DOI: 10.5281/zenodo.15659181
title: The effect of slab touchdown on anticrack arrest in propagation saw tests dataset and data processing

description: Touchdown Analysis: Snow Avalanche Research Framework
This repository contains a comprehensive analysis framework for touchdown research in snow avalanche mechanics, focused on crack propagation, energy release rates, and slab-weak layer interactions.

Overview
This research framework implements multiple analytical approaches to understand touchdown behavior in avalanche mechanics:





Parametric Studies: Systematic analysis of how material properties (density, thickness, modulus) affect touchdown distances

Model Validation: Comparison between DEM simulations, WEAC analytical models, and experimental data

Crack Propagation Analysis: Energy release rate calculations and propagation length predictions

Parameter Sensitivity: Effects of geometric and material parameters on structural response

Fracture Mechanics: Critical energy release rate ratios for crack arrest prediction

Long PST Analysis: Extended propagation saw test experimental validation

Profile Deformation: Standard slab profile analysis under different loading conditions



Repository Structure



touchdown_analysis/
├── src/
│ ├── main.ipynb # Main analysis notebook with all figures
│ ├── analysis.py # Core analysis functions and physics models
│ └── plotting.py # Visualization functions for all analyses
├── raw_data/
│ ├── figure4/ # Standard slab profile deformation data
│ ├── figure5/ # DEM model validation data
│ ├── figure6/ # Crack propagation comparison data
│ ├── figure7/ # Parameter variation study data
│ └── figure9/ # Long PST experimental data
├── output/
│ ├── figure4/ # Slab profile analysis results
│ ├── figure5/ # Validation analysis outputs (displacements/stresses)
│ ├── figure6/ # Crack propagation results (touchdown/energy)
│ ├── figure7/ # Parameter sensitivity analysis results
│ ├── figure8/ # Touchdown parametric study results (cached)
│ └── figure9/ # Long PST analysis outputs
├── requirements.txt # Python dependencies
└── README.md # This file


Key Analyses

Figure 4: Standard Slab Profile Deformation



Analysis of different snow slab profiles (homogeneous, hard-soft-hard, soft-hard-soft) under loading conditions, comparing ABAQUS finite element and WEAC analytical models.


Figure 5: DEM Model Validation



Validation of discrete element method (DEM) simulations against continuum mechanics for displacement and stress fields at different slope angles (-35°, 0°, 35°).


Figure 6: Crack Propagation Comparison



Comparative analysis of crack propagation using different numerical methods (WEAC, ANSYS) showing touchdown length evolution and energy release rates over time.

Figure 7: Parameter Sensitivity Analysis

Systematic study of how material and geometric parameters (height, density, Gerling number, inclination, weak layer properties) affect touchdown behavior.

Figure 8: Touchdown Parametric Study

Comprehensive parametric analysis of touchdown distances as functions of slab thickness, density, and weak layer thickness using different snow profiles and the Heierli analytical model.

Figure 9: Long PST Experimental Analysis

Analysis of extended propagation saw test (PST) experiments comparing WEAC simulations, fitted models, and experimental measurements for crack arrest and full propagation cases.


Table 3: Fracture Toughness Ratios

Critical energy release rate ratios (G_c/G_sw) from PST experiments for predicting crack arrest behavior.

Usage

Quick Start:



# Install dependencies
pip install -r requirements.txt

# Run complete analysis
jupyter notebook src/main.ipynb

Data Organization


Input Data (raw_data/)



Figure 4: ABAQUS and WEAC simulation results for standard profiles

Figure 5: DEM simulation data for validation studies

Figure 6: Time-series crack propagation data from multiple methods

Figure 7: Parameter variation study datasets

Figure 9: Long PST experimental measurements


Output Data (output/)



Processed analysis results organized by figure

Cached computations for efficient re-analysis

Subdirectories for different aspects of each analysis


Dependencies





Python: 3.8 or higher

NumPy: Numerical computing and array operations

SciPy: Scientific computing for signal processing

Matplotlib: Plotting and visualization

Pandas: Data manipulation and analysis

Jupyter: Interactive notebook environment


See `requirements.txt` for complete dependency specifications.