Published August 4, 2022 | Version 1.0.0
Dataset Open

Database of Uniaxial Cyclic and Tensile Coupon Tests for Structural Metallic Materials

Description

Database of Uniaxial Cyclic and Tensile Coupon Tests for Structural Metallic Materials

 

Background

This dataset contains data from monotonic and cyclic loading experiments on structural metallic materials. The materials are primarily structural steels and one iron-based shape memory alloy is also included. Summary files are included that provide an overview of the database and data from the individual experiments is also included.

The files included in the database are outlined below and the format of the files is briefly described. Additional information regarding the formatting can be found through the post-processing library (https://github.com/ahartloper/rlmtp/tree/master/protocols).

Usage

  • The data is licensed through the Creative Commons Attribution 4.0 International.
  • If you have used our data and are publishing your work, we ask that you please reference both:
    1. this database through its DOI, and
    2. any publication that is associated with the experiments. See the Overall_Summary and Database_References files for the associated publication references.

Included Files

  • Overall_Summary_2022-08-25_v1-0-0.csv: summarises the specimen information for all experiments in the database.
  • Summarized_Mechanical_Props_Campaign_2022-08-25_v1-0-0.csv: summarises the average initial yield stress and average initial elastic modulus per campaign.
  • Unreduced_Data-#_v1-0-0.zip: contain the original (not downsampled) data
    • Where # is one of: 1, 2, 3, 4, 5, 6. The unreduced data is broken into separate archives because of upload limitations to Zenodo. Together they provide all the experimental data.
    • We recommend you un-zip all the folders and place them in one "Unreduced_Data" directory similar to the "Clean_Data"
    • The experimental data is provided through .csv files for each test that contain the processed data. The experiments are organised by experimental campaign and named by load protocol and specimen. A .pdf file accompanies each test showing the stress-strain graph.
    • There is a "db_tag_clean_data_map.csv" file that is used to map the database summary with the unreduced data.
    • The computed yield stresses and elastic moduli are stored in the "yield_stress" directory.
  • Clean_Data_v1-0-0.zip: contains all the downsampled data
    • The experimental data is provided through .csv files for each test that contain the processed data. The experiments are organised by experimental campaign and named by load protocol and specimen. A .pdf file accompanies each test showing the stress-strain graph.
    • There is a "db_tag_clean_data_map.csv" file that is used to map the database summary with the clean data.
    • The computed yield stresses and elastic moduli are stored in the "yield_stress" directory.
  • Database_References_v1-0-0.bib
    • Contains a bibtex reference for many of the experiments in the database. Corresponds to the "citekey" entry in the summary files. 

 

File Format: Downsampled Data

These are the "LP_<N>_Specimen_<M>_processed_data.csv" files in the "Clean_Data" directory. The <N> is the load protocol designation and the <M> is the specimen number for that load protocol and material source. Each file contains the following columns:

  • The header of the first column is empty: the first column corresponds to the index of the sample point in the original (unreduced) data
  • Time[s]: time in seconds since the start of the test
  • e_true: true strain
  • Sigma_true: true stress in MPa
  • (optional) Temperature[C]: the surface temperature in degC

These data files can be easily loaded using the pandas library in Python through:

import pandas
data = pandas.read_csv(data_file, index_col=0)

The data is formatted so it can be used directly in RESSPyLab (https://github.com/AlbanoCastroSousa/RESSPyLab). Note that the column names "e_true" and "Sigma_true" were kept for backwards compatibility reasons with RESSPyLab.

