• Structural Engineering and Mechanics
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• v.45 no.6
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• pp.759-777
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• 2013

In this paper, a topology optimization method based on the element independent nodal density (EIND) is developed for continuum solids with multiple load cases and multiple constraints. The optimization problem is formulated ad minimizing the volume subject to displacement constraints. Nodal densities of the finite element mesh are used a the design variable. The nodal densities are interpolated into any point in the design domain by the Shepard interpolation scheme and the Heaviside function. Without using additional constraints (such ad the filtering technique), mesh-independent, checkerboard-free, distinct optimal topology can be obtained. Adopting the rational approximation for material properties (RAMP), the topology optimization procedure is implemented using a solid isotropic material with penalization (SIMP) method and a dual programming optimization algorithm. The computational efficiency is greatly improved by multithread parallel computing with OpenMP to run parallel programs for the shared-memory model of parallel computation. Finally, several examples are presented to demonstrate the effectiveness of the developed techniques.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.6
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• pp.527-532
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• 2009

In this paper simulations for the impact into ceramics and/or metal materials have been discussed. To model discrete nature for fracture and damage of brittle materials, we implemented cohesive-law fracture model with a node separation algorithm for the tensile failure and Mohr-Coulomb model for the compressive loading. The drawback of this scheme is that it requires a heavy computational time. This is because new nodes are generated continuously whenever a new crack surface is created. In order to reduce the amount of calculation, parallelization with MPI library has been implemented. For the high-speed impact problems, the mesh configuration and contact calculation changes continuously as time step advances and it causes unbalance of computational load of each processor. Dynamic load balancing technique which re-allocates the loading dynamically is used to achieve good parallel performance. Some impact problems have been simulated and the parallel performance and accuracy of the solutions are discussed.

• Geophysics and Geophysical Exploration
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• v.16 no.3
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• pp.119-130
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• 2013

We developed a method for inverting magnetic data to recover the 3D susceptibility models. The major difficulty in the inversion of the potential data is the non-uniqueness and the vast computing time. The insufficient number of data compared with that of inversion blocks intensifies the non-uniqueness problem. Furthermore, there is poor depth resolution inherent in magnetic data. To overcome this non-uniqueness problem, we propose a resolution model constraint that imposes large penalty on the model parameter with good resolution; on the other hand, small penalty on the model parameter with poor resolution. Using this model constraint, the model parameter with a poor resolution can be effectively resolved. Moreover, the wavelet transform and parallel solving were introduced to save the computing time. Through the wavelet transform, a large system matrix was transformed to a sparse matrix and solved by a parallel linear equation solver. This procedure is able to enormously save the computing time for the 3D inversion of magnetic data. The developed inversion algorithm is applied to the inversion of the synthetic data for typical models of magnetic anomalies and real airborne data obtained at the Geumsan area of Korea.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.6
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• pp.567-581
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• 2008

As the size of the web is growing explosively, search engines are becoming increasingly important as the primary means to retrieve information from the Internet. A search engine periodically downloads web pages and stores them in the database to provide readers with up-to-date search results. The web crawler is a program that downloads and stores web pages for this purpose. A large-scale search engines uses a parallel web crawler to retrieve the collection of web pages maximizing the download rate. However, the service architecture or experimental analysis of parallel web crawlers has not been fully discussed in the literature. In this paper, we propose an architecture of the parallel web crawler and discuss implementation issues in detail. The proposed parallel web crawler is based on the coordinator/agent model using multiple machines to download web pages in parallel. The coordinator/agent model consists of multiple agent machines to collect web pages and a single coordinator machine to manage them. The parallel web crawler consists of three components: a crawling module for collecting web pages, a converting module for transforming the web pages into a database-friendly format, a ranking module for rating web pages based on their relative importance. We explain each component of the parallel web crawler and implementation methods in detail. Finally, we conduct extensive experiments to analyze the effectiveness of the parallel web crawler. The experimental results clarify the merit of our architecture in that the proposed parallel web crawler is scalable to the number of web pages to crawl and the number of machines used.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.21-28
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• 2015

In the semi-conductor process, a simulation process is performed to detect defects by analyzing the behavior of the impurity through the physical quantity calculation of the inner element. In order to perform the simulation, Finite-Difference Time-Domain(FDTD) algorithm is used. The improvement of semiconductor which is composed of nanoscale elements, the size of simulation is getting bigger. Problems that a processor such as CPU or GPU cannot perform the simulation due to the massive size of matrix or a computer consist of multiple processors cannot handle a massive FDTD may come up. For those problems, studies are performed with parallel/distributed computing. However, in the past, only single type of processor was used. In GPU's case, it performs fast, but at the same time, it has limited memory. On the other hand, in CPU, it performs slower than that of GPU. To solve the problem, we implemented a computing model that can handle any FDTD simulation regardless of size on the cluster which consist of heterogeneous processors. We tested the simulation on processors using MPI libraries which is based on 'point to point' communication and verified that it operates correctly regardless of the number of node and type. Also, we analyzed the performance by measuring the total execution time and specific time for the simulation on each test.

