• International Journal of Automotive Technology
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• v.7 no.7
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• pp.867-872
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• 2006

Fuel cells are devices that convert chemical energy directly into electrical energy. Owing to the high efficiency of the fuel cells, a large number of research work have been done during these years. Among many kinds of the fuel cells, a polymer electrolyte membrane fuel cell is such kind of thing which works under low temperature. Because of the specialty, it stimulated intense global R&D competition. Most of the major world automakers are racing to develop polymer electrolyte membrane fuel cell passenger vehicles. Unfortunately, there are still many problems to be solved in order to make them into the commercial use, such as the thermal and water management in working process of PEMFCs. To solve the difficulites facing the researcher, the analysis of the inner mechanism of PEMFC should be implemented as much as possible and mathematical modeling is an important tool for the research of the fuel cell especially with the combination of experiment. By regarding some of the assumptions and simplifications, using the finite element technique, a two-dimensional electrochemical mode is presented in this paper for the further comparison with experimental data. Based on the principals of the problem, the equations of electronic charge conservation equation, gas-phase continuity equation, and mass balance equation are used in calculating. Finally, modeling results indicate some of the phenomenon in a unit cell, and the relationships between potential and current density.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.60-67
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• 2008

The vibrations and noise origin in electric material is due to several coupled physical phenomena. The revolving electric machine complete modeling is complex; it does not allow simple parametric machine structure studies for various operation modes. This work presents a simple electromagnetic model which makes possible the machine principal parts flow estimation from flux density. Special interest is given in determining Switched Reluctance Machine (S.R.M) radial acceleration in accordance with the current supply. Our focus will be only on the magnetic origin efforts that are dominating in the S.R.M. The efforts calculation versus the current is presented in the case of a machine with a linearized rate. These efforts are considered as a tangential force producing the torque and a radial force that generates no torque. The application is realized on a 6/4 low power S.R.M type (6 stator teeth and 4 teeth rotor). The mechanical response is substituted in a transfer function. The model takes account of the power supply of the machine, the relation between the current supply and the efforts as well as the vibratory response of the machine to these efforts. Finally, the model is validated by comparison with similar experimental results within the framework of the definite assumptions.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.1358-1365
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• 2010

Estimating condition of slope is difficult because of nonlinear time dependency and seasonal effects, which affect the displacements. Displacements and displacement patterns of landslides are highly variable in time and space, and a unique approach cannot be defined to model landslide movements. Characteristics of movements are obtained by using a statistical method called Principal Component Analysis(PCA). The PCA is a non-parametric method to separate unknown, statistically uncorrelated source processes from observed mixed processes. In the non-parametric approaches, no physical assumptions of target systems are required. Instead, since the "best" mathematical relationship is estimated for given data sets of the input and output measured from target systems. As a consequence, non-parametric approaches are advantageous in modeling systems whose geomechanical properties are unknown or difficult to be measured. Non-parametric approaches are consequently more flexible in modeling than parametric approaches. This method is expected to be a useful tool for the slope management of and alarm systems.

• The Journal of the Petrological Society of Korea
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• v.22 no.4
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• pp.273-289
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• 2013

Fallout ash is a notorious hazard that can have a variety of damages on agriculture and infrastructure and, most notably to aviation and human health. This study discusses the design of a conceptual model to aid in modeling the dispersal and deposition of ash from Mt. Baekdu volcano. It includes a discussion of assumptions and boundary conditions of the model as well as a detailed diagram of the conceptual model, complete with input parameters, units and equations. The two main processes contained within the model are the dispersal and deposition of ash, the outputs obtained from running the model, if designed, would be the total amount of fine ash contained in the eruption column, distance travelled by ash and ash thickness at surface.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.2 s.95
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• pp.148-155
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• 2005

As functional requirement of massive digital information storage devices are on a trend for the higher data transfer rate and lower cost, many different technical efforts are being tested and implemented in the industry. FDB(fluid dynamic bearing) is one of the major breakthroughs in rotor design in terms of TMR(track misregistration) budget. Although FDB analysis based on Reynolds' equation is well established and popularly being used for FDB design especially for the estimation of bearing stiffness, there are obvious limitations in the approach due to the inherent assumptions. A generalized analysis tool employing the full Navier-Stokes equation and the energy balance is to be beneficial for detailed FDB design. In this publication, an efficient geometry modeling method is presented that provides fully integrated inputs for general FVM/FDM(finite volume method/ finite difference method) codes. By virtue of the flexibility of the presented method, many different detailed FDB design and analysis are carried over with ease.

