• Wind and Structures
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• v.22 no.2
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• pp.185-209
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• 2016

Across-wind aerodynamic damping ratios are identified from the wind-induced acceleration responses of 15 aeroelastic models of rectangular super-high-rise buildings in various simulated wind conditions by using the random decrement technique. The influences of amplitude-dependent structural damping ratio and natural frequency on the estimation of the aerodynamic damping ratio are discussed and the identifying method for aerodynamic damping is improved at first. Based on these works, effects of turbulence intensity $I_u$, aspect ratio H/B, and side ratio B/D on the across-wind aerodynamic damping ratio are investigated. The results indicate that turbulence intensity and side ratio are the most important factors that affect across-wind aerodynamic damping ratio, whereas aspect ratio indirectly affects the aerodynamic damping ratio by changing the response amplitude. Furthermore, empirical aerodynamic damping functions are proposed to estimate aerodynamic damping ratios at low and high reduced speeds for rectangular super-high-rise buildings with an aspect ratio in the range of 5 to 10, a side ratio of 1/3 to 3, and turbulence intensity varying from 1.7% to 25%.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.10
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• pp.491-497
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• 2006

For high efficiency and easy speed control of brushless DC (BLDC) motor, the demand of BLDC motor is increasing. Especially demand of interior permanent magnet (IPM) BLDC with high efficiency and high power in electric motion vehicle is increasing. However, IPM BLDC basically has a high cogging torque that results from the interaction of permanent magnet magnetomotive force (MMF) harmonics and air-gap permeance harmonics due to slotting. This cogging torque generates vibration and acoustic noises during the driving of motor. Thus reduction of the cogging torque has to be considered in IPM BLDC motor design by analytical methods. This paper proposes the cogging torque reduction method for IPM BLDC motor. For reduction of cogging torque of IPM BLDC motor, this paper describes new technique of the flux barriers design. The proposed method uses sinusoidal form of flux density to reduce the cogging torque. To make the sinusoidal air-gap flux density, flux barriers are applied in the rotor and flux barriers that installed in the rotor produce the sinusoidal form of flux density. Changing the number of flux barrier, the cogging torque is analyzed by finite element method. Also characteristics of designed model by the proposed method are analyzed by finite element method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.5
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• pp.585-591
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• 2014

An improved numerical scattering model with the 2-dimensional moment method including roof-top basis and a modified window-function to reduce edge-effect is presented in this study. The roof-top basis function is used to depict randomly positioned surface currents and increase an efficiency of the moment method. To reduce the edge-effect which occurs at the end of numerically generated surfaces, an enhanced window-function which is weighted by incident angle variable is proposed. To validate an proposed 2-dimensional scattering model and numerical analysis techniques for randomly rough surfaces, computational results are compared and analyzed to SPM(Small Perturbation Model) as well.

• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.580-586
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• 2011

Low impact development (LID) technique is recently proposed as new concept to reduce surface runoff and pollutant loading with various best management practices (BMPs). In this study, LIDMOD2, which is one of the model to evaluate LID, was applied at Mohyeon developing area to evaluate the redcution of annual runoff and pollution loading, cost-reduction efficient by LID with design of structural BMPs including bioretention, wet pond, and wetland. As a simulation results, the bioretention had the highest reduction efficiency for runoff (41.43%), and 22% for T-N and 22% for BOD. Wet pont had the highest reduction efficiency for T-P as showing 25% of reduction rate. As a results of cost-reduction efficient, wet pont represented the highest cost-effective for T-N and BOD with showing 0.43 T-P kg/million won and 17.37 BOD kg/million won, respectively, and bioretention represented the highest cost-effective for T-P with showing 2.52 T-P kg/million won. LID technology could reduce effectively surface runoff and nonpoint source pollution and construct sustainable development. LIDMOD2 could be suggested as useful tool to evaluate and design LID.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.295-302
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• 2022

Sparse-view computed tomography (CT) imaging technique is able to reduce radiation dose, ensure the uniformity of image characteristics among projections and suppress noise. However, the reconstructed images obtained by the sparse-view CT imaging technique suffer from severe artifacts, resulting in the distortion of image quality and internal structures. In this study, we proposed a convolutional neural network (CNN) with wavelet transformation and residual learning for reducing artifacts in sparse-view CT image, and the performance of the trained model was quantitatively analyzed. The CNN consisted of wavelet transformation, convolutional and inverse wavelet transformation layers, and input and output images were configured as sparse-view CT images and residual images, respectively. For training the CNN, the loss function was calculated by using mean squared error (MSE), and the Adam function was used as an optimizer. Result images were obtained by subtracting the residual images, which were predicted by the trained model, from sparse-view CT images. The quantitative accuracy of the result images were measured in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The results showed that the trained model is able to improve the spatial resolution of the result images as well as reduce artifacts in sparse-view CT images effectively. Also, the trained model increased the PSNR and SSIM by 8.18% and 19.71% in comparison to the imaging model trained without wavelet transformation and residual learning, respectively. Therefore, the imaging model proposed in this study can restore the image quality of sparse-view CT image by reducing artifacts, improving spatial resolution and quantitative accuracy.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.213-216
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• 1996

