• Title/Summary/Keyword: large scale model test

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Nonlinear Behavior Characteristics and Seismic Performance of the Existing RC Piers without Seismic Detailing (비내진 상세 기존 RC 교각의 비선형 거동특성 및 내진성능)

  • 김재관
    • Proceedings of the Earthquake Engineering Society of Korea Conference
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    • 2000.04a
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    • pp.327-334
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    • 2000
  • The seismic performance evaluation of the existing non-seismic detailed RC piers has risen as urgent task for rational and cost-effective seismic retrofitting works as well as development of new seismic design concept. The scale model test has been conducted to investigate nonlinear behavior characteristics and the seismic performance of existing piers with lap-spliced longitudinal reinforcements in the plastic hinge zone which are of the solid circular and the hollow rectangular section. The lap splice in this zone is found to cause premature bond failure. The experimental results show very poor seismic performance of circular section pier but relatively large ductility of the rectangular one.

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The Study on permeability enhancement in smear zone using electro-osmotic pressure (전기 삼투압을 이용한 교란영역의 투수성 개선에 관한 연구)

  • Ahn, Byung-Wook;Noh, Hee-Jeon;Kim, Hyun-Ki;Cho, Nam-Jun
    • Proceedings of the Korean Geotechical Society Conference
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    • 2008.03a
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    • pp.435-441
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    • 2008
  • More time is required for consolidating soft clay when its hydraulic conductivity around the vertical drains is reduced by soil disturbance. One of the methods to be proposed to solve such problem is the electro-osmotic flow application. This study presents the experimental results of model tests using a modified oedometer and a large-scale cylinder with a sand drain. Results show that the development of negative excessive pore water pressure due to the DC electrical field in saturated clay can be transformed to additional loads causing more consolidation settlement.

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A B-spline based Branch & Bound Algorithm for Global Optimization (전역 최적화를 위한 B-스플라인 기반의 Branch & Bound알고리즘)

  • Park, Sang-Kun
    • Korean Journal of Computational Design and Engineering
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    • v.15 no.1
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    • pp.24-32
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    • 2010
  • This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.

ON THE STUDY OF SOLUTION UNIQUENESS TO THE TASK OF DETERMINING UNKNOWN PARAMETERS OF MATHEMATICAL MODELS

  • Avdeenko, T.V.;Je, Hai-Gon
    • East Asian mathematical journal
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    • v.16 no.2
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    • pp.251-266
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    • 2000
  • The problem of solution uniqueness to the task of determining unknown parameters of mathematical models from input-output observations is studied. This problem is known as structural identifiability problem. We offer a new approach for testing structural identifiability of linear state space models. The approach compares favorably with numerous methods proposed by other authors for two main reasons. First, it is formulated in obvious mathematical form. Secondly, the method does not involve unfeasible symbolic computations and thus allows to test identifiability of large-scale models. In case of non-identifiability, when there is a set of solutions to the task, we offer a method of computing functions of the unknown parameters which can be determined uniquely from input-output observations and later used as new parameters of the model. Such functions are called parametric functions capable of estimation. To develop the method of computation of these functions we use Lie group transformation theory. Illustrative example is given to demonstrate applicability of presented methods.

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소프트웨어 시험평가 모델 설계에 관한 연구(공공분야 CALS/EC 중심으로)

  • 임만택;이상호;김성용;변재정
    • Proceedings of the CALSEC Conference
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    • 1999.07a
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    • pp.193-205
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    • 1999
  • Nowadays, public domain software CALS/EC projects give their attention to the importance of test and evaluation (T&E). This article proposed a survey on T&E procedures of the international standards ISO 9000-3, ISO/IEC 9126 and ISO 14598, and of the U.S. Army pamphlet as well as that of MIL-STD-498. And features of testing tools such as their characteristics were reviewed for a reference in selecting appropriate one. Large-scale software projects often encounter with problems during T&E, when they become close to the end of development cycle. The problems generally act as a bottleneck of a project, leading to slippage of the entire schedule. This article tried a close look at the problems and solution alternatives of the T&E policy, management, and technical issues, and proposed a T&E model to support a variety of software development environment.

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Information Retrieval System : Condor (콘도르 정보 검색 시스템)

  • 박순철;안동언
    • Journal of Korea Society of Industrial Information Systems
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    • v.8 no.4
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    • pp.31-37
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    • 2003
  • This paper is a review of the large-scale information retrieval system, CONDOR. This system was developed by the consortium that consists of Chonbuk National University, Searchline Co. and Carnegie Mellon University. This system is based on the probabilistic model of information retrieval systems. The multi-language query processing, online document summarization based on query and dynamic hierarchy clustering of this system make difference of other systems. We test this system with 30 million web documents successfully.

