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562 results for “faulting”
Laboratory visualization of fault asymmetry formation via acoustic emission and digital imaging correlation
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Understanding Transaction-Reverting Faults in Smart Contracts
<div> <h1>Understanding Transaction-Reverting Faults in Smart Contracts</h1> </div> <p>This project aims to provide a benchmark for smart contract developers and researchers to enhance their understanding of transaction-reverting faults (TR faults) in smart contracts. The project is associated with a paper titled <strong>Understanding Transaction-Reverting Faults in Smart Contracts</strong>.</p> <div> <h2>Dataset Description</h2> </div> <div> <h3>Overview</h3> </div> <p>We identify 301 real-world TR faults from open-source GitHub project and categorize them into machine auditable and machine unauditable faults. Among these faults, 224 (74.4%) fall into the machine auditable category, while the remaining 77 (25.6%) fall into the machine unauditable category. For detailed information on these 301 TR fault contracts, please refer to the <a href="../api/records/11889080/draft/files/TRFaults.zip/content" target="_blank" rel="noopener noreferrer">TRFaults.zip</a>. For more details, please refer to our GitHub repo. </p> <div> <h3>Folder Structure</h3> </div> <p>The dataset is structured into four distinct sections within the <a href="../api/records/11889080/draft/files/TRFaults.zip/content" target="_blank" rel="noopener noreferrer">TRFaults.zip</a> :</p> <ul> <li>machine_auditable_faults: includes the buggy and patched version of the 224 machine auditable faults.</li> <li>machine_unauditable_faults: includes the buggy and patched version of the 77 machine unauditable faults.</li> <li>machine_auditable_faults.csv: contains detailed information of each machine auditable fault, including the commit URL, category, and project type.</li> <li>machine_unauditable_faults.csv: contains the detailed information of each machine unauditable fault, including the commit URL, category, and project type.</li> </ul>
Fault-Tolerant Computing with Single Qudit Encoding in a Molecular Spin. Open data set
<div> <p>Data supporting the original figures 2, 3 and 4 (ESI) of the related manuscript.</p> </div>
Supporting GIS file for: Tectonic landform and lithologic age impact uncertainties in fault displacement hazard models
<p>This project aims to understand how the error in mapped fault location and the residual between the modeled and observed coseismic displacements vary with tectonic landform and the surficial lithologic age. We focus on four historical earthquakes: the M6.9 Borah Peak, 2014 M6.0 Napa, 2016 M7.0 Kumamoto, and 2016 M7.8 Kaikoura earthquakes.</p> <p>The GIS shape file contains information about the tectonic landform, the surficial landscape age, the observed and modelled coseismic displacement, fault location error, and the confidence ranking of the mapped fault trace. Each entry corresponds to a location where a displacement measurement was made following the earthquake of focus. Additional detail is given in the readme.</p> <p>The entries in the GIS file are collected from the following references:</p> <p>Chiou, B., Chen, R., Thomas, K., Milliner, C. W. D., Dawson, T., & Petersen, M. D. (2022). Surface Fault Displacement Models for Strike-Slip Faults. <em>Natural Hazards Risk and Resiliency Research Center B. John Garrick Institute for the Risk Sciences University of California, Los Angeles</em>, <em>Report GIRS‐2022‐07</em>, 186. https://doi.org/10.34948/N3RG6X</p> <p>Crone, A. J., Machette, M. N., Bonilla, M., Lienkaemper, J. J., Pierce, K., Scott, W., & Bucknam, R. (1987). Surface faulting accompanying the Borah Peak earthquake and segmentation of the lost river fault, central Idaho. <em>Bulletin of the Seismological Society of America</em>, <em>77</em>.