• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.23 no.8
• /
• pp.1063-1071
• /
• 1999

Fine grid calculations are reported for the developing turbulent flow in a curved duct of square cross-section with a radius of curvature to hydraulic diameter ratio ${\delta}=Rc/D_H=3.357 $ and a bend angle of 720 deg. A sequence of modeling refinements is introduced; the replacement of wall function by a fine mesh across the sublayer and a low Reynolds number algebraic second moment closure up to the near wall sublayer in which the non-linear return to isotropy model and the cubic-quasi-isotropy model for the pressure strain are adopted; and the introduction of a multiple source model for the exact dissipation rate equation. Each refinement is shown to lead to an appreciable improvement in the agreement between measurement and computation.

• Journal of Welding and Joining
• /
• v.22 no.6
• /
• pp.25-29
• /
• 2004

Some industrial steel structures are composed by components linked by several welding joints to constitute an assembly. The main interest of assembly simulation is to evaluate the global distortion of welded structure. The general method, thermo-elasto-plastic analysis, leads to excessive model size and computation time. In this study, a simplified method called "Local and Global approach" was developed to break down this limit and to provide a accurate solution for distortion. Local and global approach is composed of 3 steps; 1) Local simulation of each welding joint on a dedicated mesh (usually very fine due to high thermal gradients), taking into account for the non linearity of the material properties and the moving heat source. 2) Transfer to the global model of the effects of the welding joints by projection of the plastic strain tensors. 3) Elastic simulation to determine final distortions in global model. The welding deformation test for mock-up structure was performed to verify this approach. The predicted welding distortion by this approach had a good agreement with experiment results.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.7
• /
• pp.663-671
• /
• 2008

This paper presents a real-time haptic rendering method for multi-contact interaction with virtual environments. Haptic systems often employ physics-based deformation models such as finite-element models and mass-spring models which demand heavy computational overhead. The haptic system can be designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. A multi-rate output-estimation with an exponential forgetting factor is proposed to implement real-time haptic rendering for the haptic systems with two sampling rates. The computational burden of the output-estimation increases rapidly as the number of contact points increases. To reduce the computation of the estimation, the multi-rate output-estimation with reduced parameters is developed in this paper. Performance of the new output-estimation with reduced parameters is compared with the original output-estimation with full parameters and an exponential forgetting factor. Estimated outputs are computed from the estimated input-output model at a high rate, and trace the analytical outputs computed from the deformation model. The performance is demonstrated by simulation with a linear tensor-mass model.

• Geophysics and Geophysical Exploration
• /
• v.20 no.3
• /
• pp.176-184
• /
• 2017

To interpret the seismic image precisely, random noises should be suppressed and the continuity of the image should be enhanced by using the appropriate smoothing techniques. Structure-Oriented Filter-Edge Preserving (SOF-EP) technique is one of the methods, that have been actively researched and used until now, to efficiently smooth seismic data while preserving the continuity of signal. This technique is based on the principle that diffusion occurs from large amplitude to small one. In a continuous structure such as a horizontal layer, diffusion or smoothing is operated along the layer, thereby increasing the continuity of layers and eliminating random noise. In addition, diffusion or smoothing across boundaries at discontinuous structures such as faults can be avoided by employing the continuity decision factor. Accordingly, the precision of the smoothing technique can be improved. However, in the case of the structure-oriented semblance technique, which has been used to calculate the continuity factor, it takes lots of time depending on the size of the filter and data. In this study, we first implemented the SOF-EP method and confirmed its effectiveness by applying it step by step to the field data. Next, we proposed and applied the corner response method which can efficiently calculate the continuity decision factor instead of structure-oriented semblance. As a result, we could confirm that the computation time can be reduced by about 6,000 times or more by applying the corner response method.

• Journal of the Korea Convergence Society
• /
• v.9 no.9
• /
• pp.431-440
• /
• 2018

In this study, authors predicted probability of resignation of newly employed nurses using TensorFlow, an open source software library for numerical computation and machine learning developed by Google, and suggested strategic human resources management plan. Data of 1,018 nurses who resigned between 2010 and 2017 in single university hospital were collected. After the order of data were randomly shuffled, 80% of total data were used for machine leaning and the remaining data were used for testing purpose. We utilized multiple neural network with one input layer, one output layer and 3 hidden layers. The machine-learning algorithm correctly predicted for 88.7% of resignation of nursing staff with in one year of employment and 79.8% of that within 3 years of employment. Most of resigned nurses were in their late 20s and 30s. Leading causes of resignation were marriage, childbirth, childcare and personal affairs. However, the most common cause of resignation of nursing staff with in one year of employment were maladaptation to the work and problems in interpersonal relationship.