• Proceedings of the KSME Conference
• /
• 2004.04a
• /
• pp.365-370
• /
• 2004

Generally, component and FR-4 board are connected by solder joint. Because material properties of components and FR-4 board are different, component and FR-4 board show different coefficients of thermal expansion (CTE) and thus strains in component and board are different when they are heated. That is, the differences in CTE of component and FR-4 board cause the dissimilarity in shear strain and solder joint' failure. The first order Taylor series expansion of the limit state function incorporating with Tresca failure criterion is used in order to estimate the failure probability of solder joints under heated condition. Using shear stresses and shear strains appeared on the solder joint, we estimate the failure probability of solder joints with the Tresca failure criterion. The effects of random variables such as CTE, distance of the solder joint from the neutral point(DNP), temperature variation and height of solder on the failure probability of the solder joint are systematically studied by using the failure probability model with first order reliability method(FORM).

• Advances in Computational Design
• /
• v.7 no.3
• /
• pp.253-279
• /
• 2022

This study investigated and predicted the Marshall stability of glass-fiber asphalt mix, carbon-fiber asphalt mix and glass-carbon-fiber asphalt (hybrid) mix by using machine learning techniques such as Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest(RF), The data was obtained from the experiments and the research articles. Assessment of results indicated that performance of the Artificial Neural Network (ANN) based model outperformed applied models in training and testing datasets with values of indices as; coefficient of correlation (CC) 0.8492 and 0.8234, mean absolute error (MAE) 2.0999 and 2.5408, root mean squared error (RMSE) 2.8541 and 3.3165, relative absolute error (RAE) 48.16% and 54.05%, relative squared error (RRSE) 53.14% and 57.39%, Willmott's index (WI) 0.7490 and 0.7011, Scattering index (SI) 0.4134 and 0.3702 and BIAS 0.3020 and 0.4300 for both training and testing stages respectively. The Taylor diagram also confirms that the ANN-based model outperforms the other models. Results of sensitivity analysis show that Carbon fiber has a major influence in predicting the Marshall stability. However, the carbon fiber (CF) followed by glass-carbon fiber (50GF:50CF) and the optimal combination CF + (50GF:50CF) are found to be most sensitive in predicting the Marshall stability of fibrous asphalt concrete.

• Ocean Systems Engineering
• /
• v.12 no.2
• /
• pp.143-157
• /
• 2022

In this study, the nominal wake field of a semi-displacement type high-speed vessel was computed at full scale by using CFD (Computational Fluid Dynamics) and GEOSIM-based approaches. A scale effect investigation on nominal wake field of benchmark Athena vessel was performed with two models which have different model lengths. The members of the model family have the same Fr number but different Re numbers. The spatial components of nominal wake field have been analyzed by considering the axial, radial and tangential velocities for models at different scales. A linear feature has been found for radial and tangential components while a nonlinear change has been obtained for axial velocity. Taylor wake fraction formulation was also computed by using the axial wake velocities and an extrapolation technique was carried out to get the nonlinear fit of nominal wake fraction. This provides not only to observe the change of nominal wake fraction versus scale ratios but also to estimate accurately the wake fraction at full-scale. Extrapolated full-scale nominal wake fractions by GEOSIM-based approach were compared with the full-scale CFD result, and a very good agreement was achieved. It can be noted that the GEOSIM-based extrapolation method can be applied for estimation of the nominal wake fraction of semi-displacement type high-speed vessels.

• Journal of Power Electronics
• /
• v.15 no.4
• /
• pp.1047-1053
• /
• 2015

A time-domain simulation tool to predict the dynamic power output of wind turbines in an offshore wind farm was developed in this study. A wind turbine model consisting of first or second order transfer functions of various wind turbine elements was combined with the Ainslie's eddy viscosity wake model to construct the simulation tool. The wind turbine model also includes an aerodynamic model that is a look up table of power and thrust coefficients with respect to the tip speed ratio and pitch angle of the wind turbine obtained by a commercial multi-body dynamics simulation tool. The wake model includes algorithms of superposition of multiple wakes and propagation based on Taylor's frozen turbulence assumption. Torque and pitch control algorithms were implemented in the simulation tool to perform max-Cp and power regulation control of the wind turbines. The simulation tool calculates wind speeds in the two-dimensional domain of the wind farm at the hub height of the wind turbines and yields power outputs from individual wind turbines. The NREL 5MW reference wind turbine was targeted as a wind turbine to obtain parameters for the simulation. To validate the simulation tool, a Danish offshore wind farm with 80 wind turbines was modelled and used to predict the power from the wind farm. A comparison of the prediction with the measured values available in literature showed that the results from the simulation program were fairly close to the measured results in literature except when the wind turbines are congruent with the wind direction.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.35 no.9
• /
• pp.1041-1050
• /
• 2011

