Sensing, data processing and modelling

The main objective of this joint research activity is the implementation and application of new types of sensors, control techniques and modelling tools capable of enhancing the measurement of the response of test specimens and improving the quality of test control. The activity also aims at developing numerical simulation tools, integrated with data processing, databases and visualisation, for an improved design of test campaigns and for enhanced interpretation of experimental results.

New types of instrumentation (wireless, fibre optics and 3D visualization tools based on several individual sensor measurements or digital video-photogrammetry) and techniques for improved testing control and for measuring structural and foundation response (point and field, local and global kinematic measurements, etc.) will be explored. Experiments at different levels of complexity will be carried out to calibrate and validate the proposed instrumentation and techniques.

Software will be developed for processing data from experiments on structures/infrastructures and foundations, for database management and for detection of errors generated by sensors or actuators. Modelling tools, data processing software and databases will be improved with the ultimate purpose of better design of the testing equipment and interpretation of experimental results. Requirements for data generated from physical tests and conforming to the distributed database, will be identified, for calibration and development of numerical models and for damage assessment. These numerical tools will be integrated in a common software platform and system environment.

Regarding data assimilation and model updating, the scope is the improvement in design of testing equipment and set up and of interpretation of experimental results, using FE codes, data processing software and databases. Techniques to be employed will be based on data assimilation to identify testing equipment and specimen by combining observational data with the state of the dynamic system. Using sophisticated concepts and updating techniques, a virtual model of the equipment, test facility and specimen will be built. This will allow reducing the number of calibration pre-tests, optimising the number and location of sensors and improving the quality of results.

Released Deliverables:

WP13 Report on advanced sensors, vision systems and control techniques for measuring structural/foundation response, improving test control and hybrid testing. Dissemination of sensor and vision systems to beneficiary infrastructures not directly involved in their development or application (.pdf, 8.5Mb)
The main objective of this report is the presentation of the state of the art as well as of the implementation and application of new types of sensors, time-integration and control techniques, visualisation and device modelling tools capable of enhancing the measurement of the response of test specimens and improving the quality of test control.
WP13 Report on software development for data processing (.pdf, 3.0Mb)
The main objective of this report that covers the research activities of Task JRA2.3 is the presentation of the development of numerical tools for processing data from experiments on structures/infrastructures, suitable for model calibration and specimen simulation. Compatibility with data formats of the distributed database to be developed in Task NA1.3 is ensured; and some tools are able to assess the uncertain propagation of random or systematic errors in computer models owing to experimental measurements.
WP13 Report on integration of modelling tools with test equipment and on virtual model development (.pdf, 2.4Mb) The main objective of this report that covers the research activities of Task JRA2.4 is the presentation of recent advances in system identification and model updating, in order to develop virtual models of test equipment-specimen-instrumentation systems. Use of virtual models, along with the latest advances in control to reduce the number of experimental substructures of calibration pre-tests, optimizes the location and number of sensors and improves the quality of results.

 

 

Highlights

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  Joint with US-NEES "Earthquake Engineering Research Infrastructures

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