State Estimation For Monitoring Structures During Extreme Loading And Environmental Conditions
Supervisor: Dr Danny Smyl
In extreme loading and environmental events, the integrity, constitution, and/or stiffness of a structure may change rapidly - usually for the worse. Presently, methods used for monitoring and assessing structures subject to such events are employed before and after the occurrence of (potential) damage. Moreover, such methods generally involve the interpretation of data alone. On the other hand, when data is collected during the extreme event, we may use the data to quantitatively reconstruct internal structural processes, either in quasi real-time or after the event. To do the reconstruction, we either solve an inverse problem (usually extremely computationally demanding) or treat the problem as a state estimation problem. The latter has never been done in cases where we aim to generate 3D images of structural data. The advantages of treating the reconstruction problem as a state estimation problem are the reduction in computing demand, increase in temporal information, and ability to incorporate temporal prior information. This thesis aims to develop state estimation algorithms for imaging structures subjected to extreme loading present in, e.g., earthquakes, blast/impact exposure, etc. In this effort, we will validate the algorithms using experimental data from structural testing and gain fundamental insights into the 3D progression of damage and other physical processes occurring in structures subject to extreme loading.
Applications are welcome now (email: firstname.lastname@example.org). This project is currently not funded, although Departmental/University scholarships are available for applicants who can demonstrate strong evidence of research potential. International students are also welcome to apply if they have a particular scholarship scheme available in their home country.