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Geosciences
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Digging Deeper: Insights and Innovations in Rock Mechanics
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Digging Deeper: Insights and Innovations in Rock Mechanics

A special issue of Geosciences (ISSN 2076-3263).

Deadline for manuscript submissions: 31 August 2025 | Viewed by 1334

Special Issue Editors

Prof. Gessica Umili

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Guest Editor
Department of Earth Sciences, Università degli Studi di Torino, via Valperga Caluso 35, 10125 Torino, Italy
Interests: rock mechanics; slope stability; numerical modelling
Special Issues, Collections and Topics in MDPI journals
Dr. Chiara Caselle

E-Mail Website
Guest Editor
Earth Sciences Department, University of Torino, Via Valperga Caluso 35, 10125 Torino, Italy
Interests: applied geology; microstructures; rock mechanics; evaporitic rocks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The characterization and monitoring of rock masses are based on information gathered at different levels. In order to establish a reliable model of a rock mass, geological, geostructural, and geomechanical information are necessary. The development of advanced survey techniques, such as digital photogrammetry, laser scanning, SAR interferometry, and optical and thermal sensing, has supplied powerful instruments in rock mechanics, particularly for the study of rock discontinuities and their role in stability. In parallel, laboratory testing equipment and procedures have greatly improved, allowing for more reliable and extensive investigations of the rock matrix. Moreover, the evolution of numerical modeling methods enables the full exploitation of the acquired data in order to understand and simulate rock mass behavior. 

This Special Issue aims to collect a broad range of innovative applications of such technologies. 

We would like to invite you to submit articles on your recent work, experimental research or case studies, with respect to the above topics. 

We also encourage you to send us a short abstract outlining the purpose of the research and the principal results obtained in order to verify at an early stage if the contribution you intend to submit fits with the objectives of the Special Issue.

Prof. Gessica Umili
Dr. Chiara Caselle
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Geosciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • rock mechanics
  • rock mass
  • laboratory testing
  • geomechanical survey
  • digital twin
  • numerical modeling
  • tunnel
  • statistical analysis

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Published Papers (2 papers)

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Research

15 pages, 4901 KiB  
Article
Effects of Rock Texture on Digital Image Correlation
by Azemeraw Wubalem, Chiara Caselle, Battista Taboni and Gessica Umili
Geosciences 2025, 15(4), 145; https://doi.org/10.3390/geosciences15040145 - 10 Apr 2025
Viewed by 235
Abstract
Digital image correlation (DIC) is a non-contact optical method that can provide high-resolution strain and displacement measurements, but its effectiveness depends on surface texture contrast. This study investigates the effects of surface characteristics on the quality of DIC results in tonalite and marble [...] Read more.
Digital image correlation (DIC) is a non-contact optical method that can provide high-resolution strain and displacement measurements, but its effectiveness depends on surface texture contrast. This study investigates the effects of surface characteristics on the quality of DIC results in tonalite and marble samples under Brazilian tests. Tonalite samples have a coarse texture with a heterogeneous mineral composition; therefore, DIC analysis was conducted without artificial speckle patterns. Marble, instead, poses a challenge due to its uniform fine texture and composition. Thus, using point and line grids to enhance surface contrast, artificial speckle patterns were applied to marble samples. A total of 39 disk samples (12 tonalite and 27 marble) were tested with video frames recorded during loading and analyzed using Ncorr software. The results confirmed that tonalite’s natural texture allows accurate strain mapping without artificial speckle patterns. In contrast, marbles without speckles are not effective in strain evolution mapping due to a lack of surface contrast. Marble with both point- and line-speckled patterns effectively mapped the strain evolution except for some distortion and directionality along speckles in displacement fields. This result suggests that the preparation of speckled surfaces need special attention for effective deformation evolution mapping in homogeneous materials. Full article
(This article belongs to the Special Issue Digging Deeper: Insights and Innovations in Rock Mechanics)
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16 pages, 3109 KiB  
Article
A Machine Learning Classification Approach to Geotechnical Characterization Using Measure-While-Drilling Data
by Daniel Goldstein, Chris Aldrich, Quanxi Shao and Louisa O'Connor
Geosciences 2025, 15(3), 93; https://doi.org/10.3390/geosciences15030093 - 7 Mar 2025
Cited by 1 | Viewed by 611
Abstract
Bench-scale geotechnical characterization often suffers from high uncertainty, reducing confidence in geotechnical analysis on account of expensive resource development drilling and mapping. The Measure-While-Drilling (MWD) system uses sensors to collect the drilling data from open-pit blast hole drill rigs. Historically, the focus of [...] Read more.
Bench-scale geotechnical characterization often suffers from high uncertainty, reducing confidence in geotechnical analysis on account of expensive resource development drilling and mapping. The Measure-While-Drilling (MWD) system uses sensors to collect the drilling data from open-pit blast hole drill rigs. Historically, the focus of MWD studies was on penetration rates to identify rock formations during drilling. This study explores the effectiveness of Artificial Intelligence (AI) classification models using MWD data to predict geotechnical categories, including stratigraphic unit, rock/soil strength, rock type, Geological Strength Index, and weathering properties. Feature importance algorithms, Minimum Redundancy Maximum Relevance and ReliefF, identified all MWD responses as influential, leading to their inclusion in Machine Learning (ML) models. ML algorithms tested included Decision Trees, Support Vector Machines (SVMs), Naive Bayes, Random Forests (RFs), K-Nearest Neighbors (KNNs), Linear Discriminant Analysis. KNN, SVMs, and RFs achieved up to 97% accuracy, outperforming other models. Prediction performance varied with class distribution, with balanced datasets showing wider accuracy ranges and skewed datasets achieving higher accuracies. The findings demonstrate a robust framework for applying AI to real-time orebody characterization, offering valuable insights for geotechnical engineers and geologists in improving orebody prediction and analysis Full article
(This article belongs to the Special Issue Digging Deeper: Insights and Innovations in Rock Mechanics)
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