.71-82
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• 2005

The shape of $7\times7$ pin-fins heat sink is optimized numerically to obtain the minimum pressure drop and thermal resistance. In this study, the fin height (h), fin width (w), and fan-to-heat sink distance (c) are chosen as the design variables and the pressure drop $({\Delta}P)$ and thermal resistance $(\theta_j)$ are adopted as the objective functions. To obtain the optimum design values, we used the finite volume method for calculating the objective functions, the BFGS method for solving the unconstrained non-linear optimization problem, and the weighting method for predicting the multi-objective problem. The results show that the optimum design variables for the weighting coefficient of 0.5 are as follows: W=4.653 mm, h=59.215mm, and c=2.667mm. The objective functions corresponding to the optimal design are calculated as ${\Delta}P=6.82$ Pa and $(\theta_j)=0.56K/W$. The Pareto solutions are also presented for various weighting coefficients and they will offer very useful data to design the pin-fins heat sink.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.1-7
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• 2009

This paper presents a process routing (PR) algorithm with multiple objectives. PR determines the optimum sequence of operations for transforming a raw material into a completed part within the available machining resources. In any computer aided process planning (CAPP) system, selection of the machining operation sequence is one of the most critical activities for manufacturing a part and for the technical specification in the part drawing. Here, the goal could be to generate the sequence that optimizes production time, production cost, machine utilization or with multiple these criteria. The Pareto Stratum Niche Cubicle (PS NC) GA has been adopted to find the optimum sequence of operations that optimize two conflicting criteria; production cost and production quality. The numerical analysis shows that the proposed PS NC GA is both effective and efficient to the PR problem.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.43-48
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• 2003

In this study the optimization of plate-fin type heat sink for the thermal stability is performed numerically. The optimum design variables are obtained when the temperature rise and the pressure drop are minimized simultaneously. The flow and thermal fields are predicted using the finite volume method and the optimization is carried out by using the sequential quadratic programming (SQP) method which is widely used in the constrained nonlinear optimization problem. The results show that when the temperature rise is less than 34.6 K, the optimal design variables are as follows; $B_{1}$ = 2.468 mm, $B_{2}$ = 1.365 mm, and t = 10.962 mm. The Pareto optimal solutions are also presented for the pressure drop and the temperature rise.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.3
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• pp.293-302
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• 2004

In this study the optimization of plate-fin type heat sink for the thermal stability is peformed numerically. The optimum design variables are obtained when the temperature rise and the pressure drop are minimized simultaneously. The flow and thermal fields are predicted using the finite volume method and the optimization is carried out by using the sequential quadratic programming (SQP) method which is widely used in the constrained non-linear optimization problem. The results show that when the temperature rise is less than 34.6K, the optimal design variables are as follows; B$_1$=2.468mm, B$_2$=1.365mm, and t=10.962mm. The Pareto optimal solutions are also presented for the pressure drop and the temperature rise.

• The KSFM Journal of Fluid Machinery
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• v.7 no.2 s.23
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• pp.7-13
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• 2004

In an attempt to solve multiobjective optimization problems, weighted sum method is most widely used for the advantage that a designer can consider the relative significance of each object functions by weight values but it can be highly sensitive to weight vector and occasionally yield a deviated optimum from the relative weighting values designer designated because the multiobjective function has the form of simple sum of the product of the weighting values and the object functions in traditional approach. To search the design solution agree well to the designer's weighting values, we proposed new multiobjective function which was the functional of each normalized objective functions and considered to find the design solution comparing the distance between the characteristic line and the ideal optimum. In this study, proposed multiobjective function was applied to design high efficiency and low noise axial flow fan and the result shows this approach is effective for the case that the quality of the design can be highly affected by the designer's subjectiveness represented as weighting values in multiobjective design optimization process.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.10
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• pp.860-869
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• 2003

Design optimization of the heat sink with 7${\times}$7 square pin-fins is performed numerically using the Computational Fluid Dynamics (CFD) and the Computer Aided Optimization (CAO). In the pin-fins heat sink, the optimum design variables for fin height (h), fin width (w), and fan-to-heat sink distance (c) can be achieved when the thermal resistance ($\theta$$_{j}$) at the junction and the overall pressure drop ($\Delta$p) are minimized simultaneously. To complete the optimization, the finite volume method for calculating the objective functions, the BFGS method for solving the unconstrained non-linear optimization problem, and the weighting method for predicting the multi-objective problem are used. The results show that the optimum design variable for the weighting coefficient of 0.5 are as follows: w=4.653 mm, h=59.215 mm, and c=2.667 mm. In this case, the objective functions are predicted as 0.56K/W of thermal resistance and 6.91 Pa of pressure drop. The Pareto optimal solutions are also presented.re also presented.d.

• 유체기계공업학회:학술대회논문집
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• 2003.12a
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• pp.397-403
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• 2003

In an attempt to solve multiobjective optimization problems, weighted sum method is most widely used for the advantage that a designer can consider the relative significance of each object functions by weight values but it can be highly sensitive to weight vector and occasionally yield a deviated optimum from the relative weighting values designer designated because the multiobjective function has the form of simple sum of the product of the weighting values and the object functions in traditional approach. To search the design solution well agree to the designer's weighting values, we proposed new multiobjective function which is the functional of each normalized objective functions and considered to find the design solution comparing the distance between the characteristic line and the ideal optimum. In this study, proposed multiobjective function was applied to design high efficiency and low noise axial flow fan and the result shows this approach will be effective for the case that the qualify of the design can be highly affected by the designer's subjectiveness represented as weighting values in multiobjective design optimization process.