110 documents found in 362ms
# 1
Spooner, Cameron • Scheck-Wenderoth, Magdalena • Götze, Hans-Jürgen • Ebbing, Jörg • Hetényi, György
Abstract: The Alps are one of the best studied mountain ranges in the world, yet significant unknowns remain regarding their crustal structure and density distribution at depth. Previous published interpretations of crustal features within the orogen have been primarily based upon 2D seismic sections, and those that do integrate multiple geo-scientific datasets in 3D, have either focused on smaller sub-sections of the Alps or included the Alps, in low resolution, as part of a much larger study area. Therefore the generation of a 3D, crustal scale, gravity constrained, structural model of the Alps and their forelands at an appropriate resolution has been created here to more accurately describe crustal heterogeneity in the region. The study area of this work focuses on a region of 660 km x 620 km covering the vast majority of the Alps and their forelands are included, with the Central and Eastern Alps and the northern foreland being the best covered regions. Surface Generation All referenced data was integrated to constrain sub-surface lithospheric features including: previous regional scale gravitationally and seismically constrained models of the TRANSALP study area, the Upper Rhine Graben, the Mollasse Basin and the Po Basin; continental scale integrative best fit models (EuCRUST-07 and EPcrust); and seismic reflection depths from numerous published deep seismic surveys (e.g. ALP’75, EGT’86, ALP 2002 and EASI). The software package Petrel was used for the creation and visualisation of the modelled surfaces in 3D, representing the key structural and density contrasts within the region. All surfaces were generated with a grid resolution of 20 km x 20 km using Petrel’s convergent interpolation algorithm. During interpolation, a hierarchy of data source types was used in the case of contradiction between the different data sources and was as follows: 1. regional scale, gravitationally and seismically constrained models; 2. regional scale, seismically constrained models; 3. individual seismic reflection surfaces and interpreted sections; 4. continental scale, seismically constrained, integrative best fit models. No subduction interfaces were modelled. Topography and bathymetry were taken from ETOPO1 and the LAB from Geissler (2010). Gravity Modelling The generated surfaces and the calculated free-air anomaly from the global gravity model EIGEN-6C4, at a fixed height of 6 km above the datum were used in the 3D gravity modelling software IGMAS+ for the constrained of lithospheric density distribution. The layers of the generated model were split laterally into domains of different density, to reflect the heterogeneous nature of the crust within the region. Densities used in the initial structural model were derived from empirical P wave velocity to density conversions (Brocher, 2005) from the input seismic data sources. The densities were then modified, through multiple iterations, until the resulting model produced a gravity field within ± 25 mGal of the observed one. Surfaces generated as part of the integration work were not modified. Files The surface depths, thicknesses and densities of the model can be found as tab separated text files for each individual layer of the model (Unconsolidated Sediments, Consolidated Sediments, Upper Crust, Lower Crust and Lithospheric Mantle). The columns in each file are identical: the Easting is given in the “X COORD (UTM Zone 32N)”, Northing in the “Y COORD (UTM Zone 32N)”, the top surface depth of each layer is given as TOP (m.a.s.l), the thickness of each layer is given as THICKNESS (m), and the bulk density of that layer is given as DENSITY (Kg/m^3).
# 2
Zieger, Toni • Lerbs, Nikolaus • Ritter, Joachim R.R. • Korn, Michael
Abstract: SMARTIE1 is a joint seismological experiment of the Karlsruhe Institute of Technology (KIT) and the Leipzig University. We installed in total 36 seismic stations as ring-like and profile-like measurements near to a single wind turbine (WT) at the Fraunhofer Institute for Chemical Technology (ICT) in Pfinztal, SW Germany, for 21 days. The main goals of this project are a better understanding of a single WT as a seismic source and the development of propagation models for the WT-induced seismic signals, depending on the geological properties. Waveform data are available from the GEOFON data centre, under network code X8 (under CC-BY 4.0 license according to GIPP-rules), and are embargoed until Jan 2020.
# 3
Wallis, David • Hansen, Lars • Britton, Ben • Wilkinson, Angus
Abstract: This dataset is supplemental to the paper Wallis et al. (2019) and contains data derived from distortion of crystal lattices measured using conventional electron backscatter diffraction (EBSD) and high-angular resolution electron backscatter diffraction (HR-EBSD). The datasets include lattice misorientation, elastic-strain heterogeneity, residual-stress heterogeneity, and densities of geometrically necessary dislocations in olivine and quartz. We intend the data and associated paper to demonstrate key aspects of the HR-EBSD technique and to draw comparisons with conventional EBSD. As the paper by Wallis et al. (2019) is a review paper, several of the datasets have also been present in, or are otherwise related to, additional previous publications listed below . Data are provided as 55 tab delimited .txt files organised by the figure in which they appear within Wallis et al. (2019). Data types are indicated in the file names. Please consult the data description file for detailed explanations.
