• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.819-829
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• 2019

In the disaster of collapse, an immediate response is needed to prevent the damage from worsening, and damage area calculation, response and recovery plan should be established. This requires accurate detection of the damage affected area. This study performed the detection of the damaged area by using UAV which can respond quickly and in real-time to detect the collapse accident. The study area was selected as B-05 housing redevelopment area in Jung-gu, Ulsan, where the demolition of houses and apartments in progress as the redevelopment project began. This area resembles a collapsed state of the building, which clear changes before and after the demolition. UAV images were acquired on May 17 and July 9, 2019, respectively. The changing area was considered as the damaged area before and after the collapse of the building, and the changing area was detected using CVA (Change Vector Analysis) the Representative Change Detection Technique, and SLIC (Simple Linear Iterative Clustering) based superpixel algorithm. In order to accurately perform the detection of the damaged area, the uninterested area (vegetation) was firstly removed using ExG (Excess Green), Among the objects that were detected by change, objects that had been falsely detected by area were finally removed by calculating the minimum area. As a result, the accuracy of the detection of damaged areas was 95.39%. In the future, it is expected to be used for various data such as response and recovery measures for collapse accidents and damage calculation.

• Computers and Concrete
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• v.13 no.1
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• pp.49-70
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• 2014

Steel fiber-reinforced concrete (SFRC) is known as one of the efficient modern composites that can greatly enhance the material performance of cracked concrete in tension. Such improved tensile resistance mechanism at crack interfaces in SFRC members can be heavily influenced by methodologies of treatments of crack direction. While most existing studies have focused on developing the numerical analysis model with the rotating-angle theory, there are only few studies on finite element analysis models with the fixed-angle model approach. According to many existing experimental studies, the direction of principal stress rotated after the formation of initial fixed-cracks, but it was also observed that new cracks with completely different angles relative to the initial crack direction very rarely occurred. Therefore, this study introduced the direct tension force transfer model (DTFTM), in which tensile resistance of the fibers at the crack interface can be easily estimated, to the nonlinear finite element analysis algorithm with the fixed-angle theory, and the proposed model was also verified by comparing the analysis results to the SFRC shear panel test results. The secant modulus method adopted in this study for iterative calculations in nonlinear finite element analysis showed highly stable and fast convergence capability when it was applied to the fixed-angle theory. The deviation angle between the principal stress direction and the fixed-crack direction significantly increased as the tensile stresses in the steel fibers at crack interfaces increased, which implies that the deviation angle is very important in the estimation of the shear behavior of SFRC members.

• Computational Structural Engineering
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• v.9 no.1
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• pp.151-159
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• 1996

A finite element formulation based on the CFT(Compression Field Theory) concept such as the effect of compression softening in cracked concrete, and macroscopic and rotating crack models etc. was presented for the nonlinear behaviour of structural concrete. In this category, tangential or secant material stiffnesses for cracked concrete were also defined and discussed in view of the iterative solution schemes for nonlinear equations. Considering the computational efficiency and the ability of modelling the post-ultimate behaviour as major concerns, the incremental displacement solution algorithm involving initial material stiffnesses and the relaxation procedure for fast convergence was adopted and formulated in a type of 8-noded quadrilateral isoparametric elements. The analysis program NASCOM(Nonlinear Analysis of structrual Concrete by FEM : Monotonic Loading) developed baed on the CFT constitutive relationships and the incremetal solution strategy described enables the predictions of strength and deformation capacities in a full range. crack patterns and their corresponding widths, and yield extents of reinforcement. As the verfication purpose of NASCOM, the prediction of Cervenka's panel test results including the load resistance and the deformation history was made. A limited number of predictions indicate a good correlation in a general sense.

• Journal of applied mathematics & informatics
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• v.11 no.1_2
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• pp.305-316
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• 2003

Recently, an iterative algorithm for finding the interior eigenvalues of a definite matrix by CG-type method has been proposed. This method compares to the inverse power method. The given matrices A, and B are assumed to be large and sparse, and SPD( Symmetric Positive Definite) The CG scheme for the optimization of the Rayleigh quotient has been proven a very attractive and promising technique for large sparse eigenproblems for smallest eigenvalue. Also, it is very amenable to parallel computations, like the CG method for the linear systems. A proper choice of the preconditioner significantly improves the convergence of the CG scheme. But for parallel computations we need to find an efficient parallel preconditioner. Our candidates we ILU(0) in the wave-front order, ILU(0) in the multi-coloring order, Point-SSOR(Symmetric Successive Overrelaxation), and Multi-Color Block SSOR preconditioner. Wavefront order is a simple way to increase parallelism in the natural order, and Multi-coloring realizes a parallelism of order(N), where N is the order of the matrix. Another choice is the Multi-Color Block SSOR(Symmetric Successive OverRelaxation) preconditioning. Block SSOR is a symmetric preconditioner which is expected to minimize the interprocessor communication due to the blocking. We implemented the results on the CRAY-T3E with 128 nodes. The MPI (Message Passing Interface) library was adopted for the interprocessor communications. The test problem was drawn from the discretizations of partial differential equations by finite difference methods. The results show that for small number of processors Multi-Color ILU(0) has the best performance, while for large number of processors Multi-Color Block SSOR performs the best.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.25-37
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• 2019

