• Transactions of the Korean Society of Mechanical Engineers
• /
• v.19 no.11
• /
• pp.3031-3040
• /
• 1995

Two-dimensional incompressible Navier-Stokes equations have been solved by the node-centered finite volume method with the unstructured triangular meshes. The pressure-velocity coupling is handled by the artificial compressibility algorithm due to its computational efficiency associated with the hyperbolic nature of the resulting equations. The convective fluxes are obtained by the Roe's flux difference splitting scheme using edge-based connectivities and higher-order differences are achieved by a reconstruction procedure. The time integration is based on an explicit four-stage Runge-Kutta scheme. Numerical procedures with local time stepping and implicit residual smoothing have been implemented to accelerate the convergence for the steady-state solutions. Comparisons with experimental data and other numerical results have proven accuracy and efficiency of the present unstructured approach.

• Journal of Mechanical Science and Technology
• /
• v.18 no.9
• /
• pp.1519-1528
• /
• 2004

Atmospheric Re-Entry guidance is divided as longitudinal and lateral. This paper proposes a longitudinal reference trajectory and control law using the inverse dynamics method with pseudospectral Legendre method. Application of this method into Re-Entry problem forces a power of calculation time-reduction due to unnecessary of integration or any iteration as well as sufficient accuracy convergence. The used guidance scheme is time-to-go.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.3 no.1
• /
• pp.20-26
• /
• 2011

A weakly nonlinear seakeeping methodology for predicting motions and loads is presented in this paper. This methodology assumes linear radiation and diffraction forces, calculated in the frequency domain, and fully nonlinear Froude-Krylov and hydrostatic forces, evaluated in the time domain. The particular approach employed here allows to overcome numerical problems connected to the determination of the impulse response functions. The procedure is divided into three consecutive steps: evaluation of dynamic sinkage and trim in calm water that can significantly influence the final results, a linear seakeeping analysis in the frequency domain and a weakly nonlinear simulation. The first two steps are performed employing a three-dimensional Rankine panel method. Nonlinear Froude-Krylov and hydrostatic forces are computed in the time domain by pressure integration on the actual wetted surface at each time step. Although nonlinear forces are evaluated into the time domain, the equations of motion are solved in the frequency domain iteratively passing from the frequency to the time domain until convergence. The containership S175 is employed as a test case for evaluating the capability of this methodology to correctly predict the nonlinear behavior related to wave induced motions and loads in head seas; numerical results are compared with experimental data provided in literature.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.6
• /
• pp.619-627
• /
• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• Journal of Wellbeing Management and Applied Psychology
• /
• v.2 no.2
• /
• pp.19-37
• /
• 2019

Over the last few decades, the atmospheric carbon dioxide emission has been amplified to a great extent in Turkey. This amplification may cause global warming, climate change and environmental degradation in Turkey. Consequently, ecological condition and human life may suffer in the near future from these indicated threats. Therefore, an attempt was made to test the relationship among a number of expected factors and carbon dioxide emissions in the case of Turkey. The study covers the time series data over the period of 1970-2017. We employed the modern econometric techniques such as Johansen co-integration, ARDL bound testing approach and the block exogeneity. The results of the Johansen co-integration test show that there is a significant long-run relationship between carbon dioxide emissions and expected factors. The long-run elasticities of the ARDL model show that a 1% increase in the GDP per capita, electric consumption, fiscal development and trade openness will increase carbon dioxide emissions by 0.14, 0.52, 0.09 and 0.20% respectively. Further, our findings reveal that the environmental Kuznets curve (EKC) hypothesis and inverted U-shaped relationship between carbon dioxide emission and economic growth prevails. Therefore, the EKC hypothesis is valid and prevailing in the Turkish economy. The diagnostic test results show that the parameters of the ARDL model are credible, sTable and reliable in the current form. Finally, Block exogeneity analysis displays that all the expected factors are contributing significantly to carbon dioxide emissions in the Turkish economy.

