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F. Besseling
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1
Smart Aggregates and Wave Interferometry in Short-Term Static Load Tests on Zeeland Bridge
Insights from an Ongoing Two-Year Field Lab
The Zeeland Bridge (Zeelandbrug) is a 5 km multi-span prestressed-concrete bridge in the Province of Zeeland, the Netherlands, completed in 1964. To reduce the uncertainties inherent in structural re-assessment, a dedicated two-year field lab has been established, focusing on long-term monitoring and targeted load testing. Within this field lab, four cross-sections across two typical spans have been instrumented with Smart Aggregates (SA) (embedded piezoelectric transducers), Fiber Bragg Grating (FBG) strain sensors, and numerous temperature and humidity sensors. The latter enables compensation for environmental effects. Static load tests were conducted using a 50-tonnes truck at different positions across the spans. Wave Interferometry (WI) was applied to the SA signals to extract wave velocity changes; these changes are potential indicators of microstructural changes or stress redistribution. The preliminary results obtained during the static load tests at different loading conditions revealed changes in wave velocity in the concrete. These findings are compared with local strain measurements from co-located FBG sensors. This enables combined analysis of both wave velocity changes and strains under static loads. The outcomes of this research will not only improve the understanding of the structural behaviour of typical spans of the Zeeland Bridge under static load conditions, but also assess the feasibility of using SAs and WI technology for long-term structural health monitoring of concrete bridges.
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The Zeeland Bridge (Zeelandbrug) is a 5 km multi-span prestressed-concrete bridge in the Province of Zeeland, the Netherlands, completed in 1964. To reduce the uncertainties inherent in structural re-assessment, a dedicated two-year field lab has been established, focusing on long-term monitoring and targeted load testing. Within this field lab, four cross-sections across two typical spans have been instrumented with Smart Aggregates (SA) (embedded piezoelectric transducers), Fiber Bragg Grating (FBG) strain sensors, and numerous temperature and humidity sensors. The latter enables compensation for environmental effects. Static load tests were conducted using a 50-tonnes truck at different positions across the spans. Wave Interferometry (WI) was applied to the SA signals to extract wave velocity changes; these changes are potential indicators of microstructural changes or stress redistribution. The preliminary results obtained during the static load tests at different loading conditions revealed changes in wave velocity in the concrete. These findings are compared with local strain measurements from co-located FBG sensors. This enables combined analysis of both wave velocity changes and strains under static loads. The outcomes of this research will not only improve the understanding of the structural behaviour of typical spans of the Zeeland Bridge under static load conditions, but also assess the feasibility of using SAs and WI technology for long-term structural health monitoring of concrete bridges.
Conference paper
(2026)
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Julie Rodet, Floris Besseling, Aurélien Croze, Steven Mookhoek, Mari Lourens
This paper presents a pioneering application of Distributed Fibre Optic Sensing (DFOS) technology for the dynamic response monitoring of the Zeeland Bridge, a 5 km long cantilever-balanced prestressed concrete bridge. The study explores the feasibility and potential of using pre-installed single-mode telecommunication fibres, embedded within ducts inside the bridge structure, as a sensing network for large-scale structural health monitoring. Spatially high-resolution dynamic strain measurements were performed under two distinct loading scenarios: (i) a controlled bridge closure during which a test vehicle was driven over the deck, and (ii) normal operational conditions under ambient traffic. These measurement campaigns allowed for the evaluation of the bridge’s dynamic behaviour under both controlled and operational loading conditions. The DFOS system successfully captured vibration signatures induced by both test and ambient loads, demonstrating its capability to detect dynamic responses over the entire monitored length of the structure. The results highlight the effectiveness of leveraging existing telecom fibre infrastructure for distributed, continuous, and minimally invasive monitoring. Ongoing data analysis focuses on identifying clear correlations between locally varying structural characteristics of the bridge and its dynamic response. These correlations are expected to provide valuable insights into the bridge’s dynamic properties and spatial variability, contributing to an improved understanding of its structural behaviour. Overall, this study demonstrates the strong potential of DFOS technology combined with existing telecommunication fibres for the long-term monitoring of large-scale civil infrastructure. The proposed approach offers a promising pathway towards more efficient asset management, condition assessment, and maintenance strategies for ageing bridge structures.
