This dataset collects the results of a series of experiments carried out on air-filled cracks injected into pigskin gelatin blocks between September 2019 and May 2020 at GFZ German Research Centre for Geosciences in Potsdam (Germany). Such experiments were intended to simulate dike propagation in the upper crust, in settings where tectonic and surface unloading stress are dominant in determining the stress field within the medium. The gelatin blocks were laterally strained and rift-like excavations were moulded on their surfaces.
These data include pictures of each experimental setup and video records of each injected crack, as well as tables collecting the measured arrival points of the cracks at the surface of the gelatin and relevant elastic and geometric parameters.
The data publication is a Supplement to Mantiloni et al. (2020): "Stress inversion in a gelatin box: testing eruptive vent location forecasts with analog models" (Geophys. Res. Lett.), to which the reader is referred for further information.
BayStress4 is a package of MatLab routine, designed to constrain the state of stress of a volcanic system by means of posterior Probability Density Functions (PDFs) of the stress tensor components. To do so, it employs the model of three-dimensional (3D) dyke pathways developed by Mantiloni et al., 2023 (SAM: Simplified Analytical Model of dyke Pathways in Three Dimensions) to match the known locations of past eruptive vents to the known or assumed volume in the subsurface ("Dyke nucleation zone" or "D") where their parent dykes nucleated from. This is achieved by a) using SAM to backtrack dyke pathways from the vents down through the crust for a given stress model; b) quantifying the intersection between such pathways and D through a misfit function; c) using this procedure to run a Markov Chain Monte Carlo (MCMC) algorithm to sample the stress parameters' space. The posterior information provided by the stress inversions can then be used to produce forward simulations of dyke pathways with SAM and forecast the surface distribution of future eruptive vents across the volcanic system.
This repository contains InVent4Cast, a package of MatLab routines designed to constrain the state of stress of a volcanic system by means of posterior Probability Density Functions (PDFs) of the stress tensor components. To do so, it employs the model of three-dimensional (3D) dyke pathways developed by Mantiloni et al., 2023a (SAM: Simplified Analytical Model of dyke Pathways in Three Dimensions) to match the known locations of past eruptive vents to the known or assumed volume in the subsurface ("Dyke nucleation zone" or "D") where their parent dykes nucleated from. This is achieved by a) using SAM to backtrack dyke pathways from the vents down through the crust for a given stress model; b) quantifying the intersection between such pathways and D through a misfit function; c) using this procedure to run a Markov Chain Monte Carlo (MCMC) algorithm to sample the stress parameters' space. The posterior information provided by the stress inversions can then be used to produce forward simulations of dyke pathways with SAM and forecast the surface distribution of future eruptive vents across the volcanic system.
The repository also collects data, figures and results of the application of InVent4Cast to some of the synthetic scenarios of dyke pathways in calderas presented by Mantiloni et al., 2023a. These results were detailed and discussed by Mantiloni et al., 2024a, to which the reader is referred for further information. The synthetic scenarios include numerical models of crustal stress state, focusing on gravitational loading/unloading due to topography and tectonic processes as the dominant stress sources. These stress sources are accounted for by a set of stress parameters. Results include posterior probability density functions (PDFs) of such stress parameters after applying the stress inversion to the scenarios, as well as probability maps of eruptive vent opening across the synthetic volcanic areas. Synthetic scenarios, stress inversions and vent forecasts were produced between May 2022 and November 2023.