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A new volcanic forecasting program was set up on the Blue Waters and iForge supercomputers in the fall of last year. The Sierra Negra volcano was being monitored by another team. Five months before the Sierra Negra eruption occurred, one of the scientists on the project, Dennis Geist of Colgate University, contacted Gregg, and he had a good idea of what was going to happen.

The new modeling approach was developed on an iMac computer and was used to recreate the Okmok volcano eruption. The team from the National Center for Supercomputing Applications wanted to test the model's new high- performance computing upgrade, while the team from the University of Illinois Urbana-Champaign wanted to see if there was an eruption.

The lead author of a new report said that the volcano is well-behaved. We would expect to see groundswell, gas release and increased seismic activity when the volcano erupts. Sierra Negra was a good test case for our upgraded model.

Many volcanoes don't follow the same patterns. Forecasting eruptions is one of the grand challenges in volcanology and the development of quantitative models to help with these tricky scenarios is the focus of the team.

The new supercomputing-powered model was used to run the Sierra Negra data. The run was supposed to be a test but ended up providing a framework for understanding Sierra Negra's eruption cycles and evaluating the potential and timing of future eruptions.

"Our model predicted that the strength of the rocks that contain Sierra Negra's magma chamber would become very unstable sometime between June 25 and July 5, and possibly result in a mechanical failure and subsequent eruption." The conclusion was presented at a scientific conference. After that, we became busy with other work and didn't look at our models again until Dennis asked me to confirm the date we had predicted. One day after our earliest predicted mechanical failure date, Sierra Negra exploded. We were shocked.

The study shows that incorporating high- performance supercomputing into practical research is possible. The co-author of the study said that the upgraded model has the advantage of being able to give a daily forecast similar to weather forecasting. It takes a lot of computing power to do this.

After working with NCSA, the team was able to bring the moving parts into place to create a modeling program.

In this case of a volcanic magma chamber, we all speak the same language when it comes to the numerical multiphysics analysis and high- performance computing needed to forecast mechanical failure.

The team hopes to incorporate artificial intelligence and machine learning into the forecasting model to make it easier for researchers to use standard laptop and desktop computers.

The results of the study can be found in the journal.

More information: Patricia M. Gregg, Forecasting mechanical failure and the 26 June 2018 eruption of Sierra Negra Volcano, Galápagos, Ecuador, Science Advances (2022). DOI: 10.1126/sciadv.abm4261. www.science.org/doi/10.1126/sciadv.abm4261 Journal information: Science Advances