15 documents found in 374ms
# 1
van den Ende, Martijn
Abstract: Intergranular pressure solution creep is an important deformation mechanism in the Earth’s crust. The phenomenon has been frequently studied and several analytical models have been proposed that describe its constitutive behavior. These models require assumptions regarding the geometry of the aggregate and the grain size distribution in order to solve for the contact stresses, and often neglect shear tractions. Furthermore, analytical models tend to overestimate experimental compaction rates at low porosities, an observation for which the underlying mechanisms remain to be elucidated. Here we present a conceptually simple, 3D Discrete Element Method (DEM) approach for simulating intergranular pressure solution creep that explicitly models individual grains, relaxing many of the assumptions that are required by analytical models. The DEM model is validated against experiments by direct comparison of macroscopic sample compaction rates. Furthermore, the sensitivity of the overall DEM compaction rate to the grain size and applied stress is tested. The effects of the interparticle friction and of a distributed grain size on macroscopic strain rates are subsequently investigated. Overall, we find that the DEM model is capable of reproducing realistic compaction behavior, and that the strain rates produced by the model are in good agreement with uniaxial compaction experiments. Characteristic features, such as the dependence of the strain rate on grain size and applied stress, as predicted by analytical models, are also observed in the simulations. DEM results show that interparticle friction and a distributed grain size affect the compaction rates by less than half an order of magnitude. The zip-file Van-den-Ende_2017.018.zip contains several folders with raw data from the laboratory experiments, output data from Discrete Element Method simulations, and Python 2.7 script files that read and process these data. All data are stored in ASCII format.
# 2
Trippetta, Fabio • Carpenter, Brett M • Mollo, Silvio • Scuderi, Marco M. • Scarlato, Piergiorgio • (et. al.)
Abstract: Here we report the raw data of the physical properties of carbonate samples collected along the Monte Maggio normal Fault (MMF), a regional structure (length ~10 km and displacement ~500 m) located within the active system of the Apennines (Italy). In particular, we report results coming from large cores (100 mm in diameter and up to 20 cm long) drilled perpendicular to the fault plane made of Calcare Massiccio (massive limestone) and Bugarone fm (limestone with 8.3 % of clay). From these large cores, we obtained smaller cores, 38 mm in diameter both parallel and perpendicular to the fault plane, that have been used for experiments. We have divided the rock samples in four categories following the fault architecture. The four structural domains of the fault are:1) the hangingwall (HW) made of Bugarone fm that is still preserved in some portions of the fault, 2) a Cemented Cataclasite (CC) and 3) a Fault Breccia (FB) that characterize the cataclastic damage zones and 4) the correspondent undeformed protolith of the footwall block made of Calcare Massiccio. Raw data reported here are those used for drawing Figures 5, 6, 8 and 9 of the paper “Physical and transport property variations within carbonate- bearing fault zones: Insights from the Monte Maggio Fault (central Italy)”, http://doi.org/10.1002/ 2017GC007097 by Trippetta et al. Dataset_Fig05.txt reports P- and S-wave velocities (in km/s) of the described samples at pressure from 0.1 MPa (ambient pressure) up to 100 MPa at ambient temperature in dry conditions and the corresponding Vp/Vs ratio. Experiments have been performed by using the permeameter at the HP-HT Laboratory of experimental Volcanology and Geophysics at INGV (Rome). Dataset_Fig06.txt reports permeability data (in m^2) on the same type of samples of fig05 for the same range of confining pressure at ambient temperature. Pore pressure values athletes each confining pressure step are indicated in the file. Data have been again acquired with the permeameter. Dataset_Fig08.txt reports P-wave velocity data (in km/s) vs depth (in m), recorded on the portion that crossed the Calare Massiccio fm of three boreholes drilled in the Apennines: Varoni 1, Monte Civitello 1 and Daniel1. Data have been obtained by digitalizing each pdf file of the boreholes mentioned above, that are available at http://unmig.sviluppoeconomico.gov.it/videpi/videpi.asp. Once digitalized, respect to the original pdf file, velocity data have been simply converted from um/f to km/s. Dataset_Fig09.txt reports values of the maximum, minimum and average values of Critical fault nucleation length (in m) at each corresponding depth (in m) and applied confining pressure (in MPa). Critical nucleation lengths have been calculated by using the equations described in the text of the Trippetta et al paper and by using the elastic parameters calculated from data reported here. Data on earthquakes-depth distribution of the 2009 L'Aquila sequence can be found on Chiaraluce et al. (2011).
