DESDEMONA Achievements

DESDEMONA achievements constitute a series of steps beyond the status of knowledge at the EU funded project starting on 1st June 2018, in the development of novel design methods, systems, procedure and technical solution, to integrate sensing and automation technologies for the purpose of self-inspection and self-monitoring of steel structures. The obtained results will lead to an increment of the service life of existing and new steel civil and industrial infrastructure and to a decrease in the cost associated to inspections, improving human activities performed in difficult conditions, safety and workers’ potential by the use of advanced tools. The research succeeded to expand new high-quality standard and practices for steel structure inspection and maintenance through the interrelated development of the following actions: i) steel structure geometry and condition virtualization through data fusion of image processing, thermography and vibration measurements; ii) developing of procedure for steel defect detection by robotic and automatic systems such as Cable-Driven Parallel Manipulators (CDPM), Unmanned Aerial Vehicles (UAV), Wall Climbing Drone (WCD), Cable Climbing Robot (CCR) and Wheeled Robot (WR) iii) embedding sensor systems to revalorize and transform steel elements and structures into self-diagnostic (smart) elements and materials even through nanotechnologies, iv) realizing an experimental lab-based apparatus and a series of case studies inspected by intelligent and robotic systems. The project outcomes are determining an impact on the reduction of the cost of steel structures inspection and maintenance and on the increase of user safety and comfort in industrial and civil environment

Advanced Applications in the Field of Structural Control and Health Monitoring After the 2009 L’Aquila Earthquake

The earthquake, which has been occurred on 6 April 2009, has been a catastrophic event for both the city and the University of L’Aquila [1]. Nevertheless, the disaster have to be trans‐ formed in a tremendous opportunity to revitalize the area, with important benefit for the national and international scientific community to experience the effectiveness of new system

Integrated process of images and acceleration measurements for damage detection

The use of mobile robots and UAV to catch unthinkable images together with on-site global automated acceleration measurements easy achievable by wireless sensors, able of remote data transfer, have strongly enhanced the capability of defect and damage evaluation in bridges. A sequential procedure is, here, proposed for damage monitoring and bridge condition assessment based on both: digital image processing for survey and defect evaluation and structural identification based on acceleration measurements. A steel bridge has been simultaneously inspected by UAV to acquire images using visible light, or infrared radiation, and monitored through a wireless sensor network (WSN) measuring structural vibrations. First, image processing has been used to construct a geometrical model and to quantify corrosion extension. Then, the consistent structural model has been updated based on the modal quantities identified using the acceleration measurements acquired by the deployed WSN. © 2017 The Authors. Published by Elsevier Ltd

Integrated Design Approach to Build a Safe and Sustainable Dual Intended Use Center in Praslin Island, Seychelles

A flexible multi-purpose center for a dual intended use—hospitality and observation and research related to climate change—has been designed in the fragile environment of Praslin Island, Seychelles. The technical solutions adopted for a low environmental impact LCA based in the designed center during the life cycle will be illustrated: starting from the local supply raw materials, the self-disassembling construction system, the described process is compatible with the site use that the owners have foreseen. Specific logistic systems have been chosen both to the transportation of the material on the site, and to the integrated structural and architectural solutions. In addition, a reconstruction of the natural characteristics of the building site has been developed both by google-earth observation and with a survey directly on the site through processing acquired images. The multi-disciplinary perspective through which the project has been conceived shows beneficial effects in terms of reduced impact on the original and resilient natural environment. Future developments of the work will be devoted to the optimization of this multi-disciplinary approach

Fatigue Damage Identification by a Global-Local Integrated Procedure for Truss-Like Steel Bridges

Civil steel structures and infrastructures, such as truss railway bridges, are often subject to potential damage, mainly due to fatigue phenomena and corrosion. Terefore, damage detection algorithms should be designed and appropriately implemented to increase their structural health. Today, the vast amount of information provided by data processing techniques and measurements coming from a monitoring system constitutes a possible tool for damage identifcation in terms of both detection and description. For this reason, the research activity aims to develop a methodology for a preliminary description of the damage in steel railway bridges induced by fatigue phenomena. Te proposed approach is developed through an integration of global and local pro cedures. At the global scale, vibration-based procedures will be applied to improve a forecast numerical model and, subsequently, to identify the zones most involved in fatigue problems. At the local scale, careful and refned local identifcation will be pursued via image processing techniques whose evidence will be analyzed and described through nonlinear numerical models. A case study of a historical railway bridge in Spain will illustrate the methodology’s performance, potentiality, and critical issue

Design of Wireless Sensor Nodes for Structural Health Monitoring applications

Enabling low-cost distributed monitoring, wireless sensor networks represents an interesting solution for the implementation of structural health monitoring systems. This work deals with the design of wireless sensor networks for health monitoring of civil structures, specifically focusing on node design in relation to the requirements of different structural monitoring application classes. Design problems are analysed with specific reference to a large-scale experimental setup (the long-term structural monitoring of the Basilica S. Maria di Collemaggio, L’Aquila, Italy). Main limitations emerged are highlighted, and adopted solution strategies are outlined, both in the case of commercial sensing platform and of full custom solutions

