Le Touquet – Paris-Plage, France
Le Touquet – Paris-Plage, France

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Cremona C.,Bouygues Travaux Publics | Cremona C.,Technical Center for Bridge Engineering | Poulin B.,West Territorial Direction
Structure and Infrastructure Engineering | Year: 2016

In recent years, the condition of deficient bridges has reached such a level that the volume of required repair actions becomes significant for many countries. As budgets for maintenance, repair and rehabilitation are always limited and demands are constantly increasing, to find an optimal balance between cost and safety is today a new trend in bridge maintenance. Optimising bridge maintenance and management is a strong expectation for owners and stakeholders facing ageing bridge stocks and increasing aggressive traffic. In this context, the assessment of the structural performance may be necessary for various reasons thorough its lifetime. In France, there are no standards or regulations for structural assessment of existing structures. The studies on a new Eurocode standard for the ‘Evaluation and rehabilitation of existing structures’ are just starting and it will be published in several years. For this reason, the French Ministry of Transport has decided to develop recommendations for the assessment of the structural performance of existing bridges. In a first part, the paper summarises today’s practice in France, but it also details the ongoing calibration process for setting appropriate partial factors for existing bridges. Implementation is given as example for the assessment of reinforced concrete slabs. © 2016 Informa UK Limited, trading as Taylor & Francis Group


Cury A.,University of Ouro Preto | Cremona C.,Technical Center for Bridge Engineering
Mechanical Systems and Signal Processing | Year: 2012

For reliable performance of vibration-based damage detection algorithms, it is important to distinguish abnormal changes in modal parameters caused by structural damage from normal changes due to environmental fluctuations. This paper firstly addresses the modeling of temperature effects on modal frequencies of a PSC box girder bridge located on the A1 motorway in France. Based on a six-month monitoring experimental program, modal frequencies of the first seven mode shapes and temperatures have been measured at three hour intervals. Neural networks are then introduced to formulate regression models for quantifying the effect of temperature on modal parameters (frequencies and mode shapes). In 2009, this bridge underwent a strengthening procedure. In order to assess the effect of strengthening on the vibration characteristics of the bridge, modal properties had to be corrected from temperature influence. Thus, the first goal is to assess the changes on the vibration signature of this bridge induced by the strengthening. For this purpose, classical statistical analysis and clustering methods are applied to the data recorded over the period after strengthening. The second goal is to evaluate the influence of temperature effects on the clustering results. It comes that the temperature correction significantly improves the confidence in the novelty detection and in the strengthening efficiency. © 2012 Elsevier Ltd.


Santos J.P.,National Laboratory for Civil Engineering | Cremona C.,Technical Center for Bridge Engineering | Orcesi A.D.,IFSTTAR | Silveira P.,National Laboratory for Civil Engineering
Engineering Structures | Year: 2013

A large amount of researches and studies have been recently performed by applying statistical methods for vibration-based damage detection. However, the global character inherent to the limited number of modal properties issued from operational modal analysis may be not appropriate for early damage, which has generally a local character.The present paper aims at detecting this type of damage by using static SHM data and by assuming that early damage produces dead load redistribution. To achieve this objective a data driven strategy is proposed, consisting in the combination of advanced multivariate statistical methods and quantities, such as principal components, symbolic data and cluster analysis.From this analysis it was observed that, under the noise levels measured on site, the proposed strategy is able to automatically detect stiffness reduction in stay cables reaching at least 1%. © 2013 Elsevier Ltd.


de Oliveira Dias Prudente dos Santos J.P.,National Laboratory for Civil Engineering | Cremona C.,Technical Center for Bridge Engineering | da Silveira A.P.C.,National Laboratory for Civil Engineering | de Oliveira Martins L.C.,University of Lisbon
Structural Concrete | Year: 2016