R'||'&'||'D project management is a process of decisions concerned with the achievement of goals of objectives. Especially, defense R'||'&'||'D project planning is the key in the successfull management of defense development. The defense project managers are constantly having to perform "what if\ulcorner" exercise, such as what if the project is extended out for an additional cost\ulcorner In this reserch, we developed a schedule-cost analysis model based upon Critical Path Method(CPM) and Venture Evaluation and Review Technique(VERT) for schedule-cost trade off analysis defense R'||'&'||'D projects. In the first step, a deterministic model is developed as a heuristic which deterministic model is developed as a heuristic which determines the schedule extension and reduction cost as a function desired schedule. In the second step, a stochastic network simulation model is developed to analyse the project risk (sucess and failure). The expected time and cost can be determined for desired schedule under the assumptions of stochastic arc data (time and cost) with a various precedence relationships. This model provides the defense R'||'&'||'D managers with an estimated and expected cost for curtailing or extending a project a given amount of time. The effectiveness and efficiency of the proposed methods, a heuristic and stochastic networks simulations, have been demonstrated through examples.

• Journal of Soil and Groundwater Environment
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• v.20 no.3
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• pp.51-64
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• 2015

In the present study, we develop two history matching techniques based on Markov chain Monte Carlo method where radial basis function and Gaussian distribution generated by unconditional geostatistical simulation are employed as the random walk transition kernels. The Bayesian inverse methods for aquifer characterization as the developed models can be effectively applied to the condition even when the targeted information such as hydraulic conductivity is absent and there are transient hydraulic head records due to imposed stress at observation wells. The model which uses unconditional simulation as random walk transition kernel has advantage in that spatial statistics can be directly associated with the predictions. The model using radial basis function network shares the same advantages as the model with unconditional simulation, yet the radial basis function network based the model does not require external geostatistical techniques. Also, by employing radial basis function as transition kernel, multi-scale nested structures can be rigorously addressed. In the validations of the developed models, the overall predictabilities of both models are sound by showing high correlation coefficient between the reference and the predicted. In terms of the model performance, the model with radial basis function network has higher error reduction rate and computational efficiency than with unconditional geostatistical simulation.

• Computers and Concrete
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• v.3 no.4
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• pp.213-233
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• 2006

Over the past years techniques for non-linear analysis have been enhanced significantly via improved solution procedures, extended finite element techniques and increased robustness of constitutive models. Nevertheless, problems remain, especially for real world structures of softening materials like concrete. The softening gives negative stiffness and risk of bifurcations due to multiple cracks that compete to survive. Incremental-iterative techniques have difficulties in selecting and handling the local peaks and snap-backs. In this contribution, an alternative method is proposed. The softening diagram of negative slope is replaced by a saw-tooth diagram of positive slopes. The incremental-iterative Newton method is replaced by a series of linear analyses using a special scaling technique with subsequent stiffness/strength reduction per critical element. It is shown that this event-by-event strategy is robust and reliable. First, the model is shown to be objective with respect to mesh refinement. Next, the example of a large-scale dog-bone specimen in direct tension is analyzed using an isotropic version of the saw-tooth model. The model is capable of automatically providing the snap-back response. Subsequently, the saw-tooth model is extended to include anisotropy for fixed crack directions to accommodate both tensile cracking and compression strut action for reinforced concrete. Three different reinforced concrete structures are analyzed, a tension-pull specimen, a slender beam and a slab. In all cases, the model naturally provides the local peaks and snap-backs associated with the subsequent development of primary cracks starting from the rebar. The secant saw-tooth stiffness is always positive and the analysis always 'converges'. Bifurcations are prevented due to the scaling technique.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.193-200
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• 2021

In this study, an analysis technique using static condensation is proposed for an efficient local nonlinear static analysis. The static condensation method is a model reduction method based on the degrees of freedom, and the analysis model is divided into a target part and a condensed part to be omitted. In this study, the nonlinear and linear parts were designated to the target and the omitted parts, respectively, and both the stiffness matrix and load vector corresponding to the linear part were condensed into the nonlinear part. After model condensation, the reduced model comprising the stiffness matrix and the load vector for the nonlinear part is constructed, and only this reduced model was updated through the Newton-Raphson iteration for an efficient nonlinear analysis. Finally, the efficiency and reliability of the proposed analysis technique were presented by applying it to various numerical examples.

• Journal of Satellite, Information and Communications
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• v.8 no.3
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• pp.10-14
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• 2013

In this paper, when applying current-mode circuit design technique showing constant power dissipation none the less operation frequency, to the low power design of dynamic voltage frequency scaling, we introduce the low power current-mode circuit design technique applying MOSFET in sub-threshold region, in order to solve the problem that has large power dissipation especially on the condition of low operating frequency. BSIM 3, was used as a MOSFET model in circuit simulation. From the simulation result, the power dissipation of the current memory circuit with sub-threshold MOSFET showed $18.98{\mu}W$, which means the consumption reduction effect of 98%, compared with $900{\mu}W$ in that with strong inversion. It is confirmed that the proposed circuit design technique will be available in DVFS using a current-mode circuit design.