Structural health monitoring of Canton Tower using Bayesian framework

Kuok, Sin-Chi,Yuen, Ka-Veng Techno-Press 2012 Smart Structures and Systems, An International Jou Vol.10 No.4

This paper reports the structural health monitoring benchmark study results for the Canton Tower using Bayesian methods. In this study, output-only modal identification and finite element model updating are considered using a given set of structural acceleration measurements and the corresponding ambient conditions of 24 hours. In the first stage, the Bayesian spectral density approach is used for output-only modal identification with the acceleration time histories as the excitation to the tower is unknown. The modal parameters and the associated uncertainty can be estimated through Bayesian inference. Uncertainty quantification is important for determination of statistically significant change of the modal parameters and for weighting assignment in the subsequent stage of model updating. In the second stage, a Bayesian model updating approach is utilized to update the finite element model of the tower. The uncertain stiffness parameters can be obtained by minimizing an objective function that is a weighted sum of the square of the differences (residuals) between the identified modal parameters and the corresponding values of the model. The weightings distinguish the contribution of different residuals with different uncertain levels. They are obtained using the Bayesian spectral density approach in the first stage. Again, uncertainty of the stiffness parameters can be quantified with Bayesian inference. Finally, this Bayesian framework is applied to the 24-hour field measurements to investigate the variation of the modal and stiffness parameters under changing ambient conditions. Results show that the Bayesian framework successfully achieves the goal of the first task of this benchmark study.

Evaluation of simulation-based ultrasound course for pediatricians: a starting point for future training curriculum

Kuok, Chon In,Leung, Avis Siu Ha,Lee, Jonan Chun Yin,Chan, Winnie Kwai Yu The Korean Pediatric Society 2022 Clinical and Experimental Pediatrics (CEP) Vol.65 No.1

Catalytic Role of Ge in Highly Reversible GeO₂/Ge/C Nanocomposite Anode Material for Lithium Batteries

Seng, Kuok Hau,Park, Mi-hee,Guo, Zai Ping,Liu, Hua Kun,Cho, Jaephil American Chemical Society 2013 Nano letters Vol.13 No.3

<P>GeO<SUB>2</SUB>/Ge/C anode material synthesized using a simple method involving simultaneous carbon coating and reduction by acetylene gas is composed of nanosized GeO<SUB>2</SUB>/Ge particles coated by a thin layer of carbon, which is also interconnected between neighboring particles to form clusters of up to 30 μm. The GeO<SUB>2</SUB>/Ge/C composite shows a high capacity of up to 1860 mAh/g and 1680 mAh/g at 1 C (2.1 A/g) and 10 C rates, respectively. This good electrochemical performance is related to the fact that the elemental germanium nanoparticles present in the composite increases the reversibility of the conversion reaction of GeO<SUB>2</SUB>. These factors have been found through investigating and comparing GeO<SUB>2</SUB>/Ge/C, GeO<SUB>2</SUB>/C, nanosized GeO<SUB>2</SUB>, and bulk GeO<SUB>2</SUB>.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/nalefd/2013/nalefd.2013.13.issue-3/nl304716e/production/images/medium/nl-2012-04716e_0008.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/nl304716e'>ACS Electronic Supporting Info</A></P>

Structural health monitoring of Canton Tower using Bayesian framework

Sin-Chi Kuok,Ka-Veng Yuen 국제구조공학회 2012 Smart Structures and Systems, An International Jou Vol.10 No.4

This paper reports the structural health monitoring benchmark study results for the Canton Tower using Bayesian methods. In this study, output-only modal identification and finite element model updating are considered using a given set of structural acceleration measurements and the corresponding ambient conditions of 24 hours. In the first stage, the Bayesian spectral density approach is used for output-only modal identification with the acceleration time histories as the excitation to the tower is unknown. The modal parameters and the associated uncertainty can be estimated through Bayesian inference. Uncertainty quantification is important for determination of statistically significant change of the modal parameters and for weighting assignment in the subsequent stage of model updating. In the second stage, a Bayesian model updating approach is utilized to update the finite element model of the tower. The uncertain stiffness parameters can be obtained by minimizing an objective function that is a weighted sum of the square of the differences (residuals) between the identified modal parameters and the corresponding values of the model. The weightings distinguish the contribution of different residuals with different uncertain levels. They are obtained using the Bayesian spectral density approach in the first stage. Again, uncertainty of the stiffness parameters can be quantified with Bayesian inference. Finally, this Bayesian framework is applied to the 24- hour field measurements to investigate the variation of the modal and stiffness parameters under changing ambient conditions. Results show that the Bayesian framework successfully achieves the goal of the first task of this benchmark study.