</p> <p>Graymer, R. W., Brabb, E., Jones, D. L., Barnes, J., Nicholson, R. S., & Stamski, R. E. (2007). <em>Geologic Map and Map Database of Eastern Sonoma and Western Napa Counties, California</em> (No. U.S. Geological Survey Scientific Investigations Map 2956). Retrieved from https://doi.org/10.3133/sim2956</p> <p>Heron, D. W. (2018). Geological Map of New Zealand 1:250 000. GNS Science Geological Map 1 (2nd ed.) Lower Hutt, New Zealand. GNS New Zealand. Retrieved from https://www.gns.cri.nz/data-and-resources/geological-map-of-new-zealand/</p> <p>Hoshizumi, H., Ozaki, M., Miyazaki, K., Matsuura, H., Toshimitsu, S., Uto, K., et al. (2004). Geological Map of Japan 1:200,000: Kumamoto. Geological Survey of Japan. Retrieved from https://www.gsj.jp/Map/EN/geology2-6.html#Kumamoto</p> <p>Janecke, S. U., & Wilson, E. (1992). Geologic map of the Borah Peak, Burnt Creek, Elkhorn Creek, and Leatherman Peak 7.5’ quadrangles, Custer County, Idaho, Scale 1:24,000. Idaho Geological Survey Technical Report 92-5. Retrieved from https://www.idahogeology.org/product/T-92-5</p> <p>Kuehn, Nicolas, Kottke, A., Madugo, C., Sarmiento, A., & Bozorgnia, Y. (2022). Report GIRS 2022-06: UCLA–PG&E Fault Displacement Model. https://doi.org/10.34948/N3X59H</p> <p>Lewis, R. S., Link, P., Stanford, L. R., & Long, S. P. (2012). <em>Geologic Map of Idaho</em>. Moscow, Boise, Pocatello: Idaho Geologic Survey. Retrieved from https://www.idahogeology.org/maps-pubs-data/state-geologic-map</p> <p>Ponti, D. J., Blair, J. L., & Rosa, C. M. (2019). Digital Datasets Documenting Fault Rupture and Ground Deformation Features Produced by the Mw 6.0 South Napa Earthquake of August 24, 2014 [Data set]. U.S. Geological Survey. https://doi.org/10.5066/F7P26W84</p> <p>Sarmiento, A., Madugo, D., Bozorgnia, Y., Shen, A., Mazzoni, S., Lavrentiadis, G., et al. (2021). Fault Displacement Hazard Initiative Database. <em>Report No. GIRS-2021-08, Revision 3.3 Dated 29 May 2024. Los Angeles, CA: The B. John Garrick Institute for the Risk Sciences at UCLA Engineering</em>. https://doi.org/10.34948/N36P48</p> <p>Scott, C., Adam, R., Arrowsmith, R., Madugo, C., Powell, J., Ford, J., et al. (2023). Evaluating how well active fault mapping predicts earthquake surface-rupture locations. <em>Geosphere</em>, <em>19</em>(4), 1128–1156. https://doi.org/10.1130/GES02611.1</p> <p>Scott, C. P., Arrowsmith, J. R., Nissen, E., Lajoie, L., Maruyama, T., & Chiba, T. (2018). The <em>M</em> 7 2016 Kumamoto, Japan, Earthquake: 3-D Deformation Along the Fault and Within the Damage Zone Constrained From Differential Lidar Topography. <em>Journal of Geophysical Research: Solid Earth</em>, <em>123</em>, 6138–6155. https://doi.org/10.1029/2018JB015581</p> <p>Vincent, K. R. (1995). Implications for models of fault behavior from earthquake surface displacement along adjacent segments of the Lost River fault, Idaho<em>:</em> University of Arizona.</p> <p>Wagner, D., & Gutierrez, C. (2017). <em>Preliminary Geologic Map of the Napa and Bodega Bay 30’ x 60’ Quadrangles, California</em>. California Department of Conservation. Retrieved from https://ngmdb.usgs.gov/Prodesc/proddesc_105819.htm</p> <p>Zinke, R., Hollingsworth, J., Dolan, J. F., & Van Dissen, R. (2019). Three‐Dimensional Surface Deformation in the 2016 M <sub>W</sub> 7.8 Kaikōura, New Zealand, Earthquake From Optical Image Correlation: Implications for Strain Localization and Long‐Term Evolution of the Pacific‐Australian Plate Boundary. <em>Geochemistry, Geophysics, Geosystems</em>, <em>20</em>(3), 1609–1628. https://doi.org/10.1029/2018GC007951</p>
DATA_building a multilake paleosismometer for the Xianshuihe Fault (SE Tibet)
<p>Sedimentological and geochemical data for lakes Mugecuo, Yalatuo and Yari Acuo (Ganzi prefecture, Sichuan province, China).</p> <p>Including grain-size data, XRF-corescanning results, SEM images and short-lived radioelements cocnentration.</p>
flood modeling datas for Catastrophic outburst floods along the middle Yarlung Tsangpo River: responses to coupled fault and glacial activity on the southern Tibetan Plateau
Open the record for dataset details and reuse information.
