• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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• pp.1950-1963
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• 1995

A modification of the approximate-factorization method is made to accelerate the convergency rate and to take sufficiently large Courant number without loss of accuracy. And a stable implicit finite-difference scheme for solving the incompressible Navier-Stokes equations employed above modified method is developed. In the present implicit scheme, the volume fluxes with contravariant velocity components and the pressure formulation in curvilinear coordinates is adopted. In order to satisfy the continuity condition completely and to remove spurious errors for the pressure, the Navier-Stokes equations are solved by a modified SMAC scheme using a staggered gird. The upstream-difference scheme such as the QUICK scheme is also employed to the right hand side. The implicit scheme is unconditionally stable and satisfies a diagonally dominant condition for scalar diagonal linear systems of implicit operator on the left hand side. Numerical results for some test calculations of the two-dimensional flow in a square cavity and over a backward-facing step are obtained using both usual approximate-factorization method and the modified one, and compared with each other. It is shown that the present scheme allows a sufficiently large Courant number of O(10$^{2}$) and reduces the computing time.

• Proceedings of the KIPE Conference
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• 2019.11a
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• pp.70-72
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• 2019

For the safe and reliable operation of Lithium-ion batteries in Electric Vehicles (EVs) or Energy Storage Systems (ESSs), it is essential to have accurate information of the battery such as State of Charge (SOC). Many kinds of different techniques to estimate the SOC of the batteries have been developed so far such as the Kalman Filter. However, when it is applied to the multiple number of batteries it is difficult to maintain the accuracy of the estimation over all cells due to the difference in parameter value of each cell. Moreover the difference in the parameter of each cell may become larger as the operation time accumulates due to aging. In this paper a novel Deep Neural Network (DNN) based SOC estimation method for multi cell application is proposed. In the proposed method DNN is implemented to learn non-linear relationship of the voltage and current of the lithium-ion battery at different SOCs and different temperatures. In the training the voltage and current data of the Lithium battery at charge and discharge cycles obtained at different temperatures are used. After the comprehensive training with the data obtained with a cell resulting estimation algorithm is applied to the other cells. The experimental results show that the Mean Absolute Error (MAE) of the estimation is 0.56% at 25℃, and 3.16% at 60℃ with the proposed SOC estimation algorithm.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.688-698
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• 2020

Point clouds have ability to express the spatial entities, however, the point clouds redundancy always involves some uncertainties in computer recognition and model construction. Therefore, point clouds thinning is an indispensable step in point clouds model reconstruction and other applications. To overcome the shortcomings of complex classification index and long time consuming in existing point clouds thinning algorithms, this paper proposes a point clouds fast thinning algorithm. Specifically, the two-dimensional index is established in plane linear array (x, y) for the scanned point clouds, and the thresholds of adjacent point distance difference and height difference are employed to further delete or retain the selected sample point. Sequentially, the index of sample point is traversed forwardly and backwardly until the process of point clouds thinning is completed. The results suggest that the proposed new algorithm can be applied to different targets when the thresholds are built in advance. Besides, the new method also performs superiority in time consuming, modelling accuracy and feature retention by comparing with octree thinning algorithm.

• Coupled systems mechanics
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• v.8 no.2
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• pp.129-146
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• 2019

The main goal of this work is to develop a numerical simulator to study an isothermal single-phase two-component flow in a naturally fractured oil reservoir, taking into account advection and diffusion effects. We use the Peng-Robinson equation of state with a volume translation to evaluate the properties of the components, and the discretization of the governing partial differential equations is carried out using the Finite Difference Method, along with implicit and first-order upwind schemes. This process leads to a coupled non-linear algebraic system for the unknowns pressure and molar fractions. After a linearization and the use of an operator splitting, the Conjugate Gradient and Bi-conjugated Gradient Stabilized methods are then used to solve two algebraic subsystems, one for the pressure and another for the molar fraction. We studied the effects of fractures in both the flow field and mass transport, as well as in computing time, and the results show that the fractures affect, as expected, the flow creating a thin preferential path for the mass transport.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.6
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• pp.348-357
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• 2021

In this paper, the generalized hydrodynamic force and response of a flexible body are calculated at different reference coordinate systems. We generalize the equation of motion for a flexible body by using the conservation of momentum (Mei et al., 2005). To obtain the equations in the generalized mode, two different reference coordinates are adopted. The first is the body-fixed coordinate system by a rigid body motion. The other is the inertial coordinate system which has been adopted for the analysis. Using the perturbation scheme in the weakly-nonlinear assumption, the equations of motion are expanded up to second-order quantities and several second-order forces are obtained. Numerical tests are conducted for the flexible barge model in head waves and the vertical bending is only considered in the hydroelastic responses. The results show that the linear response does not have the difference between the two formulations. On the other hand, second-order quantities have different values for which the rigid body motion is relatively large. However, the total summation of second-order quantities has not shown a large difference at each reference coordinate system.

