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562 results for “faulting”
Reproduction Package for Article `Fault Localization on Witnesses'
<h2>Fault Localization on Witnesses</h2> <h2>Article Abstract</h2> <p>When verifiers report an alarm, they export a violation witness (exchangeable counterexample)<br>that helps validate the reachability of that alarm.<br>Conventional wisdom says that this violation witness should be very precise:<br>the ideal witness describes a single error path for the validator to check.<br>But we claim that verifiers overshoot and produce large witnesses<br>with information that makes validation unnecessarily difficult.<br>To check our hypothesis, we reduce violation witnesses to that information<br>that automated fault-localization approaches deem relevant for triggering the reported alarm in the program.<br>We perform a large experimental evaluation on the witnesses<br>produced in the International Competition on Software Verification (SV-COMP 2023).<br>It shows that our reduction shrinks the witnesses considerably<br>and enables the confirmation of verification results that were not confirmable before.</p> <h2>VM</h2> <p>The username for the VM is `vagrant`.<br>The password for the VM is `vagrant`.</p> <h2>System Requirements</h2> <p>The artifact requires 4 CPU cores and 8 GB of RAM.</p> <p>To inspect the data, we require at least 150GB of empty disk space to run the VM.<br>To reproduce the results, we require 155GB.<br>To run the full reproduction, we require 300GB.</p> <p>The VM was tested on Ubuntu with Virtual Box Version 7.0.10 r158379 (Qt5.15.3).</p> <h2>Reproduction</h2> <p>Import the VM to VirtualBox and start it.<br>We provide symbolic links to the reproduction directory on the Desktop.<br>Please follow the instructions in the `ReadMe.md` inside the VM (located at `~/fault-localization-witnesses/ReadMe.md`).<br>The upcoming three subsections serve as a quick-start guide for our artifact.</p> <h3>Reproduce the Example</h3> <p>To reproduce the example in our paper, navigate to `~/fault-localization-witnesses` and execute `./example.sh`.</p> <h3>Reproduce the Plots</h3> <p>Execute `./reproduce.sh` from `~/fault-localization-witnesses/` to reproduce our experiments.</p>
Simulation Results in the Paper "Propagation of Slow Slip Events on Rough Faults: Clustering, Back Propagation, and Re-rupturing" [Dataset]
<p>Data file "simulations.mat" contains the 5 simulations of slow slip events on flat or rough faults. </p> <table> <tbody> <tr> <td>structure array</td> <td>description</td> <td>reference</td> </tr> <tr> <td>s0</td> <td> 2.5 km long flat fault</td> <td>Fig. 2b</td> </tr> <tr> <td>s1</td> <td>2.5 km long rough fault</td> <td>Fig. 2c</td> </tr> <tr> <td>s2</td> <td>10 km long rough fault</td> <td>Fig. 5</td> </tr> <tr> <td>s3</td> <td>10 km long fractal fault</td> <td>Fig. 7</td> </tr> </tbody> </table> <p>structure array consists of:</p> <p>t: time (s)</p> <p>x: distance (m)</p> <p>v: slip rate (m/s)</p> <p>slip: accumulated slip (m)</p> <p>tau: shear stress (Pa)</p> <p>sigma: normal stress (Pa)</p> <p>notes: description</p> <p> </p> <p>Data file "catalog.mat" contains 3 simulated slow slip events' catalogs on flat and rough faults, c0, c1, and c2, in Fig. 4a, 4b, and 4c, respectively.</p> <p>It consists of:</p> <p>l: rupture length (m)</p> <p>time: time (s)</p> <p>notes: description</p>
Replication package for the paper: Harnessing Test Call Structures for Improved Fault Localization Effectiveness
<p>This repository contains the replication package for the paper <strong>"Harnessing Test Call Structures for Improved Fault Localization Effectiveness"</strong>. The package includes the necessary scripts, data, and instructions to reproduce the results presented in the study, focusing on the effectiveness of Spectrum-Based Fault Localization (SBFL) using the Barinel algorithm.</p> <h3>Description of Folders and Files:</h3> <ul> <li><strong>algorithms/</strong>: Contains the SBFL algorithms implemented for this study. Note that only the Barinel algorithm was used in the presented results.</li> <li><strong>base/</strong>: Contains the scripts needed for calculating spectra for SBFL.