# 3
Sembroni, Andrea • Kiraly, Agnes • Faccenna, Claudio • Funiciello, Francesca • Becker, Thorsten W. • (et. al.)
Abstract: We present videos and figures from 22 scaled analogue models used to investigate the interactions between a density anomaly rising in the mantle and the lithosphere in a Newtonian system. The experimental setup consists of a two layers viscous lithosphere-upper mantle system obtained by using silicone putty-glucose syrup in a tank sized 40 cm × 40 cm× 50 cm. Glucose syrup (i.e., mantle) is a Newtonian, low viscosity, high-density fluid while silicone putty (i.e., lithosphere) is a visco-elastic material that behaves in a quasi-Newtonian fashion. The mantle upwelling (i.e., plume head) is produced by a high viscosity, low-density silicone sphere with a constant radius (15 mm) rising through the mantle at an average rise velocity of ~2.6 mm/s. A side-view camera images the ascending path of the sphere, allowing to track the sphere location and compute its velocity. A top-view, 3-D scanner records the evolution of topography from which the lithospheric uplift rate is inferred. All details about the model set-up, modeling results and interpretation are detailed in Sembroni et al. (2017). The additional material presented in this publication includes 2 tables, 5 figures, and 23 time-lapse movie. The rheological properties of materials used in each model are listed in Table 1.Table 2 is an excel file where the raw data of the models are specified (i.e., bulge width, topography, and uplift rate). Such data have been obtained by the 3-D scanner and then processed by a MATLAB code.Figure 1, Figure 2, Figure 3, Figure 4, Figure 5 represent the 2-D topography evolution of the bulge in each experiment. Images have been grouped by considering the different experimental setups (i.e., homogeneous continental lithosphere - Figure 1, homogeneous oceanic lithosphere - Figure 2, low viscous decoupling layer - Figure 3, intermediate viscous decoupling layer - Figure 4, high viscous decoupling layer - Figure 5). Such figures consist of topographic profiles extracted from the surface obtained by the 3-D scanner in four different time steps (red numbers in the figures). 22 side-view videos (from Movie 1 to Movie 22) show the progress of the models from the releasing to the impingement of the sphere beneath the plate. The velocity of the video has been accelerated by a factor of 7. While, the first 22 movies show the evolution of the experiments, Movie 23 shows the mantle convective flow associated to the ascending path of the mantle upwelling. Such flow has been detected by tracking the bubbles inside the syrup. In this model, no lithosphere has been placed on top of the syrup.
# 4
Brizzi, Silvia • Funiciello, Francesca • Corbi, Fabio • Di Giuseppe, Erika • Mojoli, Giorgio
Abstract: Gelatin is a versatile material commonly used in analogue modelling because of its complex rheology, which allows simulating a wide range of tectonic processes requiring either elastic (e.g., dyke intrusions models) and viscoelastic behavior (e.g., analog earthquakes models). Salt (NaCl) is generally added to gelatin to improve the scaling of the models by increasing the density of the material. The addition of salt results also in a weakening of the gelatin structure, which in turn can dramatically affect its rheological properties. Here, we provide raw data of rheometric measurements performed to test the rheological properties of type A (pig-skin) 2.5 wt% gelatin at T=10°C as a function of salt concentration and ageing time. Each sample was analyzed using dynamical oscillation tests (i.e., amplitude, frequency and time sweep tests) in shear strain controlled mode. All details about sample preparation procedure, measuring protocol, as well as results and data interpretation can be found in Brizzi et al. (2016). The data are provided as Excel files in *.xlsx format and comma-separated files in *.csv format. Each contains multiple measurements. In the Excel files, each measurement is presented as a table in different spreadsheets. In the comma-separated files, each measurement start with its own data series information, followed by the actual data. All files can be opened using MS Excel or equivalent software. An overview of tested salt concentrations and performed measurements can be found in the Explanation_Brizzi_et_al_2016.pdf file. A full list of the files included is given in List_of_files_Brizzi_et_al_2016.pdf.
# 5
Souloumiac, Pauline • Maillot, Bertrand • Herbert, Justin W. • McBeck, Jessica A. • Cooke, Michele L.
