Geotechnical Resilience through Intelligent Design

Project Information

GRID

Grant agreement ID: 101182689

DOI

10.3030/101182689

EC signature date 4 October 2024

Start date 1 November 2024

End date 31 October 2028

Funded under

• Marie Skłodowska-Curie Actions (MSCA)

Total cost

No data

EU contribution

€ 1 242 000,00

Coordinated by

UNIVERSITAET FUER BODENKULTUR WIEN
Austria

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Data sets, microdata, etc (1)

Repository of bechmark monitoring and testing data sets

Digital repository of standardised benchmark geotechnical monitoring and testing data sets for ML model development and calibration with description of the development and application of innovative geotechnical monitoring technologies for big data acquisition

Documents, reports (1)

Guideline for integration of ML in geotechnical engineering

Guideline for the application and integration of ML in geotechnical engineering projects

Data Management Plan (1)

Data Management Plan

Publications

Conference proceedings (4)

Machine learning predictions on an extensive geotechnical dataset of laboratory tests in Austria

Author(s): Enrico Soranzo
Publisher: Research Publishing, Singapore
DOI: 10.3850/GRF-25280825_ISGSR-166-P377-CD

MACHINE LEARNING PREDICTION OF SOIL PARTICLE SIZE DISTRIBUTION FROM SMARTPHONE IMAGES

Author(s): Enrico Soranzo
Publisher: FOMLIG2025

AI-assisted student grading system in geotechnics

Author(s): Soranzo, E.
Publisher: ÖGG, Austrian Society for Geomechanics
DOI: 10.53243/ICSMGE2026-809

An Adaptive Physics-informed Deep Operator Neural Network for 1-D Unsaturated Infiltration Model Coupled with Soil Deformation

Author(s): Biao Yuan, Xiaohui Chen
Publisher: Research Publishing, Singapore
DOI: 10.3850/GRF-25280825_ISGSR-081-P054-CD

Other (1)

Predicting Soil Grain Size Distributions from Images

Author(s): Lukas Leibold, Enrico Soranzo
Published in: Kaggle
Publisher: Kaggle

Peer reviewed articles (7)

Revisiting strain localization from the view of structured inhomogeneity

Author(s): Zhihui Wang, Roberto Cudmani
Published in: Computers and Geotechnics, Issue 190, 2025, ISSN 0266-352X
Publisher: Elsevier BV
DOI: 10.1016/J.COMPGEO.2025.107694

Predictive modeling of pore pressure build-up in vibratory pile driving through machine learning

Author(s): Sepideh Fadaei, Amir Hamidi, Enrico Soranzo
Published in: Geoscience Frontiers, 2025, ISSN 1674-9871
Publisher: Elsevier BV
DOI: 10.1016/J.GSF.2025.102209

Large language models for automated grading in geotechnics

Author(s): Enrico Soranzo
Published in: Machine Learning and Data Science in Geotechnics, 2025, ISSN 3029-0414
Publisher: Emerald
DOI: 10.1108/MLAG-01-2025-0001

Comprehensive Dataset of Dynamic Probing Heavy Test Results for Subsurface Characterization

Author(s): E. Soranzo
Published in: Data in Brief, 2025, ISSN 2352-3409
Publisher: Elsevier BV
DOI: 10.1016/j.dib.2025.111391

Convolutional neural network prediction of the particle size distribution of soil from close-range images

Author(s): Enrico Soranzo, Carlotta Guardiani, Wei Wu
Published in: Soils and Foundations, Issue 65, 2025, ISSN 0038-0806
Publisher: Elsevier BV
DOI: 10.1016/j.sandf.2025.101575

Soil improvement with laponite: effects on soil-structure interaction in liquefiable sands

Author(s): Jinghua Zhang, Zhihua Yang, Emilio Bilotta, Lucia Mele, Qing Sun, Haitao Yu, Yong Yuan
Published in: Computers and Geotechnics, Issue 185, 2025, ISSN 0266-352X
Publisher: Elsevier BV
DOI: 10.1016/J.COMPGEO.2025.107360

Dataset of close-range soil images of soils and corresponding particle size distributions

Author(s): E. Soranzo
Published in: Data in Brief, 2025, ISSN 2352-3409
Publisher: Elsevier BV
DOI: 10.1016/J.DIB.2025.111631