• 한국전산유체공학회:학술대회논문집
• /
• 1995.10a
• /
• pp.175-181
• /
• 1995

Three-Dimensional Euler equations are solved numerically for the analysis of contraction flows in wind or water tunnels. A second-order finite difference method is used for the spatial discretization on the nonstaggered grid system and the 4-stage Runge-Kutta scheme for the numerical integration in time. In order to speed up the convergence, the local time stepping and the implicit residual-averaging schemes are introduced. The pressure field is obtained by solving the pressure-Poisson equation with the Neumann boundary condition. For the evaluation of the present Euler solver, numerical computations are carried out for the various contraction geometries, one of which was adopted in the Large Cavitation Channel for the U.S. Navy. The comparison of the computational results with the available experimental data shows good agreements.

• Journal of computational fluids engineering
• /
• v.2 no.1
• /
• pp.8-12
• /
• 1997

The three-dimensional Euler equations are solved numerically for the analysis of contraction flows in wind or water tunnels. A second-order finite difference method is used for the spatial discretization on the nonstaggered grid system and the 4-stage Runge-Kutta scheme for the numerical integration in time. In order to speed up the convergence, the local time stepping and the implicit residual-averaging schemes are introduced. The pressure field is obtained by solving the pressure-Poisson equation with the Neumann boundary condition. For the evaluation of the present Euler solver, numerical computations are carried out for three contraction geometries, one of which was adopted in the Large Cavitation Channel for the U.S. Navy. The comparison of the computational results with the available experimental data shows good agreement.

• Asia pacific journal of information systems
• /
• v.29 no.4
• /
• pp.615-643
• /
• 2019

Now is the time for IS scholars to demonstrate the added value of academic theory through its integration with text mining, clearly outline how to implement this for text mining experts outside of the academic field, and move towards establishing this integration as a standard practice. Therefore, in this study we develop a systematic theory-based text-mining framework (TTMF), and illustrate the use and benefits of TTMF by conducting a text-mining project in an actual business case evaluating and improving hotel service quality using a large volume of actual user-generated reviews. A total of 61,304 sentences extracted from actual customer reviews were successfully allocated to SERVQUAL dimensions, and the pragmatic validity of our model was tested by the OLS regression analysis results between the sentiment scores of each SERVQUAL dimension and customer satisfaction (star rates), and showed significant relationships. As a post-hoc analysis, the results of the co-occurrence analysis to define the root causes of positive and negative service quality perceptions and provide action plans to implement improvements were reported.

• Korean Journal of Artificial Intelligence
• /
• v.12 no.2
• /
• pp.17-23
• /
• 2024

Various methods have been developed to predict the flight path of an air-launched weapon to intercept a fast-moving target in the air. However, it is also getting more challenging to predict the optimal firing zone and provide it to a pilot in real-time during engagements for advanced weapons having new complicated guidance and thrust control. In this study, a method is proposed to develop an optimized weapon engagement zone by the SCG (Scaled Conjugate Gradient) algorithm to achieve both accurate and fast estimates and provide an optimized launch display to a pilot during combat engagement. SCG algorithm is fully automated, includes no critical user-dependent parameters, and avoids an exhaustive search used repeatedly to determine the appropriate stage and size of machine learning. Compared with real data, this study showed that the development of a machine learning-based weapon aiming algorithm can provide proper output for optimum weapon launch zones that can be used for operational fighters. This study also established a process to develop one of the critical aircraft-weapon integration software, which can be commonly used for aircraft integration of air-launched weapons.

• Journal of Convergence for Information Technology
• /
• v.10 no.3
• /
• pp.7-15
• /
• 2020

As the paradigm shifts from treatment and provider-centered healthcare to prevention and consumer-centered healthcare, the integration of ICT convergence technology is calling for an era of digital healthcare industry revival in the Fourth Industrial Revolution. It is possible to provide individual customized medical services utilizing various medical data, and it is possible to provide various medical services that transcend time and space through integration with other industries. Such digital healthcare includes health, nutrition, exercise, and patient care, while the digital healthcare industry includes healthcare and IT related to medical devices, medical information systems, and healthcare platforms that can provide personal health and medical information. Due to the social demands of the aging and the increase of chronic diseases, digital healthcare is considered as an important policy in the fourth industrial revolution in Korea. In order for the digital healthcare industry to contribute to the prolongation of human life and the improvement of quality of life, it is urgent to develop related infrastructures, legal institutions, and prepare policies. In addition, it is important to activate convergent education to foster talents who will lead the digital healthcare industry. The purpose of this study was to examine the trends of the digital healthcare industry in the era of the fourth industrial revolution and the direction of government R & D policies, and to derive directions and suggestions for future development.