Data on One-dimensional Vertical Free Swelling Potential of Soils and Related Soil Properties

TL;DR

This paper presents a comprehensive dataset of one-dimensional soil swelling potential and related properties, aiding geotechnical analysis and predictive modeling for soil expansion issues in civil engineering.

Contribution

It provides a large, standardized dataset of soil swelling and properties, compiled from laboratory tests and standards, for use in statistical and machine learning studies.

Findings

395 data points on soil swelling potential

Extensive soil property data including moisture, density, and classification

Dataset supports advanced analysis and prediction of soil expansion

Abstract

Most of the damaging geo-hazards recorded in modern history are caused by soil swelling or expansion. Therefore, proper evaluation of a soils capacity to swell is very crucial for the achievement of a secure and safe foundation for civil infrastructure. Hence, in this brief, a dataset of standardised one-dimensional soil swelling on laboratory engineered and natural soils is reported. Corresponding properties of these soils such as moisture content, void ratio, specific gravity, unit weight, Atterberg limits, size fractions, soil activity index including the state of compaction of the soils where applicable, are also presented. The dataset is made up of a total of 395 data on soil swelling potential are reported. With regards to the corresponding soil properties, a total of 219 data records of soil specific gravity, 321 data of initial moisture content, 163 data of void ratio, 273 data of dry unit weight, 347 data of liquid limit, 347 data of plastic limit, 395 data of plasticity index, 209 data of activity index, 339 data of clay content, 174 data of silt content, 246 data of optimum moisture content, 228 data of maximum dry density and 347 data of Unified Soil Classification System (USCS). The procedures followed for the determination of soil swelling and related soil properties are mostly contained in American Standards for Testing of Materials (ASTM D 4546, ASTM D 698, ASTM D 1557 and ASTM D698), American Association of State Highways Transport Officials (AASHTO T 258 and AASHTO-T99) and Turkish Standards (TS1900). Finally, the dataset described herein are intended to aid geotechnical engineers and researchers who are involved in statistical correlation studies, data analytics, machine learning predictions using soft computing methods mostly aimed at evaluating soil expansion especially during the preliminary phases of soil investigation and foundation design.