The antecedents of in-­service teacher burnout:A study of their occupational health and perception

Angus C. H. Kuok,Stacy M. I. Lam 한국교육개발원 2018 KEDI Journal of Educational Policy Vol.15 No.2

As Macau is one of the cities with high students’ grade retention rate, the local teachers, therefore, have a considerably heavy workload to prepare the students to achieve the requirements of a particular academic setting. This study examined 173 full-time in-service secondary school teachers at Macau via questionnaire. The result shows in-service teachers feel emotional exhaustion in teaching students. However, teachers perceive their competence in teaching and would not depersonalize the students as an object. Moreover, significant variations are found among the three factors of burnout for teachers. That is, teachers experience higher emotional exhaustion than reduced personal accomplishment and depersonalisation. By reviewing previous studies about teachers’ burnout as compared to the present findings, an upward trend of teachers’ emotional exhaustion is suggested. The increase of emotional exhausting could be related to the launch of new policies in terms of enhancing the professionalism of teachers. Needs for achievement, which is negatively correlated to burnout, is found to be a powerful predictor. Organisational socialisation in terms of training, understanding, co-worker support, and future prospects are discovered to have negative correlations to burnout. Particularly, understanding and future prospect are found to be the negative predictors of reduced personal accomplishment and emotional exhaustion, respectively. The results and implications are interpreted for teachers’ professional development and school administration.

HEAT TRANSFER MEASUREMNT DURING DROPWISE CONDENSATION USING MICRO/NA NO-SCALE POROUS SURFACE

Sangsoo Lee,Kuok Cheng,Viljar Palmrel,Kwang Kim,Hyungkee Yoon 한국신재생에너지학회 2012 AFORE Vol.2012 No.-

DROPWISE CONDENSATION HEAT TRANSFER

Kwang J. KIM,Kuok CHENG 한국신재생에너지학회 2014 AFORE Vol.2014 No.-

Effects of Co-current and Cross Flows on Circular Enhanced Gravity Plate Separator Efficiencies

Lock Hei Ngu,Puong Ling Law,Kien Kuok Wong 대한환경공학회 2014 Environmental Engineering Research Vol.19 No.2

This study compares the effects of flow on oil and suspended solids removal efficiencies in circular enhanced gravity plate separator equipped with coalescence medium. Coalescence medium acts to capture rising oil droplets and settling solid particles and assist in the coalescence of oil and coagulation of solid. The circular separator uses an up flow center-feed perforated-pipe distributor as the inlet. The co-current flow is achieved using 4 increasing sizes of frustum, whereas cross flow uses inclined coalescence plates running along the radius of the separator. The different arrangement gave the cross flow separator a higher coalescence plan area per operational volume, minimal and constant travelling distance for the oil droplets and particles, lower retention time, and higher operational flowrate. The cross flow separator exhibited 6.04% and 13.16% higher oil and total suspended solids removal efficiencies as compared to co-current flow.

Online estimation of noise parameters for Kalman filter

Yuen, Ka-Veng,Liang, Peng-Fei,Kuok, Sin-Chi Techno-Press 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.47 No.3

A Bayesian probabilistic method is proposed for online estimation of the process noise and measurement noise parameters for Kalman filter. Kalman filter is a well-known recursive algorithm for state estimation of dynamical systems. In this algorithm, it is required to prescribe the covariance matrices of the process noise and measurement noise. However, inappropriate choice of these covariance matrices substantially deteriorates the performance of the Kalman filter. In this paper, a probabilistic method is proposed for online estimation of the noise parameters which govern the noise covariance matrices. The proposed Bayesian method not only estimates the optimal noise parameters but also quantifies the associated estimation uncertainty in an online manner. By utilizing the estimated noise parameters, reliable state estimation can be accomplished. Moreover, the proposed method does not assume any stationarity condition of the process noise and/or measurement noise. By removing the stationarity constraint, the proposed method enhances the applicability of the state estimation algorithm for nonstationary circumstances generally encountered in practice. To illustrate the efficacy and efficiency of the proposed method, examples using a fifty-story building with different stationarity scenarios of the process noise and measurement noise are presented.

Investigation of modal identification and modal identifiability of a cable-stayed bridge with Bayesian framework

Ka-Veng Yuen,Sin-Chi Kuok 국제구조공학회 2016 Smart Structures and Systems, An International Jou Vol.17 No.3

In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.