Abstract: The data set includes photos, force measurements, and incremental displacement fields captured in experiment E240 run at the physical modeling laboratory (GEC) at the Université de Cergy-Pontoise. We built the accretionary wedge using a novel sedimentation device [Maillot, 2013] that distributes sand in planar layers and creates homogeneous sandpacks. We include photos of the side of the accretionary wedge in a zipped folder (E240_sideviews). Throughout the experiment, we took a photo every 5 seconds. We include the incremental displacement fields calculated from digital image correlation of sequential photos [Adam et al., 2005; Hoth, 2005] as matlab (.mat) files in a zipped folder (E240_001-062_DIC_MAT), and as .csv files in a zipped folder (E240_001-062_DIC_CSV). The .mat and .csv files are numbered to indicate which sequential photo pairs were used to calculate the displacements. For example, E240_001-062_0001_CSV.csv (and E240_001-062_0001.mat) contain the incremental displacements between photo 001.jpg and 002.jpg. All files are included in a single zip folder (Souloumiac-et-al-2017-supplementary-datasets.zip). The matlab files include the variable arrays x, y, u, v, which are the x and y coordinates (in pixels relative to the upper left corner of the image), and the horizontal (u) and vertical (v) incremental displacement fields (in pixels), respectively. The .csv files contain four columns of data with the x and y coordinates in the first two columns, and the horizontal (u) and vertical (v) displacements in the last two columns. We include force measurements in a text file (E240_force_corrected) with two columns: the first column is the total displacement of the backwall in millimeters at the time that the force measurement was recorded, and the second column is the normal force exerted on the backwall, in Newtons. The force measurements are calculated from measurements of strain gauges mounted on a wall of the sand box (i.e., the backwall) [e.g., Souloumiac et al., 2012].
# 6
Verberne, Berend Antonie • Chen, Jianye • Pennock, Gillian
Abstract: The largest magnitude earthquakes nucleate at depths near the base of the seismogenic zone, near the transition from velocity weakening frictional slip to velocity strengthening ductile flow. However, the mechanisms controlling this transition, and relevant to earthquake nucleation, remain poorly understood. Here we present data from experiments investigating the effect of slip rate on the mechanical properties and microstructure development of simulated calcite fault gouge sheared at ~550°C, close to the transition from (unstable) velocity weakening to (stable) velocity strengthening behaviour, reported by Verberne et al. (2015). We conducted experiments at a constant effective normal stress (σneff) of 50 MPa, as well as σneff-stepping tests employing 20 MPa ≤ σneff ≤ 140 MPa, at constant sliding velocities (v) of 0.1, 1, 10, or 100 µm/s. Samples sheared at v ≥ 1 µm/s showed a microstructure characterized by a single, 30 to 40 μm wide boundary shear, as well as a linear correlation of shear strength (τ) with σneff. Remarkably, electron backscatter diffraction mapping of polygonal shear band grains demonstrated a crystallographic preferred orientation. By contrast, samples sheared at 0.1 µm/s showed a microstructure characterized by homogeneous deformation and plastic flow, as well as a flattening-off of the τ-σneff curve. Our results point to a strain rate dependent frictional-to-viscous transition in simulated calcite fault gouge, and have important implications for the processes controlling earthquake nucleation at the base of the seismogenic zone.
