• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2009년도 춘계학술대회 논문집
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• pp.645-645
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• 2009

In many practical applications of the centrifugal fan, the impeller-diffuser interaction noise is considered as a main source of fan noise. The housing for an electric motor is also expected to play an important role on noise propagation because of its complicated configuration. This study investigates the impeller-diffuser interaction noise and its sources by computing three-dimensional, incompressible flow field of the centrifugal fan in motor housing. The effect of motor case on fan noise characteristic is then investigated using the Brinkman penalization method, while the noise source associated with impeller-diffuser interaction is mathematically modeled. It is found that the present methodology combined with mathematical description of noise source provides a fairly good agreement with the experimental results, indicating that the motor housing has significant effect on noise characteristics. Finally, aeroacoustic noise prediction for various impeller-diffuser blade count ratios is conducted for noise reduction.

• Communications for Statistical Applications and Methods
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• 제20권4호
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• pp.259-270
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• 2013

This paper considers a penalized composite quantile regression (CQR) that performs a variable selection in the linear model with grouped variables. An adaptive sup-norm penalized CQR (ASCQR) is proposed to select variables in a grouped manner; in addition, the consistency and oracle property of the resulting estimator are also derived under some regularity conditions. To improve the efficiency of estimation and variable selection, this paper suggests the two-stage penalized CQR (TSCQR), which uses the ASCQR to select relevant groups in the first stage and the adaptive lasso penalized CQR to select important variables in the second stage. Simulation studies are conducted to illustrate the finite sample performance of the proposed methods.

• Computers and Concrete
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• 제19권4호
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• pp.405-411
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• 2017

Carbon Fiber Reinforced Plastic (CFRP) has commonly been used to strengthen existing RC structures. Wrapping the whole component with CFRP is an effective method and simple to execute. Besides, specific configuration of CFRP sheets (L, X and T shape) has also been considered in some experiments to examine CFRP effects in advance. This study aimed to provide an optimal CFRP configuration to effectively retrofit the beam-column connection using continuous material topology optimization procedure. In addition, Moved and Regularized Heaviside Functions and penalization factors were also considered. Furthermore, a multi-material procedure was also used to compare with the results from the single material procedure.

• Communications for Statistical Applications and Methods
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• 제24권6호
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• pp.651-662
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• 2017

We propose an alternative procedure to select penalty parameter in $L_1$ penalized robust regression. This procedure is based on marginalization of prior distribution over the penalty parameter. Thus, resulting objective function does not include the penalty parameter due to marginalizing it out. In addition, its estimating algorithm automatically chooses a penalty parameter using the previous estimate of regression coefficients. The proposed approach bypasses cross validation as well as saves computing time. Variable-wise penalization also performs best in prediction and variable selection perspectives. Numerical studies using simulation data demonstrate the performance of our proposals. The proposed methods are applied to Boston housing data. Through simulation study and real data application we demonstrate that our proposals are competitive to or much better than cross-validation in prediction, variable selection, and computing time perspectives.

• 대한기계학회논문집A
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• 제30권9호
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• pp.1102-1109
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• 2006

In this paper, the polarization of piezoelectric materials is considered to improve actuation since the piezoelectric polarization has influences on the performance of the actuator. The topology design of compliant mechanism can be formulated as an optimization problem of material distribution in a fixed design domain and continuous approximation of material distribution (CAMD) method has demonstrated its effectiveness to prevent the numerical instabilities in topology optimization. The optimization problem is formulated to maximize the mean transduction ratio subject to the total volume constraints and solved using a sequential linear programming algorithm. The effect of CAMD and the performance improvement of actuator are confirmed through Moonie actuator and PZT suspension design.

• 대한기계학회논문집A
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• 제28권4호
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• pp.370-377
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• 2004

The density approach and the homogenization design method are representative methods in topology optimization problems. In the topology optimization in magnetic fields, those methods are applied based on the results of the applications In elastic fields. In this study, the density method is modified considering the concept of the homogenization design method. Also, the results of the topology optimization in magnetic fields by the modified density method as well as the homogenization method are compared especially focusing the change of the penalization parameter in the density approach. The effect of the definition of the design domain such as global/local design domain is also discussed.

• 대한기계학회논문집A
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• 제28권11호
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• pp.1703-1710
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• 2004

The objective of this investigation is to formulate and carry out the topology optimization of a magnetic system consisting of permanent magnets and yokes. Earlier investigations on magnetic field topology optimization have been limited on the design optimization of yokes or permanent magnets alone. After giving the motivation for the simultaneous design of permanent magnets and yokes, we develop the topology optimization formulation of the coupled system by extending the technique used in structural problems. In the present development, we will also examine the effects of the functional form for permeability penalization on the optimized topology.

• Communications for Statistical Applications and Methods
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• 제28권3호
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• pp.281-294
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• 2021

In this paper, we propose an adaptive regression method based on the single-layer neural network structure. We adopt a symmetric activation function as units of the structure. The activation function has a flexibility of its form with a parametrization and has a localizing property that is useful to improve the quality of estimation. In order to provide a spatially adaptive estimator, we regularize coefficients of the activation functions via ℓ₁-penalization, through which the activation functions to be regarded as unnecessary are removed. In implementation, an efficient coordinate descent algorithm is applied for the proposed estimator. To obtain the stable results of estimation, we present an initialization scheme suited for our structure. Model selection procedure based on the Akaike information criterion is described. The simulation results show that the proposed estimator performs favorably in relation to existing methods and recovers the local structure of the underlying function based on the sample.

• Nonlinear Functional Analysis and Applications
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• 제26권2호
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• pp.347-371
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• 2021

A plethora of applications from mathematical programmings, such as minimax, mathematical programming, penalization and fixed point problems can be framed as variational inequality problems. Most of the methods that used to solve such problems involve iterative methods, that is why, in this paper, we introduce a new extragradient-like method to solve pseudomonotone variational inequalities in a real Hilbert space. The proposed method has the advantage of a variable step size rule that is updated for each iteration based on previous iterations. The main advantage of this method is that it operates without the previous knowledge of the Lipschitz constants of an operator. A strong convergence theorem for the proposed method is proved by letting the mild conditions on an operator 𝒢. Numerical experiments have been studied in order to validate the numerical performance of the proposed method and to compare it with existing methods.

• 대한수학회지
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• 제59권3호
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• pp.519-548
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• 2022

In this paper, a stabilized-penalized collocated finite volume (SPCFV) scheme is developed and studied for the stationary generalized Navier-Stokes equations with mixed Dirichlet-traction boundary conditions modelling an incompressible biological fluid flow. This method is based on the lowest order approximation (piecewise constants) for both velocity and pressure unknowns. The stabilization-penalization is performed by adding discrete pressure terms to the approximate formulation. These simultaneously involve discrete jump pressures through the interior volume-boundaries and discrete pressures of volumes on the domain boundary. Stability, existence and uniqueness of discrete solutions are established. Moreover, a convergence analysis of the nonlinear solver is also provided. Numerical results from model tests are performed to demonstrate the stability, optimal convergence in the usual L² and discrete H¹ norms as well as robustness of the proposed scheme with respect to the choice of the given traction vector.