
Earthquakes are common and profound natural disasters that pose serious threats to human life and economic activities. High-precision earthquake simulation and visualisation is an effective means to reduce loss of life and to future-proof building and urban planning designs. It is widely used in fields such as virtual production, filmmaking, gaming, emergency response, robotics training and education.
However, existing methods of earthquake simulation typically require substantial computing resources, rarely operating in real time. That means their data processing is falling short in efficiency and interactive capabilities. Equally, visual fidelity tends to be on the lower spectrum. This means current methods pose challenges to an integration with virtual production systems as these rely on real-time and high-fidelity rendering and intuitive visual design workflows.
In response to this, a team comprising researchers from Royal College of Art’sSNAP Visualisation Laband UNSW iCinema, in collaboration with London-based architecture studio Foster + Partners Ltd,integrate ANSYS material physics simulation with theUnreal Engine 5fracturing system to simulate earthquakes inUnrealat high accuracy while maintaining visual fidelity and real-time interactivity.
The core questions driving this research are:
- How can we integrate advanced physical simulation with high-fidelity rendering technologies of game engines?
- How to ensure the system meets the authenticity (super realistic and believable) and computational efficiency needs for Virtual Production and Extended Reality (XR)?
- How to make the earthquake simulation environment both accurate and user friendly?
The research focuses in particular on enhancing the ANSYS material bridge plugin, on expandingUnreal's fractured material library, and on improving overall user friendliness. For example, they are implementing dynamic deformations of the ground caused by earthquake waves to enhance simulation precision and realism. To furnish a seamless XR experience, the team is developing cross-platform interfaces to support applications from immersive surround projectors, XR devices and CoStar facilities, ensuring real-time interaction. Outcomes of the research will include a real-time emergency response demo to demonstrate future application potential.
The research is funded by theXR Network+ Virtual Production in the Digital Economyproject, supported by the UK’s Engineering & Physical Sciences Research Council (Grant Ref: EP/W020602/1).
- Overview
- Publications
Project Director:A/Prof. Ali Asadipour
Project Collaborators and Partners:Laureate Prof. Dennis Del Favero FAHA, Dr Marina Konstantatou (Foster + Partners Ltd), Mr Yitong Sun (RCA)
Project Title:Development of a High-Fidelity Earthquake Simulation Environment for Virtual Production Based on Unreal Engine
Project Funding: UK Engineering & Physical Sciences Research Council’s XR Network+ Virtual Production in the Digital Economy project (EP/W020602/1)
2024-25
Sun, Y., H. Wang, Z. Zhang, C. Diels & A. Asadipour (2023). “RESenv: A Realistic Earthquake Simulation Environment Based on Unreal Engine.”InN. Pelechano, F. Liarokapis, D. Rohmer & A. Asadipour (eds.),International Conference on Interactive Media, Smart Systems and Emerging Technologies (IMET). Barcelona: Eurographics Association.
Song, Y., M. Pagnucco, F. Wu, A. Asadipour & M.J. Ostwald (2024). “Intelligent Architectures for Extreme Event Visualisation.” In D. Del Favero, S. Thurow, M. J. Ostwald, & U. Frohne (eds.),Climate Disaster Preparedness: Reimagining Extreme Events through Art and Technology(pp. 37–48). Cham: Springer.
Green, C., B. Smaill & S. Cubitt (2024). “Iconographies of Climate Catastrophe: The Representation of Climate Change in Art and Film.” InD. Del Favero,S. Thurow, M.J. Ostwald & U. Frohne (eds.),Climate Disaster Preparedness: Reimagining Extreme Events through Art and Technology(pp. 93–106). Cham: Springer.
Moinuddin, K., C. Tirado Cortes, A. Hassan, G. Accary & F. Wu (2024). “Simulation of Extreme Fire Event Scenarios Using Fully Physical Models and Visualisation Systems.” InD. Del Favero, S. Thurow, M.J. Ostwald & U. Frohne (eds.),Climate Disaster Preparedness: Reimagining Extreme Events through Art and Technology(pp. 49–63). Cham: Springer.
Roussel, R., S. Jacoby & A.Asadipour(2024). “Robust Building Identification from Street Views Using Deep Convolutional Neural Networks,”Buildings14.3: 578.