Structural health monitoring (SHM) can be defined as the process of developing and implementing structural damage detection strategies. Ideally, this detection should be carried out in real time before damage reaches a critical state and impairs structural performance and safety. Hence, it must be based on sensorial systems permanently installed on the target structures and on fully automatic detection methodologies. The ability to detect damage in real-time is vital for controlling the safety of old structures or for post-retrofitting/post-accident situations, where it might even be mandatory for ensuring a safe service. Under these constraints, SHM systems and strategies must be capable of conducting baseline-free damage identification, i.e. they must not rely on comparing newly acquired data with baseline references in which structures must be assumed as undamaged. The present paper describes an original strategy for baseline-free damage detection based on the application of artificial neural networks and clustering methods in a moving windows process. The proposed strategy was tested on and validated with numerical and experimental data obtained from a concrete cable stayed bridge and proved effective for the automatic detection of small stiffness reductions in single stay cables as well as the detachment of neoprene pads in anchoring devices, requiring only a small number of inexpensive sensors. © 2016 Ernst & Sohn Verlag für Architektur und technische Wissenschaften GmbH & Co. KG, Berlin.


Cremona C.,Technical Center for Bridge Engineering | Eichler B.,RWTH Aachen | Johansson B.,Lulea University of Technology | Larsson T.,Lulea University of Technology
Journal of Bridge Engineering | Year: 2013

A large number of railway structures in Europe are metallic bridges. The increasing volume of traffic and axle weight of trains mean that, for many structures, the loads today are much higher than those envisaged when they were designed. This paper presents a summary of the different recommendations and advice proposed in European guidelines for assessing load and resistance of railway bridges issued from a research project. The knowledge of the material properties of existing metallic bridges is essential for the resistance assessment and the determination of the remaining lifetime of old metallic bridges. Furthermore, old bridges require more exact and efficient assessment methods that call for a precise description of the material. Among the problems met in metallic structures and material properties estimation, fatigue is the most common cause of failure. To be able to make accurate assessments of existing bridges, it is important to know the behavior of bridges exposed to fatigue and how the old materials behave owing to cyclic exposure. The main question answered in this paper is how to make a safe estimation concerning the remaining life in service. The possible traffic load on steel rail bridges is usually limited by the fatigue resistance, but for certain situations the static resistance also has to be checked. Most design rules for steel structures are applicable also to riveted structures. However, some information is missing on how to deal with the special case when elements are intermittently connected in contrast to welded structures that are connected continuously. Because the traditional methods for assessing the resistance of steel bridges are based on elastic analysis, a method for utilizing a limited redistribution of bending moments based on beam theory is proposed. © 2013 American Society of Civil Engineers.


Bouteiller V.,University Paris Est Creteil | Cremona C.,Technical Center for Bridge Engineering | Baroghel-Bouny V.,University Paris Est Creteil | Maloula A.,University Paris Est Creteil
Cement and Concrete Research | Year: 2012

The ingress of chlorides in cylindrical reinforced concretes based on ordinary Portland cement (OPC) or ground granulated blast furnace slag cement (GGBS) has been investigated together with the corrosion behaviour of the steel rebar. Chloride exposure was obtained by wetting and drying cycles during one to two years. The evolution of total and free chloride contents versus time of exposure shows that GGBS concretes induced a delay in chloride ingress. Corrosion initiation of steel was evaluated through nondestructive electrochemical measurements (half cell potential and linear polarization resistance) versus time of exposure. For GGBS concretes, corrosion assessment was not reliable based on the ASTM standard or RILEM recommendations. For OPC concretes, the transition from passive to active corrosion was studied considering a drop of potential or a corrosion current threshold value. Considering this latter, total and free chloride contents larger than 2.2% or 0.7% by weight of cement were estimated. © 2012 Elsevier Ltd. All rights reserved.


Santos J.P.,National Laboratory for Civil Engineering | Orcesi A.D.,University Paris Est Creteil | Cremona C.,Technical Center for Bridge Engineering | Silveira P.,National Laboratory for Civil Engineering
Structure and Infrastructure Engineering | Year: 2015

This article addresses the subject of data-driven structural health monitoring and proposes a real-time strategy to conduct structural assessment without the need to define a baseline period, in which the monitored structure is assumed healthy and unchanged. Independence from baseline references is achieved using unsupervised discrimination machine-learning methods, widely known as clustering algorithms, which are able to find groups in data relying only on their intrinsic features and without requiring prior knowledge as input. Real-time capability is based on the definition of symbolic data, which allows describing large amounts of information without loss of generality or structural-related information. The efficiency of the proposed methodology is illustrated using an experimental case study in which structural changes were imposed to a suspended bridge during an extensive rehabilitation programme. A single-value novelty index capable of describing multi-sensor data is proposed, and its effectiveness in identifying structural changes in real time, using outlier analysis, is discussed. © 2015, © 2014 Taylor & Francis.


