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Eleni Chatzi   Professor  Senior Scientist or Principal Investigator 
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Eleni Chatzi published an article in April 2019.
Top co-authors See all
Costas Papadimitriou

134 shared publications

Department of Mechanical Engineering, University of Thessaly, Volos, Greece

Stefano Mariani

124 shared publications

Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milano, Italy

Simon Laflamme

121 shared publications

Department of Civil, Construction and Environmental Engineering, Iowa State University, 813 Bissell Road, Ames, IA 50011, USA

Filippo Ubertini

112 shared publications

Department of Civil and Environmental Engineering, University of Perugia, 06125 Perugia, Italy

Babak Moaveni

83 shared publications

Department of Civil and Environmental Engineering; Tufts University; Medford Massachusetts

Publication Record
Distribution of Articles published per year 
(2007 - 2019)
Total number of journals
published in
Publications See all
Article 3 Reads 0 Citations Improving the conditioning of XFEM/GFEM for fracture mechanics problems through enrichment quasi-orthogonalization Konstantinos Agathos, Stéphane P.A. Bordas, Eleni Chatzi Published: 01 April 2019
Computer Methods in Applied Mechanics and Engineering, doi: 10.1016/j.cma.2018.08.007
DOI See at publisher website
Article 0 Reads 0 Citations A Novel Approach for 3D-Structural Identification through Video Recording: Magnified Tracking † Yunus Emre Harmanci, Utku Gülan, Markus Holzner, Eleni Chatz... Published: 11 March 2019
Sensors, doi: 10.3390/s19051229
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Advancements in optical imaging devices and computer vision algorithms allow the exploration of novel diagnostic techniques for use within engineering systems. A recent field of application lies in the adoption of such devices for non-contact vibrational response recordings of structures, allowing high spatial density measurements without the burden of heavy cabling associated with conventional technologies. This, however, is not a straightforward task due to the typically low-amplitude displacement response of structures under ambient operational conditions. A novel framework, namely Magnified Tracking (MT), is proposed herein to overcome this limitation through the synergistic use of two computer vision techniques. The recently proposed phase-based motion magnification (PBMM) framework, for amplifying motion in a video within a defined frequency band, is coupled with motion tracking by means of particle tracking velocimetry (PTV). An experimental campaign was conducted to validate a proof-of-concept, where the dynamic response of a shear frame was measured both by conventional sensors as well as a video camera setup, and cross-compared to prove the feasibility of the proposed non-contact approach. The methodology was explored both in 2D and 3D configurations, with PTV revealing a powerful tool for the measurement of perceptible motion. When MT is utilized for tracking “imperceptible” structural responses (i.e., below PTV sensitivity), via the use of PBMM around the resonant frequencies of the structure, the amplified motion reveals the operational deflection shapes, which are otherwise intractable. The modal results extracted from the magnified videos, using PTV, demonstrate MT to be a viable non-contact alternative for 3D modal identification with the benefit of a spatially dense measurement grid.
Article 0 Reads 1 Citation Model updating of a historic concrete bridge by sensitivity- and global optimization-based Latin Hypercube Sampling Rosalba Ferrari, Diego Froio, Egidio Rizzi, Carmelo Gentile,... Published: 01 January 2019
Engineering Structures, doi: 10.1016/j.engstruct.2018.08.004
DOI See at publisher website
Article 0 Reads 0 Citations Implications of subsoil-foundation modelling on the dynamic characteristics of a monitored bridge Periklis Faraonis, Anastasios Sextos, Costas Papadimitriou, ... Published: 29 December 2018
Structure and Infrastructure Engineering, doi: 10.1080/15732479.2018.1503689
DOI See at publisher website
Article 0 Reads 0 Citations Condition Assessment of Roadway Bridges: From Performance Parameters to Performance Goals Maria Pina Limongelli, Eleni Chatzi, Andrej Anžlin Published: 21 December 2018
The Baltic Journal of Road and Bridge Engineering, doi: 10.7250/bjrbe.2018-13.421
DOI See at publisher website ABS Show/hide abstract
Deterioration of bridges due to ageing and higher demands, induced by increased traffic load, require the development of effective maintenance policies and intervention strategies. Such concern should be aimed at ensuring the required levels of safety, while optimally managing the limited economic resources. This approach requires a transversal advance; from the element level, through the system level, all the way to the network level. At the same time intervention prioritisation based on the importance of the system (bridge) inside the network (e.g. highway), or of the single structural element inside the bridge is dependent. The first step in bridge condition assessment is the verification of safety and reliability requirements that is carried out using the traditional prescriptive (deterministic) approach or the current performance- based (probabilistic) approach. A critical issue for efficient management of infrastructures lies in the available knowledge on condition and performance of bridge asset. This information is obtained using a collection of significant Performance Parameters at one or more of the three levels (element, system, and network). Traditional techniques for estimation of Performance Parameters rely on already established visual inspection. However, a more reliable description of the system performance is obtained through Non-Destructive Testing and Structural Health Monitoring. Condition assessment essentially pertains to the check of compliance with Performance Goals and requires the definition and computation of Performance Indicators. They are calculated directly from Performance Parameters or from physical models calibrated using the Performance Parameters collected on the structure. Paper overviews the steps to bridge condition assessment regarding safety and reliability.
CONFERENCE-ARTICLE 24 Reads 1 Citation <strong>Computer Vision Aided Structural Identification: Feature Tracking Using Particle Tracking Velocimetry versus Opt... Yunus Harmanci, Zhilu Lai, Utku Gülan, Markus Holzner, Eleni... Published: 14 November 2018
Proceedings, doi: 10.3390/ecsa-5-05750
DOI See at publisher website ABS Show/hide abstract

Recent advances in computer vision techniques allow to obtain information on the dynamic behavior of structures using commercial grade video recording devices. The advantage of such schemes is due to the non-invasive nature of video recording, and the ability to extract information at a high spatial density utilizing features on the structure. This creates an advantage over conventional contact sensors since constraints such as cabling and maximum channel availability are alleviated. In this study, two such schemes are explored, namely Particle Tracking Velocimetry (PTV) and the optical flow algorithm. Both are validated against conventional sensors for a lab-scale shear frame and compared. In cases of imperceptible motion, the recently proposed Phase-based Motion Magnification (PBMM) technique is employed to obtain modal information within frequency bands of interest and further used for modal analysis. The optical flow scheme combined with (PBMM) is further tested on a large-scale post-tensioned concrete beam and validated against conventional measurements, as a transition from lab- to outdoor field applications.