Data Analysis and Processing
Our approach encompasses the analysis and processing of geotechnical data using statistical methods, stochastic simulations, and AI/ML models in order to obtain reliable results:
Analysis of laboratory data on the physical–mechanical properties of soils.
Analysis of in-situ test data (SPT, CPT, DMT, PMT).
Reconstruction of results from different types of geotechnical investigations.
Rapid classification of soil layers based on CPT and SPT data; additional in-depth analysis of soil layer parameters.
Analysis of foundation conditions and pile–soil interaction behavior.
Liquefaction potential analysis for pile foundations.
Analysis of the Geotechnical Report.
Analysis during and after pile construction, including review of documents (pile records/passports) on construction protocols.
Geospatial analysis, processing, and presentation of soil and pile testing data: correlations, interpolations, extrapolations, regressions, etc.
Selection, filtering, grouping, textual and visual presentation of data; mathematical modeling through statistical data distributions.
Analysis and processing of client data, our in-house data, web-collected data, artificially generated data, and image-based data.
Stochastic simulations, parameterization, and modeling of pile behavior and variability of geometric–physical–mechanical parameters of piles and soil.
Development of AI solutions and ML models for predicting bearing capacity and behavior based on proprietary, web, and artificially generated databases.
AI models for various types of predictions tailored to specific project requirements.
Data analysis and data science: processing of real data, generation of artificial data using statistical distributions and stochastic methods, predictive modeling, and probabilistic approaches.