• Steel and Composite Structures
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• v.33 no.5
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• pp.641-652
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• 2019

This paper investigates the effect of aftershocks on the seismic performance of self-centering (SC) prestressed concrete frames using the probabilistic seismic demand analysis methodology. For this purpose, a 4-story SC concrete frame and a conventional reinforced concrete (RC) frame are designed and numerically analyzed through nonlinear dynamic analyses based on a set of as-recorded mainshock-aftershock seismic sequences. The peak and residual story drifts are selected as the demand parameters. The probabilistic seismic demand models of the SC and RC frames are compared, and the SC frame is found to have less dispersion of peak and residual story drifts. The results of drift demand hazard analyses reveal that the SC frame experiences lower peak story drift hazards and significantly reduced residual story drift hazards than the RC frame when subjected to the mainshocks only or the mainshock-aftershock sequences, which demonstrates the advantages of the SC frame over the RC frame. For both the SC and RC frames, the influence of as-recorded aftershocks on the drift demand hazards is small. It is shown that artificial aftershocks can produce notably increased drift demand hazards of the RC frame, while the incremental effect of artificial aftershocks on the drift demand hazards of the SC frame is much smaller. It is also found that aftershock polarity does not influence the drift demand hazards of both the SC and RC frames.

• Structural Engineering and Mechanics
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• v.30 no.4
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• pp.445-466
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• 2008

This paper presents a novel structural damage detection method with a new damage index based on the statistical moments of dynamic responses of a structure under a random excitation. After a brief introduction to statistical moment theory, the principle of the new method is put forward in terms of a single-degree-of-freedom (SDOF) system. The sensitivity of statistical moment to structural damage is discussed for various types of structural responses and different orders of statistical moment. The formulae for statistical moment-based damage detection are derived. The effect of measurement noise on damage detection is ascertained. The new damage index and the proposed statistical moment-based damage detection method are then extended to multi-degree-of-freedom (MDOF) systems with resort to the leastsquares method. As numerical studies, the proposed method is applied to both single and multi-story shear buildings. Numerical results show that the fourth-order statistical moment of story drifts is a more sensitive indicator to structural stiffness reduction than the natural frequencies, the second order moment of story drift, and the fourth-order moments of velocity and acceleration responses of the shear building. The fourth-order statistical moment of story drifts can be used to accurately identify both location and severity of structural stiffness reduction of the shear building. Furthermore, a significant advantage of the proposed damage detection method lies in that it is insensitive to measurement noise.

• Smart Structures and Systems
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• v.18 no.3
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• pp.375-387
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• 2016

The classical Kalman filter (KF) can provide effective state estimation for structural identification and vibration control, but it is applicable only when external inputs are measured. So far, some studies of Kalman filter with unknown inputs (KF-UI) have been proposed. However, previous KF-UI approaches based solely on acceleration measurements are inherently unstable which leads to poor tracking and fictitious drifts in the identified structural displacements and unknown inputs in the presence of measurement noises. Moreover, it is necessary to have the measurements of acceleration responses at the locations where unknown inputs applied, i.e., with collocated acceleration measurements in these approaches. In this paper, it aims to extend the classical KF approach to circumvent the above limitations for general real time estimation of structural state and unknown inputs without using collocated acceleration measurements. Based on the scheme of the classical KF, an improved Kalman filter with unknown excitations (KF-UI) and without collocated acceleration measurements is derived. Then, data fusion of acceleration and displacement or strain measurements is used to prevent the drifts in the identified structural state and unknown inputs in real time. Such algorithm is not available in the literature. Some numerical examples are used to demonstrate the effectiveness of the proposed approach.

• Smart Structures and Systems
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• v.29 no.2
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• pp.287-299
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• 2022

Rather than using smartphones as seismometers with designated locations and orientations, this study proposes to employ crowds' smartphones in buildings to perform fast safety assessment of buildings. The principal advantage of using crowds' smartphones is the potential to monitor the safety of millions of buildings without hardware costs, installation labor, and long-term maintenance. This study's goal is to measure the maximum interstory drift ratios during earthquake excitation using crowds' smartphones. Beacons inside the building are required to provide the location and relevant building information for the smartphones via Bluetooth. Wi-Fi Direct is employed between nearby smartphones to conduct peer-to-peer time synchronization and exchange the acceleration data measured. An algorithm to align the orientation between nearby smartphones is proposed, and the performance of the orientation alignment, interstory drift measurement, and damage level estimation are studied numerically. Finally, the proposed approach's performance is verified using large-scale shaking table tests of a scaled steel building. The results presented in this study illustrate the potential to use crowds' smartphones with the proposed approach to record building motions during earthquakes and use those data to estimate buildings' safety based on the interstory drift ratios measured.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2747-2756
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• 2023

Reinforced Concrete (RC) shear walls are one of the civil structures in nuclear power plants to resist lateral loads such as earthquakes and wind loads effectively. Risk-informed and performance-based regulation in the nuclear industry requires considering possible accidents and determining desirable performance on structures. As a result, rather than predicting only the ultimate capacity of structures, the prediction of performances on structures depending on different damage states or various accident scenarios have increasingly needed. This study aims to develop machine-learning models predicting drifts of the RC shear walls according to the damage limit states. The damage limit states are divided into four categories: the onset of cracking, yielding of rebars, crushing of concrete, and structural failure. The data on the drift of shear walls at each damage state are collected from the existing studies, and four regression machine-learning models are used to train the datasets. In addition, the bagging ensemble method is applied to improve the accuracy of the individual machine-learning models. The developed models are to predict the drifts of shear walls consisting of various cross-sections based on designated damage limit states in advance and help to determine the repairing methods according to damage levels to shear walls.

