Researchers at the University of East London (UEL) have developed a new framework for assessing earthquake risks, using AI-assisted technology to examine how soil conditions, ground shaking and structural strength influence a building’s ability to withstand seismic activity.
Designing buildings to withstand earthquakes is a complex challenge. Engineers must consider not only an earthquake’s strength, but also the ground beneath a building, how the structure moves and whether its individual components can withstand the forces involved. These factors are often assessed using separate engineering tools, making it difficult to understand how they interact and influence a building’s overall performance.
The UEL study tested a computer model of a five-storey reinforced concrete building using recorded ground-motion data from the devastating Northridge and Kobe earthquakes in 1994 and 1995, drawing on a Proto-Artificial General Intelligence (Proto-AGI) framework. The latter brings together four specialist technologies in a single coordinated workflow under human supervision to provide a more complete assessment of structural risks.
The results revealed that although the Northridge record produced approximately 3.4 times the median seismic demand of the Kobe record at the building’s natural period (the number of seconds it takes for the building to naturally vibrate back and forth), the difference in peak structural movement was only 1.32 times.
The comparison shows that the relationship between ground shaking and structural movement is not straightforward. A larger difference in the shaking a building experiences does not necessarily translate into an equally large difference in its movement.
Increasing engineers’ understanding
The characteristics of the earthquake, the soil beneath the building and the structure’s design all influence the outcome, which is why stronger shaking does not necessarily produce a proportionately greater amount of building movement. According to the researchers, examining these factors together could help engineers understand how vulnerabilities develop across a structure, rather than considering each part of the assessment in isolation.
Further testing is needed before the approach can be used routinely in engineering practice. The initial study used one soil profile and two earthquake records, with engineers manually coordinating information between the technologies. Future research could explore larger earthquake datasets, greater automation and information from building inspections and structural monitoring.
The research was led by Dr Jawed Qureshi, senior lecturer in structural engineering and design at UEL. He said: “Structural engineers have always known that buildings do not fail in isolation. What happens beneath the ground affects how a structure moves, and how a structure moves determines whether it survives. Now, for the first time, we have a framework that joins all those pieces together.
“The goal was never to replace engineering judgement with AI. It was to give engineers a clearer, more complete picture before they make their decisions. That is what this research delivers.”