 

File Format: Unreduced Data

These are the "LP_<N>_Specimen_<M>_processed_data.csv" files in the "Unreduced_Data" directory. The <N> is the load protocol designation and the <M> is the specimen number for that load protocol and material source. Each file contains the following columns:

  • The first column is the index of each data point
  • S/No: sample number recorded by the DAQ
  • System Date: Date and time of sample
  • Time[s]: time in seconds since the start of the test
  • C_1_Force[kN]: load cell force
  • C_1_Déform1[mm]: extensometer displacement
  • C_1_Déplacement[mm]: cross-head displacement
  • Eng_Stress[MPa]: engineering stress
  • Eng_Strain[]: engineering strain
  • e_true: true strain
  • Sigma_true: true stress in MPa
  • (optional) Temperature[C]: specimen surface temperature in degC

The data can be loaded and used similarly to the downsampled data.

 

File Format: Overall_Summary

The overall summary file provides data on all the test specimens in the database. The columns include:

  • hidden_index: internal reference ID
  • grade: material grade
  • spec: specifications for the material
  • source: base material for the test specimen
  • id: internal name for the specimen
  • lp: load protocol
  • size: type of specimen (M8, M12, M20)
  • gage_length__mm_: unreduced section length in mm
  • avg_reduced_dia__mm_: average measured diameter for the reduced section in mm
  • avg_fractured_dia_top__mm_: average measured diameter of the top fracture surface in mm
  • avg_fractured_dia_bot__mm_: average measured diameter of the bottom fracture surface in mm
  • fy_n__mpa_: nominal yield stress
  • fu_n__mpa_: nominal ultimate stress
  • t_a__deg_c_: ambient temperature in degC
  • date: date of test
  • investigator: person(s) who conducted the test
  • location: laboratory where test was conducted
  • machine: setup used to conduct test
  • pid_force_k_p, pid_force_t_i, pid_force_t_d: PID parameters for force control
  • pid_disp_k_p, pid_disp_t_i, pid_disp_t_d: PID parameters for displacement control
  • pid_extenso_k_p, pid_extenso_t_i, pid_extenso_t_d: PID parameters for extensometer control
  • citekey: reference corresponding to the Database_References.bib file
  • yield_stress__mpa_: computed yield stress in MPa
  • elastic_modulus__mpa_: computed elastic modulus in MPa
  • fracture_strain: computed average true strain across the fracture surface
  • c,si,mn,p,s,n,cu,mo,ni,cr,v,nb,ti,al,b,zr,sn,ca,h,fe: chemical compositions in units of %mass
  • file: file name of corresponding clean (downsampled) stress-strain data

 

File Format: Summarized_Mechanical_Props_Campaign

Meant to be loaded in Python as a pandas DataFrame with multi-indexing, e.g.,

tab1 = pd.read_csv('Summarized_Mechanical_Props_Campaign_' + date + version + '.csv',
                   index_col=[0, 1, 2, 3], skipinitialspace=True, header=[0, 1],
                   keep_default_na=False, na_values='')
  • citekey: reference in "Campaign_References.bib".
  • Grade: material grade.
  • Spec.: specifications (e.g., J2+N).
  • Yield Stress [MPa]: initial yield stress in MPa
    • size, count, mean, coefvar: number of experiments in campaign, number of experiments in mean, mean value for campaign, coefficient of variation for campaign
  • Elastic Modulus [MPa]: initial elastic modulus in MPa
    • size, count, mean, coefvar: number of experiments in campaign, number of experiments in mean, mean value for campaign, coefficient of variation for campaign

 

Caveats

  • The files in the following directories were tested before the protocol was established. Therefore, only the true stress-strain is available for each:
    • A500
    • A992_Gr50
    • BCP325
    • BCR295
    • HYP400
    • S460NL
    • S690QL/25mm
    • S355J2_Plates/S355J2_N_25mm and S355J2_N_50mm

Files

Clean_Data_v1-0-0.zip

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Additional details

Funding

Reduced-Basis Nonlinear Models for Simulating Synergistic Geometric Instabilities in Metal Structures under Extreme Loading 200021_188476
Swiss National Science Foundation
Analytical Expressions for Predicting Inelastic Local Buckling in Steel Beam-columns P500PT_206929
Swiss National Science Foundation