BioI am a doctoral researcher working in the Institute for Risk and Uncertainty at the University of Liverpool. Broadly, my interests include seismic reliability assessments for structures and systems, reliability-based optimisation techniques and fragility analysis. More specifically, I am interested in the use of advanced probabilistic algorithms ( e.g. Artificial Neural Networks, Classification algorithms, Metamodels , Reliability analysis, Sensitivity analysis etc.) ,mostly coming from the machine learning field , to account for the uncertainty that affect the seismic reliability assuming different failure criteria. The same methodologies can be easily applied for the uncertainty quantification and risk management in a wide range of applications and my collaboration with the nuclear industry Areva GmbH is an example of that.
Research Interests: Seismic reliability analysis; reliability-based optimisation; fragility curves
Research project title: Seismic reliability assessment of structures and systems
Project description: The safety of civil structures and the protection of their human occupants represent goals of primary importance during the design stage. Events like earthquakes and extreme winds are the main causes that generate the need for dynamic protective measures of such structures. One way to prevent and mitigate the effect of dynamic loads on such structures is by means of hydraulic devices able to dissipate kinetic energy during an earthquake or extreme wind. The optimal design of viscous dampers under uncertain seismic excitations has represented one of the main research topic of my first PhD year. In addition, as result of a strong collaboration with the industrial partner AREVA GmbH, the research is also focused on the analysis of dynamic interactions between fuel assemblies in case of a seismic event. A first study estimates fragility curves of contiguous fuel assemblies in a nuclear reactor , analyzing the effects of dynamic impacts between spacer grids. Secondly, for a more general approach, a simplified structural system is analyzed to provide a dimensionless probabilistic demand model to estimate the risk connected to the pounding phenomena between adjacent systems. Finally, a further research topic that aim at defining a non-parametric efficient approach to evaluate conditional failure probabilities and seismic fragility curves is under development.
Supervisory team: Edoardo Patelli, Michael Beer, Andreas Rietbrock, Hector Jensen