</li> <li><strong>D4J/</strong>: Contains the Defects4J projects. These need to be unpacked using the appropriate scripts provided in this folder.</li> <li><strong>changeset.json</strong>: Contains metadata about changesets for the projects analyzed in this study.</li> <li><strong>main.py</strong>: The main script for calculating ranks and metrics for the selected projects and heuristics.</li> <li><strong>SBFL ranks.csv</strong>: Contains the SBFL ranks calculated from the analysis.</li> </ul> <h2>Requirements</h2> <p>To run the scripts, you will need:</p> <ul> <li><strong>Python 3.9</strong></li> <li><strong>Defects4J</strong>: The <code>D4J</code> folder should contain unpacked Defects4J projects. Please ensure you have followed the instructions in the <code>D4J</code> folder to unpack the projects accordingly.</li> <li><strong>Required Python packages</strong> (install using <code><a href="http://localhost:63343/markdownPreview/1636345610/markdown-preview-index-2076127249.html?_ijt=mqjd55qrfb1m1q15g8bm74pk1u#"></a>pip</code>): <code><a href="http://localhost:63343/markdownPreview/1636345610/markdown-preview-index-2076127249.html?_ijt=mqjd55qrfb1m1q15g8bm74pk1u#"></a>pip install -r requirements.txt</code></li> <li><strong>Prepare the Defects4J Projects</strong>: <ul> <li>Navigate to the <code>D4J</code> directory.</li> <li>Run the provided scripts to unpack the necessary Defects4J projects.</li> <li>Ensure that each project folder is structured properly to be used by the <code>main.py</code> script.</li> </ul> </li> </ul> <h2>Running the Main Script</h2> <p>The main analysis script is <code>main.py</code>, which calculates the SBFL ranks using the Barinel algorithm based on the selected heuristics.</p> <h3>Usage</h3> <p>To run the main script:</p> <div></div> <pre><code><a href="http://localhost:63343/markdownPreview/1636345610/markdown-preview-index-2076127249.html?_ijt=mqjd55qrfb1m1q15g8bm74pk1u#"></a>python main.py </code></pre> <h3>Parameters and Settings:</h3> <ul> <li><strong>Projects and Ranges</strong>: The projects are defined in the <code>projects</code> list, with their respective bug ranges in the <code>ranges</code> list. The script iterates over these projects and bug IDs to calculate SBFL ranks.</li> </ul> <h3>Outputs:</h3> <ul> <li>The script outputs the ranks and coverage metrics directly to the console. Results can be redirected or saved as needed.</li> <li>It uses the <code>Ranks.RankContainer</code> class to calculate and print the minimum suspiciousness ranks for the selected metrics.</li> </ul>
Isotopic Constraints from Carbonates on the Thermochronologic Evolution of Fluid Flow and Faulting in the Monitor Range, Central Nevada, USA
<p>The dataset contains the following information:</p> <p>"Full data summary"- Isotopic data and GPS coordinates for all samples analyzed in this study.</p> <p>"L013 report", "L052 report"- Raw clumped isotope data for all samples.</p> <p>"U-Pb raw data"- Calcite U/Pb ratios of psuedo-spots for all unknown samples and standards analyzed in this study.</p> <p>"Yanay CC20"- Zircon U/Pb data for standards and unkown sample grains.</p>
Dataset for "History and dynamics of Fennoscandian Ice Sheet retreat, contemporary ice-dammed lake evolution, and faulting in the Torneträsk area, northwestern Sweden"
<p>This dataset contains the GIS shapefiles and the high resolution map for the manuscript "Ice-dammed lakes and contemporary faulting in the Torneträsk region of northern Sweden are key to understanding regional Fennoscandian Ice Sheet deglaciation patterns and dynamics" in preparation for <em>The Cryosphere</em>. </p>
Characteristically repeating earthquake catalog for Mendocino - Maacama fault
<p>Characteristically repeating earthquake catalog for Mendocino - Maacama fault</p>
Controls of Grain Breakage on Shear Band Morphology and Permeability Evolution in Fault Gouges
<p>The simulations are designed and run within the software platform PFC (https://www.itascacg.com/software/PFC). The data set is composed of results of two-dimensional (2D) Discrete Element Method (DEM) modeling performed by Li et al., with the licensed commercial <em>Particle Flow Code </em>2D version 6.0 (PFC2D 6.0) from Itasca Consulting Group, Ltd. </p>
