Time‑Dependent Seismic Risk Assessment: Fault Interaction, Clustering, and Damage Accumulation

Project ID: 2531bc1593

(You will need this ID for your application)

Research Theme: Engineering

Research Area(s): Engineering
Physics

UCL Lead department: Civil, Environmental and Geomatic Engineering (CEGE)

Department Website

Lead Supervisor: Carmine Galasso

Partner Organisation: Howden Re

Stipend enhancement: £ 12,000

Project Summary:

Why this research is important

Conventional seismic risk models assume constant earthquake likelihoods, ignoring that fault segments’ rupture probability evolves and that nearby faults can trigger one another. Also, earthquakes commonly occur as sequences of smaller shocks before and after a main event, which progressively weaken buildings, delay recovery, and amplify losses. Treating events as time‑independent and isolated therefore understates hazard and financial risk, yielding misleading loss estimates for communities and insurers, as demonstrated by recent seismic events. This project will develop simulations that couple time‑dependent fault behaviour, explicit Epidemic‑Type Aftershock Sequence (ETAS) modelling, and cumulative damage tracking for engineering structures to produce decision‑ready risk information and practical guidance for planners/responders/insurers.

Who you will be working with

You will be supervised by a multidisciplinary team combining expertise in catastrophe risk engineering, statistical seismology, and structural vulnerability modelling. The team collaborates with regional seismic observatories and industry partners in catastrophe insurance, providing access to seismic catalogues, exposure data, and practical problem framing to ensure real-world relevance and impact.

What you will be doing

You will develop and validate a modular modelling pipeline that implements time-dependent fault recurrence and interaction, fits ETAS models to regional catalogues, generates conditional and unconditional stochastic event sets, and couples ground-motion predictions with vulnerability models that allow cumulative damage and repair-lag scenarios. You will compare results against conventional Poisson/mainshock-only approaches, perform systematic sensitivity and uncertainty analyses, and distil thresholds and actionable guidance where aftershock inclusion or damage accumulation alter planning or insurance pricing decisions.

Who we are looking for

We seek a candidate with strong quantitative skills in statistics, geophysics, or engineering, familiarity with stochastic simulation and hazard or risk modelling, proficiency in programming (Python, R, MATLAB), and an interest in translating methods into practical, auditable tools. Enthusiasm for interdisciplinary collaboration and clear scientific communication is essential.