Engineering Geology

Three shale samples are immersed in water for different immersing time t (t=0days, 1day, 3days, 5days, 10days). Then these samples are tested using the nanoindentation experiment with Berkovich indenter and Cube Corner indenter. The indentation grid of Berkovich indenter consists of 225 indentations, and the indentation grid of Cube Corner indenter consists of 100 indentations. The data includes the elastic modulus and hardness measured by Berkovich indenter, as well as the hardness measured by Cube Corner indenter.

Matlab codes and input data for the example used in the paper

The related data of the generated 3-D discontinuity network is given in the EXCEL file.

This zip file contains all input files necessary to run the SHERIFS calculation performed in this study as well as the outputs (txt files, figures, etc.). This study was done with the latest SHERIFS version (1.1) available for free download and use at: https://github.com/tomchartier/SHERIFS. The file is structured in different folders as follows: Inputs such as fault geometry and properties, earthquake catalogue and completeness are located in the 'data' folder (SHERIFS-master\SHERIFS_V1_1\data). The parameters of the models set in our study (scaling laws, background seismicity ratio, fault rupture hypotheses, etc.) are located in the 'Model_EBSZ_1' folder (SHERIFS-master\SHERIFS_V1_1\Complete_EBSZ\Model_EBSZ_1). The different fault rupture hypotheses are separated in different folders named 'sc_Set_1' for hyp. 1, 'sc_Set_5' for hyp. 2, 'sc_Set_6' for hyp. 3 and 'sc_Set_7' for hyp. 4. All fault and multi-fault ruptures of each hypothesis are specified in the 'faults_n_scenarios.txt' file. The different source models (.xml) used to build the MFD of each hypothesis are located in the 'MFD_GR' folder of each set (SHERIFS-master\SHERIFS_V1_1\Complete_EBSZ\Model_EBSZ_1\bg_BG_1\WC1994_A_a\sc_Set_1\bmin_0.8_bmax_1.2\MFD_GR). Txt files of the sampling process and figures of the MFD target fitting of each hypothesis are also visibile in the 'Log' folder of each set (i.e. SHERIFS-master\SHERIFS_V1_1\Complete_EBSZ\Model_EBSZ_1\bg_BG_1\WC1994_A_a\sc_Set_1\bmin_0.8_bmax_1.2\MFD_GR\Log). Outputs of the calculations are located in the 'analysis' folder (SHERIFS-master\SHERIFS_V1_1\Complete_EBSZ\analysis). Inside this, the 'figures' folder is the one that contains the main figures of this study such as the MFDs of each hypothesis, the catalogue MFD, maps of the multi_fault ruptures (FtF) and their NMS distribution. Figures such as participation rates and comparison with paleoseismic data are included (i.e. 'rupture_rate_for_each_fault_cum' folder) as well as additional figures that have not been used in our study. The 'txt_files' folder contains raw data on the MFDs of the different models, slip rate distribution on the different faults for each hypothesis, performance of the models in terms on fit with the catalogue, etc. Read the SHERIFS user manual available in the ‘SHERIFS-master’ folder for more details on the structure of this type of calculation, the content of the files, etc. * The folder structure is set in the correct SHERIFS format so anyone can reproduce or modify the calculation of our study.

This is the unified, declustered, magnitude-complete catalog used to compute activity rates for hazard analysis in Kanti and Kamai.

The used monitored data and some photos

The data includes the point cloud data of 7 sets of the three-dimensional geometry of landslide dams measured in this paper. These are the raw data for figures 3 and 4 in the manuscript. The data in excel format are 42 historical cases of landslide dams, including the occurrence site of landslide dam and detailed geometry parameters.

The research in the manuscript.

some algorithms (which can open access in Matlab environment) that have been used and cited in this paper. And some matlab figures of the case study are persented here.

A database for 11 clay parameters covering 50 sites in Shanghai with 4051 data points is compiled. These sites are distributed in 8 Districts of Shanghai covering approximately 145 km2 in area. This is the first sizeable multivariate soil database compiled at the municipal level. The data points are collected from site investigation reports of Shanghai. Soil properties which are measured in close proximity are selected to constitute a set of data points. This database is useful for studies of the soil properties about Shanghai clay. It also enriches the information of soil properties from a global perspective and will contribute to the development of machine learning algorithm for geotechnical problems.