Alves V.,Federal University of Ouro Preto | Cury A.,Federal University of Juiz de fora | Roitman N.,Federal University of Rio de Janeiro | Magluta C.,Federal University of Rio de Janeiro | Cremona C.,Technical Center for Bridge Engineering
Structural Control and Health Monitoring | Year: 2015

Structural health monitoring is a problem that can be addressed at many levels. One of the most promising approaches used in damage assessment problems is based on pattern recognition. The idea is to extract features from data that characterize only the normal condition and to use them as a template or reference. During structural monitoring, data are measured, and appropriate features are extracted as well as compared with the reference. Any significant deviations are considered as signal novelty or possible damage. Several studies present in the literature are based on the comparison of measured vibration data such as natural frequencies and vibration modes in undamaged and damaged states of the structure. This methodology has proven to be efficient; however, its application may not be the most adequate in cases where the engineer needs to know with certain imperativeness the condition of a given structure. This paper proposes a novelty detection approach where the concept of symbolic data analysis is used to manipulate raw vibration data (i.e., acceleration measurements). These quantities (transformed into symbolic data) are combined to three unsupervised classification techniques: hierarchy agglomerative, dynamic clouds and soft c-means clustering. In order to attest the robustness of this approach, experimental tests are performed on a simply supported beam considering different damage scenarios. Moreover, this paper presents a study with tests conducted on a motorway bridge, in France, where thermal variation effects also play a major role. In summary, results obtained confirm the efficiency of the proposed methodology. © 2015 John Wiley & Sons, Ltd.


Alves V.,Federal University of Ouro Preto | Cury A.,Federal University of Juiz de fora | Cremona C.,Technical Center for Bridge Engineering
Proceedings of the Institution of Civil Engineers: Structures and Buildings | Year: 2016

Structural health monitoring is based on the development of reliable and robust indicators able to detect, locate, quantify or even predict damage. Studies related to damage detection in civil engineering structures are of interest to researches in this area. Indeed, the detection of structural changes likely to become critical can prevent the occurrence of major dysfunction associated with social, economic and environmental consequences. Recently, many researchers have focused on dynamic assessment as part of structural diagnosis. Most of the studied techniques are based on time or frequency domain analyses to extract information from modal characteristics or based on indicators built from those parameters. The main goal of this study relies on the application of symbolic data analysis coupled with classification methods to detect structural damage, especially using raw data (i.e. in situ measurements). Modal parameters, such as natural frequencies and mode shapes, are also considered in the analysis. In order to attest to the efficiency of the proposed approach, experimental investigations in the laboratory and on two real case studies–railway and motorway bridges–are carried out. It is shown that symbolic data analysis coupled with classification methods is able to distinguish structural conditions with very encouraging results. © 2016, Thomas Telford Services Ltd. All rights reserved.


Cremona C.,Technical Center for Bridge Engineering
Bridge Maintenance, Safety, Management and Life Extension - Proceedings of the 7th International Conference of Bridge Maintenance, Safety and Management, IABMAS 2014 | Year: 2014

In recent years, the state of deterioration of the bridges' stock has been such that the volume of necessary works has reached un-manageable proportions in many countries. As budgets for maintenance, repair and rehabilitation are always limited and demands are constantly increasing, to find an optimal balance between cost and safety is today a new trend in bridge maintenance. Optimizing bridge maintenance and management is a strong expectation for owners and stakeholders facing aging bridge stocks and increasing aggressive traffic. In this context, the assessment of the structural performance may be necessary for various reasons thorough its lifetime. However, there are no standards or regulations on structural assessment in France compared to some countries. The studies upon a new Eurocode for the "Evaluation and rehabilitation of existing structures" are just starting and it will not be available before several years. For this reason, the French Ministry of Transport has decided to develop recommendations for the assessment of the structural performance of existing bridges. The paper summarizes today's practice and details the research work engaged in the calibration of appropriate partial factors for existing structures when investigation results are available. © 2014 Taylor & Francis Group.

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