The Herschel-Heterodyne Instrument for the Far-Infrared (HIFI): instrument and pre-launch testing

This paper describes the Heterodyne Instrument for the Far-Infrared (HIFI), to be launched onboard of ESA's Herschel Space Observatory, by 2008. It includes the first results from the instrument level tests. The instrument is designed to be electronically tuneable over a wide and continuous frequency range in the Far Infrared, with velocity resolutions better than 0.1 km/s with a high sensitivity. This will enable detailed investigations of a wide variety of astronomical sources, ranging from solar system objects, star formation regions to nuclei of galaxies. The instrument comprises 5 frequency bands covering 480-1150 GHz with SIS mixers and a sixth dual frequency band, for the 1410-1910 GHz range, with Hot Electron Bolometer Mixers (HEB). The Local Oscillator (LO) subsystem consists of a dedicated Ka-band synthesizer followed by 7 times 2 chains of frequency multipliers, 2 chains for each frequency band. A pair of Auto-Correlators and a pair of Acousto-Optic spectrometers process the two IF signals from the dual-polarization front-ends to provide instantaneous frequency coverage of 4 GHz, with a set of resolutions (140 kHz to 1 MHz), better than < 0.1 km/s. After a successful qualification program, the flight instrument was delivered and entered the testing phase at satellite level. We will also report on the pre-flight test and calibration results together with the expected in-flight performance

Fast fatigue characterization of metallic materials from ancient French railway bridges: a comparative study

International audienc

A self-heating approach to characterize anisotropy effects in fatigue behaviour: application to a nineteenth century puddled iron from a French railway bridge

International audienc

Influence of the MASONRY VAULTS building process on their stiffness: Numerical analysis using a homogenised DAMAGE MODEL including mortar joint shrinkage and induced crack re-closure effect

International audienceThe assessment of masonry structures is more and more useful to characterize the behaviour of masonry walls, tower and bridges. The owner of these constructions would like to understand the mechanical performance of their structures. Experiments and computational methods are two essential elements to accurately study and determine the sensitive points of the edifices. This paper presents the numerical modelling of a vault in undamaged and damaged domain with a macro-homogenisation analysis. The importance of considering the building phases in order to determine the actual stiffness of the structure is highlighted. The numerical tool is a continuous finite element model based on an original anisotropic damage model considering the masonry as a homogenised continuous media. The model is implemented in a massive finite element for three dimensional formulation. It computes the localized damage and allows indicating zones of privileged crack opening in the structure. It is able to predict the cracking zones in large masonry constructions without pre-positioning joint elements. It uses a regularization method ensuring an independence of the numerical response from the mesh. The model includes also a re-closure function for cracks. This re-closure function allows simulating the progressive stiffness restitution during the crack re-closure process. The paper focuses on this aspect in relation with the crack induced by restrained shrinkage of joint mortar during the building history. First, a state of the arts is proposed, then the damage model is presented. In order to validate the model and to propose a global methodology, the damage model is applied to analyse a thin masonry vault previously tested in a laboratory. The numerical results are discussed regarding the experimental ones

Symbolic data analysis and supervised/ non supervised learning algorithms for bridge health monitoring.

In the past few years, numerous methods for damage assessment in connection with structural health monitoring were proposed in the literature. Several problems are raised for making these approaches practical for the engineer. The first concern is to determine whether a structure presents an abnormal behavior or not. Statistical inference is concerned with the implementation of algorithms that analyze the distribution of extracted features in an effort to make decisions on damage diagnosis. Learning algorithms have extensively been applied to classification and pattern recognition problems in the past years and deserve to be used for structural health monitoring. Two approaches are nevertheless available depending on the ability to perform supervised or unsupervised learning. The first group of methods forms the family of classification methods whereas the second group is referred to clustering techniques. In addition, data acquisition campaigns of civil engineering structures can last from several minutes to years. Dealing with large amounts of data is not an easy task and suitable tools are required to correctly extract important features from them. To deal with this issue, symbolic data analysis (SDA) is introduced for managing complex, aggregated, relational, and higher-level data. SDA is then coupled with supervised and non supervised learning algorithms to form a new family of hybrid techniques. From the non supervised learning side, dynamic clouds and hierarchy-divisive method have been used. From the supervised learning side, neural networks and support vector machines have been introduced. All these techniques have been developed within the concept of symbolic data analysis in order to compress data without losing its inherent variability. To highlight the different features of these techniques for structural health monitoring, this paper focuses attention on the monitoring of a railway bridge belonging to the high speed track between Paris and Lyon. During the month of June 2003, a strengthening procedure was carried out in this bridge. In so doing, vibration measurements were recorded under three different structural conditions: before, during and strengthening. In the following years (2004, 2005 and 2006), new tests were performed to observe how the dynamic behavior of the bridge evolved, especially for the case of frequency changes. The objective was to verify whether the strengthening procedure was still effective or not, in order terms if the new data could be still assigned to the condition ?after strengthening?. This paper reports the major results obtained and shows how the techniques can be applied to cluster structural behaviors and classify new data

Fast characterization of fatigue properties of an anisotropic metallic material: application to a puddled iron from a nineteenth century French railway bridge

International audienc

Instrumentation of the Avesnes/Helpe bridge

This paper details the different instrumentations installed on the Avesnes/Helpe bridge between 2005 and 2007 in France for recording its structural response and its loading conditions during a two-days monitoring campaign (June 2005), for performing dynamic assessments (March 2006) and for detecting damages (June 2006, March 2007). The first series of tests were performed when the bridge was still operated by the French railways SNCF. In August 2005, the bridge was removed from operating conditions and conserved for research and demonstration purposes within the Sustainable Bridges project