• Journal of Distribution Science
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• v.21 no.9
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• pp.103-114
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• 2023

Purpose: This paper aims to assess psychological heuristics' effectiveness on cumulative returns after significant stock price changes. Specifically, it compares availability and anchoring heuristics' empirical validity due to conflicting stock return predictions. Research Design, Data, and Methodology: This paper analyzes stock price changes of Korean distribution industry stocks in the KOSPI market from January 2004 to July 2022, where daily fluctuations exceed 10%. It evaluates availability heuristics using daily KOSPI index changes and tests anchoring heuristics using 52-week high and low stock prices as reference points. Results: As a result of the empirical analysis, stock price reversals did not consistently appear alongside changes in the daily KOSPI index. By contrast, stock price drifts consistently appeared around the 52-week highest stock price and 52-week lowest stock price. The result of the multiple regression analysis which controlled for both company-specific and event-specific variables supported the anchoring heuristics. Conclusions: For stocks related to the Korean distribution industry in the KOSPI market, the anchoring heuristics theory provides a consistent explanation for stock returns after large-scale stock price fluctuations that initially appear to be random movements.

• Structural Engineering and Mechanics
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• v.88 no.5
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• pp.463-480
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• 2023

The buckling-restrained braced frames with eccentric configurations (BRBF-Es) exhibit stable cyclic behavior and possess a high energy absorption capacity. Additionally, they offer architectural advantages for incorporating openings, much like Eccentrically Braced Frames (EBFs). However, studies have indicated that significant residual drifts occur in this system when subjected to earthquakes at the Maximum Considered Earthquake (MCE) hazard level. Consequently, in order to mitigate these residual drifts, it is recommended to employ self-centering systems alongside the BRBF-E system. In our current research, we propose the utilization of the Direct Displacement-Based Seismic Design method to determine the design base shear for a hybrid system that combines BRBF with an eccentric configuration and a self-centering frame. Furthermore, we present a methodology for designing the individual components of this composite system. To assess the effectiveness of this design approach, we designed 3-, 6-, and 9-story buildings equipped with the BRBF-E-SCF system and developed finite element models. These models were subjected to two sets of ground motions representing the Maximum Considered Earthquake (MCE) and Design Basis Earthquake (DBE) seismic hazard levels. The results of our study reveal that although the combined system requires a higher amount of steel material compared to the BRBF-E system, it substantially reduces residual drift. Furthermore, the combined system demonstrates satisfactory performance in terms of story drift and ductility demand.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.875-888
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• 2013

The researches have recently progressed toward the use of the superelastic shape memory alloys (SMAs) to develop new smart control systems that reduce permanent deformation occurring due to severe earthquake events and that automatically recover original configuration. The superelastic SMA materials are unique metallic alloys that can return to undeformed shape without additional heat treatments only after the removal of applied loads. Once the superelastic SMA materials are thus installed at the place where large deformations are likely to intensively occur, the structural system can make the best use of recentering capabilities. Therefore, this study is intended to propose new buckling-restrained braced frames (BRBFs) with superelastic SMA bracing systems. In order to verify the performance of such bracing systems, 6-story braced frame buildings were designed in accordance with the current design specifications and then nonlinear dynamic analyses were performed at 2D frame model by using seismic hazard ground motions. Based on the analysis results, BRBFs with innovative SMA bracing systems are compared to those with conventional steel bracing systems in terms of peak and residual inter-story drifts. Finally, the analysis results show that new SMA bracing systems are very effective to reduce the residual inter-story drifts.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.889-894
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• 1993

This paper presents a robust adaptive control scheme based on the Lyapunov design for robot manipulators subjected to inertial parameter uncertainties and bounded torque disturbances. The scheme is a modified version of the adaptive computed torque method which adopts a dead zone into the adaptation mechanism so as to avoid parameter drifts by disturbances. It is shown via stability analysis and computer simulations that all the signals in the overall adaptive system are bounded and tracking errors lie within a prespecified bound.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.503-507
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• 1989

A new decentralized adaptive controller design is proposed. In large scale interconnected system with unknown parameters, nonlinearities and bounded disturbances, even though the interconnection is weak, the controller parameter drifts due to the interconnection, so the decentralized adaptive controller comes to be unstable. The proposed new decentralized adaptive controller guarantees exponential convergence of tracking and parameter errors to residual sets which depend on the bound for the local disturbances and interconnections as well as on some arbitrary design parameters.