• Journal of Computing Science and Engineering
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• v.6 no.2
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• pp.105-118
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• 2012

We propose two new approaches that automatically parallelize Java programs at runtime. These approaches, which rely on run-time trace information collected during program execution, dynamically recompile Java byte code that can be executed in parallel. One approach utilizes trace information to improve traditional loop parallelization, and the other parallelizes traces instead of loop iterations. We also describe a cost/benefit model that makes intelligent parallelization decisions, as well as a parallel execution environment to execute parallelized programs. These techniques are based on Jikes RVM. Our approach is evaluated by parallelizing sequential Java programs, and its performance is compared to that of the manually parallelized code. According to the experimental results, our approach has low overheads and achieves competitive speedups compared to the manually parallelizing code. Moreover, trace parallelization can exploit parallelism beyond loop iterations.

• Journal of the Korea Society for Simulation
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• v.5 no.2
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• pp.13-24
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• 1996

Workflow is an ordered sequence of interdependent component data activities each of which can be executed on an integrated information system by accessing a remote information system. In our previous research [4], we proposed a distributed CIM Workflow system which consists of a workflow execution model called DAF-Net and an agent-based information systems called AIMIS. Given a component data activity, there needs an interaction protocol among agents which allocates the component data activity to a relevant information systems exist. The objective of this research is to propose and test two protocols: ARR(Asynchronous Request and Response)protocol and NCL(Negotiation with Case based Learning) protocol. To test the effectiveness of the protocols, we applied the PVM(Parallel Virtual Machine) software to simulate the distributed CIM Workflow system. PVM provides a distributed computing environment in which users can run different software processes in different computers while allowing communication among the processes.

• Smart Structures and Systems
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• v.23 no.2
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• pp.185-194
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• 2019

The probabilistic tsunami risk assessment of large coastal areas is challenging because the inland propagation of a tsunami wave requires an accurate numerical model that takes into account the interaction between the ground, the infrastructures, and the wave itself. Classic mesh-based methods face many challenges in the propagation of a tsunami wave inland due to their ever-moving boundary conditions. In alternative, mesh-less based methods can be used, but they require too much computational power in the far-field. This study proposes a hybrid approach. A mesh-based method propagates the tsunami wave from the far-field to the near-field, where the influence of the sea floor is negligible, and a mesh-less based method, smooth particle hydrodynamic, propagates the wave onto the coast and inland, and takes into account the wave structure interaction. Nowadays, this can be done because the advent of general purpose GPUs made mesh-less methods computationally affordable. The method is used to simulate the inland propagation of the 2004 Indian Ocean tsunami off the coast of Indonesia.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.632-637
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• 1992

Recently many dynamics control algorithms using robot dynamic equation have been proposed. One of them, Kawato's feedback error learning scheme requires neither an accurate model nor parameter estimation and makes the robot motion closer to the desired trajectory by repeating operation. In this paper, the feedback error learning algorithm is implemented to control a robot system, 5 DOF revolute type movemaster. For this purpose, an actuator dynamic model is constructed considering equivalent robot dynamics model with respect to actuator as well as friction model. The command input acquired from the actuator dynamic model is the sum of products of unknown parameters and known functions. To compute the control algorithm, a parallel processing computer, transputer, is used and real-time computing is achieved. The experiment is done for the three major link of movemaster and its result is presented.

• Journal of Power Electronics
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• v.10 no.6
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• pp.739-748
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• 2010

The increased integration of fuel cells with power electronics, critical loads, and control systems has prompted recent interest in accurate electrical terminal models of the polymer electrolyte membrane (PEM) fuel cell. Advancement in computing technologies, particularly parallel computation techniques and various real-time simulation tools have allowed the prototyping of novel apparatus to be investigated in a virtual system under a wide range of realistic conditions repeatedly, safely, and economically. This paper builds upon both advancements and provides a means of optimized model construction boosting computation speeds for a fuel cell model on a real-time simulator which can be used in a power hardware-in-the-loop (PHIL) application. Significant improvement in computation time has been achieved. The effectiveness of the proposed model developed on Opal RT's RT-Lab Matlab/Simulink based real-time engineering simulator is verified using experimental results from a Ballard Nexa fuel cell system.