3D FEM-based inverse model of Nevado del Ruiz - St. Isabel volcanoes (Colombia)
- 1. Department of Earth Sciences, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
- 2. Istituto per il Rilevamento Elettromagnetico dell'Ambiente, IREA-CNR, 80124 Napoli, Italy
Description
Description of model and data
The files include a FEM-based inverse model for the optimization of parameters of a pressure source responsible for surface deformation. The investigated source parameters are the position of the source center, the three semi-axis, the source strike orientation, the source dip orientation, and the source overpressure. The observations used for the inversion are ascending and descending ground velocities. The optimization is based on Least-Squares objectives using the Monte Carlo method. The file of observations needed for the computation of the Least-Squares objectives (to be uploaded in the optimization node) requires four columns (x,y,z, velocities. All in meters, UTM coordinates-UTM zone 18N, and comma-separated).
The model takes into consideration the heterogeneous distribution of material elastic properties. The model does not provide the files for the observations and material properties (at the link: https://zenodo.org/record/5575972), but the structure for the optimization model in which new files can be uploaded for a customized model.
The model includes the compensation for the stresses induced by the topography (edifices’ load). The file for the construction of the topographic surface is included as a .txt file (the position x,y of the points is in UTM coordinates-UTM zone 18N, the altitude z is in meters). The far-field is modeled as a hemisphere and it is located at 35 km from the center of the model, which is between the Nevado del Ruiz volcano and Santa Isabel volcano.
The model is built with Comsol Multiphysics v 5.6 using the modules Optimization and Structural Mechanics modules, and it is provided as a Comsol .mph file.
Datasets and model are results of PICVOLC project. PICVOLC has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 79381