Research Data on Fatigue Tests of As-Welded, Deep-Rolled, and HFMI-Treated Joints

This repository contains experimental, geometrical, and numerical data from fatigue investigations on butt-welded steel specimens with different post-weld treatment conditions, including:

* As-welded
* Deep-rolled
* HFMI-treated

The data are stored in open, text-based formats (UTF-8 encoded, tab-delimited or CSV) to ensure long-term accessibility and compatibility with MATLAB, Python, and other tools. Each file includes human-readable headers and can be directly imported.

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# Repository Structure

<pre>
scan_geometry/
3D point cloud data of weld geometries (front/back)

raw/
Original scan data without modifications

processed/
Transformed and post-processed scan data:
coordinate systems aligned
weld profiles smoothed

metadata.txt / .csv
General specimen information:
SpecimenName, Material, Condition, Geometry, Thickness_mm

fatigue_test_data.txt / .csv
Fatigue test results:
StressRatio, NominalStressRange_MPa, LoadCyclesToFailure,
LoadCyclesToCrack, RunOut, Outlier, FailedNotch, Date

imperfections.txt / .csv
Measured welding imperfections:
AngularMisalignment_mm, AxialMisalignment_mm

scan_files.txt / .csv
Mapping between specimen names and scan files:
Raw and processed scans (front/back)

fe_results.txt / .csv
Finite element results per specimen and notch (1–4):
ClampingStressNominal_MPa
ClampingStressNotch_MPa
NotchFactor_TCD

weldtoe_geometry.txt / .csv
Weld toe geometry per specimen and notch (1–4):
Radius_IM_mm, Radius_LSM_mm, Radius_CM_mm,
Angle_MAX_deg

The values represent averaged weld toe geometry parameters.
Radii and angles are computed as mean values along the weld toe line
for each notch and measurement side, excluding invalid values (NaN).

import_examples/
Example scripts for reading and processing the data
in MATLAB and Python
</pre>

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# Data Format

* TXT files are tab-separated (\t)
* CSV files are comma-separated
* UTF-8 encoding is used throughout
* Missing values are represented by NA

Each file contains descriptive column headers and can be imported directly into standard data analysis tools.

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# Dataset Characteristics

* SpecimenName uniquely identifies each specimen.
* Most tables contain one row per specimen.
* FE and weld toe geometry datasets contain multiple rows per specimen (one row per notch).
* Processed scan geometries are spatially aligned and smoothed for further analysis.
* Weld toe geometry parameters are averaged along the weld toe line after exclusion of invalid (NaN) values.

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# Example Import

## MATLAB

T = readtable('fatigue_test_data.txt', 'Delimiter', '\t');

## Python

import pandas as pd
df = pd.read_csv('fatigue_test_data.txt', sep='\t')

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# Intended Applications

The dataset can be used for:

* Fatigue assessment of welded joints
* Investigation of post-weld treatment effects
* Statistical evaluation of weld imperfections
* Validation of finite element models
* Geometry-based fatigue analysis
* Data-driven and machine learning approaches in fatigue research

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# Related Publication

Associated dissertation:

Dänekas, C. (2026).
*Influence of deep rolling on the fatigue resistance of butt-welded joints.*
Leibniz University Hannover.

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# Contact

Christian Dänekas
Institute of Steel Construction
Leibniz University Hannover

LinkedIn:
[Christian Dänekas on LinkedIn](https://www.linkedin.com/in/christian-daenekas?utm_source=chatgpt.com)

Institute Email:
[[e-mail]](mailto:[e-mail])

Institute Website:
[Institute of Steel Construction – Leibniz University Hannover](https://www.stahlbau.uni-hannover.de/en/institute?utm_source=chatgpt.com)