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This paper presents a pioneering application of Distributed Fibre Optic Sensing (DFOS) technology for the dynamic response monitoring of the Zeeland Bridge, a 5 km long cantilever-balanced prestressed concrete bridge. The study explores the feasibility and potential of using pre-installed single-mode telecommunication fibres, embedded within ducts inside the bridge structure, as a sensing network for large-scale structural health monitoring. Spatially high-resolution dynamic strain measurements were performed under two distinct loading scenarios: (i) a controlled bridge closure during which a test vehicle was driven over the deck, and (ii) normal operational conditions under ambient traffic. These measurement campaigns allowed for the evaluation of the bridge’s dynamic behaviour under both controlled and operational loading conditions. The DFOS system successfully captured vibration signatures induced by both test and ambient loads, demonstrating its capability to detect dynamic responses over the entire monitored length of the structure. The results highlight the effectiveness of leveraging existing telecom fibre infrastructure for distributed, continuous, and minimally invasive monitoring. Ongoing data analysis focuses on identifying clear correlations between locally varying structural characteristics of the bridge and its dynamic response. These correlations are expected to provide valuable insights into the bridge’s dynamic properties and spatial variability, contributing to an improved understanding of its structural behaviour. Overall, this study demonstrates the strong potential of DFOS technology combined with existing telecommunication fibres for the long-term monitoring of large-scale civil infrastructure. The proposed approach offers a promising pathway towards more efficient asset management, condition assessment, and maintenance strategies for ageing bridge structures.
Accurate model updating is essential for reliable structural assessment and performance prediction of civil infrastructure. Classical Bayesian model updating approaches, while powerful, are often limited by their reliance on predefined parametric distributions, and by the computational burden of sampling-based inference, which becomes prohibitive as the number of updating parameters increases. These limitations hinder their applicability to complex structures where high-dimensional parameter spaces and uncertain parameter-output relations are prevalent. The restriction on the number of updating parameters often leads to a mismatch between the global-level formulation of the updating problem and the local structural behavior or failure mechanisms of interest. To address these limitations, this paper proposes a novel model updating framework that integrates load test data, Finite Element Modelling (FEM), and Copula-Based Bayesian Networks (CBBNs). The approach uses load test measurements to calibrate FEM parameters, and employs CBBNs to efficiently capture complex dependencies among model variables. This paper presents the framework’s formulation and implementation, along with key verification steps. The flexibility and computational tractability of the CBBN-based framework make it particularly suited for structural engineering applications, contributing to more reliable data-driven asset management.
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Accurate model updating is essential for reliable structural assessment and performance prediction of civil infrastructure. Classical Bayesian model updating approaches, while powerful, are often limited by their reliance on predefined parametric distributions, and by the computational burden of sampling-based inference, which becomes prohibitive as the number of updating parameters increases. These limitations hinder their applicability to complex structures where high-dimensional parameter spaces and uncertain parameter-output relations are prevalent. The restriction on the number of updating parameters often leads to a mismatch between the global-level formulation of the updating problem and the local structural behavior or failure mechanisms of interest. To address these limitations, this paper proposes a novel model updating framework that integrates load test data, Finite Element Modelling (FEM), and Copula-Based Bayesian Networks (CBBNs). The approach uses load test measurements to calibrate FEM parameters, and employs CBBNs to efficiently capture complex dependencies among model variables. This paper presents the framework’s formulation and implementation, along with key verification steps. The flexibility and computational tractability of the CBBN-based framework make it particularly suited for structural engineering applications, contributing to more reliable data-driven asset management.
To reduce uncertainties associated with its structural reassessment, the Zeeland Bridge in the Netherlands is currently the subject of a field lab, which will run for 2 years. In this contribution, numerical investigations to study the dependencies between variables associated with uncertain structural properties of the bridge and various response/measurement quantities are presented. Initial focus is on load testing of the bridge to obtain insight into the possibly varying response in different spans of the bridge. Parametric studies to expose input-output parameter dependencies are performed on a representative subsystem of the bridge, and the results are used to assist in the design of a measurement campaign and the development of a robust model updating strategy for the bridge.
