4 papers
Reduced Order Modeling for Tsunami Forecasting with Bayesian Hierarchical Pooling
Shane X. Coffing, John Tipton, Arvind T. Mohan +1
Reduced-order models (ROMs) can represent spatiotemporal processes in significantly fewer dimensions and can often be solved many orders of magnitude faster than their governing pa…
Attention-Based Reconstruction of Full-Field Tsunami Waves from Sparse Tsunameter Networks
Edward McDugald, Arvind Mohan, Darren Engwirda +2
We investigate the potential of an attention-based neural network architecture, the Senseiver, for sparse sensing in tsunami forecasting. Specifically, we focus on the Tsunami Data…
Local Time-Stepping for the Shallow Water Equations using CFL Optimized Forward-Backward Runge-Kutta Schemes
Jeremy R. Lilly, Giacomo Capodaglio, Darren Engwirda +2
The Courant-Friedrichs-Lewy (CFL) condition is a well known, necessary condition for the stability of explicit time-stepping schemes that effectively places a limit on the size of…
Fast Mapping onto Census Blocks
Jeremy Kepner, Andreas Kipf, Darren Engwirda +21
Pandemic measures such as social distancing and contact tracing can be enhanced by rapidly integrating dynamic location data and demographic data. Projecting billions of longitude…