Parameters of Spearman Correlation Analysis for Sandstone Mechanical Properties

Davood Fereidooni's dataset contains parameters from a Spearman correlation analysis for predicting sandstone mechanical properties. It is based on laboratory tests of 20 sandstone samples from four Iranian formations, measuring physical and mechanical properties. The dataset was last updated on May 15, 2026.

Use Cases

• Predict uniaxial compressive strength (UCS) based on dry unit weight and porosity correlations.
• Predict elasticity modulus (E) using Schmidt hammer rebound values as a key predictor.
• Compare the performance of AI models (ANN, RF, kNN) for geotechnical property prediction.
• Assess the influence of geological formation on sandstone mechanical properties like UCS and E.

Strengths

• Dataset includes specific correlation metrics, such as Pearson R values up to 0.971 for dry unit weight vs. E.
• Laboratory test results cover a defined range for key properties (e.g., UCS from 55.46 to 104.16 MPa).
• Analysis identifies the most influential predictor (Schmidt hammer rebound) with a specific Univariate Regression score (3406.678).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 13.5 KB, indicating limited scope.

Provenance

Source

figshare

Collection Method

Comprehensive laboratory tests performed on 20 sandstone samples.

Freshness

Last updated 2026-05-15 17:33:49; freshness should be verified.

Geography

Samples from four Iranian formations.