• Computers and Concrete
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• v.16 no.5
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• pp.759-774
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• 2015

This study simulates the flexural behavior of ultra-high-performance fiber-reinforced concrete (UHPFRC) beams reinforced with steel and glass fiber-reinforced polymer (GFRP) rebars. For this, micromechanics-based modeling was first carried out on the basis of single fiber pullout models considering inclination angle. Two different tension-softening curves (TSCs) with the assumptions of 2-dimensional (2-D) and 3-dimensional (3-D) random fiber orientations were obtained from the micromechanics-based modeling, and linear elastic compressive and tensile models before the occurrence of cracks were obtained from the mechanical tests and rule of mixture. Finite element analysis incorporating smeared crack model was used due to the multiple cracking behaviors of structural UHPFRC beams, and the characteristic length of two times the element width (or two times the average crack spacing at the peak load) was suggested as a result of parametric study. Analytical results showed that the assumption of 2-D random fiber orientation is appropriate to a non-reinforced UHPFRC beam, whereas the assumption of 3-D random fiber orientation is suitable for UHPFRC beams reinforced with steel and GFRP rebars due to disorder of fiber alignment from the internal reinforcements. The micromechanics-based finite element analysis also well predicted the serviceability deflections of UHPFRC beams with GFRP rebars and hybrid reinforcements.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.203-208
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• 2007

Due to the long tectonic history and the very complex geologic formations in Korea, the anisotropic characteristics of subsurface material may often change very greatly and locally. The algorithms for the travel time computation commonly used, however, may not give sufficiently precise results particularly for the complex and strong anisotropic model, since they are based on the two-dimensional (2D) earth and/or weak anisotropy assumptions. This study is intended to develope a three-dimensional (3D) modeling algorithm to precisely calculate the first arrival time in the complex anisotropic media. We assume 3D TTI (tilted transversely isotropy) medium having the arbitrary symmetry axis. The algorithm includes the 2D non-linear interpolation scheme to calculate the traveltimes inside the grid and the 3D traveltime mapping to fill the 3D model with first arrival times. The weak anisotropy assumption, moreover, can be overcome through devising a numerical approach of the steepest descent method in the calculation of minimum traveltime, instead of using approximate solution.

• Structural Engineering and Mechanics
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• v.26 no.3
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• pp.343-361
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• 2007

This article presents a numerical tool for dimensioning two-threaded fasteners connecting prismatic parts subjected to fatigue tension loads that are coplanar with the screw axis. A simplified numerical model is developed from unidirectional finite elements, modeling the connected parts and screws with bent elements and the elastic contact layer between the parts with springs. An algorithm updating the contact stiffness matrix, calculating forces and displacements at each node of the structure and thus normal stresses in the screws in both static and fatigue is further developed using C language. An experimental study is also conducted in parallel with the numerical approach to validate the developed model assumptions, the numerical model and the 3D finite element results. Since stiffness values for the compressive zones in the parts are analytically difficult to determine, a statistical software method is used, from which a tuning factor is derived for identifying these stiffness values. The method is also applied to set out the influence of each parameter on the fatigue behaviour of each screw. Finally, the developed model will be used to establish a new, sophisticated, fast and accurate tool for dimensioning bolted mechanical structures.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.393-399
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• 2009

This paper introduces an automated tool named Advanced Stochastic Schedule Simulation System (AS4). The system automatically integrates CPM schedule data exported from Primavera Project Planner (P3) and historical activity duration data obtained from a project data warehouse, computes the best fit probability distribution functions (PDFs) of historical activity durations, assigns the PDFs identified to respective activities, computes the optimum number of simulation runs, simulates the schedule network for the optimum number of simulation runs, and estimates the best fit PDF of project completion times (PCTs). AS4 improves the reliability of simulation-based scheduling by effectively dealing with the uncertainties of the activities' durations, increases the usability of the schedule data obtained from commercial CPM software, and effectively handles the variability of the PCTs by finding the best fit PDF of PCTs. It is designed as an easy-to-use computer tool programmed in MATLAB. AS4 encourages the use of simulation-based scheduling because it is simple to use, it simplifies the tedious and burdensome process involved in finding the PDFs of the many activities' durations and in assigning the PDFs to the many activities of a new network under modeling, and it does away with the normality assumptions used by most simulation-based scheduling systems in modeling PCTs.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2305-2314
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• 2023

The governing equations of atmospheric dispersion most often taking the form of a second-order partial differential equation (PDE). Currently, typical computational codes for predicting atmospheric dispersion use the Gaussian plume model that is an analytic solution. A Gaussian model is simple and enables rapid simulations, but it can be difficult to apply to situations with complex model parameters. Recently, a method of solving PDEs using artificial neural networks called physics-informed neural network (PINN) has been proposed. The PINN assumes the latent (hidden) solution of a PDE as an arbitrary neural network model and approximates the solution by optimizing the model. Unlike a Gaussian model, the PINN is intuitive in that it does not require special assumptions and uses the original equation without modifications. In this paper, we describe an approach to atmospheric dispersion modeling using the PINN and show its applicability through simple case studies. The results are compared with analytic and fundamental numerical methods to assess the accuracy and other features. The proposed PINN approximates the solution with reasonable accuracy. Considering that its procedure is divided into training and prediction steps, the PINN also offers the advantage of rapid simulations once the training is over.