ce/papers最新文献

Climate change is altering the operating conditions of critical infrastructures (CI) and jeopardizing the objectives for which they were designed. It is therefore necessary to adapt these infrastructures or to strengthen their fitness in order to bring their functionality to an appropriate level. One way to do this is to support them with nature-based solutions (NbS). In this contribution, a probabilistic based decision-making tool will be presented that was developed by a group of experts involved in the NATURE-DEMO Horizon project based on the Dutch RAMSSHE€P approach. It allows to efficiently use NbS to protect CI against natural hazards and climate change effects. The challenges in linking natural hazards and NbS with the classic RAMSSHE€P assessment of infrastructure lie in the complexity of natural hazards, their cascading effects, their dependence on the region-specific environment and the natural conditions. In the case of NbS, there are also their temporal and ecological dependencies. The developed decision-making system makes it possible to integrate the effectiveness of NbS and natural hazards into a RAMSSHE€P asset management system that can also be used by regional and supra-regional experts.

Climate change is a major cause of economic loss particularly as hazards are becoming more frequent and intense. In addition, climate change introduces new patterns and variations that historical data alone cannot capture, necessitating a shift in design methodologies to account for future conditions over the entire life cycle of infrastructure projects. Infrastructure requires behavioral or structural health analysis for more accurate lifecycle risk assessment. The NATURE-DEMO project aims to use Earth Observation InSAR interferometry derived products to validate the use of Nature-based Solutions (NbS) for the protection of vulnerable infrastructure. This paper highlights the importance of ongoing monitoring and adaptation to ensure their resilience and functionality in a changing climate. It also discusses the need for a harmonized resilience assessment methodology that can reduce the impact and the consequences for short, medium and long-term events affecting infrastructures by means of the latest GIS/BIM mapping technologies.

In the framework of the Horizon Europe project SETO we investigated the integration of the RAMSHEEP and reliability analysis into bridge asset management and life cycle cost analysis with special emphasis on the impact of overloading of vehicles on bridge service life and availability in the context of an ageing bridge stock. For this we conducted an extensive investigation into bridge costs for construction, rehabilitation and operation, different performance functions and impact of rehabilitation measures. Based on the age distribution and standardized bridge life cycles we investigated current challenges regarding investment needs and possible strategies to ensure a reliable, available and safe bridge network based on the bridge network of regional roads in the province of Styria, Austria.

The service life and reliability of civil engineering structures are essential to achieving sustainable infrastructure development. This paper investigates how deviations in material properties, construction practices, and evolving load demands influence structural performance over time. It highlights the importance of data-driven reliability assessments and demonstrates how partial safety factors can be recalibrated to extend the service life of both new and existing structures while maintaining defined reliability targets. The study explores the relationship between service life duration, consequence classes, and reliability indices, with a particular focus on structures designed for 50, 100, and 150 years. Practical applications are demonstrated using calculation methods for safety indices and thresholds for partial safety factors. The findings contribute to a framework for performance-based evaluations, ensuring continued safety and cost-effective infrastructure management.

This paper proposes a novel approach for Structural Health Monitoring (SHM) of cable-stayed bridges that utilizes load cell recordings for both static tension monitoring and vibration-based assessment. By capturing high-frequency force fluctuations, load cells enable Ambient Vibration Testing (AVT), which supports the identification of bridge dynamic properties through Operational Modal Analysis (OMA). This dual-purpose use of load cells offers a cost-effective alternative to conventional systems, reducing the number of required sensors and associated data management efforts. A key challenge addressed is the Optimal Sensor Placement (OSP) of load cells to ensure monitoring efficiency while minimizing cost and data overload. To this end, the paper introduces a new OSP algorithm tailored to identify the most informative stays for monitoring. The methodology is validated through a real-world case study involving a cable-stayed bridge with 40 stay cables, where only 8 were instrumented. Results demonstrate the effectiveness of the proposed strategy in capturing both static and dynamic structural behaviours, underscoring its potential for advanced, force-based SHM in cable-stayed bridges.

