Student Profile: Xavier Bellagamba



Perspectives on lifeline resilience


About Xavier


Xavier comes from the Canton of Valais at the heart of the Northern Alps in Switzerland. After completing an undergraduate program in Civil Engineering from EPFL, Lausanne, he joined the Master’s program of Civil Engineering at ETH, Zurich.

Interested to pursue his research on infrastructure resilience he started at ETH. As well as exploring new horizons, Xavier applied for a co-funded Resilience to Nature’s Challenges-QuakeCoRE scholarship and started his work in February 2016 at University of Canterbury under Professor Brendon Bradley. He is co-supervised by Dr. Liam Wotherspoon and Dr. Matthew Hughes. His work explores multiple aspects of underground lifeline seismic resilience and exploits the data collected on the water supply network of Christchurch after the Canterbury earthquake sequence events. Excited by the digital revolution, Xavier enthusiastically applies some machine learning and AI techniques to tackle problems related to the seismic resilience of urban water supply systems.

During his free time, Xavier enjoys reading (economics, sociology and psychology), jogging and cooking. If the weather is good, you better look for him in the mountains (on skis, in tramping or running shoes or harnessed at one end of a rope).


You’ve said resilience…

The resilience of a system (either if it is a building composed of several frames, an organization or spatially-distributed infrastructure) should be considered from three different perspectives: the loss assessment (what parts of the system are damaged and how does it affect its operability?), the risk mitigation (what parts of the system should be retrofitted, removed or strengthened to minimize future losses?) and the recovery (what parts of system should be repaired first to minimize disruption?).


Loss assessment

The loss assessment of an interconnected system is carried out in two steps: first, the damage estimation and second its impact on the system operability. As Christchurch is located in a liquefaction-prone area, new and easy-to-apply fragility functions for pipelines in such soils have been developed utilizing the aforementioned dataset.

These functions are then utilized in a connectivity-based network engine to estimate the systemic loss of service (e.g. disconnected population or dwellings). This engine has been used to estimate the number of people, businesses and global utility that have been affected by a water outage following the 2011 February Mw6.2 Christchurch earthquake as shown below.


Simulated water outage after the 2011 February Mw 6.2 Christchurch earthquake
Simulated water outage after the 2011 February Mw 6.2 Christchurch earthquake



Urban infrastructure are complex systems that evolve over time through the adoption of new standards or materials, growth, asset renewal and mitigation strategies. Hence, designing sound strategies accounting for multiple natural hazards is a very difficult task. In order to help horizontal infrastructure asset managers or urban planners to assess their options, a framework that could be applied across multiple systems and hazards is proposed. Based on the results of time-dependent event catalogues, it will rank the different strategies based on their relative performance, mitigating future losses for the considered hazards.



The recovery of a system encapsulates two key factors: the recovery process optimization and the ability to rapidly estimate the damage extent. Based on the engine developed for the loss assessment, a resource-based recovery model is proposed. Its objective is to minimize the selected community metric (population, dwellings or utility) suffering from a water outage over the restoration period. Figure 2 provides an example of simulated water outage recovery.

Simulated recovery of water services following the 2011 February Mw6.2 Christchurch earthquake
Simulated recovery of water services following the 2011 February Mw6.2 Christchurch earthquake

Built on the CyberShake program and modern deep learning methods, a tool is being developed to rapidly estimate the most probable shake map after potential future earthquakes. Combining this approach with state-of-the-art damage assessment software will allow emergency response planners to fasten and sharpen their decisions within a chaotic environment.


Why is this useful?

The development of these tools will contribute to a better understanding of complex civil infrastructure systems subject to earthquakes. In particular, whereas parts of this work can easily be implemented into existing loss modelling software, other portions could be directly applied by consultants, urban planners or asset managers to assist them in the assessment of their mitigation, development or recovery strategies.

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