F A V T ORCED AND MBIENT IBRATION ESTING F S B OF ULL CALE RIDGES By Piotr Omenzetter1 Sherif Beskhyroun2 Faisal Shabbir2 Ge-Wei Chen2 Xinghua Chen2 Shengzhe Wang2 Alex Zha2 A report submitted to Earthquake Commission Research Foundation (Project No. UNI/578) October 2013 1) The LRF Centre for Safety and Reliability Engineering School of Engineering University of Aberdeen UK 2) Department of Civil and Environmental Engineering The University of Auckland New Zealand N - ON TECHNICAL ABSTRACT Knowledge about the performance of structural systems, such as bridges, can be created using laboratory-scale experimentation, analytical and numerical simulations, and full-scale, in-situ experimentation on existing structures. The latter method has several advantages as it is free from many assumptions, omissions and simplifications inherently present in the former two. For example, soil-structure interaction, non-structural components, and nonlinearities in stiffness and energy dissipation are always present in their true form in full- scale, in-situ testing. Thus, full-scale experimentation results present the ground truth about structural performance. The performance evaluated this way is used for advanced assessment of the working condition of the structure, detection of the causes and effects of damage, aging and deterioration, evaluation of the quality of construction, checking of design assumptions, and also provides important lessons for future design and construction of similar structures. In this research, four different bridges (a two-span cable-stayed pedestrian bridge, a two-span concrete motorway bridge, an 11-span post-tensioned concrete motorway off-ramp, and a major 12-span post-tensioned concrete motorway viaduct) were tested using environmental excitation (e.g. vehicular traffic) and/or forcing provided by shakers. Experimental data were analysed using techniques that were able to extract the resonant frequencies of the bridges, quantify vibration energy dissipation and visualise the shapes of bridge vibrations. The analyses of data collected in field experiments included observing how stiffness and energy dissipation change with the amplitude of forcing and response. Another way of gaining insights into the dynamics of the tested bridges was via detailed computer modelling of the structures. This enabled identification and understanding of the mechanisms responsible for their measured performance. Because the experimental results and numerical predictions always differ to a certain degree, novel methods for calibration, or updating, of structural models were investigated. These methods, based on mathematical metaphors describing of the behaviour of a swarm of bees or school of fish proved to be efficient tools for model calibration. i ii T ECHNICAL ABSTRACT A great deal of knowledge about the performance of structural systems, such as bridges, can be created using full-scale, in-situ experimentation on existing structures. Full-scale testing offers several advantages as it is free from many assumptions and simplifications inherently present in laboratory experiments and numerical simulations. For example, soil-structure interaction, non-structural components, and nonlinearities in stiffness and energy dissipation are always present in their true form in full-scale, in-situ testing. Thus, full-scale experimentation results present the ground truth about structural performance and indeed provide the ultimate test for both actual constructed systems and laboratory and numerical investigations. The performance evaluated this way can be used for advanced assessment of structural condition, detection of damage, aging and deterioration, evaluation of the construction quality, validation of design assumptions, and also as lessons for future design and construction of similar structures. In this research, four different bridges (a two-span cable-stayed pedestrian bridge, a two-span concrete motorway bridge, an 11-span post-tensioned concrete motorway off-ramp, and a major 12-span post-tensioned concrete motorway viaduct) were tested using ambient excitation (e.g. vehicular traffic) and/or forcing provided by shakers. Experimental data were analysed using multiple system identification techniques to extract the resonant frequencies, damping ratios and mode shapes. For the 12-span viaduct, these techniques were compared and recommendations were made for their use in future testing exercises. The analyses of experimental data included quantification of resonant frequency and damping ratio changes with the amplitude of forcing and response for the 11-span motorway off-ramp. The frequencies were found to decrease and damping ratios to initially increase and then stabilise, respectively, with increasing response amplitude. Detailed computer modelling of the structures was also undertaken and enabled identification and understanding of the mechanisms responsible for their measured performance. A novel optimisation method for updating of structural models was proposed and investigated. The method, particle swarm optimisation with sequential niche technique, belongs to global optimisation algorithms, mimics the behaviour of a swarm of bees or school of fish in search for the most fertile feeding location, systematically searches the updating parameter domain for multiple minima to discover the global one, and proved effective when applied to the experimental data from the pedestrian bridge tested in this study. iii iv A CKNOWLEDGEMENTS This research was financially supported by Earthquake Commission Research Foundation (Project No. UNI/578 “Forced and ambient vibration testing of full scale bridges”). The authors are grateful for this support. Ben Ryder of Aurecon and Graeme Cummings of HEB Construction assisted in obtaining access to the Clarks Lane bridge and information for modelling. NGA Newmarket facilitated the field testing of Newmarket Viaduct and Gillies Avenue bridge, and New Zealand Transport Agency allowed the use of Newmarket Viaduct, Nelson St off-ramp and Gillies Avenue bridge for research. Particular thanks go to David Leitner, Jonathan Lane and Jim Baker. The authors would also like to acknowledge the efforts and help of the technical and laboratory staff at the Department of Civil and Environmental Engineering, the University of Auckland involved in this research, in particular Daniel Ripley. The assistance of research students at the University of Auckland: Lucas Hogan, Luke Williams, Graham Bougen, Shahab Ramhormozian, Peifen Chua, Jessica Barrell and Daphne Luez in conducting experimental field testing is much appreciated. Piotr Omenzetter’s work within The LRF Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd's Register Foundation (LRF). LRF, a UK registered charity and sole shareholder of Lloyd’s Register Group Ltd, invests in science, engineering and technology for public benefit, worldwide. v vi T ABLE OF CONTENTS Non-technical abstract …………………………………………………………………….... i Technical abstract …………………………………………………………………………. iii Acknowledgements …………………………………………………………………………. v Table of contents ………………………………………………………………………….. vii List of abbreviations ……………………………………………………………………..... xi Notation …………….