Data for Using Contextual Knowledge in Interactive Fault Localization
<p>Data used for the experiments in the paper.</p>
Fault test cases for series compensated transmission line with the capacitor at the middle of the line
<p><strong>Description</strong></p> <p>This data set contains time series data of different simulated fault cases in high voltage series compensated transmission lines. The simulation is done in PSCAD using the Python automation library. The capacitor is located in the middle of the line. The model of the line is given in the attached pdf file. The CT and VT are located at bus S. The distance are counted from bus S. The modelled line is 500 kV and 200 km long. The simulation is run for 1 second with 10 kHz sampling rate. </p> <p>Each file contains 10 data in the following order, </p> <p>Time<br> Voltage phase A<br> Voltage phase B<br> Voltage phase C<br> Current phase A<br> Current phase B<br> Current phase C<br> Voltage across capacitor phase A<br> Voltage across capacitor phase B<br> Voltage across capacitor phase C</p> <p>The variables used to study different test cases are shown below,</p> <p>Fault inception angle (referred to phase A voltage): 0 and 90 degree<br> Source impedance ratio: 0.20 and 0.35<br> Capacitor compensation level: 94 µF(50%), 78 µF(60%), 67 µF(70%)<br> Fault resistance: 0.10, 10, 20 ohm<br> Fault location: 10 km, 30 km, 50, 70 km, 90 km, 95 km, 105 km, 110 km, 130 km, 150 km, 160 km, 170 km, 180 km<br> Fault type: No-fault, AG, BG, CG, ABG, CAG, BCG, ABCG, AB, CA, BC, ABC</p> <p>All these factors lead to 5616 test cases in total. The test cases are organized in four (4) zipped folders each containing 1404 test cases. The PSCAD model file and an example python script that can be used to automate the simulations are also included herewith for anyone interested to replicate the results. </p> <p> </p> <p>The name of the folders contains the information regarding fault inception angle and source impedance ratio for all test cases inside that folder, for example, the folder name <strong>Outputs_0_0.20</strong> can be decoded as,</p> <p>0: Fault inception angle (phase A)<br> 0.20: Source impedance ration</p> <p>The files names inside the folders include information about the other variables used in generating the test case. For example, the name<strong> test_f_10_0_67_0.01</strong> can be interpreted as,</p> <p>test_f: f for forward fault<br> 10: fault location, 10 km<br> 0: Fault type<br> 67: Compensation level<br> 0.01: Fault resistance</p> <p>Fault types are interpreted as in PSCAD.</p> <p>0 = No-Fault,<br> 1 = Phase A to Ground<br> 2 = Phase B to Ground<br> 3 = Phase C to Ground<br> 4 = Phase AB to Ground<br> 5 = Phase AC to Ground<br> 6 = Phase BC to Ground<br> 7 = Phase ABC to Ground<br> 8 = Phase AB<br> 9 = Phase AC<br> 10 = Phase BC<br> 11 = Phase ABC</p> <p>The different line parameters used in the PSCAD model is as below,</p> <p><strong>Conductor</strong></p> <p>Type: Chukar<br> Geometric mean radius: 20.345 mm<br> DC resistance: 0.0318Ω/km<br> Strands: 84<br> Strand radius: 1.8491 mm<br> Relative permeability: 1.0<br> Sag: 12 m<br> Height: 22 m<br> Sub-conductor: 2<br> Sub-conductor spacing: 0.4572 m<br> Ground wire number: 2<br> Radius: 5.5245 mm<br> DC resistance: 2.8645Ω/km<br> Relative permeability: 1.0<br> Sag: 10 m<br> Height: 10 m</p> <p><strong>Impedance</strong></p> <p>Positive sequence 0.018 +j0.339 Ω/km<br> Zero sequence 0.266 +j1.017 Ω/km</p> <p> </p> <p><strong>These simulations were run for assessing time-domain protections. Therefore, the parallel CB protection across the series capacitor is disabled, as one can safely assume even with the highest current levels, the CB will take at least 20 ms to operate. This is higher than the time limits for time-domain protection. </strong></p>
Rate-and-state friction parameters for "Frictional Characteristics of Oceanic Transform Faults: Progressive Deformation and Alteration Controls Seismic Style"
<p>Rate-and-state friction parameters to accompany "Frictional Characteristics of Oceanic Transform Faults: Progressive Deformation and Alteration Controls Seismic Style"</p>