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To reduce uncertainties associated with its structural reassessment, the Zeeland Bridge in the Netherlands is currently the subject of a field lab, which will run for 2 years. In this contribution, numerical investigations to study the dependencies between variables associated with uncertain structural properties of the bridge and various response/measurement quantities are presented. Initial focus is on load testing of the bridge to obtain insight into the possibly varying response in different spans of the bridge. Parametric studies to expose input-output parameter dependencies are performed on a representative subsystem of the bridge, and the results are used to assist in the design of a measurement campaign and the development of a robust model updating strategy for the bridge.
The concrete slab bridge on Balladelaan in the Netherlands was built in 1946. It is a cast-in-place concrete bridge with five spans that together form a statically indeterminate deck system. For this type of concrete bridge, shear failure often appears to be the critical failure mechanism, raising concerns about the structural capacity and remaining service life of the bridge. Additionally, the bridge has undergone several undocumented modifications over its lifetime, making it difficult to accurately assess its safety. To monitor this bridge and predict its structural capacity, 22 ultrasonic sensors, known as Smart Aggregates (SAs), and 16 temperature sensors were embedded in the bridge by drilling holes to track changes such as crack development, stress variations, and temperature fluctuations. This paper presents the initial phase measurements from the SAs and temperature sensors in the monitoring project. The main goals of this phase are (1) to ensure that the installed sensors function properly and (2) to establish a preliminary correlation between the measurements from the SAs and the temperature sensors.
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The concrete slab bridge on Balladelaan in the Netherlands was built in 1946. It is a cast-in-place concrete bridge with five spans that together form a statically indeterminate deck system. For this type of concrete bridge, shear failure often appears to be the critical failure mechanism, raising concerns about the structural capacity and remaining service life of the bridge. Additionally, the bridge has undergone several undocumented modifications over its lifetime, making it difficult to accurately assess its safety. To monitor this bridge and predict its structural capacity, 22 ultrasonic sensors, known as Smart Aggregates (SAs), and 16 temperature sensors were embedded in the bridge by drilling holes to track changes such as crack development, stress variations, and temperature fluctuations. This paper presents the initial phase measurements from the SAs and temperature sensors in the monitoring project. The main goals of this phase are (1) to ensure that the installed sensors function properly and (2) to establish a preliminary correlation between the measurements from the SAs and the temperature sensors.
Rail vibrations cause nuisance to people living near rail transport routes. Especially cargo transport is known to cause the highest vibration levels. The Netherlands have an intensively used railway network, forming one of the important cargo transport corridors from the Port of Rotterdam to other countries in Europe. With increasing use of the rail network, both in terms of the number of trains and higher speed of passenger trains, nuisance caused by rail vibrations is expected to increase as well. ProRail, the operator of the rail network in The Netherlands, has lauched the 'Innovatieagenda Bronaanpak Spoortrillingen' (IBS) research programme in order to develop more knowledge about rail vibrations and evaluate the effectiveness of potential mitigating measures. One of the project under this IBS research programme specifically addresses the contribution of train wheel defects to rail vibrations and their effects on nearby buildings. Witteveen+Bos is executing this project, working closely with ProRail and it's scientific partners. A measurement setup was developed optimized for linking ground vibrations to train wheels. This measurement setup has been operated at different locations along the Dutch rail network. Data analysis of the monitoring results has generated interesting insights into the characteristics of ground vibrations caused by train passages and the contribution wheel defects may have.
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Rail vibrations cause nuisance to people living near rail transport routes. Especially cargo transport is known to cause the highest vibration levels. The Netherlands have an intensively used railway network, forming one of the important cargo transport corridors from the Port of Rotterdam to other countries in Europe. With increasing use of the rail network, both in terms of the number of trains and higher speed of passenger trains, nuisance caused by rail vibrations is expected to increase as well. ProRail, the operator of the rail network in The Netherlands, has lauched the 'Innovatieagenda Bronaanpak Spoortrillingen' (IBS) research programme in order to develop more knowledge about rail vibrations and evaluate the effectiveness of potential mitigating measures. One of the project under this IBS research programme specifically addresses the contribution of train wheel defects to rail vibrations and their effects on nearby buildings. Witteveen+Bos is executing this project, working closely with ProRail and it's scientific partners. A measurement setup was developed optimized for linking ground vibrations to train wheels. This measurement setup has been operated at different locations along the Dutch rail network. Data analysis of the monitoring results has generated interesting insights into the characteristics of ground vibrations caused by train passages and the contribution wheel defects may have.