• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.8
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• pp.341-350
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• 2006

This paper presents a new methodology to draw the components of locational marginal price (LMP) in electricity market. Recently, the changing environments surrounding electricity industries resulted in the unbundled services provided by electricity market players, which may require the new pricing mechanisms based on the LMP. The changed pricing mechanisms will provide the price signals of time and location to the market participants. Most of the existing studies of LMP are based on the Lagrangian multipliers as shadow prices to evaluate the equivalent values of constraints or factors for security, reliability and quality. However, the shadow prices cannot provide enough information for components of LMP. In this paper, therefore, we proposed a new approach that LMP is divided into three components. To do this, we first present the method for shadow prices calculation and then break down LMP into a variety of parts corresponding to the concerned factors. The proposed approach is applied to 5-bus and modified IEEE 14-bus sample system in order to verify its validity.

• Korea-Australia Rheology Journal
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• v.21 no.3
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• pp.193-200
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• 2009

We present a direct simulation technique for two-dimensional mold-filling simulations of fluids filled with a large number of circular disk-like rigid particles. It is a direct simulation in that the hydrodynamic interaction between particles and fluid is fully considered. We employ a pseudo-concentration method for the evolution of the flow front and the DLM (distributed Lagrangian multipliers)-like fictitious domain method for the implicit treatment of the hydrodynamic interaction. Both methods allow the use of a fixed regular discretization during the entire computation. The discontinuous Galerkin method has been used to solve the concentration evolution equation and the rigid-ring description has been introduced for freely suspended particles. A buffer zone, the gate region of a finite area subject to the uniform velocity profile, has been introduced to put discrete particles into the computational domain avoiding any artificial discontinuity. From example problems of 450 particles, we investigated the particle motion and effects of particles on the flow for both Newtonian and shear-thinning fluid media. We report the prolonged particle movement toward the wall in case of a shear-thinning fluid, which has been interpreted with the shear rate distribution.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.249-256
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• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1229-1244
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• 2017

In recent years, as demand for data-based analytical methodologies increases in various fields, optimization methods have been developed to handle them. In particular, various constraints required for problems in statistics and machine learning can be solved by convex optimization. Alternating direction method of multipliers (ADMM) can effectively deal with linear constraints, and it can be effectively used as a parallel optimization algorithm. ADMM is an approximation algorithm that solves complex original problems by dividing and combining the partial problems that are easier to optimize than original problems. It is useful for optimizing non-smooth or composite objective functions. It is widely used in statistical and machine learning because it can systematically construct algorithms based on dual theory and proximal operator. In this paper, we will examine applications of ADMM algorithm in various fields related to statistics, and focus on two major points: (1) splitting strategy of objective function, and (2) role of the proximal operator in explaining the Lagrangian method and its dual problem. In this case, we introduce methodologies that utilize regularization. Simulation results are presented to demonstrate effectiveness of the lasso.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.139-149
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• 2018

The resistivity monitoring is a practical method to resolve changes in resistivity of underground structures over time. With the advance of sophisticated automatic data acquisition system and rapid data communication technology, resistivity monitoring has been widely applied to understand spatio-temporal changes of subsurface. In this study, a new 4D inversion algorithm is developed, which can effectively emphasize significant changes of underground resistivity with time. To overcome the overly smoothing problem in 4D inversion, the Lagrangian multipliers in the space-domain and time-domain are determined automatically so that the proportion of the model constraints to the misfit roughness remains constant throughout entire inversion process. Furthermore, a focusing model constraint is added to emphasize significant spatio-temporal changes. The performance of the developed algorithm is demonstrated by the numerical experiments using the synthetic data set for a time-lapse model.