Cable-deck dynamic interactions at the International Guadiana Bridge: On-site measurements and finite element modelling

SUMMARY The International Guadiana Bridge is a cable-stayed bridge crossing the Guadiana River, which marks the southern border between Portugal and Spain. The bridge has a central span of 324 m and a total length of 666 m and was open to traffic in 1991. Despite the globally satisfying behaviour under the common environmental loads, which largely ensures the bridge serviceability, frequent episodes of cable vibration have been observed since completion of the construction. In this paper, the bridge modal properties and dynamic behaviour, identified from repeated campaigns of vibration data acquisitions, are compared with the response of a three-dimensional finite element model, including the description of the cable transversal motion. The model, after minor updating, furnishes a realistic reproduction of the current bridge dynamic behaviour. Then different possible justifications of the local vibrations are evaluated, briefly scanning the known sources of large amplitude cable oscillations both in the linear and the nonlinear field. In particular, the occurrence of different internal resonance conditions is deeply discussed, in order to verify whether the experimental observations could be really justified by a cable–deck dynamic interaction mechanism. Among different possibilities, a beating phenomenon between two resonant modes, amplified by the lower damping and inertial characteristics of the local mode with respect to the global one, is selected as the most critical cable excitation source. Since the cable vibrations are proved to persist for different wind conditions, the heavy traffic load on the bridge deck is investigated as one possible source of the global mode direct excitation. On this respect, the model response to random load and moving forces acting on the bridge deck is numerically evaluated evidencing how some particular features of the real bridge behaviour can be qualitatively reproduced. Copyright # 2008 John Wiley & Sons, Ltd

Damage Identification of Railway Bridges through Temporal Autoregressive Modeling

The damage identification of railway bridges poses a formidable challenge given the large variability in the environmental and operational conditions that such structures are subjected to along their lifespan. To address this challenge, this paper proposes a novel damage identification approach exploiting continuously extracted time series of autoregressive (AR) coefficients from strain data with moving train loads as highly sensitive damage features. Through a statistical pattern recognition algorithm involving data clustering and quality control charts, the proposed approach offers a set of sensor-level damage indicators with damage detection, quantification, and localization capabilities. The effectiveness of the developed approach is appraised through two case studies, involving a theoretical simply supported beam and a real-world in-operation railway bridge. The latter corresponds to the Mascarat Viaduct, a 20th century historical steel truss railway bridge that remains active in TRAM line 9 in the province of Alicante, Spain. A detailed 3D finite element model (FEM) of the viaduct was defined and experimentally validated. On this basis, an extensive synthetic dataset was constructed accounting for both environmental and operational conditions, as well as a variety of damage scenarios of increasing severity. Overall, the presented results and discussion evidence the superior performance of strain measurements over acceleration, offering great potential for unsupervised damage detection with full damage identification capabilities (detection, quantification, and localization).E. García-Macías was partially supported by the research project “SMART-BRIDGES-Monitorización Inteligente del Estado Estructural de Puentes Ferroviarios” (Ref. PLEC2021-007798) funded by the Spanish Ministry of Science and Innovation, the Spanish State Research Agency, and NextGenerationEU. F. Ubertini acknowledges the support of the Italian Ministry of University and Research (MUR) through the project of National Interest (PRIN PNRR 2022) “TIMING–Time evolution laws for IMproving the structural reliability evaluation of existING post-tensioned concrete deck bridges” (Prot. P20223Y947). The authors also acknowledge the regional administration of the Valencian Community in Spain for the financial support provided by the projects GRISOLIAAP/2019/122 and APOTIP/2021/003, and the European Union for the Project DESDEMONA Grant Agreement n. 800687. Finally, the authors would also like to express their gratitude to FGV (Ferrocarrils de la Generalitat Valenciana) and CALSENS S.L., for their invaluable cooperation and recommendations

Strain-based autoregressive modelling for system identification of railway bridges

Vehicular traffic represents the most influential loads on the structural integrity of railway bridges, therefore the design on dynamic criteria. This work explores the use of strain dynamic measurements to characterize the health condition of railway bridges under moving train loads. Specifically, the approach proposed in this work exploits the implementation of auto-regressive (AR) time series analysis for continuous damage detection. In this light, continuously extracted AR coefficients are used as damage-sensitive features. To automate the definition of the order of the AR model, the methodology implements a model selection approach based on the Bayesian information criterion (BIC), Akaike Information Criterion (AIC) and Mean Squared Error (MSE). In this exploratory investigation, the suitability and effectiveness of strain measurements against acceleration-based systems are appraised through a case study of a simply supported Euler-Bernoulli beam under moving loads. The moving loads problem in terms of vertical accelerations and normal strains is solved through modal decomposition in closed form. The presented numerical results and discussion evidence the effectiveness of the proposed approach, laying the basis for its implementation to real-world instrumented bridges