Browsing by Author "Lin, Tzu Kang"

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Optimal Distribution of Damping Coefficients for Viscous Dampers in Buildings
(2017-05-01)
Lin, Tzu Kang
;
Hwang, Jenn Shin
;
Chen, Kuan Hui
;
土木工程學系
;
Department of Civil Engineering
Design guidelines for implementing viscous dampers to buildings have been broadly included in seismic design codes worldwide. Although the relationship between the damping coefficient of viscous dampers and the added damping ratio to the structure has been theoretically studied, the process of distributing the damping coefficient onto each story of a building has not been regulated by the codes. For practical applications, some distribution methods have been previously proposed. However, no comparison has been made between these proposed methods considering the controllability and design economy. In this paper, two search methods based on the genetic algorithms (GAs) are adopted to examine the optimal distribution of damping coefficients. The results are then compared with a variety of existing distribution methods. A comparison is made for the distribution methods assuming the same added damping ratio for the structure. Three two-dimensional frames are adopted in the comparison: a regular moment frame, a moment frame with a soft-story, and a setback building. The results indicated that similar seismic response reduction can be achieved by using different distribution methods if the supplemental damping ratio is the same, while the optimal story damping coefficient can be obtained by using the proposed optimization method. Moreover, the "story shear strain energy to efficient stories" (SSSEES) method, among others, offers advantages in terms of seismic reduction efficiency, economical design, and practical application simplicity.
Real-time seismic structural response prediction system based on support vector machine
(2020-02-01)
Lin, Kuang Yi
;
Lin, Tzu Kang
;
Lin, Yo
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土木工程學系
;
Department of Civil Engineering
Floor acceleration plays a major role in the seismic design of nonstructural components and equipment supported by structures. Large floor acceleration may cause structural damage to or even collapse of buildings. For precision instruments in high-tech factories, even small floor accelerations can cause considerable damage in this study. Six P-wave parameters, namely the peak measurement of acceleration, peak measurement of velocity, peak measurement of displacement, effective predominant period, integral of squared velocity, and cumulative absolute velocity, were estimated from the first 3 s of a vertical ground acceleration time history. Subsequently, a new predictive algorithm was developed, which utilizes the aforementioned parameters with the floor height and fundamental period of the structure as the new inputs of a support vector regression model. Representative earthquakes, which were recorded by the Structure Strong Earthquake Monitoring System of the Central Weather Bureau in Taiwan from 1992 to 2016, were used to construct the support vector regression model for predicting the peak floor acceleration (PFA) of each floor. The results indicated that the accuracy of the predicted PFA, which was defined as a PFA within a one-level difference from the measured PFA on Taiwan's seismic intensity scale, was 96.96%. The proposed system can be integrated into the existing earthquake early warning system to provide complete protection to life and the economy.
Three-dimensional structural health monitoring based on multiscale cross-sample entropy
(2017-06-01)
Lin, Tzu Kang
;
Tseng, Tzu Chi
;
Lainez, Ana G.
;
土木工程學系
;
Department of Civil Engineering
A three-dimensional structural health monitoring (SHM) system based on multiscale entropy (MSE) and multiscale cross-sample entropy (MSCE) is proposed in this paper. The damage condition of a structure is rapidly screened through MSE analysis by measuring the ambient vibration signal on the roof of the structure. Subsequently, the vertical damage location is evaluated by analyzing individual signals on different floors through vertical MSCE analysis. The results are quantified using the vertical damage index (DI). Planar MSCE analysis is applied to detect the damage orientation of damaged floors by analyzing the biaxial signals in four directions on each damaged floor. The results are physically quantified using the planar DI. With progressive vertical and planar analysis methods, the damaged floors and damage locations can be accurately and efficiently diagnosed. To demonstrate the performance of the proposed system, performance evaluation was conducted on a three-dimensional seven-story steel structure. According to the results, the damage condition and elevation were reliably detected. Moreover, the damage location was efficiently quantified by the DI. Average accuracy rates of 93% (vertical) and 91% (planar) were achieved through the proposed DI method. A reference measurement of the current stage can initially launch the SHM system; therefore, structural damage can be reliably detected after major earthquakes.