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Lennart Elfgren - One of the best experts on this subject based on the ideXlab platform.
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Event-based strain monitoring on a Railway Bridge with a wireless sensor network
Proceedings of the 4th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-4), 2009Co-Authors: Reinhard Bischoff, Ola Enochsson, Glauco Feltrin, Jonas Meyer, Lennart ElfgrenAbstract:This paper presents a monitoring application with a wireless sensor network that was performed on a 95 years old riveted steel Railway Bridge. In order to perform an accurate assessment, strains were monitored on critical elements to catch the real loading during the passage of heavy freight trains. The wireless sensor network deployed on the Bridge consisted of 8 nodes supplied with resistance strain gages and the root node connected to a solar energy rechargeable, battery powered base station. The monitoring system was operated in event-based mode to achieve an energy efficient operation to prolong the lifetime of the sensor network. The event detection was carried out with ultra low power MEMS acceleration sensors, which measured continuously the accelerations of the Bridge and detected an approaching train. If this occurred, the sensor generated an interrupt that immediately switched on the strain gage's conditioning board and starts the measurement. Switching on the conditioning board shortly before starting the measurement, however, produces biased raw data because the strain gage was still heating up due to the current flow. Instead of eliminating the time-dependent bias by adding a dummy gage to the Wheatstone Bridge, the bias was removed by post-processing the raw data. The paper demonstrates that this procedure provides sufficiently accurate input data for use in cycle counting based fatigue assessment of steel Bridges.
Rui Calcada - One of the best experts on this subject based on the ideXlab platform.
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calibration of the numerical model of a stone masonry Railway Bridge based on experimentally identified modal parameters
Engineering Structures, 2016Co-Authors: Cristina Costa, Diogo Ribeiro, P A S Jorge, Ruben Silva, Antonio Arede, Rui CalcadaAbstract:This paper focuses on the calibration of a numerical model of a stone masonry arch Railway Bridge using dynamic modal parameters estimated from an ambient vibration test. The developed 3D numerical model is based on the finite element method, featuring a realistic representation of the Bridge structural components and materials. The calibration methodology relied on a genetic algorithm strategy which allowed estimating and updating numerical model parameters, particularly the elastic properties of materials. The validation of the updated Bridge material properties’ parameters was based on the results of material testing, on existing Bridge design data and on observations resulting from in situ visual inspections.
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probabilistic safety assessment of a short span high speed Railway Bridge
Engineering Structures, 2014Co-Authors: Joao M Rocha, A Henriques, Rui CalcadaAbstract:Abstract A probabilistic methodology for the safety assessment of short span Railway Bridges for high-speed traffic is presented. The purpose is to create a simple, efficient and automatic procedure that allows identifying the critical train speeds over the Bridge and assessing the safety of the train–Bridge system. The methodology combines simulation techniques with the extreme value theory in order to minimise the required computational time and guarantee accurate results. Stochastic simulation is employed as it allows reflecting the real variability of the parameters that characterise the dynamic response of the train–Bridge system. As a case study the safety of a short span filler beam Railway Bridge crossed by a TGV double train is assessed. The behaviour of short span Railway Bridges is known to be particularly difficult to predict due to the complexity of the coupled train–track–Bridge system, as well as for being particularly sensitive to resonant phenomena. The variability of the Bridge, the track and the train was accounted for, as well as the existence of track irregularities. The proposed probabilistic methodology proved to be efficient as it allowed identifying the critical train speeds with a reduced computational cost. Furthermore, for these critical train speeds two different methods were used to estimate the probability of failure. The obtained results showed a good agreement guaranteeing the accuracy of the methodology.
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finite element model updating of a bowstring arch Railway Bridge based on experimental modal parameters
Engineering Structures, 2012Co-Authors: Diogo Ribeiro, Rui Calcada, Raimundo Delgado, Maik Brehm, Volkmar ZabelAbstract:This article describes the calibration of the numerical model of a bowstring-arch Railway Bridge based on modal parameters. An ambient vibration test allowed the identification of the natural frequencies, mode shapes and damping coefficients of several global and local modes of vibration of the Bridge by the application of an output-only technique based on the enhanced frequency domain decomposition method. The calibration was performed using a genetic algorithm that allowed obtaining the optimal values of fifteen parameters of the numerical model. For the mode pairing, a new technique based on the calculation of the modal strain energy was used. The stability of a significant number of parameters, considering different initial populations, proved the robustness of the adopted algorithm in the scope of the optimization of the numerical model. The updated numerical model was validated based on an experimental test for the characterization of the modulus of deformability of the concrete and a dynamic test under Railway traffic. The results showed an excellent agreement between numerical and experimental results.