• MALSORI
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• no.52
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• pp.145-160
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• 2004

In this paper, a new noise compensation method based on the eigenvoice framework in feature space is proposed to reduce the mismatch between training and testing environments. The difference between clean and noisy environments is represented by the linear combination of K eigenvectors that represent the variation among environments. In the proposed method, the performance improvement of speech recognition systems is largely affected by how to construct the noisy models and the bias vector set. In this paper, two methods, the one based on MAP adaptation method and the other using stereo DB, are proposed to construct the noisy models. In experiments using Aurora 2 DB, we obtained 44.86% relative improvement with eigen-environment method in comparison with baseline system. Especially, in clean condition training mode, our proposed method yielded 66.74% relative improvement, which is better performance than several methods previously proposed in Aurora project.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.269-272
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• 2003

Industry is now seeing a dramatic increase in robot simulation and off-line programming. In order to use off-line programming effectively, the simulated workcell has to be identical to the real workcell. This requires an efficient and accurate method for the workcell calibration. Currently used techniques in the industry, however, are typically time-consuming, expensive and therefore not suitable for in-process application. This is because most of these techniques are based on the so-called “absolute calibration” method. In contrast to absolute method, relative calibration only measures the difference of an interested object relative to a standard reference. Owing to the small measurement range requirement, relative calibration method is very cheap and can achieve very high accuracy. In this paper the relative method is applied to calibrate an entire grinding workcell. Linear gauge is the only measurement device used. This workcell calibration includes tool center point (TCP) calibration and work object frame calibration. Due to the efficiency of the calibration algorithm and the simplicity of the calibration setup, the described calibration procedure can be done in process.

• Smart Structures and Systems
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• v.16 no.6
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• pp.1133-1145
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• 2015

A new neural network (NN) predictive controller (NNPC) algorithm has been developed and tested in the computer simulation of active control of a nonlinear structure. In the present method an NN is used as a predictor. This NN has been trained to predict the future response of the structure to determine the control forces. These control forces are calculated by minimizing the difference between the predicted and desired responses via a numerical minimization algorithm. Since the NNPC is very time consuming and not suitable for real-time control, it is then used to train an NN controller. To consider the effectiveness of the controller on probability of damage, fragility curves are generated. The approach is validated by using simulated response of a 3 story nonlinear benchmark building excited by several historical earthquake records. The simulation results are then compared with a linear quadratic Gaussian (LQG) active controller. The results indicate that the proposed algorithm is completely effective in relative displacement reduction.

• International Journal of Human Ecology
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• v.12 no.1
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• pp.115-124
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• 2011

This study investigates the efficacy and coping strategies of Home Economics teachers in secondary schools. Data were collected from 75 Home Economics teachers via a mailed survey and from 282 Home Economics teachers via an online survey. Descriptive statistics including frequency, percentage, average, and standard deviation; in addition, the ANOVA, t-test, multiple linear regression, and correlation results were reported using SPSS statistics 17.0. The results were as follows: First, the average Home Economics teachers efficacy level was 3.82 out of 5-point Likert scale. The efficacy level of learning assistance was the highest. The composite efficacy of Home Economics teachers showed a significant difference depending on the major. Second, the averages of the positive and negative coping strategy level of Home Economics teachers were 3.54 and 2.03, respectively. Third, the efficacy of instructional strategy out of the five components of efficacy was the most influential to the positive coping strategy. There was no significant relationship between teacher efficacy and the negative strategy.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.540-545
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• 1988

In this study a microcomputer-aided design program has been developed to design and analysis for the digital adaptive control system. DACS(Digital Adaptive Control System) program has been written in GWBASIC language which is suitable for IBM-PC compatible. The dynamics of each element was modulized and described by linear difference equations. By the aid of this program, sampling time, the number of bits of A/D and D/A converter and the stability for the digital adaptive control system can be determined. In order to estimate the system parameters an on-line identification and a regression analysis method are utilized. The simulation results have been well agreed with the experiments. To demonstrate the utility of this program, an adaptive control system has been designed for air-heating system.