Experimental verification of the interpolation method on a real damaged bridge

The identification of damage in a bridge from changes in its vibrational behavior is an inverse problem of important practical value. Significant advances have been obtained on this topic in the last two-three decades, both from the theoretical and applied point of view. One of the main problems when dealing with the assessment of vibration based damage identification methods is the lack of experimental data recorded on real damaged structures. Due to this, a large number of damage identification algorithms are tested using data simulated by numerical models. The availability of data recorded on a damaged bridge before its demolition gave the authors the uncommon chance to verify the sensitivity and reliability of the IDDM basing on data recorded on a real structure. Specifically data recorded on a reinforced concrete single-span supported bridge in the Municipality of Dogna (Friuli, Italy) were used to apply the damage localization algorithm. Harmonically forced tests were conducted after imposing artificial, increasing levels of localized damage. In this paper the sensitivity of the method is discussed with respect to the number of instrumented locations and to the severity of the damage scenarios considere

LIFECYCLE MANAGEMENT, MONITORING AND ASSESSMENT FOR SAFE LARGE-SCALE INFRASTRUCTURES: CHALLENGES AND NEEDS

Many European infrastructures dating back to ’50 and ’60 of the last century like bridges and viaducts are approaching the end of their design lifetime. In most European countries costs related to maintenance of infrastructures reach a quite high percentage of the construction budget and additional costs in terms of traffic delay are due to downtime related to the inspection and maintenance interventions. In the last 30 years, the rate of deterioration of these infrastructures has increased due to increased traffic loads, climate change related events and man-made hazards. A sustainable approach to infrastructures management over their lifecycle plays a key role in reducing the impact of mobility on safety (over 50 000 fatalities in EU per year) and the impact of greenhouse gases emission related to fossil fuels. The events related to the recent collapse of the Morandi bridge in Italy tragically highlighted the sheer need to improve resilience of aging transport infrastructures, in order to increase the safety for people and goods and to reduce losses of functionality and the related consequences. In this focus Structural Health Monitoring (SHM) is one of the key strategies with a great potential to provide a new approach to performance assessment and maintenance over the life cycle for an efficient, safe, resilient and sustainable management of the infrastructures. In this paper research efforts, needs and challenges in terms of performance monitoring, assessment and standardization are described and discussed.The networking support of COST Action TU1402 on ‘Quantifying the Value of Structural Health Monitoring’ and of COST Action TU1406 on ‘Quality specifications for roadway bridges, standardization at a European level (BridgeSpec)

Clinical and genetic characterization of patients with hypertrophic cardiomyopathy and right atrial enlargement

AIMS: Prevalence and clinical significance of right atrial enlargement (RAE) has been poorly characterized in hypertrophic cardiomyopathy. METHODS: One hundred and sixty consecutive patients with hypertrophic cardiomyopathy (35.5 ± 20 years; 64% men) were studied. They underwent clinical examination, standard ECG, M-mode, 2D and Doppler echocardiography, stress test and ECG Holter monitoring. Major adverse cardiac events were considered: cardiac death (sudden death, heart failure death); cardiac transplant; resuscitated cardiac arrest or appropriate implantable cardioverter defibrillator discharge. Genetic analysis of eight sarcomeric genes was performed using Sanger sequencing. RESULTS: RAE was observed in 22 patients (14%), associated with left atrial enlargement in all cases. Patients with RAE were likely to have restrictive mitral pattern (P < 0.001) and had higher New York Heart Association (P < 0.001), N-terminal prohormone of brain natriuretic peptide (P < 0.001), left atrial volume index (P < 0.001), lateral (P = 0.04) and septal (P = 0.002) E/e', systolic pulmonary artery pressure (P < 0.001) and lower ejection fraction (all P < 0.001). On cardiopulmonary exercise testing, peak VO2 was lower and VE/VCO2 higher in patients with RAE (P < 0.001). During a mean follow-up of 4 ± 2.1 years, 30 major adverse cardiac events in 24 patients (15%) were observed. Cox proportional hazards regression analysis identified RAE as an independent predictor of major adverse cardiac events (odds ratio = 2.6; confidence interval 1.5-4.6; P = 0.001). In patients with RAE who were genetically tested, there was a higher prevalence of sarcomeric gene mutations (68%), double mutations (16%) and troponin T mutations (21%). CONCLUSION: RAE is present in a small subset of patients with hypertrophic cardiomyopathy, and largely reflects increased pulmonary pressures because of severe diastolic and/or systolic left ventricular dysfunction. Patients with RAE had a higher prevalence of sarcomeric gene mutations, troponin T mutations and complex genotypes. In conclusion, RAE may serve as a very useful marker of disease progression and adverse outcome in patients with sarcomeric hypertrophic cardiomyopathy

Synthetic Aperture Radar Interferometry for Structural Health Monitoring of Bridges: Potentialities and Open Research Questions