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safety assessment of a short span Railway Bridge for high speed traffic using simulation techniques
Engineering Structures, 2012Co-Authors: Joao M Rocha, A Henriques, Rui CalcadaAbstract:Abstract The dynamic behaviour of Railway Bridges in high-speed lines has been the subject of several studies in recent years. Nevertheless, most of the work was developed assuming a deterministic perspective. In this paper a probabilistic approach is used to analyse the sensitivity of the dynamic response of a small span Bridge due to the variability of the main structural parameters. A filler beam Railway Bridge was selected as case study and random variables were identified. A variable screening procedure was performed in order to determine which variables had a higher influence on the dynamic response of the Bridge. Simulation techniques were applied to analyse the variability of the dynamic response of the Bridge, as these methods allow an accurate consideration of the randomness of the main structural parameters. Based on the simulation results, a traffic safety assessment of the Bridge was performed. As conclusion, the safety assessment results are discussed, with special focus on the comparison between the results obtained when adopting the European standards approach and when considering a probabilistic approach.
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dynamic analysis of metallic arch Railway Bridge
Journal of Bridge Engineering, 2002Co-Authors: Rui Calcada, A Cunha, Raimundo DelgadoAbstract:This work describes some of the most interesting aspects of the experimental and numerical dynamic analyses of the Luiz I Bridge, an old arch double-deck iron Bridge, when subjected to the moving loads of the new light metro of Porto. Presented are the methodology and computational tools developed, as well as some of the most significant results obtained from numerical simulations conducted on the basis of an experimentally calibrated finite-element model, both in terms of structural safety and of the comfort of pedestrians and train passengers.
Reinhard Bischoff - One of the best experts on this subject based on the ideXlab platform.
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Event-based strain monitoring on a Railway Bridge with a wireless sensor network
Proceedings of the 4th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-4), 2009Co-Authors: Reinhard Bischoff, Ola Enochsson, Glauco Feltrin, Jonas Meyer, Lennart ElfgrenAbstract:This paper presents a monitoring application with a wireless sensor network that was performed on a 95 years old riveted steel Railway Bridge. In order to perform an accurate assessment, strains were monitored on critical elements to catch the real loading during the passage of heavy freight trains. The wireless sensor network deployed on the Bridge consisted of 8 nodes supplied with resistance strain gages and the root node connected to a solar energy rechargeable, battery powered base station. The monitoring system was operated in event-based mode to achieve an energy efficient operation to prolong the lifetime of the sensor network. The event detection was carried out with ultra low power MEMS acceleration sensors, which measured continuously the accelerations of the Bridge and detected an approaching train. If this occurred, the sensor generated an interrupt that immediately switched on the strain gage's conditioning board and starts the measurement. Switching on the conditioning board shortly before starting the measurement, however, produces biased raw data because the strain gage was still heating up due to the current flow. Instead of eliminating the time-dependent bias by adding a dummy gage to the Wheatstone Bridge, the bias was removed by post-processing the raw data. The paper demonstrates that this procedure provides sufficiently accurate input data for use in cycle counting based fatigue assessment of steel Bridges.
Raid Karoumi - One of the best experts on this subject based on the ideXlab platform.
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Life cycle assessment of a Railway Bridge: comparison of two superstructure designs
Structure and Infrastructure Engineering, 2013Co-Authors: Guangli Du, Raid KaroumiAbstract:Railway Bridges currently encounter the challenges of increasing the load capacity while the environmental sustainability should be achieved. However, it has been realized that the environmental assessment of Railway Bridges has not been integrated into the decision making process, the standard guideline and criterion is still missing in this field. Therefore, the implementation of life cycle assessment (LCA) method is introduced into Railway Bridges. This paper provides a systematic Bridge LCA model as a guideline to quantify the environmental burdens for the Railway Bridge structures. A comparison case study between two alternative designs of Banafjal Bridge is further carried out through the whole life cycle, with the consideration of several key maintenance and EOL scenarios. Six impact categories are investigated by using the LCA CML 2001 method and the known LCI database. Results show that the fixed-slab Bridge option has a better environmental performance than the ballasted design due to the ease of maintenances. The initial material manufacture stage is responsible for the largest environmental burden, while the impacts from the construction machinery and material transportations are ignorable. Sensitivity analysis illustrates the maintenance scenario planning and steel recycling have the significant influence on the final results other than the traffic disturbances.