The data were acquired on an FEI Quanta 650 field emission gun SEM equipped with an Oxford Instruments AZtec EBSD system and NordlysNano EBSD detector in the Department of Earth Sciences, University of Oxford. Reference frames for data acquisition and processing were validated following the approach of Britton et al. (2016). The pattern centre was determined prior to each run using an automated camera stepping routine in the acquisition software, implementing a process similar to that proposed by Maurice et al. (2011). Shifts in the pattern centre due to beam scanning were calibrated on an undeformed single crystal Si standard (Wallis et al., 2016; Wilkinson et al., 2006). All data sets were collected at the full resolution of the EBSD detector giving diffraction patterns of 1,344 × 1,024 pixels. All data sets were processed using 100 ROIs of 256 × 256 pixels and the robust iterative fitting and pattern remapping approaches of Britton and Wilkinson (2011, 2012). Data points were filtered out if they had either a mean angular error > 0.004 radians in the deformation gradient tensor or a normalized peak height < 0.3 in the cross‐correlation function (Britton & Wilkinson, 2011). Additional details of the data sets are presented in Table 1 of Wallis et al. (2019) and in the data description file.
# 4
Petricca, Patrizio
Abstract: Based on available geological and geophysical data, the depth of the basal thrust decollement for compressional areas of Italy is collected. The proposed dataset is useful to a large scientific and risk-management audience (e.g., input for numerical modelling of regional studies, or providing the maximum depth of brittle crust useful to constraints maximum expected magnitudes for the study region). The dataset is presented as a long table (2019-028_Petricca_Table1.txt) in tab-separated text format. The table contains three columns indicating 1) the longitude, 2) the latitude and 3) the depth (in km) values of the maximum thrust faulting depth. Obtained depths range between 1 and 17 km. Conceptual model for the definition of the active thrust decollement depths (see Petricca et al., 2019): to define the basal decollement depth of active thrust faults are selected 75 published geological and seismic sections plus two maps of basal decollement (Table 1 in Petricca et al., 2019 for references). The study domain is gridded with nodes every 10x10 km. At each node coinciding with a seismic or geological section, the punctual value of the basal decollement depth with respect to the sea level is assigned. For the Calabrian Arc and part of Sicily, we used values picked from depth maps. Depth values at empty nodes are assigned by interpolation criteria using the minimum curvature method (Briggs, 1974), generalized by Smith and Wessel (1990) including the tension factor (i.e., the smoothing grade - 0.5 in this case). Further, the trend of the obtained isodepth contours is recalibrated following the composite sources (i.e. the maximum depth of seismogenic sources given in the DISS database - see Basili et al., 2008). Depth correction is obtained adding/subtracting the topography/bathymetry elevation/depth at nodes using values interpolated from ETOPO1 Global Relief Model. Due to the fact that the brittle-ductile transition (BDT) depth is possibly and locally shallower than the basal thrust depth (zbt), further correction is necessary. For this purpose, the BDT depths from Petricca et al. (2015) is compared with the basal thrust depths zbt from this study to select at each node of the computation grid the shallower value. The majority of the studied areas show a basal thrust depth (zmax) shallower than the BDT. An exception occurs offshore in the southern Tyrrhenian Sea, Sicily, where the BDT depth (10-12 km) is considerably shallower than the basal thrust depth (zmax<30 km). Limited portions of the northern Apennines and the part of the Calabrian arc close to the coast show comparable depths between the basal thrust (zmax) and BDT (i.e., 14-17 km).
# 5
Stern, Sönke • Cimarelli, Corrado • Gaudin, Damien • Scheu, Bettina • Dingwell, Donald B.
Abstract: This data publication provides data from 42 experiments from 2018 and 2019 in the Fragmentation Lab at the Ludwig-Maximilians University Munich (Germany). The experiments were taken out to analyse the influence of the water content and the initial temperature of the pre-experimental sample on the produced electrification in rapid decompression, shock-tube experiments. All samples used in this study are 90-300 μm loose ash samples from the lower Laacher See unit. To carry out this study, we have built up on previous studies by Cimarelli et al. (2014) and Gaudin & Cimarelli (2019b, dataset to be found in Gaudin & Cimarelli, 2019a). A sample of loose ash gets placed in an autoclave. In our study, we have added water in some experiments. Also, a furnace was often used to heat the sample to up to 320 °C. After both water addition and heating, the autoclave gets pressurized using argon gas. Once a target pressure of 9 MPa is reached, the experiment gets triggered by rupturing metal diaphragms, which rapid decompresses the sample and ejects it into a collector tank. This collector tank is made out of steel and electrically insulated from its surrounding, thus working as a Faraday cage (FC), which is able to detect the net charge within at any point during the experiment. We detect discharges on that net charge up to 10 ms after the ejection of the particles.This dataset contains: - an overview .xlsx file (ExperimentOverview) containing key information for the 42 experiments used for analysis in this study- raw .csv files for all experiments- .pdf files showing the key elements of the analysed experiments, incl. data from Faraday cage and pressure sensors For more information please refer to the data description and the associated publication (Stern et al., 2019).
