• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.527-534
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• 2006

A real-time hybrid method, in which the experimental implementation and the numerical computation of a structure are simultaneously carried out in real-time and combined on-line, has been used as a dynamic testing technique of structure to investigate its dynamic behaviors. In this paper, an experimental hybrid method, which implements the earthquake response control of a building structure with a TLD by using only a TLD as an experimental part, is proposed and is experimentally verified through a shaking table test. In the proposed methodology, the whole building structure with a TLD is divided into the upper TLD and the lower structural parts as experimental and numerical substructures, respectively. At the moment, the control force acting between their interface is measured from the experimental TLD with shear-type load-cell which is mounted on shaking table. Shaking table vibrates the upper experimental TLD with the response calculated from the numerical substructure, which is subjected to the excitations of the measured interface control force at its top story and an earthquake input at its base. The experimental results show that the conventional method, in which both a TLD and a building model are physically manufactured and are tested, can be replaced by the proposed methodology with a simple experimental installation and a good accuracy for evaluating the control performance of a TLD.

• Journal of Power Electronics
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• v.16 no.1
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• pp.217-226
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• 2016

A new method is proposed based on a hidden Markov model (HMM) to estimate and analyze battery states of health. Battery system health states are defined according to the relationship between internal resistance and lifetime of cells. The source data (terminal voltages and currents) can be obtained from vehicular battery models. A characteristic value extraction method is proposed for HMM. A recognition framework and testing datasets are built to test the estimation rates of different states. Test results show that the estimation rates achieved based on this method are above 90% under single conditions. The method achieves the same results under hybrid conditions. We can also use the HMMs that correspond to hybrid conditions to estimate the states under a single condition. Therefore, this method can achieve the purpose of the study in estimating battery life states. Only voltage and current are used in this method, thereby establishing its simplicity compared with other methods. The batteries can also be tested online, and the method can be used for online prediction.

• Progress in Superconductivity and Cryogenics
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• v.25 no.4
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• pp.28-31
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• 2023

This study presents a comprehensive procedure for the low cycle fatigue test of ultrasonically welded (UW) coated conductor (CC) lap-joints. The entire process is examined in detail, from the robust fabrication of the UW REBCO CC joints to the reliability testing under a low number of repeated cycle fatigue conditions. A continuous I_c measurement system enables real-time monitoring of I_c variations throughout the fatigue tests. The study aims to provide a step-by-step procedure that involves joint fabrication, electromechanical property (EMP) tests under uniaxial tension for stress level determination, and subsequent low-cycle fatigue tests. The joints are fabricated using a hybrid method that combines UW with adding In-Sn soldering, achieving a flux-free hybrid welding approach (UW-HW flux-free). The selected conditions for the low cycle fatigue tests include a stress ratio of R=0.1 and a frequency of 0.02 Hz. The results reveal some insights into the fatigue behavior, irreversible changes, and cumulative damage in the CC joints.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.4 s.74
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• pp.419-427
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• 2006

In this paper, an experimental real-time hybrid method, which implements the earthquake response control of a building structure with a TLD(Tuned Liquid Damper) by using only a TLD as an experimental part, is proposed and is experimentally verified through a shaking table test. In the proposed methodology, the whole building structure with a TLD is divided into the upper TLD and the lower structural parts as experimental and numerical substructures, respectively. The control force acting between their interface is measured with a shear-type load-cell which is mounted on the shaking table. The shaking table vibrates the upper experimental TLD with the response calculated from the numerical substructure, which is subjected to the excitations of the measured interface control force at its top story and an earthquake input at its base. The experimental results show that the conventional method, in which both a TLD and a building structure model are physically manufactured and are tested, can be replaced by the proposed methodology with a simple experimental installation and a good accuracy for evaluating the control performance of a TLD.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4072-4079
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• 2021

This article presents a study on the state-of-the-art methods for automated radioactive material detection and identification, using gamma-ray spectra and modern machine learning methods. The recent developments inspired this in deep learning algorithms, and the proposed method provided better performance than the current state-of-the-art models. Machine learning models such as: fully connected, recurrent, convolutional, and gradient boosted decision trees, are applied under a wide variety of testing conditions, and their advantage and disadvantage are discussed. Furthermore, a hybrid model is developed by combining the fully-connected and convolutional neural network, which shows the best performance among the different machine learning models. These improvements are represented by the model's test performance metric (i.e., F1 score) of 93.33% with an improvement of 2%-12% than the state-of-the-art model at various conditions. The experimental results show that fusion of classical neural networks and modern deep learning architecture is a suitable choice for interpreting gamma spectra data where real-time and remote detection is necessary.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.2
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• pp.217-225
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• 2007