# 7
Hunfeld, Luuk • Niemeijer, André • Spiers, Christopher
Abstract: We investigated the frictional properties of simulated fault gouges derived from the main lithologies present in the seismogenic Groningen gas field (NE Netherlands), employing in-situ P-T conditions and varying pore fluid salinity. Direct shear experiments were performed on gouges prepared from the Carboniferous Shale/Siltstone underburden, the Upper Rotliegend Slochteren Sandstone reservoir, the overlying Ten Boer Claystone, and the Basal Zechstein anhydrite-carbonate caprock, at 100 ºC, 40 MPa effective normal stress, and sliding velocities of 0.1-10 µm/s. As pore fluids, we used pure water, 0.5-6.2 M NaCl solutions, and a 6.9 M mixed chloride brine mimicking the formation water. Our results show a mechanical stratigraphy, with a maximum friction coefficient (µ) of ~0.65 for the Basal Zechstein, a minimum of ~0.37 for the Ten Boer claystone, ~0.6 for the reservoir sandstone, ~0.5 for the Carboniferous, and µ-values between the end-members for mixed gouges. Pore fluid salinity had no effect on frictional strength. Most gouges showed velocity-strengthening behavior, with little effect of pore fluid salinity on (a-b). However, Basal Zechstein gouge showed velocity-weakening at low salinities and/or sliding velocities, as did 50:50 mixtures with sandstone gouges, tested with the 6.9 M reservoir brine. From a Rate-and-State-Friction viewpoint, our results imply that faults incorporating Basal Zechstein anhydrite-carbonate material at the top of the reservoir are the most prone to accelerating slip, i.e. have the highest seismogenic potential. The results are equally relevant to other Dutch Rotliegend fields and to similar sequences globally. The data is provided in a .zip folder with 29 subfolders for 29 experiments/samples. Detailed information about the files in these subfolders as well as information on how the data is processed is given in the explanatory file Hunfeld-et-al-2017-Data-Description.pdf
# 8
Del Bello, Elisabetta • Taddeucci, Jacopo • Scarlato, Piergiorgio • Giacalone, Emanuele
Abstract: This data publication includes particle size distribution data of natural volcanic ash samples used as starting material for laboratory experiments simulating the aggregation/disaggregation of colliding volcanic ash particles. Full details of the experimental method can be found in Del Bello et. al. (2015) and in the data description file provided here. Here we report raw particle size distribution data obtained through separation analysis. Two types of volcanic ash were analysed: i) andesitic ash from the Sakurajima volcano (Japan), collected from July 2013 deposits (named Sak sample); ii) phonolitic ash collected from the basal fallout layer of the ~10 ka old Pomici Principali eruptive unit [Di Vito et al., 1999]) of the Campi Flegrei (named Ppa). For both compositions, 3 different starting materials were obtained by hand sieving the natural samples into three main particle size classes: (i) <32 μm, (ii) 32–63 μm, and (iii) 63–90 μm. For the phonolitic composition Ppa two additional starting materials were obtained by mixing the <32 μm and the 32–63 μm classes in known proportions. For each starting material, the grain size distribution of the sample was measured by a multiwavelength separation analyzer (LUMIReader®, https://www.lum-gmbh.com/lumireader_en.html). This device measures space and time resolved profiles of the transmitted light across the water-diluted sample (5% solid content) during sedimentation of particles. The cumulative volume-weighted particle size distribution is obtained from the extinction profiles using the multi-wavelength Particle size Analyser modulus (PSA). Details on the sample preparation procedure can be found in Detloff et al. (2006). For each measurement performed (see Table 1), a pdf file and a excel file are provided. The pdf file lists the analysis summary, including a description of the analysis settings and conditions, materials used, and distribution model adopted for the fit. It also provides graphs of the obtained volume weighted cumulative grain size distribution, and of the measured transmission profiles for each wavelength (870 nm, 630 nm and 470 nm, respectively). The Excel (*.xlsx format) file include 4 datasheets, listing the results (sheet name ending *_R) and the fit data (sheet names ending *_F01,*_F02, *_F03) obtained for the different instrument wavelength. In each datasheet the following data are listed in the columns: particle grain size (x3 in µm), volume weighted distribution (Q3(x) in %), Martin diameter (x3m in µm), volume weighted density distribution (q3(x) in 1/µm). The fit datasheets also include information on the fit such as distribution model used and distribution parameters (quantiles, median, standard deviation, span, etc..). A full list of the files included is given in List_of_files_DelBello et al 2017.pdf.
Measurement name Sample type Size class (µm)* Ppamag32_01 Phonolite (Ppa) 32-63 Ppamag32_03 Phonolite (Ppa) 32-63 Ppamag32_61 Phonolite (Ppa) 32-63Ppamag64_01 Phonolite (Ppa) 63-90Ppamin32_00 Phonolite (Ppa) <32 Ppamin32_02 Phonolite (Ppa) <32 Ppamin32_35 Phonolite (Ppa) <32 Ppamix32_02 Phonolite (Ppa) <32 + 32-63 (1:1) Ppamix32_03 Phonolite (Ppa) <32 + 32-63 (1:10)Ppamix32_04 Phonolite (Ppa) <32 + 32-63 (1:5) Ppamix32_05 Phonolite (Ppa) <32 + 32-63 (1:2) Ppamix32_06 Phonolite (Ppa) <32 + 32-63 (1:1) Ppamix32_70 Phonolite (Ppa) <32 + 32-63 (1:10) Ppamix32_71 Phonolite (Ppa) <32 + 32-63 (1:5) Ppamix32_72 Phonolite (Ppa) <32 + 32-63 (1:2) Ppamix32_73 Phonolite (Ppa) <32 + 32-63 (1:1) Ppamix63_02 Phonolite (Ppa) <32 + 63-90 (1:1) Ppatotal_01 Phonolite (Ppa) total Sakmag32_02 Andesite (Sak) 32-63 Sakmag63_01 Andesite (Sak) 32-63 Sakmag90_01 Andesite (Sak) 63-90 Sakmin32_01 Andesite (Sak) <32 Sakmin32_02 Andesite (Sak) <32 Saktotal_01 Andesite (Sak) total Table 1. List of particle size characterization measurements included in this dataset. *When mixed sample are used, the respective weight proportion of the component classes used are reported in brackets.