An elasto-plastic finite element method using the theory of strain gradient plasticity is proposed to evaluate the size dependency of structural plasticity that occurs when the configuration size decreases to micron scale. For this method, we suggest a low-order plane and three-dimensional displacement-based elements, eliminating the need for a high order, many degrees of freedom, a mixed element, or super elements, which have been considered necessary in previous researches. The proposed method can be performed in the framework of nonlinear incremental analysis in which plastic strains are calculated and averaged at nodes. These strains are then interpolated and differentiated for gradient calculation. We adopted a strain-gradient-hardening constitutive equation from the Taylor dislocation model, which requires the plastic strain gradient. The developed finite elements are tested numerically on the basis of typical size-effect problems such as micro-bending, micro-torsion, and micro-voids. With respect to the strain gradient plasticity, i.e., the size effects, the results obtained by using the proposed method, which are simple in their calculation, are in good agreement with the experimental results cited in previously published papers.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1141-1180
• /
• 2022

The application of satellite imageries has increased in the field of hydrology and water resources in recent years. However, challenges have been encountered on obtaining accurate evapotranspiration and soil moisture. Therefore, present researches have emphasized the necessity to obtain estimations of satellite-based evapotranspiration and soil moisture with related development researches. In this study, we presented the research status in Korea by investigating the current trends and methodologies for evapotranspiration and soil moisture. As a result of examining the detailed methodologies, we have ascertained that, in general, evapotranspiration is estimated using Energy balance models, such as Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration with Internalized Calibration (METRIC). In addition, Penman-Monteith and Priestley-Taylor equations are also used to estimate evapotranspiration. In the case of soil moisture, in general, active (AMSR-E, AMSR2, MIRAS, and SMAP) and passive (ASCAT and SAR)sensors are used for estimation. In terms of statistics, deep learning, as well as linear regression equations and artificial neural networks, are used for estimating these parameters. There were a number of research cases in which various indices were calculated using satellite-based data and applied to the characterization of drought. In some cases, hydrological cycle factors of evapotranspiration and soil moisture were calculated based on the Land Surface Model (LSM). Through this process, by comparing, reviewing, and presenting major detailed methodologies, we intend to use these references in related research, and lay the foundation for the advancement of researches on the calculation of satellite-based hydrological cycle data in the future.

• The Korean Journal of Applied Statistics
• /
• v.21 no.2
• /
• pp.327-340
• /
• 2008

This paper derives joint and conditional Lagrange multiplier tests based on information matrix for testing functional form and/or the presence of autocorrelation in a regression model. Small sample properties of these tests are assessed by Monte Carlo study and comparisons are made with LM tests based on Hessian matrix. The results show that the proposed $LM_E$ tests have the most appropriate finite sample performance.

• Journal of Korea Water Resources Association
• /
• v.51 no.3
• /
• pp.273-280
• /
• 2018

Accurate estimation of evapotranspiration is mightily important for understanding and analyzing the hydrological cycle. There are various methods for estimating evapotranspiration and each method has its own advantages and limitations. Therefore, it is necessary to develop an optimal evapotranspiration product by combing different evapotranspiration products. In this study, we developed an optimal evapotranspiration by fusing two satellite- and model-based evapotranspiration estimates, including revised remote sensing-based Penman-Monteith (RS-PM) and Modified Satellite-Based Priestley-Taylor (MS-PT) methods, Global Land Data Assimilation System (GLDAS), and Global Land Evaporation Amsterdam Model (GLEAM). The statistical analysis (i.e., correlation coefficients, index of agreement, MAE, and RMSE) of combined evapotranspiration product showed to be improved compared to the individual model results. After confirming the overall results, in future studies, advanced data fusion techniques will be used to obtained improved results.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.36 no.12
• /
• pp.1543-1549
• /
• 2012

This study focuses on the state space model and the design of a state observer for the slip dynamics between rolls in STS cold cluster mills. First, a mathematical model of the roll slip is given as a nonlinear differential equation. Then, by using a Taylor series expansion, it is linearized as a state space model. Next, by using Gopinath's algorithm, a minimal-order state observer based on the state space model is designed to estimate the angular speed of all idle rolls except for an actuated roll that is measureable. Finally, a computer simulation is used to validate that the proposed state space model very well describes slip dynamics between, and moreover, the state observer very well estimates the angular speed of the idle roll.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.16 no.3
• /
• pp.540-546
• /
• 1992

Turbulent Couette flow between coaxial cylinders with inner one rotating has been investigated experimentally and numerically. The radius ratio of the coaxial cylinders is 0.43. Mean velocity and turbulent stresses have been measured by hot-wire anemometer in the range of Reynolds number based on the velocity at rotating wall and the radial distance between walls, 60,900-187,000. For the numerical computation, the Reynolds stress model has been used as a turbulence closure model. Measurements of mean velocity show that the velocity profile of wall layer largely deviates from universal logarithmic law due to the effect of streamline curvature, especially in the region near the stationary outer cylinder. The results computed with the Reynolds stress model agree well with the experimental data in the prediction of circumferential intensity of turbulent fluctuations. However, the computed level of radial intensity is much higher than the measurement. Curvature-corrected versions of the Reynolds stress model improves the prediction of turbulent intensities, but the results are not fully satisfactory.