In vibration-based structural health monitoring (SHM) modal parameters from operational modal analysis help assess structural safety condition, especially after earthquakes. Finite element model updating (FEMU) techniques provide support in analysing SHM data and enable more reliable previsions about the damage state of monitored structures. Linear modelling assumption is valid while the structure remains elastic but become unreliable after earthquake-induced damage introduces nonlinear behaviour. This study examines how accurately the dynamic behaviour of an infilled reinforced concrete frame building can be simulated, under both ambient noise and low-intensity earthquakes, using linear FEMU techniques. The study starts by analysing the building's real response to ambient and seismic excitations. The research then focuses on the calibration of FE models, using the Particle Swarm Optimization and following three FEMU approaches based on both pre-event modal data and actual time history data from the earthquake. The accuracy of calibrated models in replicating the building's response is evaluated, also focusing on their usefulness for post-earthquake assessment. Finally, optimisation outcomes for the three approaches are compared to assess the strengths and weakness of each.

The integration of precise positioning technologies in transportation systems is increasingly essential for enhancing automation and operational efficiency. Post-Processing Kinematic (PPK) combined with Global Navigation Satellite Systems (GNSS) presents a promising solution for achieving accurate and reliable vehicle position monitoring. This study provides a comprehensive evaluation of the accuracy and feasibility of PPK-GNSS in simulated vehicle tracking. Key factors influencing accuracy, such as satellite geometry, atmospheric and multipath errors, and real-time corrections, are thoroughly examined. To further enhance positioning accuracy, a Kalman filter is applied to refine vehicle trajectory estimations. By analyzing existing research and case study results, this study highlights the advantages of PPK-GNSS, particularly its capability for high-precision vehicle tracking in open environments. The findings underscore the potential of PPK-GNSS in improving highway transportation digitalization, offering valuable insights for the advancement of intelligent transportation systems.

Scour, the erosion of sediment around bridge foundations caused by water flow, poses a serious threat to structural stability, particularly during high-water events such as floods. Network Rail has identified scour as the leading cause of bridge failures in the UK over the past century, with approximately 4500 structures currently at risk. This paper underscores the urgent need for enhanced scour monitoring, a need that is increasingly important due to the rising frequency of flood events driven by climate change. It critically reviews recent advances in scour monitoring technologies, focusing on systems that measure scour depth or detect structural dynamic changes. The review highlights emerging methods including interferometric synthetic aperture radar, water penetrating radar, electromagnetic probes, underwater sonar scanning, as well as vibration-based techniques such as natural frequency, mode shape and operating deflection shape analysis, and indirect approaches using drive-by monitoring, computer vision, and satellite-based synthetic aperture radar. These advancements are needed for developing more resilient infrastructure management strategies and the paper includes a comparative evaluation of the benefits and limitations of each approach.

Post-tensioned Gerber bridges represent a critical component in transportation networks, combining structural efficiency with ease of construction. However, their complex mechanical behaviour and the effects of long-term loading demand advanced methodologies for accurate assessment and maintenance. This work provides some insights in using advanced NDTs for the evaluation of residual prestressing of the ‘Unità d'Italia’ bridge, located in Verona, a half-joint PRC bridge. Considerations related to the effectiveness of the analytical process, and future implications for similar bridge types are provided in order to give practitiones useful guidelines when dealing with the structural assessment of similar structural types, supporting more informed decision making in the management of post-tensioned Gerber bridges within the frame of Level 4 analysis within the Italian Guidelines for Assessment of Existing Bridges (2022).

The fourth industrial revolution has driven technological advancements in construction, particularly in safety inspection and the development of taller structures. Traditional structural inspections, relying on contact-based methods, are costly, time-consuming, and pose safety risks for inspectors, with issues of data subjectivity. As a result, there is a need for more efficient, non-contact defect detection techniques. Infrared thermography has emerged as a promising non-destructive testing method, widely used in detecting defects in concrete structures; however, its application in to identify welding defects in steel structures remains underexplored. This study aims to detect welded defects in steel structures swiftly and accurately using infrared thermography. Test specimens with artificial defects were fabricated and evaluated using the passive infrared method. Thermal images and surface temperature data of defective and normal welds were analyzed, with defect presence determined based on the standard deviation of weld temperature. The passive method, conducted outdoors, revealed significant differences in standard deviation between defective and normal parts, demonstrating the potential of infrared thermography for effectively detecting welding defects in steel structures.