• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1998.10a
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• pp.93-99
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• 1998

Mathematical model can be obtained by physical law or engineering theory. However it is always incomplete expression of the real system. In active controls to suppress vibration due to earthquake or wind load, modeling errors can often cause the problems of instability and performance degradation. In this paper, robust optimal controller design method using H$\infty$ control theory is developed for the systems which have uncertain natural frequency and design constraints. Numerical results show that the proposed H$\infty$ controller can avoid the performance degradation due to several errors and has better performance than conventional LQR method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.3
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• pp.898-906
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• 1991

본 연구에서는 입경부식법에 의한 재질열화 평가법의 표준화에 연구목적을 두 고, 고온부재의 열화에 따른 조직의 특성변화를 관찰하였다.

• 한국전기화학회:학술대회논문집
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• 2000.10a
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• pp.32-32
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• 2000

• Proceedings of the KWS Conference
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• 1999.05a
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• pp.81-83
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• 1999

• Proceedings of the KWS Conference
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• 1999.05a
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• pp.88-90
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• 1999

• Smart Structures and Systems
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• v.16 no.5
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• pp.835-851
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• 2015

This paper presents theoretical and experimental evaluation of the structural health monitoring (SHM) capability of piezoelectric wafer active sensors (PWAS) at elevated temperatures. This is important because the technologies for structural sensing and monitoring need to account for the thermal effect and compensate for it. Permanently installed PWAS transducers have been One of the extensively employed sensor technologies for in-situ continuous SHM. In this paper, the electro-mechanical impedance spectroscopy (EMIS) method has been utilized as a dynamic descriptor of PWAS behavior and as a high frequency standing wave local modal technique. Another SHM technology utilizes PWAS as far-field transient transducers to excite and detect guided waves propagating through the structure. This paper first presents how the EMIS method is used to qualify and quantify circular PWAS resonators in an increasing temperature environment up to 230 deg C. The piezoelectric material degradation with temperature was investigated and trends of variation with temperature were deduced from experimental measurements. These effects were introduced in a wave propagation simulation software called Wave Form Revealer (WFR). The thermal effects on the substrate material were also considered. Thus, the changes in the propagating guided wave signal at various temperatures could be simulated. The paper ends with summary and conclusions followed by suggestions for further work.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2009.11a
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• pp.443-446
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• 2009

In this study, a series of degradation test for structural adhesives was performed to investigate the possibility of replacement of the alternative adhesives to the conventional adhesives. Four types of the adhesives were exposed to combined environmental conditions over 1000 hours at an accelerated aging tester, which can simulate natural weather conditions such temperature, moisture and ultraviolet. Mechanical and chemical properties of the adhesives were evaluated through material testing system and FT/IR spectrometer. According to the results, the conventional adhesives can be replaced by the alternative adhesives because the alternative adhesives were more stable to environmental conditions rather than the conventional adhesives.

• Journal of Korean Association for Spatial Structures
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• v.24 no.2
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• pp.83-90
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• 2024

Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.

• Journal of Distribution Science
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• v.22 no.8
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• pp.37-53
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• 2024

Purpose: Global warming is increasingly aggravated by environmental degradation, a challenge that can be mitigated through strategic logistic policies. This study introduces the dynamics of green trade in environmental goods for the Organisation of Islamic Cooperation (OIC) nations. It is a region known for its high environmental degradation, political risk and instability. This study examines how technological innovation and political factors influence the geographic distribution of green trade among OIC nations from 1994 to 2021 using the structural gravity model. The COVID-19 pandemic further emphasised the need for resilient and eco-friendly approaches. Research design, data and methodology: The main objective of the study is to analyse the impact of technological innovation along with scrutinising political determinants of green trade in the OIC region from 1994 to 2021 using the structural gravity model. Results: The results reveal geographic proximity, RTA, and innovation significantly boost green trade. Similarly, OIC's green trade performance has been impeded by high political risk and instability. Conclusions: The research recommends fostering political stability, and conducting further research using longitudinal studies and machine learning to strengthen the understanding of innovation and green trade in the OIC. This will inform policies for sustainable economic growth through green trade.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.12 no.2
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• pp.50-57
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• 2016

The study presents structural integrity assessment of ductility degradation of a baffle former assembly by performing finite element analysis considering real loading conditions and stress triaxiality. Variations of fracture strain curves of type 304 austenitic stainless steel with stress triaxiality are derived based on the previous study results. Temperature distributions during normal operation such as heat-up, steady state, and cool-down are calculated via finite element temperature analysis considering gamma heating and heat convection with reactor coolant. Variations of stress and strain state during long operation period are also calculated by performing sequentially coupled temperature-stress analysis. Fracture strain is derived by using the fracture curve and the stress triaxility. Finally, variations of ductility degradation damage indicator with the fracture strain and the equivalent inelastic strain are investigated. It is found that maximum value of the ductility degradation damage index continuously increases and becomes 0.4877 at 40 EFPYs. Also, the maximum value occurs at top and middle inner parts of the baffle former assembly before and after 20 EFPYs, respectively.