The development of synthetic aperture radar (SAR) interferometry has provided unprecedented opportunities to remotely analyze the behavior of civil structures, transcending traditional limitations associated with in-situ methods. However, while the effectiveness of SAR technology in monitoring wide-area geohazards is demonstrated in several applications, its extension to civil structures, which have a much smaller footprint, requires further investigation of several aspects. This paper investigates the potentialities and challenges connected with the use of SAR technology for civil engineering artifacts, fostered by the availability of remote satellite open data. Recently, the European Space Agency has introduced the European Ground Motion Service (EGMS) under the Copernicus program. This innovative and freely accessible resource provides comprehensive information regarding ground motion across Europe through multitemporal interferometric analysis of Sentinel-1 images acquired since 2015. In this paper the focus is on the Palatino Bridge in Rome, Italy. Data from the ascending and descending orbit are combined to obtain vertical and longitudinal displacements of the structure, allowing for a better estimation of the bridge's response to varying environmental conditions. Results are then compared with those obtained processing high resolution data from COSMO-SkyMed of the Italian Space Agency, showing the consistency of findings

Value of Information Analysis Accounting for Sensor Data Quality: focus on drift

Structural health monitoring plays a crucial role in assessing the condition of civil structures, providing information for regular maintenance and post-disaster emergency management. However, the reliability of structural health monitoring outcomes can be compromised by sensor malfunctions. Over the past two decades, sensor validation tools have been proposed to identify and discard abnormal measurements before extracting information from the structural health monitoring system. The long-term benefits of structural health monitoring systems are commonly evaluated without considering the possibility of faulty sensors. This can lead to suboptimal maintenance decisions. Recently, a Bayesian decision theory-based framework has been introduced to account for different data quality issues and quantify the benefit of implementing a sensor validation tool. This novel approach expands the traditional Value of Information concept to encompass multiple "functioning" states of the structural health monitoring system. This paper mainly focused on a specific data quality issue, i.e., bias or drift in the monitoring outcome. Previous applications of this framework regard simplified decision scenarios, where the monitoring system was either “damaged” or “undamaged”, considering a fixed drift value. In this paper, the impact of uncertain drift levels on the Value of Information in structural health monitoring is investigated, addressing real-world complexities. A numerical case study is considered to illustrate the practical implications of the VoI framework

Incidence and risk factors for pacemaker implantation following aortic valve replacement

Our aim was to identify the predictive factors for permanent pacemaker (PM) implantation in patients undergoing isolated aortic valve replacement (AVR). A total of 3534 patients received an AVR between January 1990 and December 2003 in our institution. Permanent PM implantation was performed in 234 (6.6%) patients, over median time of three days (range one to 24 days). This patient population was compared to a random sample of 191 patients undergoing AVR without permanent PM implantation. The overall mean age was 63.5 years (±14.2) and 261 patients (62%) were male. Univariate and multivariate logistic regression analysis of pre- and perioperative data were performed. Overall the 30 days mortality was 4.2% (10/234) in patients with PM and 1% (2/191) in the control group (P=0.046). Patients with PMs were older (P<0.001), had more additional coronary artery bypass grafting (CABG) surgery or mitral valve replacement (MVR) (P<0.001), complete right bundle branch block (RBBB) prior to surgery, and more frequently underwent re-operations compared to patients without PMs (P<0.001). The multivariate logistic regression model with PM implantation as the dependent variable demonstrated that older age was not independently associated with PM implantation. As independent predictors concomitant severe mitral valve insufficiency, CABG, subaortic stenosis (SAS) or re-do operations were identified

Lightweight vehicles in indirect structural health monitoring: Current advances and future prospects

Recent research has explored the potential of using the dynamic response of passing vehicles to conduct Structural Health Monitoring (SHM) efficiently. Various types of vehicles, including cars, vans, trucks, and even manually propelled carts, have been employed in this approach, with different configurations of exciters and receivers. A noteworthy development in this field involves the inclusion of lightweight vehicles like bicycles and scooters. Lightweight vehicles offer several advantages, including their affordability, sustainability, and minimal environmental impact. These vehicles have a negligible impact on the dynamic behavior of structures due to their low speeds and negligible mass, making them ideal for monitoring structures that are challenging to access, such as footbridges. This paper provides a comprehensive review of recent literature on the application of lightweight vehicles in SHM of urban bridges. It emphasizes the potential benefits and current challenges associated with these applications while offering insights into future research directions

Structural Health Monitoring for Performance Assessment of Bridges under Flooding and Seismic Actions

Bridges can be subjected to damaging environmental actions due to flooding and seismic hazards. Flood actions that result in scour are a leading cause of bridge failure, while seismic actions that induce lateral forces may lead to high ductility demand that exceeds pier capacity. When combined, seismic actions and scour can lead to effects that depend on the governing scour condition affecting a bridge. Loss of stiffness under scour can reduce the ductility capacity of a bridge but can also lead to an increase in flexibility that may reduce seismic inertial forces. Conversely, increased flexibility can lead to deck collapse due to support loss, so there exists some uncertainty about the combined effect of both phenomena. A necessary step towards the performance assessment of bridges under flooding and seismic actions is to calibrate numerical models that can reproduce structural responses under different actions. A further step is verifying the achievement of performance goals defined by codes. Structural health monitoring (SHM) techniques allow the computation of performance parameters that are useful for calibrating numerical models and performing direct checks of performance goal compliance. In this paper, various strategies employed to monitor bridge health against scour and seismic actions are discussed, with a particular focus on vibration-based damage identification methods