This paper proposes the real-time hybrid shaking table testing methods to simulate the dynamic behavior of a soil-structure interaction system with dynamic soil stiffness by using only a structure model as the physical specimen and verifies their effectiveness for experimental implementation. Experimental methodologies proposed in this paper adopt such a way that absolute accelerations measured from the superstructure and shaking table are feedback to the shaking table controller, and then the shaking table is driven by the calculated motion of the absolute acceleration (acceleration feedback method) or the absolute velocity (velocity feedback method) of foundation that is required to simulate the dynamic behavior of a whole soil-structure interaction system. The shaking table test is implemented by reflecting the dynamic soil stiffness, which are differently approximated from the theoretical one depending on the feedback methods, on the shaking table controller to calculate soil part. The effectiveness of the proposed experimental methods is verified by comparing the response measured from the test on a foundation-fixed structural model and that obtained from the experiment of a soil-interaction system under the consideration in this paper and by matching the dynamic soil stiffness reflected on the shaking table controller with that identified using the experimentally measured data.

• Smart Structures and Systems
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• v.26 no.4
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• pp.495-506
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• 2020

Monitoring of complex processes faces several challenges mainly due to the lack of relevant sensory information or insufficient elaborated decision-making strategies. These challenges motivate researchers to adopt complex data processing and analysis in order to improve the process representation. This paper presents the development and implementation of quality monitoring framework based on a model-driven approach using embedded artificial intelligence strategies. In this work, the strategies are applied to the supervision of a microfabrication process aiming at showing the great performance of the framework in a very complex system in the manufacturing sector. The procedure involves two methods for modelling a representative quality variable, such as surface roughness. Firstly, the hybrid incremental modelling strategy is applied. Secondly, a generalized fuzzy clustering c-means method is developed. Finally, a comparative study of the behavior of the two models for predicting a quality indicator, represented by surface roughness of manufactured components, is presented for specific manufacturing process. The manufactured part used in this study is a critical structural aerospace component. In addition, the validation and testing are performed at laboratory and industrial levels, demonstrating proper real-time operation for non-linear processes with relatively fast dynamics. The results of this study are very promising in terms of computational efficiency and transfer of knowledge to manufacturing industry.

• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.4
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• pp.413-420
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• 2020

In this study, a new lab-scale test equipment was developed to evaluate the variation of concrete workability after pumping. The equipment was designed to simulate the pressure and shearing applied to concrete during actual pumping. In order to examine the feasibility of evaluating variation of concrete workability through lab-scale test equipment, real-scale pumping tests and lab-scale tests were performed together. The design strength of concrete used in the both tests was 24, 35, and 60MPa, and the length of pipe used in pumping tests was 130, 304, and 518m. The lab-scale tests were performed in consideration of actual pumping conditions(pressure, shearing, and pumping duration time). The workability(slump or slum flow) of concrete was measured before test, after the pumping test, and after lab-scale test. In all tests, workability of all concrete mixtures decreased. In addition, the results of both tests were measured greatly similarly.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.590-596
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• 2020

In the island areas where system connection with the commercial power grid is difficult, it is quite important to find a method to efficiently manage energy produced with independent microgrids. In this paper, a prosumer management system for P2P power transaction was realized through the testing the power meter and the response rate of the collected data for the power produced in the small-scale microgrids in which hybrid models of solar power and wind power were implemented. The power network of the microgrid prosumer was composed of mesh structure and the P2P power transaction was tested through the power meter and DC power transmitter in the off-grid sites which were independently constructed in three places. The measurement values of the power meter showed significant results of voltage (average): 380V + 0.9V, current (average): + 0.01A, power: 1000W (-1W) with an error range within ±1%. Stabilization of the server was also confirmed with the response rate of 0.32 sec. for the main screen, 2.61 sec. for the cumulative power generation, and 0.11 sec for the power transaction through the transmission of 50 data in real time. Therefore, the proposed system was validated as a P2P power transaction system that can be used as an independent network without transmitted by Korea Electric Power Corporation (KEPCO).