Improving the Quantification and Estimation of Damping for Bridges under Traffic Loading

It is important for engineers and designers to be able to accurately estimate the damping within a structure; however, this is not a trivial task. Simplifications are often made in an effort to make damping estimation easier, but these simplifications rely on assumptions that may not be universally true. One important assumption is that the excitation input for a structure may be modeled as broad-band noise, but traffic loading on a bridge likely violates that assumption. Traffic loads are characterized by the velocities of the vehicles and trains crossing the bridge, which gives the input specific frequency content. This added complexity increases the difficulty in accurately estimating the damping. The problem of traffic crossing a bridge was studied by creating a finite element model of a bridge using a beam system that consisted of a series of stringers resting on top of a larger girder. Traffic loads were then simulated using moving point loads and moving masses to represent cars and trains crossing the bridge. In addition to the traffic loading case, an ambient loading case was conducted using uniform broad-band noise as a means of comparison. The accelerations at several locations along the bridge span were recorded and used as input for a variety of operational modal analysis (OMA) methods. The OMA methods included both frequency domain techniques, such as Frequency Domain Decomposition (FDD), and time domain based identification, such as blind source separation (BSS). The results from the various OMA methods demonstrated how traffic loading creates distortion in the frequency response spectra of the bridge. This distortion had adverse effects for damping ratio estimation and in certain cases led to extreme errors. The mode shape estimates were not found to be affected by the distortion, but that meant that mode shape estimates could not be used to identify potentially erroneous damping estimates. The cause for the distortion was later identified as the driving frequencies produced by the vehicle-bridge interactions. The term ``driving frequency'' refers to the frequency created by a car traveling over a bridge or, by analogy, by a moving load traveling over a beam. This frequency is directly correlated with the speed of the vehicle and the length of the bridge. By considering a single moving point load traveling across the bridge, the responses of the stringers and girder were studied and the effects of the driving frequencies were better quantified in both the time and frequency domains. It was found that peaks in frequency domain appear at the even multiples of each car's driving frequency, and as more cars travel across the bridge the peaks of closely spaced driving frequency multiples begin to merge. As the number of cars increases to a full hour-long simulation and the car velocities become uniformly distributed over a given interval, numerous peaks merge together to form sustained regions of elevated energy in the frequency domain. These regions distort the frequency response spectra of the bridge and obscure the modal information. In order to deal with these distorted regions, a new approach to modal identification was proposed that focused on using partial information from the modal peaks. The peaks in the frequency domain were divided into left- and right-side spectra in order to take advantage of any undistorted portions of the modal peaks. These side spectra were analyzed using a curve-fitting approach based on combining optimization methods with clustering analysis. The presence of distortion presented certain challenges to traditional curve-fitting approaches, such as polynomial least squares, but the optimization algorithm was able to overcome these issues while also adding efficiency to the curve-fitting process. The clustering analysis was used to quickly find the optimal subsets within the optimization-based curve-fitting results. By performing curve-fitting to side spectra, different sets of modal parameters were produced that fit each side. It was found that the modal parameters for the intact or undistorted side compared favorably with the true modal parameters. While this optimization and clustering methodology could not account for all types of distortion, it demonstrated large improvements as compared to traditional OMA approaches for the modes most severely impacted by the distortion. Another potential benefit of this method is that the distributions within the final clusters could be used to provide ranges of possible values for the damping ratios instead of only a single value

Modeling and Model Updating of a Full-Scale Experimental Base-Isolated Building

Studies on seismic risk mitigation [3] and town centre regeneration [4], have identified economic, social, environmental, cultural, and regulatory factors that could strongly control the viability of achieving seismic resilience and sustainability by using the adaptive reuse approach [5]. However, understanding the effectiveness of using the adaptive reuse approach to balance the varying objectives of seismic resilience, economic sustainability, built heritage preservation, and building demand, towards achieving a resilient and sustainable town centre living, remains a major challenge for most decision makers in New Zealand

Dynamical response identification of a class of nonlinear hysteretic systems

The experimental dynamical response of three types of nonlinear hysteretic systems is identified employing phenomenological models togheter with the Differential Evolutionary algorithm. The mass–spring–damper system is characterized by hysteretic restoring forces provided by assemblies of shape memory and steel wire ropes subject to flexure or coupled states of tension and flexure. The energy dissipation due to phase transformations and inter-wire friction and the stretching-induced geometric nonlinearities give rise to different shapes of hysteresis cycles. The mechanical device subject to strong seismic excitations is investigated in its ultimate limit state whereby inelastic strains are induced in the steel wires together with a global nonsymmetric response of the system. The targeted dynamical characterization of the hysteretic oscillator up to its ultimate limit state has a special meaning when the device is employed in the field of vibration control. The dynamical response is identified exploiting the measurements of the oscillating mass relative displacement and inertia force that must be balanced, at each time instant, by the overall restoring forces provided by the mechanism. The restoring force is assumed to be the sum of different contributions such as a cubic nonsymmetric elastic force and a nonsymmetric hysteretic force modeled according to a modified version of the Bouc–Wen model. The parameters are identified minimizing the difference between the numerical and the experimental restoring force histories. High levels of accuracy are achieved in the identification with mean square errors lower than 2%

Enabling reduced-order data-driven nonlinear identification and modeling through naive elastic net regularization

This work discusses an improved method of reduced-order modeling for existing data-driven nonlinear identification techniques through the incorporation of naïve elastic net regularization. The data-driven methods considered for this study operate using basis functions to represent the observed nonlinearity. Elastic net regularization is used to minimize the number of non-zero coefficients, thus modifying the basis functions and providing a compact representation. The ability of the naïve elastic net to provide reduced-order nonlinear models that can both accurately fit various data sets and computationally simulate new responses is illustrated through studies considering both synthetic data and experimental data. In both cases, the results obtained with the naïve elastic net are shown to match or outperform those from other traditional methods

Vibration Mitigation and Monitoring: A Case Study of Construction in a Museum

<p>Vibration from demolition and construction activities poses a serious risk to museum objects. This case study presents preventive conservation and vibration monitoring strategies developed in response to a large-scale renovation project on the floor directly below the Egyptian Art galleries of the Metropolitan Museum of Art in order to safeguard this fragile, ancient art collection. The paper discusses the methods and procedures that were developed not only to protect the art but also to allow visitors continued access to as much of the collection as possible during the work period. In advance of the construction, pilot testing was performed to determine the levels of vibrations caused by different tools, as well as to gain a better understanding of vibration propagation within the museum and to specific objects through their mounts, pedestals, and display shelves. Vibration prone installations were modified with isolation and/or dampening approaches to mitigate vibration, or when possible, selected objects were deinstalled. A variety of mitigation solutions were shown to be effective through testing. During the demolition and construction phase, continuous wireless vibration monitoring was provided from within the galleries, and sometimes from sensors directly on objects or their shelves to provide near real-time alerts to museum staff and construction personnel. Alert levels were based on frequency independent velocity levels.</p