Time-domain modal identification of bridges based on uncertainty quantification

2021 ◽  
pp. 979-986
Author(s):  
Y. Goi ◽  
C.W. Kim
Keyword(s):  
Uncertainty Quantification ◽  
Time Domain ◽  
Modal Identification

scholarly journals A Short Review of FDTD-Based Methods for Uncertainty Quantification in Computational Electromagnetics

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Theodoros T. Zygiridis
Keyword(s):  
Finite Difference ◽  
Uncertainty Quantification ◽  
Time Domain ◽  
Finite Difference Time Domain ◽  
Computational Electromagnetics ◽  
Short Review ◽  
Electromagnetic Problems ◽  
Difference Time

We provide a review of selected computational methodologies that are based on the deterministic finite-difference time-domain algorithm and are suitable for the investigation of electromagnetic problems involving uncertainties. As it will become apparent, several alternatives capable of performing uncertainty quantification in a variety of cases exist, each one exhibiting different qualities and ranges of applicability, which we intend to point out here. Given the numerous available approaches, the purpose of this paper is to clarify the main strengths and weaknesses of the described methodologies and help the potential readers to safely select the most suitable approach for their problem under consideration.

Vector Triggering Random Decrement for High Identification Accuracy

1998 ◽  
Vol 120 (4) ◽  
pp. 970-975 ◽  
Author(s):  
S. R. Ibrahim ◽  
J. C. Asmussen ◽  
R. Brincker
Keyword(s):  
Time Domain ◽  
Modal Identification ◽  
Identification Accuracy ◽  
Mode Shapes ◽  
Phase Information ◽  
Free Response ◽  
Identification Methods ◽  
Random Decrement ◽  
Identification Technique ◽  
Triggering Conditions

Using the Random Decrement (RD) technique to obtain free response estimates and combining this with time domain modal identification methods to obtain the poles and the mode shapes is acknowledged as a fast and accurate way of analysing measured responses of structures subject to ambient loads. When commonly accepted triggering conditions are used however, the user is restricted to use a combination of auto RD and cross RD functions with high noise contents on the cross RD functions. Use of the auto RD functions alone causes the loss of phase information and thus the possibility of estimating mode shapes. In this paper a new algorithm based on pure auto triggering is suggested. Equivalent auto RD functions are estimated for all channels to obtain functions with a minimum of noise, using a vector triggering condition that preserves phase information, and thus, allows for estimation of both poles and mode shapes. The proposed technique (VRD) is compared with the traditional RD technique by evaluating modal parameters extracted from the RD and the VRD functions using ITD identification technique on simulated and experimentally obtained data.

Mass, Stiffness, and Damping Matrix Identification: An Integrated Approach

1992 ◽  
Vol 114 (3) ◽  
pp. 358-363 ◽  
Author(s):  
M. J. Roemer ◽  
D. J. Mook
Keyword(s):  
Steady State ◽  
Time Domain ◽  
Estimation Method ◽  
Integrated Approach ◽  
Modal Identification ◽  
Mode Shapes ◽  
Steady State Condition ◽  
Frequency Domain Techniques ◽  
Identification Techniques ◽  
Stiffness And Damping

Accurate estimates of the mass, stiffness, and damping characteristics of a structure are necessary for determining the control laws best suited for active control methodologies. There are several modal identification techniques available for determining the frequencies, damping ratios, and mode shapes of a structure. However, modal identification methods in both the frequency and time domains have difficulties for certain circumstances. Frequency domain techniques which utilize the steady-state response from various harmonic inputs often encounter difficulties when the frequencies are closely distributed, the structure exhibits a high degree of damping, or the steady-state condition is hard to establish. Time domain techniques have produced successful results, but lack robustness with respect to measurement noise. In this paper, two identification techniques and an estimation method are combined to form a time-domain technique to accurately identify the mass, stiffness, and damping matrices from noisy measurements.

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