……………………………………………………………………... xiii List of figures ……...……………………………………………………………………... xvii List of tables …………………………………………………………………………….. xxiii Chapter 1. Introduction …………………………………………………………………. 1-1 1.1. Background and motivation for research ...................................................................... 1-1 1.2. Objective, contribution and scope of research .............................................................. 1-2 1.3. Report layout ................................................................................................................. 1-4 1.4. References ..................................................................................................................... 1-5 Chapter 2. Literature review ……………………………………………………………. 2-1 2.1. Introduction ................................................................................................................... 2-1 2.2. Modal testing ................................................................................................................ 2-1 2.2.1. Excitation ................................................................................................................. 2-2 2.2.2. Sensing ..................................................................................................................... 2-3 2.2.3. Data acquisition and processing ............................................................................... 2-3 2.3. Model updating ............................................................................................................. 2-4 2.3.1. Uncertainties in modelling of structures ................................................................. 2-5 2.3.2. Approaches to model updating …………………………………………………... 2-7 2.3.2.1. Manual model updating ………………………………………...……………... 2-8 2.3.2.2. Sensitivity method for model updating ……………………………………...... 2-8 2.3.2.3. Global optimisation algorithms for model updating ………………………... 2-9 2.4. Examples of past modal testing and model updating exercises ……………………. 2-10 2.4.1. Modal testing …………………………………………………………………… 2-10 2.4.2. Dependence of modal properties on response amplitude ………………………2-11 2.4.2. Updating using sensitivity method ………………………………………….….. 2-16 2.4.3. Updating using global optimisation algorithms…………………………….…... 2-18 2.5. Summary …………………………………………………………………………… 2-20 vii 2.6. References ………………………………………………………………………….. 2-20 Chapter 3. Theory ………………………………………………………………………... 3-1 3.1. Introduction ................................................................................................................... 3-1 3.2. System identification concepts and methods .............................................................. 3-1 3.2.1. Spectral analysis and frequency response function ............................................. 3-1 3.2.2. Peak picking ......................................................................................................... 3-3 3.2.2. Half-power …………………………………………………………………….. 3-3 3.2.4. Frequency domain decomposition and enhanced frequency domain decomposition …………………………………………………………………. 3-4 3.2.5. Subspace system identification ............................................................................ 3-5 3.2.6. Natural excitation technique – eigenvalue realisation algorithm ......................... 3-8 3.3. Model updating concepts and methods ..................................................................... 3-11 3.3.1. Objective function for updating ......................................................................... 3-11 3.3.2. Sensitivity based updating ................................................................................. 3-12 3.3.3. Global optimisation algorithms.......................................................................... 3-13 3.3.3.1. Particle swarm optimisation ......................................................................... 3-13 3.3.3.2. Sequential niche technique………………………………………………... 3-15 3.4. Summary ..................................................................................................................... 3-16 3.5. References ................................................................................................................... 3-17 Chapter 4. Forced vibration testing, system identification and model updating of a cable-stayed footbridge ………….…………………………………………... 4-1 4.1. Introduction .................................................................................................................. 4-1 4.2. Bridge description ......................................................................................................... 4-2 4.3. Forced vibration testing and system identification ....................................................... 4-4 4.4.Finite element modelling ............................................................................................. 4-10 4.5. Model updating .......................................................................................................... 4-14 4.5.1. Selection of updating parameters and objective function ...................................... 4-14 4.5.2. Assessment of the performance of model updating methodology ........................ 4-17 4.5.2.1. Updating using a sensitivity-based technique ................................................... 4-18 4.5.2.2. Updating of uncertain parameters using particle swarm optimisation and sequential niche technique ................................................................................ 4-20 4.6. Conclusions ................................................................................................................. 4-23 4.7. References ................................................................................................................... 4-24 viii