Damage assessment to a reinforced concrete beam-column joint through ambient vibrations measurements
Reference persons MARCO CIVERA
External reference persons Dr. Silvia Ientile (firstname.lastname@example.org)
Thesis type EXPERIMENTAL
Description The assessment of existing buildings animates the debate at the European level on the methods to be used for the design calculation, beyond the scope of standard design codes for new structures. There is a need, therefore, to develop new methodologies for the evaluation, re-use and retrofitting of Reinforced Concrete (RC) existing structures in keeping with the Eurocodes design requirements.
Common weaknesses in the structural system are due to strength and stiffness discontinuities, vertical, horizontal and mass irregularities; weak column/strong beam; and eccentricities.
The dynamic identification techniques provide the modal parameters for the evaluation of structural health through non-destructive testing, increasingly common in the civil engineering field, by means of vibration measurements. These techniques are particularly useful to assess their state of conservation and deterioration.
The thesis work will benefit from vibration measurements acquired during cyclic tests data of an experimental campaign carried out at the EMGCU laboratory of the Gustave Eiffel University, on unrepaired and repaired RC column-beam joint through Fiber-Reinforced Polymer (FRP) reinforcement stripes.
The aim of the master thesis is to evaluate the change in the structural behaviour of RC column-beam joint by observing the variation of modal parameters and finally to give a damage index.
Moreover, the comparison between the unrepaired and repaired modal parameters will also provide an evaluation of the effectiveness of FRP retrofitting.
The thesis will be performed in the facilities of the EMGCU Laboratory at Université Gustave Eiffel (https://emgcu.univ-gustave-eiffel.fr/)
Required skills Good Knowledge of MatLab and of Structural Dynamics and Vibration.
Average grade≥27, Good English Knowledge required B2/C1
Deadline 29/09/2024 PROPONI LA TUA CANDIDATURA