# 9
Rufin, Philippe • Levers, Christian • Baumann, Matthias • Jägermeyr, Jonas • Krueger, Tobias • (et. al.)
Abstract: The spatial distribution of irrigation dam benefits is poorly understood at the global scale due to a scarcity of spatial information on irrigation dam command areas. Several studies aimed at mapping irrigated lands globally, but the spatially explicit attribution of irrigated lands to dams has rarely been undertaken. First approaches attributing changes in agricultural production to dams were based on aggregated areal units, such as administrative districts (Duflo and Pande, 2007), or watershed boundaries (Strobl and Strobl, 2011). These approaches represent only indirect approximations of command areas, and may be improved by considering spatially explicit dam- and location-specific parameters (e.g. reservoir storage capacity or topography). Such a refined dataset is required for better understanding the spatial distribution and properties of irrigation dam command areas. We approximated irrigation dam command areas for 1,370 dams with irrigation function which were commissioned across 71 countries since 1985. We approximated a) the extent and b) the location of irrigation dam command areas at 500m spatial resolution using global-scale assumptions motivated by existing literature. We first estimated command area extent [ha] based on reservoir storage capacity [m³], while accounting for country-level variations in the ratio of land irrigated with surface water per unit of total national reservoir storage capacity [ha/m³]. We then spatially allocated the estimated command area extent for each dam, accounting for parameters representing: irrigated cropland abundance (P1), topography relative to the dam (P2), watershed boundaries (P3), reservoir size (P4), national borders (P5), and distance to the dam (P6). To understand the sensitivity of the allocation towards the assumptions underlying the selected parameters, we tested 24 different allocation schemes with varying parameter settings. An overview of the datasets used for the command area extent estimation and the spatial allocation procedure, as well as an illustration of an exemplary allocation is included in the download. For a detailed description of the methods used to produce these data, please see Rufin et al. (2018).
The CA1985 dataset includes two raster datasets in geographic coordinates (WGS1984, EPSG: 4326) in GeoTiff format: 1) CA1985_binary.tif: The spatial dataset of irrigation dam command areas commissioned since 1985 used for the analyses in Rufin et al. (under review). Command areas (value 1) are here defined as irrigated areas, within watershed delineations scaled according to the reservoir storage capacity, located topographically below, but at maximum 10 m above the impoundment and within the national borders of the dam location. A detailed description of the parameters and underlying assumptions is provided in Rufin et al. (2018). 2) CA1985_sensitivity.tif: An overlay of 24 allocation schemes with varying parametrizations to inform about the uncertainty associated with each allocated pixel. The data values range between 0 (not identified as a command area in any allocation scheme) and 24 (this pixel was identified as a command area in all 24 allocation schemes). A detailed description of the parameters used in the sensitivity analysis is provided in Rufin et al. (2018).
# 10
Vogel, Kristin • Laudan, Jonas • Sieg, Tobias • Rözer, Viktor • Winter, Benjamin • (et. al.)
Abstract: A severe flash flood event hit the town of Braunsbach (Baden-Württemberg, Germany) on the evening of May 29, 2016, heavily damaging and destroying several dozens of buildings. It was only one of several disastrous events in Central Europe caused by the low-pressure system “Elvira”. The DFG Research Training Group “Natural hazards and risks in a changing world” (NatRiskChange, GRK 2043/1) at the University of Potsdam investigated the Braunsbach flash flood. In this context damage data for 94 affected buildings, describing building characteristics, the degree of impact and the caused damage, were collected ten days after the flood event and provide the basis for damage assessment studies (Agarwal et al., 2017; Laudan et al., 2017, Vogel et al., 2017).
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