Home  About us  Contact
 

Modal Frequencies (modal + frequency)

Distribution by Scientific Domains
Engineering100%

Selected Abstracts

Long-Term Monitoring and Identification of Bridge Structural Parameters

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 2 2009
Serdar Soyoz
This three-span 111-m long bridge is instrumented with 13 acceleration sensors at both the superstructure and the columns. The sensor data are transmitted to a server computer wirelessly. Modal parameters of the bridge, that is, the frequencies and the modal shapes were identified by processing 1,707 vibration data sets collected under traffic excitations, based on which the bridge structural parameters, stiffness and mass, and the soil spring values were identified by employing the neural network technique. The identified superstructure stiffness at the beginning of the monitoring was 97% of the stiffness value based on the design drawings. In the identified modal frequencies, a variation from ,10% to +10% was observed over the monitoring period. In the identified stiffness values of the bridge superstructure, a variation from ,3% to +3% was observed over the monitoring period. Based on the statistical analysis of the collected data for each year, 5% decrease in the first modal frequency and 2% decrease in the superstructure stiffness were observed over the 5-year monitoring period. Probability density functions were obtained for stiffness values each year. Stiffness threshold values for the collapse of the bridge under the operational loading can be determined. Then the number of years can be assessed for which the area under the proposed probability density functions is greater than the threshold value. So the information obtained in this study is valuable for studying aging and long-term performance assessment of similar bridges. [source]

Forced vibration testing of buildings using the linear shaker seismic simulation (LSSS) testing method

EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 7 2005
Eunjong Yu
Abstract This paper describes the development and numerical verification of a test method to realistically simulate the seismic structural response of full-scale buildings. The result is a new field testing procedure referred to as the linear shaker seismic simulation (LSSS) testing method. This test method uses a linear shaker system in which a mass mounted on the structure is commanded a specified acceleration time history, which in turn induces inertial forces in the structure. The inertia force of the moving mass is transferred as dynamic force excitation to the structure. The key issues associated with the LSSS method are (1) determining for a given ground motion displacement, xg, a linear shaker motion which induces a structural response that matches as closely as possible the response of the building if it had been excited at its base by xg (i.e. the motion transformation problem) and (2) correcting the linear shaker motion from Step (1) to compensate for control,structure interaction effects associated with the fact that linear shaker systems cannot impart perfectly to the structure the specified forcing functions (i.e. the CSI problem). The motion transformation problem is solved using filters that modify xg both in the frequency domain using building transfer functions and in the time domain using a least squares approximation. The CSI problem, which is most important near the modal frequencies of the structural system, is solved for the example of a linear shaker system that is part of the NEES@UCLA equipment site. Copyright © 2005 John Wiley & Sons, Ltd. [source]

A simple LMS-based approach to the structural health monitoring benchmark problem

EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 6 2005
J. Geoffrey Chase
Abstract A structure's health or level of damage can be monitored by identifying changes in structural or modal parameters. However, the fundamental modal frequencies can sometimes be less sensitive to (localized) damage in large civil structures, although there are developing algorithms that seek to reduce this difficulty. This research directly identifies changes in structural stiffness due to modeling error or damage using a structural health monitoring method based on adaptive least mean square (LMS) filtering theory. The focus is on computational simplicity to enable real-time implementation. Several adaptive LMS filtering based approaches are used to analyze the data from the IASC,ASCE Structural Health Monitoring Task Group Benchmark problem. Results are compared with those from the task group and other published results. The proposed methods are shown to be very effective, accurately identifying damage to within 1%, with convergence times of 0.4,13.0 s for the twelve different 4 and 12 degree of freedom benchmark problems. The resulting modal parameters match to within 1% those from the benchmark problem definition. Finally, the methods developed require 1.4,14.0 Mcycles of computation and therefore could easily be implemented in real time. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Identification of structural and soil properties from vibration tests of the Hualien containment model

EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 1 2005
J. Enrique Luco
Abstract Measurements of the response of the ¼-scale reinforced concrete Hualien (Taiwan) containment model obtained during forced vibration tests are used to identify some of the characteristics of the superstructure and the soil. In particular, attempts are made to determine the fixed-base modal frequencies, modal damping ratios, modal masses and participation factors associated with translation and rocking of the base. The shell superstructure appears to be softer than could have been predicted on the basis of the given geometry and of test data for the properties of concrete. Estimates of the shear-wave velocity and damping ratio in the top layer of soil are obtained by matching the observed and theoretical system frequency and peak amplitude of the response at the top of the structure. The resulting models for the superstructure and the soil lead to theoretical results for the displacement and rotations at the base and top of the structure which closely match the observed response. Copyright © 2004 John Wiley & Sons, Ltd. [source]

System identification of instrumented bridge systems

EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 7 2003
Yalin Arici
Abstract Several recorded motions for seven bridge systems in California during recent earthquakes were analysed using parametric and non-parametric system identification (SI) methods. The bridges were selected considering the availability of an adequate array of accelerometers and accounting for different structural systems, materials, geometry and soil types. The results of the application of SI methods included identification of modal frequencies and damping ratios. Excellent fits of the recorded motion in the time domain were obtained using parametric methods. The multi-input/single-output SI method was a suitable approach considering the instrumentation layout for these bridges. Use of the constructed linear filters for prediction purposes was also demonstrated for three bridge systems. Reasonable prediction results were obtained considering the various limitations of the procedure. Finally, the study was concluded by identifying the change of the modal frequencies and damping of a particular bridge system in time using recursive filters. Copyright © 2003 John Wiley & Sons, Ltd. [source]

Efficient modal analysis of systems with local stiffness uncertainties

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 6-7 2009
S. F. Wojtkiewicz
Abstract The characterization of the uncertainty in modal quantities of an uncertain linear structural system is essential to the rapid determination of its response to arbitrary loadings. Although the size of many computational structural models used is extremely large, i.e. thousands of equations, the uncertainty to be analyzed is oftentimes localized to very small regions of the model. This paper addresses the development of an efficient, computational methodology for the modal analysis of linear structural systems with local stiffness uncertainties. The newly developed methodology utilizes an enriched basis that consists of the sub-spectrum of a nominal structural system augmented with additional basis vectors generated from a knowledge of the structure of the stiffness uncertainty. In addition, methods for determining bounds on the approximate modal frequencies and mode shapes are discussed. Numerical results demonstrate that the algorithm produces highly accurate results with greatly reduced computational effort. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Long-Term Monitoring and Identification of Bridge Structural Parameters

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 2 2009
Serdar Soyoz
This three-span 111-m long bridge is instrumented with 13 acceleration sensors at both the superstructure and the columns. The sensor data are transmitted to a server computer wirelessly. Modal parameters of the bridge, that is, the frequencies and the modal shapes were identified by processing 1,707 vibration data sets collected under traffic excitations, based on which the bridge structural parameters, stiffness and mass, and the soil spring values were identified by employing the neural network technique. The identified superstructure stiffness at the beginning of the monitoring was 97% of the stiffness value based on the design drawings. In the identified modal frequencies, a variation from ,10% to +10% was observed over the monitoring period. In the identified stiffness values of the bridge superstructure, a variation from ,3% to +3% was observed over the monitoring period. Based on the statistical analysis of the collected data for each year, 5% decrease in the first modal frequency and 2% decrease in the superstructure stiffness were observed over the 5-year monitoring period. Probability density functions were obtained for stiffness values each year. Stiffness threshold values for the collapse of the bridge under the operational loading can be determined. Then the number of years can be assessed for which the area under the proposed probability density functions is greater than the threshold value. So the information obtained in this study is valuable for studying aging and long-term performance assessment of similar bridges. [source]