# 6
Gómez-García, Ángela María • Meeßen, Christian • Scheck-Wenderoth, Magdalena • Monsalve, Gaspar • Bott, Judith • (et. al.)
Abstract: The scripts and workflow are supplementary material to "3D Modelling of Vertical Gravity Gradients and the delimitation of tectonic boundaries: The Caribbean oceanic domain as a case study" (Gómez-García et al., 2019). The codes include the calculation of the VGG response of a 3D lithospheric model, in spherical coordinates, using the software Tesseroids (Uieda, 2016). The "Readme_Workflow_2019_002.pdf" file provide very detail information about the structure of this repository, as well as the step-by-step for the scripts execution, and the list of the requiered software for the correct workflow performance. All the information provided here will allow the user to reproduce the results and figures of the main paper. Detailed information are also given in the associated README.
# 7
Gómez-García, Ángela María • Meeßen, Christian • Scheck-Wenderoth, Magdalena • Monsalve, Gaspar • Bott, Judith • (et. al.)
Abstract: These data are supplementary material to "3D Modelling of Vertical Gravity Gradients and the delimitation of tectonic boundaries: The Caribbean oceanic domain as a case study" (Gómez-García et al., 2019). This dataset contains information about the structure of the Caribbean oceanic crust, based on the modelling of the Vertical Gravity Gradients, which are gravity derivatives especially sensitive to density contrasts in the upper layers of the Earth. The files included are:1) The inferred densities of the Caribbean crystalline crust, in the file “CrustalDensities.txt”.2) The residuals of the Vertical Gravity Gradients (VGG), in the file “ResidualsVGG.txt”, which were used to define the terrain boundaries.3) A collection of shapefiles (2019GC008340_Gdb.gdb) with the main inferred tectonic/terrain boundaries and additional geologic features.4) A "Read me" file with the description of the different shapefiles available in the geodatabase.
# 8
Elena Hensel • Oliver Bödeker • Olaf Bubenzer • Ralf Vogelsang
Abstract: This data corresponds to the article and shall be quoted as such using the provided DOI: Hensel, E. A., Bödeker, O., Bubenzer, O., and Vogelsang, R.: Combining geomorphological–hydrological analyses and the location of settlement and raw material sites – a case study on understanding prehistoric human settlement activity in the southwestern Ethiopian Highlands, E
# 9
Ge, Zhiyuan • Rosenau, Matthias • Warsitzka, Michael • Robert, Gawthorpe
Abstract: This data set includes the results of digital image correlation (DIC) of two experiments on gravitational tectonics at passive margins performed at the Helmholtz Laboratory for Tectonic Modelling (HelTec) of the GFZ German Research Centre for Geosciences in Potsdam in the framework of EPOS transnational access activities in 2018. The experiments aim at documenting the difference in structural evolution between two tilting scenarios: Instant versus progressive, or fast versus slow. Detailed descriptions of the experiments and results can be found in Ge et al. (2019, Geology) to which this data set is supplement. The DIC analysis yields quantitative deformation information of the experiment surfaces by means of 3D surface displacements from which strain has been calculated. The data presented here are visualized as surface uplift and strain maps, strain evolution maps and surface velocity time-series. Python scripts for visualization of data are appended. Parts of this data (see list of files) are derived from Ge et al. (2019, http://doi.org/10.5880/GFZ.4.1.2019.001).
# 10
Steinberger, Bernhard
Abstract: The data are the modelling results for Yellowstone hotspot motion and plume conduits on which the figures of the paper "Yellowstone plume conduit tilt caused by large-scale mantle flow" by Steinberger, Nelson, Grand and Wang are based. Detailed description on how they are obtained is given in that paper. The naming of the files is as follows: First letter: c for plume conduit, s for surface motion. Then figure number (6, 7, or 8; s1 and s2 for Supporting Figure 1 and 2), then a, b, c or d for which column of the figure, or 2a etc for the specific panel. Each file has in the first column time, in the second longitude, in the third latitude, in the fourth depth (given as normalized radius, i.e. 1 at the surface, 0.5448 at the core-mantle boundary). For the plume conduit the time (first column) is always zero = present-day. For the surface motion the depth is always close to 0.9843 (base of the lithosphere). The file rotvec.na.nn gives the North America plate motion (stage rotations) used to convert hotspot motions to hotspot tracks on the North American plate. Stage rotation rates are given in omega_x, omega_y, omega_z (units of degrees per million years) followed by the time interval in million. Stage rotation rates are given in cartesian coordinates omega_x, omega_y, omega_z (units of degrees per million years) followed by the time interval in million years.
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