Power-line communication (PLC) has influenced smart grid development. In addition, PLC has also been instrumental in current research on internet-of-things (IoT). Due to the implementation of PLC in smart grid and IoT environments, strides have been made in PLC and its combination with the wireless system to form a hybrid communication system. Also, PLC has evolved from a single-input-single-output (SISO) configuration to multiple-input-multiple-output (MIMO) configuration system, and from a point-to-point communication system to cooperative communication systems. In this work, we extend a MIMO wireless two-way amplify-and-forward (AF) cooperative communication system to a hybrid PLC and wireless (PLC/W) system configuration. We then maximize the weighted sum-rate for the hybrid PLC/W by optimizing the precoders at each node within the hybrid PLC/W system. The sum-rate problem was found to be non-convex, therefore, an iterative algorithm is used to find the optimal precoders that locally maximize the system sum-rate. For our simulation results, we compare our proposed hybrid PLC/W configuration to a PLC only and wireless only configuration at each node. Due to an improvement in system diversity, the hybrid PLC/W configuration outperformed the PLC only and wireless only system configurations in all simulation results presented in this paper.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.1
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• pp.27-36
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• 2000

As a potential approach for non-destructive testing of concrete structures, we evaluate the time-of-flight (TOF) ultrasound tomography technique In conventional X ray tomography, the reconstructed Image corresponds to the internal attenuation coefficient However, in TOF ultrasound tomography, the reconstructed Image is proportional to the retractive index of the medium Because refractive effects are minimal for X-rays, conventional reconstruction techniques are applied to reconstruct the Image in X-ray tomography However, since ultrasound travels in curved path, due to the spatial variations in the refractive index of the medium, the path must be known to correctly reconstruct the Image. Algorithm for determining the ultrasound path is developed from a Geometrical Optics point view and the image reconstruction algorithm, since the paths are curved It requires the algebraic approach, namely the ART or the SIRT Here, the difference between the computed and the measured TOP data is used as a basis, for the iteration process First the initial image is reconstructed assuming straight paths. It then updates the path based on the recently reconstructed image This process of reconstruction and path determination repeats until convergence The proposed algorithm is evaluated by computer simulations, and in addition is applied to a real concrete structure.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.2
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• pp.67-75
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• 1986

This paper introduces the nonlinear Stream Function Wave Theory for design waves efficiently to compute the wave energy and energy transport quantities and to analyze the effects of nonlinearities on them. The Stream Function Wave Theory was developed by Dean for case of the observed waves with assymmetric wave profiles and of the design waves with symmetric theoretical wave profiles. Dalrymple later improved the computational procedure by adding two Lagrangian constraints so that more efficient convergence of the iterative numerical method to a specified wave height and to a zero mean free surface displacement resulted. And the Stream Function coefficients are computed numerically by the improved Marquardt algorithm developed for this study. As the result of this study the effects of nonlinearities on the wave quantities of the average potential energy density, the average kinetic energy density result in overestimation by linear wave theory compared to the Stream Function Wave Theory and increase monotonically with decreasing $L^*/L_O$ and with increasing $H/H_B$. The effects of nonlinearities on the group velocity and the wavelength quantities result in underestimation by linear wave theory and increase monotonically with increasing $H/H_B$. Finally the effect of nonlinearity on the average total energy flux results in overestimation for shallow water waves and underestimation for deep water waves by linear wave theory.

• Geophysics and Geophysical Exploration
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• v.2 no.4
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• pp.167-173
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• 1999

Since the resolution of the 2-D hole-to-hole seismic traveltime tomography is affected by the limited ray transmission angle, various methods were used to improve the resolution. Linear traveltime interpolation(LTI) ray tracing method was chosen for forward-modeling method. Inversion results using the LTI method were compared with those using the other ray tracing methods. As an inversion algorithm, SIRT method was used. In the iterative non-linear inversion method, the cost of ray tracing is quite expensive. To reduce the cost, each raypath was stored and the inversion was performed from this information. Using the proposed method, fast convergence was achieved. Inversion results are likely to be affected by the initial velocity guess, especially when the ray transmission angle was limited. To provide a good initial guess for the inversion, generalized regression neural network(GRNN) method was used. When the transmitted raypath angle is not limited or the geological model is very complex, the inversion results are not affected by initial velocity model very much. Since the raypath angles, however, are limited in most geophysical tomographic problems, the enhancement of resolution in tomography can be achieved by providing a proper initial velocity model by another inversion algorithm such as GRNN.

• Geophysics and Geophysical Exploration
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• v.7 no.3
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• pp.207-212
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• 2004

This article reviews recent developments in three-dimensional (3-D) magntotelluric (MT) imaging. The inversion of MT data is fundamentally ill-posed, and therefore the resultant solution is non-unique. A regularizing scheme must be involved to reduce the non-uniqueness while retaining certain a priori information in the solution. The standard approach to nonlinear inversion in geophysis has been the Gauss-Newton method, which solves a sequence of linearized inverse problems. When running to convergence, the algorithm minimizes an objective function over the space of models and in the sense produces an optimal solution of the inverse problem. The general usefulness of iterative, linearized inversion algorithms, however is greatly limited in 3-D MT applications by the requirement of computing the Jacobian(partial derivative, sensitivity) matrix of the forward problem. The difficulty may be relaxed using conjugate gradients(CG) methods. A linear CG technique is used to solve each step of Gauss-Newton iterations incompletely, while the method of nonlinear CG is applied directly to the minimization of the objective function. These CG techniques replace computation of jacobian matrix and solution of a large linear system with computations equivalent to only three forward problems per inversion iteration. Consequently, the algorithms are efficient in computational speed and memory requirement, making 3-D inversion feasible.