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Eleni Chatzi published an article in June 2018.
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(2014 - 2018)
(2014 - 2018)
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Article 1 Read 1 Citation Structural Health Monitoring Sensor Network Optimization through Bayesian Experimental Design Published: 01 June 2018
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, doi: 10.1061/ajrua6.0000966
Structural health monitoring (SHM) may be exploited to estimate the mechanical properties of existing structures and check for potential damage. Among commonly used methodologies for property characterization, the Bayesian approach holds the lead because it is endowed with the particular advantage of quantifying associated uncertainties. These uncertainties arise owing to diverse factors including (1) sensor accuracy and positioning, (2) environmental influences, and (3) modeling errors. In minimizing the influence of sensor-related uncertainties, an optimal design may be adopted for the SHM campaign to maximize the information content of the measurements. Here, a procedure based on Bayesian experimental design is proposed to quantify the expected utility of the sensor network. The positions of the used sensors are selected in a way that maximizes the Shannon information gain between the prior and posterior probability distributions of the parameters to be estimated. In order to numerically solve the resulting optimization problem, surrogate models based on polynomial chaos expansion (PCE) and stochastic optimization methods are used. The use of surrogates allows one to reduce the computational cost of the associated model runs. The method is applied to a large-scale example, namely the Pirelli Tower in Milan.
Article 1 Read 0 Citations Robust-to-Uncertainties Optimal Design of Seismic Metamaterials Published: 01 March 2018
Journal of Engineering Mechanics, doi: 10.1061/(asce)em.1943-7889.0001404
Metamaterials, which draw their origin from a special class of structured (periodic) materials characterized by a dynamic filtering effect, have recently emerged as a prospective means for structural seismic protection. This paper explores such a periodic arrangement in the form of local adaptive resonators buried in the soil, serving as a seismic protection barrier. As a starting point, a simplistic representation is chosen herein that comprises chains of mass-in-mass unit cells. A robust-to-uncertainties optimization of such a chain, addressing uncertainties at the level of the excitation, the system properties and the model structure itself, is conducted. The optimization problem is formulated within the context of reliability assessment, where the objective function is the failure probability of the structure to be protected against seismic input. The problem is solved through adoption of the subset optimization algorithm enhanced through the simultaneous implementation of a stochastic approximation algorithm. It is demonstrated that not all parameters of the chain model require optimization, because the failure probability proves to be a monotonic function of a subset of the parameters. A primary objective herein lies in optimizing the internal unit-cell stiffness properties. It is further demonstrated that the effectiveness of the protection offered by the metamaterial is improved for spatially varying unit-cell properties. The optimization procedure is carried out in the frequency domain, with an example application confirming that a time domain optimization is expected to yield similar optimal configurations. A parametric study using a nonlinear model is also presented, offering a starting point for more refined future investigations.
Article 2 Reads 0 Citations On the use of mode shape curvatures for damage localization under varying environmental conditions Published: 29 January 2018
Structural Control and Health Monitoring, doi: 10.1002/stc.2132
A novel damage localization method is introduced in this study, which exploits mode shape curvatures as damage features, while accounting for operational variability. The developed framework operates in an output-only regime,that is, it does not assume availability of records from the influencing environmental/operational quantities but rather from response quantities alone. The introduced tool comprises 3 stages pertaining to training, validation, and diagnostics. During the training stage, a representation of the healthy, or baseline, structural state is acquired over varying operational conditions. A data matrix is formulated, whose individual columns correspond to mode shape curvatures at distinct operational conditions, and principal component analysis (PCA) is applied for extraction of the imprints of separate operational sources on these curvatures. To this end, a residual matrix between the original and the PCA mapped data is formed serving for statistical characterization of each mode. Subsequently, during the validation and diagnostics stages, the mode shape curvature matrices for the currently inspected structural state are assembled and the same PCA mapping is enforced. A typical hypothesis test and a corresponding damage index are then adopted in order to firstly detect damage, and to secondly localize damage, should this exist. The implementation of the proposed method in 2 numerical case studies confirms its effectiveness and the encouraging results suggest further investigation on operating structural systems.
BOOK-CHAPTER 1 Read 0 Citations Numerical and Experimental Investigations of Reinforced Masonry Structures Across Multiple Scales Published: 01 January 2018
Cyber Security: Power and Technology, doi: 10.1007/978-3-319-68646-2_15
This review chapter outlines the outcomes of a combined experimental-numerical investigation on the retrofitting of masonry structures by means of polymeric textile reinforcement. Masonry systems comprise a significant portion of cultural heritage structures, particularly within European borders. Several of these systems are faced with progressive ageing effects and are exposed to extreme events, as for instance intense seismicity levels for structures in the center of Italy. As a result, the attention of the engineering community and infrastructure operators has turned to the development, testing, and eventual implementation of effective strengthening and protection solutions. This work overviews such a candidate, identified as a full-coverage reinforcement in the form of a polymeric multi-axial textile. This investigation is motivated by the EU-funded projects Polytect and Polymast, in the context of which this protection solution was developed. This chapter is primarily concerned with the adequate simulation and verification of the retrofitted system, in ways that are computationally affordable yet robust in terms of simulation accuracy. To this end, finite element-based mesoscopic and multiscale representations are overviewed and discussed within the context of characterization, identification and performance assessment.
Article 1 Read 1 Citation Gaussian Process Time-Series Models for Structures under Operational Variability Published: 08 December 2017
Frontiers in Built Environment, doi: 10.3389/fbuil.2017.00069
Article 2 Reads 1 Citation A Discontinuous Unscented Kalman Filter for Non-Smooth Dynamic Problems Published: 19 October 2017
Frontiers in Built Environment, doi: 10.3389/fbuil.2017.00056