Fault geometry of the 2016 Mw 7.8 Kaikoura earthquake, New Zealand
<p>Citation:</p> <p>Xu, W., Feng, G., Meng, L., Zhang, A., Ampuero, J. P., Bürgmann, R., & Fang, L. (2018). Transpressional rupture cascade of the 2016 Mw 7.8 Kaikoura earthquake, New Zealand. Journal of Geophysical Research: Solid Earth, 123, 2396–2409. https://doi.org/10.1002/2017JB015168</p>
Data Set: The influence of roughness on experimental fault mechanical behaviour and associated microseismicity
<p>This is the data set used to create the figures for the submitted manuscript, The influence of roughness on experimental fault mechanical behaviour and associated microseismicity. Submitted July 2022 to the Journal of Geophysical Research: Solid Earth. Article DOI: 10.1029/2022JB025113</p>
Marikina Valley Fault Creeping Segment (Philippines) - Groundwater Extraction Data
<p>This dataset contain information on groundwater extraction for different well locations along the creeping segment of the Marikina Valley Fault System (Philippines). </p>
Foreshock Activity Promoted by Locally Elevated Loading Rate on a 4-meter-long Laboratory Fault
<p>Experimental data and event catalog used for the study "Foreshock Activity Promoted by Locally Elevated Loading Rate on a 4-meter-long Laboratory Fault"</p>
Estimation of paleotemperature recorded in carbonaceous fault rocks by rock magnetism and vitrinite reflectance — A study from the Haiyuan fault zone in northeastern Tibetan Plateau
<p>A dataset for the article of "<strong>Estimation of paleotemperature recorded in carbonaceous fault rocks by rock magnetism and vitrinite reflectance — A study from the Haiyuan fault zone in northeastern Tibetan Plateau</strong>"</p>
Frictional Properties of Fault Rocks and Creep Mechanism for the Laohushan Segment of the Haiyuan Fault, Northeastern Tibet
<p>All raw data of XRD analyses of fault rocks, particle size analyses of fault gouges, and mechanical data of fault gouge at different temperature are related to this paper.</p>
Preparatory Slip in Laboratory Faults: Effect of Roughness and Loading Rate
<p>Mechanical and acoustic emission data presented in the GRL manuscript: 'Preparatory Slip in Laboratory Faults: Effect of Roughness and Loading Rate', 2022</p>
Modeling Sequences of Earthquakes and Aseismic Slip (SEAS) in Elasto-Plastic Fault Zones With a Hybrid Finite Element Spectral Boundary Integral Scheme
<p>This repository contains the results of 2D simulations of the earthquake cycles accounting for off-fault plasticity.</p> <p>Folder Case1 contains the slip rate and time history for all simulations with cohesion c = 47 MPa</p> <p>Folder Case2 contains the slip rate and time history for all simulations with cohesion c = 25 MPa</p> <p>the mat files contain equivalent plastic strain of each element stored at the start and end of each event with element connectivity and node coordinates.</p>
Isotropic and azimuthally anisotropic lithospheric Vs models beneath the central-southern Tanlu fault
<p>We obtained high-resolution isotropic and azimuthally anisotropic Vs models beneath the central and southern Tanlu fault from ambient noise and earthquake surface waves.</p> <p>The Tanlu3D_iso.mod is a 3D isotropic Vs model with a grid spacing of 0.25deg*0.25deg. The data format is "longitude, latitude, depth, Vs, Vp, density."</p> <p>The Tanlu3D_anis.mod is the 3D azimuthally anisotropic Vs model with a grid spacing of 0.5deg*0.5deg. The data format follows "longitude, latitude, depth, Vs, Vp, density, anis_azimuth, anis_amplitude, azimuth_uncertanty, amplitude_uncertainty".</p> <p> </p> <p>Reference</p> <p>Luo S.*, Yao H.*, Zhang Z., Bem T. S. 2022. High-resolution crustal and upper mantle shear-wave structure beneath the central-southern Tanlu fault: Implications for its initiation and evolution. Earth and Planetary Science Letters, 595. doi:10.1016/j.epsl.2022.117763.</p>
Carson Valley Fault Profiles
<p>These are topographic profiles across fault scarps extracted from lidar data in Carson Valley. </p>
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International Brain Laboratory public data
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OpenNeuro
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