• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.12
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• pp.645-653
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• 2017

Thermal and flow modeling and fin structure optimization were performed to reduce the weight of an electrical device with a staggered fin. First, a numerical model for thermal and flow characteristics was suggested, and then, the model was verified experimentally. Using the verified model, improvement in cooling performance of the cooling system through the staggered fins was predicted. As a result, 87.5% of total heat generated was dissipated through the cooling fins, and a thermal island was observed in the rotor because of low velocity of the internal air flow through the air gap. In addition, it was confirmed that the staggered fin improves the cooling performance but it also increases the total pressure drop within the cooling system, by maximizing the leading edge effect. Based on this analysis result, the effect of each design parameter on the thermal and flow characteristics was analyzed to select the main optimal design parameters, and multi-objective optimization was performed by considering the cooling performance and the fin weight. In conclusion, the optimized fin structure improved the cooling performance by 7% and reduced the fin weight by 28% without any compromise of the pressure drop.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.719-728
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• 2022

The prediction of short-term traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction systems. The research on short-term traffic flow prediction has showed the considerable social value. At present, the support vector regression (SVR) intelligent prediction model that is suitable for small samples has been applied in this domain. Aiming at parameter selection difficulty and prediction accuracy improvement, the artificial bee colony (ABC) is adopted in optimizing SVR parameters, which is referred to as the ABC-SVR algorithm in the paper. The simulation experiments are carried out by comparing the ABC-SVR algorithm with SVR algorithm, and the feasibility of the proposed ABC-SVR algorithm is verified by result analysis. Continuously, the simulation experiments are carried out by comparing the ABC-SVR algorithm with particle swarm optimization SVR (PSO-SVR) algorithm and genetic optimization SVR (GA-SVR) algorithm, and a better optimization effect has been attained by simulation experiments and verified by statistical test. Simultaneously, the simulation experiments are carried out by comparing the ABC-SVR algorithm and wavelet neural network time series (WNN-TS) algorithm, and the prediction accuracy of the proposed ABC-SVR algorithm is improved and satisfactory prediction effects have been obtained.

• Advances in aircraft and spacecraft science
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• v.10 no.3
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• pp.245-256
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• 2023

In order to improve aerodynamic performance of multi-stage axial flow turbines used in aircraft engines, a one-dimensional aerodynamic design and optimization framework is constructed. In the method, flow path is generated by solving mass continuation and energy conservation with loss computed by the Craig & Cox model; Also real gas properties has been taken into consideration. To obtain an optimal result, a multi-objective genetic algorithm is used to optimize the efficiencies and determine values of various design variables; Final design can be selected from obtained Pareto optimal solution sets. A three-stage axial turbine is used to verify the effectiveness of the developed optimization framework, and designs are checked by three-dimensional CFD simulation. Results show that the aerodynamic performance of the optimized turbine has been significantly improved at design point, with the total-to-total efficiency increased by 1.17% and the total-to-static efficiency increased by 1.48%. As for the off-design performance, the optimized one is improved at all working points except those at small mass flow.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.10 no.5
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• pp.630-639
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• 1998

The present research aimed at development of a computer code for the optimal design of ventilation system based on one-dimensional analysis of the air flow. Model experiment and three-dimensional flow analysis have been implemented to determine loss coefficients that were needed for the optimization technique. A research on optimum shape of ventilation shaft has been also carried out through the three-dimensional analysis of the flow.

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.413-419
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• 2007

The optimal power flow (OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, it has been intensively studied and widely used in power system operation and planning. In the past few decades, many stochastic optimization methods such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm Optimization (PSO) have been applied to solve the OPF problem. In particular, PSO is a newly proposed population based stochastic optimization algorithm. The main idea behind it is based on the food-searching behavior of birds and fish. Compared with other stochastic optimization methods, PSO has comparable or even superior search performance for some hard optimization problems in real power systems. Nowadays, some modifications such as breeding and selection operators are considered to make the PSO superior and robust. In this paper, we propose the Modified PSO (MPSO), in which the mutation operator of GA is incorporated into the conventional PSO to improve the search performance. To verify the optimal solution searching ability, the proposed approach has been evaluated on an IEEE 3D-bus test system. The results showed that performance of the proposed approach is better than that of the standard PSO.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1418-1423
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• 2004

Optimization of a heat exchanger with internally finned circular tubes has been performed for three-dimensional periodically fully developed turbulent flow and heat transfer. The design variables of fin number N, fin width ($d_1,d_2$) and fin height(H), are numerically optimized for the limiting conditions of $N=22{\sim}37$, $d_1=0.5{\sim}1.5$ mm, $d_2=0.5{\sim}1.5$ mm, $H=0.1{\sim}1.5$. Due to the periodic boundary conditions along main flow direction, the three layers of meshes are considered. The CFD and the mathematical optimization are coupled to optimize the heat exchanger. 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.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.2
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• pp.155-162
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• 2003

Design optimization of a transonic compressor rotor (NASA rotor 37) using response surface method and three-dimensional Navier-Stokes analysis has been carried out in this work. Baldwin-Lomax turbulence model was used in the flow analysis. Three design variables were selected to optimize the stacking line of the blade. Data points for response evaluations were selected by D-optimal design, and linear programming method was used for the optimization on the response surface. As a main result of the optimization, adiabatic efficiency was successfully improved. It is also found that the design process provides reliable design of a turbomachinery blade with reasonable computing time.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.8
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• pp.519-525
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• 2016

In a pump, from the performance point of view, it is very important to minimize the shock loss at the inlet of the rotor blades. In this study, the effects of shape and install angle of the inlet guide on the performance of an axial-flow pump are numerically simulated using commercial CFD code, Ansys CFX. Finally, to obtain the optimized shape of the vanes and the install angle of the vanes in the inlet guide under given operating conditions, optimization analysis is conducted using Analysis design exploration based on response surface optimization.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2009.11a
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• pp.257-265
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• 2009

The present study deals with the leading edge shape on a wing-body junction to decrease a horseshoe vortex, one of the main factors to generate the secondary flow losses. The shape of leading-edge is optimized with design variables form the leading-edge shape. Approximate optimization design method is used for the optimization. The study is investigated using $FLUENT^{TM}$ and $iSIGHT^{TM}$. As the result, total pressure coefficient of the optimized design case was decreased about 9.79% compare to the baseline case.

• The KSFM Journal of Fluid Machinery
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• v.11 no.2
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• pp.46-54
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• 2008

This study presents a numerical optimization to optimize an axial flow fan blade to increase the efficiency. The radial basis neural network is used as an optimization method with the numerical analysis by Reynolds-averaged Navier-Stokes equations using SST model as turbulence closure. Four design variables related to airfoil maximum camber, maximum camber location, leading edge radius and trailing edge radius, respectively, are selected, and efficiency is considered as objective function which is to be maximized. Thirty designs are evaluated to get the objective function values of each design used to train the neural network. Optimum shape shows the efficiency increased by 1.0%.