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The application of a damage detection method using Artificial Neural Network and train-induced vibrations on a simplified Railway Bridge model
Engineering Structures, 2013Co-Authors: Jiangpeng Shu, Ziye Zhang, Ignacio Gonzalez, Raid KaroumiAbstract:A damage detection algorithm based on Artificial Neural Network (ANN) was implemented in this study using the statistical properties of structural dynamic responses as input for the ANN. Sensitivity analysis is performed to study the feasibility of using the changes of variances and covariances of the dynamic responses of the structure as input to the ANN. A finite element (FE) model of a one-span simply supported beam Railway Bridge was developed in ABAQUS®, considering both single damage case and multi-damage case. A Back-Propagation Neural Network (BPNN) was built and trained to perform damage detection. A series of numerical tests on the FE model with different vehicle properties was conducted to prove the validity and efficiency of the proposed approach. The results reveal not only that the ANN, together with the statistics, can correctly estimate the location and severity of damage, but also that the identification of the damage location is more difficult than that of the damage severity. In summary, it is concluded that the use of statistical property of the structural dynamic responses as damage index along with the Artificial Neural Network as tool for damage detection for an idealized model of a Bridge is reliable and effective. © 2013 Elsevier Ltd.
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strengthening of a steel Railway Bridge and its impact on the dynamic response to passing trains
Engineering Structures, 2011Co-Authors: Joakim Wallin, John Leander, Raid KaroumiAbstract:Two different strengthening methods for a through-girder steel Railway Bridge are investigated. The studied structure is the Soderstrom Bridge, located in the city of Stockholm, Sweden. Due to fatigue problems, it is in need of assessment and strengthening. In one of the methods, arches are added under the Bridge modifying the structural system and lowering the stress ranges for all structural members. The other method consists of prestressing the floor beams. This increases their stiffness and transforms the mean stress in the lower flanges from tension to compression. A 3D finite element model is created and verified with measurements. The different strengthening methods are tested in the model by dynamic analysis with moving train loads. The strengthening methods show some positive effect concerning the fatigue life. Changes in vertical Bridge deck acceleration for high speed traffic are also presented. A comparison between the European code and the Swedish code regarding vertical Bridge deck acceleration levels for high speed traffic shows large differences for the Bridge.
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simplified analysis of the dynamic soil structure interaction of a portal frame Railway Bridge
Engineering Structures, 2010Co-Authors: Mahir Ulkerkaustell, Raid Karoumi, Costin PacosteAbstract:A qualitative analysis of the dynamic soil-structure interaction (SSI) of a portal frame Railway Bridge based on the linear theory of elasticity is presented. The influence of SSI on the dynamic pr ...
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dynamic testing of a soil steel composite Railway Bridge
Engineering Structures, 2009Co-Authors: Esra Bayoglu Flener, Raid KaroumiAbstract:Actual dynamic response of a long-span corrugated steel culvert Railway Bridge is studied. The Bridge, which is a type of soil-steel composite structures, has a span of 11 m. Tests were carried out ...
Jonas Meyer - One of the best experts on this subject based on the ideXlab platform.
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Event-based strain monitoring on a Railway Bridge with a wireless sensor network
Proceedings of the 4th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-4), 2009Co-Authors: Reinhard Bischoff, Ola Enochsson, Glauco Feltrin, Jonas Meyer, Lennart ElfgrenAbstract:This paper presents a monitoring application with a wireless sensor network that was performed on a 95 years old riveted steel Railway Bridge. In order to perform an accurate assessment, strains were monitored on critical elements to catch the real loading during the passage of heavy freight trains. The wireless sensor network deployed on the Bridge consisted of 8 nodes supplied with resistance strain gages and the root node connected to a solar energy rechargeable, battery powered base station. The monitoring system was operated in event-based mode to achieve an energy efficient operation to prolong the lifetime of the sensor network. The event detection was carried out with ultra low power MEMS acceleration sensors, which measured continuously the accelerations of the Bridge and detected an approaching train. If this occurred, the sensor generated an interrupt that immediately switched on the strain gage's conditioning board and starts the measurement. Switching on the conditioning board shortly before starting the measurement, however, produces biased raw data because the strain gage was still heating up due to the current flow. Instead of eliminating the time-dependent bias by adding a dummy gage to the Wheatstone Bridge, the bias was removed by post-processing the raw data. The paper demonstrates that this procedure provides sufficiently accurate input data for use in cycle counting based fatigue assessment of steel Bridges.