Probing the Evolution of Fault Properties During the Seismic Cycle with Deep Learning - Dataset
<p>This dataset is intended to be used in conjunction with the code provided at the following link: <a href="https://github.com/lauralaurenti/CNN_Norcia_sequence_evolution">https://github.com/lauralaurenti/CNN_Norcia_sequence_evolution</a></p>
Anisotropic Tomography and Seismotectonics of the Longmenshan Fault Zone in East Tibet
<p>This file includes velocity and anisotropic dataset of the Longmenshan Fault Zone in East Tibet.</p>
UAV surveying data along the Dong Co Fault and its traces, in central Tibet
<p>These data are the Dong Co Fault traces(.kmz) based on the interpretation of a Landsat image, and the unmanned aerial vehicle topography surveying (UAV data) of two offset fluvial terraces along the Dong Co Fault. </p> <p>The UAV data was acquired by 80-m-altitude aerial photographs using a DJI (Dajiang Innovations Science and Technology Co., Ltd.) Phantom 4 quadrotor copter mounted with a 12.4-megapixel digital camera and measured 12 ground control points (GCPs) using a Trimble R8 RTK-GPS with an accuracy of several centimeters. A 5.94 cm/pix-resolution digital elevation model (DEM) was produced by PhotoScan software.</p>
Adaptive Online Fault Diagnosis in Robot Swarms
<p>Contained are the data sets generated and analysed for the paper 'Adaptive Online Fault Diagnosis in Robot Swarms' by James O'Keeffe, Danesh Tarapore, Alan G. Millard and Jon Timmis</p>
Table for Paper: Late Pleistocene-Holocene Paleoseismology of Mingle-Damaying Fault and the Indication for the Crustal Shortening Mechanism of East Qilian Shan, Northeast Tibetan Plateau
<p>The material for sampling is charred material and they are analyzed in Beta Analytic Inc., USA and AMS <sup>14</sup>C dating laboratory of Peking University. Both of the laboratories provide conventional age, as well as calibrated age using INTCAL13 (Reimer et al., 2013).</p>
Data for paper: Late Pleistocene-Holocene Paleoseismology of Mingle-Damaying Fault and the Indication for the Crustal Shortening Mechanism of East Qilian Shan, Northeast Tibetan Plateau
<p>All of the data are in format of JPG</p>
Mechanical data from rotary shear experiments for the manuscript: Mechanical behavior of fluid-lubricated faults
<p>Mechanical data from rotary shear experiments. <strong>sNNNN</strong> has no file extension but it is a tab-delimited file including all the original raw measurements. Raw measurements are acquired via a National Instruments Labview interface communicating with a real-time acquisition system. Use the ReadMe.txt file for the explanation on the conversion of the raw data.</p>
Data for paper: Segmented Thrust Faulting: Example from the Northeastern Margin of the Tibetan Plateau
<p>If additional data is needed, please contact me by E-mail: skatetangshan@vip.126.com</p>
Data used in the paper "The minimum scale of grooving on a recently ruptured limestone fault"
<p>There are two types of data presented: matlab structures and xyz files.</p> <p>We include two matlab structures of the results of our analysis, one for the Mt. Vettoretto fault and one for the Corona Heights fault. They have the following 9 fields:</p> <ul> <li>div_x: The length scale where parallel and perpendicular roughness in respect to the striations converge. This is also known as the minimum scale of grooving or the critical length scale, L<sub>c</sub>.</li> <li>div_y: The RMS height where parallel and perpendicular roughness converge.</li> <li>L1 and L2: The length scales in parallel and perpendicular directions.</li> <li>H1 and H2: The RMS height along the length scales in parallel and perpendicular directions. If L1 is in the parallel direction then H1 is also in the parallel direction.</li> <li>Z: The gridded topographic map that is used in the Monte Carlos RMS analysis to then calculate L1, L2, H1, and H2.</li> <li>dx: The spacing of the gridded data points in the gridded topographic map.</li> <li>FileName: The name of the original xyz scan for the Mt. Vettoretto data. For the Corona Heights data, the name of the files given to me by T. Candela.</li> </ul> <p>The xyz files presented are white light interferometer and structure from motion scans of the Mt. Vettoretto fault surface. They correspond to the "FileName" field of the MtVet_MinScaleRMS.mat file.</p>
Segmented Thrust Faulting: Example from the Northeastern Margin of the Tibetan Plateau
<p>If more information is needed, please contact the author by skatetangshan@vip.126.com</p>
Dataset for the study of "Seismic fault slip at depths simulated by high-velocity friction experiments under hydrothermal conditions"
<p>These are measured data of high-velocity friction experiments conducted on gabbro and marble under hydrothermal conditions (initial ambient temperature of 40 to 400 degC and pore pressure of 30 MPa). </p> <p>In each txt file, Column1 to Column9: Time (s), Slip Velocity (m/s), Displacement (m), Friction coefficient, Axial Displacement (mm), Pore water pressure (MPa), Effective normal stress (MPa), Sample Temperature (degC) and Furnace Temperature (degC).</p>
Earthquake data in the East Anatolian fault
<p>This earthquake data in the East Anatolian Fault was published by previous documents and was used in my paper submitted. </p>
Millennial slip-rates variability of along-strike active faults in the Italian Southern Apennines revealed by cosmogenic 36Cl dating of fault scarps
<p>Supporting information for "<span>Millennial slip-rates variability of along-strike active faults in the Italian Southern Apennines revealed by cosmogenic <sup>36</sup>Cl dating of fault scarps"</span></p>
3-D Crustal Vp, Vs, Vp anisotropy tomography models of the Suqian segment of the Tanlu fault zone
<p>3-D Crustal Vp, Vs, Vp anisotropy tomography models of the Suqian segment of the Tanlu fault zone</p>
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