The doctoral work of Dag Pasca explore the use of ambient vibration testing techniques combined with modeling and supervised learning methods to identify the mechanical properties of civil engineering structures in a number of practical case studies.
This thesis treats ambient vibration testing of civil engineering structures with a special attention given to timber structures.
It presents an open-source Python module that allows to perform two very much used output-only dynamic identification techniques. One of the reasons behind the open-source release of the module is the hope to attract other persons willing to help extending the module's capabilities also to continuous monitoring applications.
Furthermore, the work presents and discusses the application of Operational Modal Analysis methods to three case studies, highlighting the usefulness and potential of such methods.
The cases are a prestressed short span concrete girder, an eight storey CLT building and a lightweight timber floor sub-assembly. Through the applications it is shown how Operational Modal Analysis may be of use not only to theoretical research-oriented applications, but also very practical tasks. For instance, in the framework of maintenance plans it is shown how ambient vibration testing results may be used to infer on the state of health of a bridge. Moreover, experimental modal properties are used to perform sensitivity analysis, update finite element models and draw comparison with analytical solutions. In fact, it is also shown how ambient vibration testing can be a viable and cheaper alternative to force vibration tests.
All in all, the goals of this work are to highlight the importance and potential of output-only identification methods and broaden the data-base present with applications to timber structures.