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The prediction of train interior noise with Statistical Energy Analysis (통계적 에너지 해석법을 이용한 전동차의 실내소음 분석)

  • Lee, Seoung-Woo;Kim, Jae-Chul;Lee, Dong-Hoon;Choo, Don-Ho
    • Proceedings of the KSR Conference
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    • 2008.11b
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    • pp.1413-1419
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    • 2008
  • As the improvements of service quality is becoming an important issue the, interior noise level of a train is an important factor of comfortable ride. To reduce the interior noise level, noise sources of the train need to be removed. However, in case with a structure of large scale and multiple noise sources, an estimation of influences of major noise sources, with indentification of its traveling paths needs to be performed. In current state, to improve the interior noise reduction, consideration of sound transmission loss of the train body prior to manufacturing is usually performed. In this study, the sound transmission loss of the train body of new model train of seoul metro's line no.2 under test opeation is measured and modeling of the train body is performed. And train interior noise is predicted using the measured values.

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An Improved Deep Learning Method for Animal Images (동물 이미지를 위한 향상된 딥러닝 학습)

  • Wang, Guangxing;Shin, Seong-Yoon;Shin, Kwang-Weong;Lee, Hyun-Chang
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.01a
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    • pp.123-124
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    • 2019
  • This paper proposes an improved deep learning method based on small data sets for animal image classification. Firstly, we use a CNN to build a training model for small data sets, and use data augmentation to expand the data samples of the training set. Secondly, using the pre-trained network on large-scale datasets, such as VGG16, the bottleneck features in the small dataset are extracted and to be stored in two NumPy files as new training datasets and test datasets. Finally, training a fully connected network with the new datasets. In this paper, we use Kaggle famous Dogs vs Cats dataset as the experimental dataset, which is a two-category classification dataset.

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A Multi-objective Placement of Phasor Measurement Units Considering Observability and Measurement Redundancy using Firefly Algorithm

  • Arul jeyaraj, K.;Rajasekaran, V.;Nandha kumar, S.K.;Chandrasekaran, K.
    • Journal of Electrical Engineering and Technology
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    • v.10 no.2
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    • pp.474-486
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    • 2015
  • This paper proposes a multi-objective optimal placement method of Phasor Measurement Units (PMUs) in large electric transmission systems. It is proposed for minimizing the number of PMUs for complete system observability and maximizing measurement redundancy of the buses, simultaneously. The measurement redundancy of the bus indicates that number of times a bus is able to monitor more than once by PMUs set. A high level of measurement redundancy can maximize the system observability and it is required for a reliable power system state estimation. Therefore, simultaneous optimizations of the two conflicting objectives are performed using a binary coded firefly algorithm. The complete observability of the power system is first prepared and then, single line loss contingency condition is added to the main model. The practical measurement limitation of PMUs is also considered. The efficiency of the proposed method is validated on IEEE 14, 30, 57 and 118 bus test systems and a real and large- scale Polish 2383 bus system. The valuable approach of firefly algorithm is demonstrated in finding the optimal number of PMUs and their locations by comparing its performance with earlier works.

Passage and Adaptation of Maaji Virus in Hamster (Maaji Virus의 Hamster 계대 및 적응)

  • Kim, Yun-Cheol;Paik, Woo-Hyun;Lee, Pyung-Woo
    • The Journal of Korean Society of Virology
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    • v.26 no.1
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    • pp.67-76
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    • 1996
  • The methods that make Hantavirus grow consist of inoculation into the experimental animals and cultured cells. The cultured cells, such as Vero-E6 and A549 cells, have been usually used for isolation of the virus and the animals, such as mice and rats, are used for large scale preparation of the virus so far. Furthermore, the cell can be used to maintain the virus and assay the infectivity and the animals can be used for the experiment of viral pathogenicity and challenge for assessment of vaccine. Apodemus mice, the own natural host of the virus, has been used for challenge test of Hantaan virus. However it has been pointed out to difficult handling and breeding the animal in laboratory. Therefore, we attempted to establish a new animal model for challenge test at the time of isolation of Maaji virus which is a new hantavirus similar but distinct to Hantaan virus. In suckling hamster, the titer of Maaji virus and the lethality to mice of the virus were increased gradually in the titer and lethality through passage by intracerebral (IC) inoculation. We tried to re-adapt this brain virus to lung of weanling hamster. The brain passaged virus was inoculated into weanling hamster intramuscularly. Again, the titer of the virus in lung was also increased by continuous passage of this virus. This facts could regarded as adaptation to new environment in which the virus proliferates. To identity the virus passaged in hamster with Maaji virus, both of the virus passaged in hamster brain and lung were compared with Maaji virus (MAA-I) and Hantaan virus (HTN 76-118) by means of restriction fragment length polymorphism (RFLP) and slingle strand conformation polymophism (SSCP). As a result, we conclude that Maaji virus could be adapted successfully to weanling hamster through this passage strategy. Utilizing this adapted Maaji virus strain, hamster model is able to be used for challenge test in hantaviral vaccinology and further experiments utilizing hamster system as a rather available and convenient lab animal are expected.

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