Supplementary Dataset for: Bearing Capacity and Safety Factors of Ring Foundations in Spatially Variable Soils: A Hybrid FELA-Machine Learning Approach

moein mohammadizadeh, mohsen mohammadizadeh

This dataset contains the supplementary numerical data generated and analysed in the study entitled: "Bearing Capacity and Safety Factors of Ring Foundations in Spatially Variable Soils: A Hybrid FELA-Machine Learning Approach." The dataset supports the investigation of ring foundation performance under spatially variable soil conditions using a hybrid Finite Element Limit Analysis (FELA)-Machine Learning framework. The repository includes: 1. FELA_results_Nc_Ng.csv:Bearing capacity factor datasets including Nc and Nγ values, normalized factors, ring geometry parameters, interface conditions, loading configurations, and soil variability parameters. 2. FELA_results_Fs.csv:Safety factor (Fs) datasets considering different loading configurations, interface conditions, soil parameters, and spatial variability characteristics. 3. random_field_realizations_sample.csv:Representative spatial random field realizations of effective cohesion (c') generated using a lognormal spatial random field approach with anisotropic correlation characteristics. 4. failure_envelopes.json:Processed failure envelope data in normalized V-H-M load space for different ring geometries, interface conditions, and loading configurations. These datasets are provided to facilitate transparency, reproducibility, and further research on numerical modelling and machine learning applications for ring foundations in spatially variable soils.