A dual Kalman filter approach for state estimation via output-only acceleration measurements

This paper presents some of the oral discussion by the author and others at the 2005 Annual Meeting of the Los Angeles Tall Buildings Structural Design Council. It also includes additional opinions added by the author after the annual meeting. These opinions address the development of a new building code for tall buildings and where the non-structural engineering decision makers can and must make contributions. It also addresses the very important topic of quality control. Copyright © 2005 John Wiley & Sons, Ltd.

The structural design of tall and special buildings

Physics-guided convolutional neural network (PhyCNN) for data-driven seismic response modeling

Changing environmental conditions, especially temperature, have been observed to be a complicated factor affecting vibration properties, such as frequencies, mode shapes, and damping, of civil structures. This paper reviews technical literature concerning variations in vibration properties of civil structures under changing temperature conditions. Most of these studies focus on variations in frequencies of bridge structures, with some studies on variations in mode shapes and damping and other types of structures. Statistical approaches to correlation between temperature and frequencies are also reviewed. A quantitative analysis shows that variations in material modulus under different temperatures are the major cause of the variations in vibration properties. A comparative study on different structures made of different materials is carried out in laboratory. Two real structures, the 1,377-m main span Tsing Ma Suspension Bridge and the 600-m-tall Guangzhou New Television Tower, are examined. Both laboratory experiments and field testing, regardless of different construction materials used and structural types, verify the quantitative analysis. Variations in frequencies of reinforced concrete structures are much more significant than those of steel structures.

/pdf/temperature-effect-on-vibration-properties-of-civil-d1j0kj7jl8.pdf

Temperature effect on vibration properties of civil structures: a literature review and case studies

Department of Civil Engineering, State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian, China Department of Civil, Environmental, and Geomatic Engineering, ETH Zurich, Zurich, Switzerland School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea Department of Civil, Construction and Environmental Engineering, Iowa State University, Ames, Iowa, USA Department of Intelligent Technologies, Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland

Recent progress and future trends on damage identification methods for bridge structures

Model updating of dynamical systems has been attracting much attention because it has a very wide range of applications in aerospace, civil, and mechanical engineering, etc. Many methods were developed and there has been substantial development in Bayesian methods for this purpose in the recent decade. This article introduces some state-of-the-art work. It consists of two main streams of model updating, namely model updating using response time history and model updating using modal measurements. The former one utilizes directly response time histories for the identification of uncertain parameters. In particular, the Bayesian time-domain approach, Bayesian spectral density approach and Bayesian fast Fourier transform approach will be introduced. The latter stream utilizes modal measurements of a dynamical system. The method introduced here does not require a mode matching process that is common in other existing methods. Afterwards, discussion will be given about the relationship among model complexity, data fitting capability and robustness. An application of a 22-story building will be presented. Its acceleration response time histories were recorded during a severe typhoon and they are utilized to identify the fundamental frequency of the building. Furthermore, three methods are used for analysis on this same set of measurements and comparison will be made.

Bayesian Methods for Updating Dynamic Models

Ambient interference in long-term monitoring of buildings

Summary
In this paper, a Bayesian sequential sensor placement algorithm, based on the robust information entropy, is proposed for multi-type of sensors. The presented methodology has two salient features. It is a holistic approach such that the overall performance of various types of sensors at different locations is assessed. Therefore, it provides a rational and effective strategy to design the sensor configuration, which optimizes the use of various available resources. This sequential algorithm is very efficient due to its Bayesian nature, in which prior distribution can be incorporated. Therefore, it avoids the possible unidentifiability problem encountered in a sequential process, which starts with small number of sensors. The proposed algorithm is demonstrated using a shear building and a lattice tower with consideration of up to four types of sensors. Copyright © 2014 John Wiley & Sons, Ltd.

Efficient Bayesian sensor placement algorithm for structural identification: a general approach for multi‐type sensory systems

Online updating and uncertainty quantification using nonstationary output-only measurement

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.

/pdf/structural-health-monitoring-of-canton-tower-using-bayesian-1aphfpus3h.pdf

Structural health monitoring of Canton Tower using Bayesian framework

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