This dataset contains supplementary materials to the manuscripts “Interpreting inverse magnetic fabric in Miocene dikes from Eastern Iceland” by Trippanera et al., (submitted to JGR) and “Anatomy of an extinct magmatic system along a divergent plate boundary: Alftafjordur, Iceland” by Urbani et al. 2015. These works present an extensive multi-scale and multi-disciplinary study focused on the magnetic fabric of dikes belonging to the Alftafjordur volcanic system in Eastern Iceland. Eastern Iceland is one of the most suitable places to analyze the roots of the volcanic systems that are composed of central volcanoes and fissure swarms. We sampled 19 NNE-SSW oriented dikes (for a total of 383 samples) belonging to the exhumed fissure swarm portion of Alftafjordur volcanic system, aiming at understanding the direction of magma propagation in the swarm by using Anisotropy of Magnetic Susceptibility (AMS) analysis. However, most of the samples (80% out of the measured cores) show an inverse geometric magnetic fabric (kmax is perpendicular to the dike margins and sub-horizontal)- therefore the study of the flow direction is complicated. Nevertheless, this result poses the problem of why the geometrically inverse fabric is present and widespread in the whole dike swarm. In order to understand the origin of this inverse fabric, besides standard AMS measurements, we also performed additional analysis such as different field and temperature AMS, Anisotropy of Anhystheretic Remanent Magnetization (AARM), Hysteresis loops and First-order reversal curves (FORC), Scanning Electron Microscope (SEM) and Optic microscope images analysis.
This dataset includes the following materials: • Location of the sampled sites (.kml) • AMS measurements at room temperature by using H=300 A/m for all samples (.ran) • AMS measurements at room temperature by using H=200 A/m and H=600 A/m for selected samples (.ran) • AMS measurements at different temperature (from 20 to 580 ℃) for selected samples (.ran) • AARM measurements for selected samples (.ran) • DayPlots data for selected samples (.xls or .csv) • SEM and Optical microscope images of thin sections of selected samples.
AMS and AARM data can be opened through Anisoft open-source software provided by Agico (Chadima and Jelinek, 2009; https://www.agico.com/text/software/anisoft/anisoft.php). Data have been acquired at: Roma Tre University (Rome, Italy), Istuto di Geofisica e Vulcanologia (INGV, Rome, Italy) and Laboratoire des Sciences du Climat et de l'Environnement, CEA, CNRS, UVSQ (Gif-sur-Yvette Cedex, France).
For the interpretation of the data refer to Urbani et al., 2015 and Trippanera et al., (submitted). The description of each dataset is provided in the description file.
This dataset provides friction and elasticity data from ring shear and axial tests, respectively, on rock analogue materials used at the University Roma Tre (Rome, IT) in “Foamquake”, a novel seismotectonic analog model mimicking the megathrust seismic cycle (Mastella et al., under review). Two granular materials (quartz sand and Jasmine rice) have been characterized by means of internal friction coefficients µ and cohesions C. An elastic material (foam rubber) have been characterized by means of Young’s modulus E and Poisson’s ratio v.
According to our analysis the granular materials show Mohr-Coulomb behaviour characterized by linear failure envelopes in the shear stress vs. normal load Mohr space. Peak, dynamic and reactivation friction coefficients of the quartz sand are µP = 0.69, µD = 0.56 and µR = 0.64, respectively. Cohesion ranges between 50 and 100 Pa. Rate-dependency of friction in quartz sand seems insignificant. Peak, dynamic and reactivation friction coefficients of the Jasmine rice are µP = 0.70, µD = 0.59 and µR = 0.61, respectively. Cohesion ranges between 30 and 50 Pa. Rate-weakening of Jasmine rice is c. 6% per tenfold change in shear velocity v. The Young’s modulus of the foam rubber has been constrained to 30 kPa, its Poisson’s ratio is v=0.1.
This data publication includes movies and figures of twenty-six analogue models which are used to investigate what controls sill emplacement, defining a hierarchy among a selection of the proposed factors: compressive stresses, interface strength between layers, rigidity contrast between layers, density layering, ratio of layer thickness, magma flow rate and driving buoyancy pressure (Sili et al., 2019).Crust layering is simulated by pig-skin gelatin layers and magma intrusions is simulated by colored water. The experimental set-up is composed of a 40.5 X 29 X 40 cm3 clear-Perspex tank where a mobile wall applies a deviatoric compressive stress (C, in Table 1) to the solid gelatin (Figure 1). In each experiment is imposed two layers with different density and rigidity, separated by a weak or strong interface, excluding two experiments characterized by homogeneous gelatin (experiment 4 and 12). Three different rigidity contrast (1, 1.3, 1.8) between the two layers are imposed, defined as the ratio between the Young’s moduli of the upper (Eu) and lower (El) layer. By using NaCl and gelatin concentration, two layers with same rigidity but different densities are obtained, investigating the influence of the density contrasts on sill emplacement. The effects of the ratio between layer thicknesses (i.e. the ratio between upper and lower layer thickness: Thu/Thl) was simulated by changing only the thickness of the upper layer; while magma flow rate are studied changing the flow rate of peristaltic pump.Water density was increased by adding NaCl to analyze the effect of changing driving buoyancy pressure (Pm) that depends on the density difference between host rock and magma (Δρ), gravitational acceleration (g) and intrusion length (H). In the table different colors indicate the experiment result: black = dike; red = sill and blue = sheet. The here provided material includes time-lapse movies showing intrusion propagation of the twenty-six models with a velocity of 5 times higher compared to the real time (1 second in the movie is 25 real seconds). These visualizations are side (XZ or YZ plane in Figure 1) and/or top views (XY plane in Figure 1).
Tracking the evolution of the deformational energy budget within accretionary systems provides insight into the driving mechanisms that control fault development. To quantify the impact of these mechanisms on overall system efficiency, we estimate energy budget components as the first thrust fault pair develops in dry-sand accretion analogue experiments.This data set includes photos taken and forces measured in four experiments performed at Université de Cergy-Pontoise in October-November 2016. The experiments are described in McBeck et al. (submitted).The data are organized into 5 main folders, with the following contents:1) E373_photos: Contains 3 subfolders: droit_RDY, gauche_RDY, haut_RDY. Each subfolder contains images taken at 1 second intervals throughout experiment. droit_RDY, gauche_RDY, and haut_RDY contain photos of the right, left, and top of the sandpack.2) E374_photos: Same organization and contents of folder E373_photos3) E375_photos: Same organization and contents of folder E373_photos4) E376_photos: Same organization and contents of folder E373_photos5) forces: Contains text files that list the normal force against the backwall (N) and total applied normal displacement to the backwall (mm) in the second and first columns, respectively. The filename indicates which experiment the text file describes.