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2.7
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Applied Sciences
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Smart Geotechnical Engineering
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Smart Geotechnical Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 3348

Special Issue Editors

Dr. Jiwei Zhang

E-Mail Website
Guest Editor
School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: intelligent shaft construction; tunnel-boring machine (TBM); computational method; intelligent geotechnical monitoring; intelligent reinforcement
Prof. Dr. Hui Cao

E-Mail Website
Guest Editor
School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: deep mining; ground pressure control; rockburst; smart evaluation
Dr. Song Zhang

E-Mail Website
Guest Editor
School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: low-carbon construction; frozen soil engineering; subgrade engineering; intelligent reinforcement

Special Issue Information

Dear Colleagues,

We are pleased to inform you that we have launched a new Special Issue of Applied Sciences (IF 2.7, JCR Q2), entitled “Smart Geotechnical Engineering”. This Special Issue aims to present a diverse range of review articles, research articles and case studies covering promising, recent, and novel research trends in the fields of geotechnical engineering intelligent design, geotechnical numerical methods, intelligent data analysis, geotechnical expert systems and intelligent geotechnical monitoring.

Smart Geotechnical Engineering is a relatively new multidisciplinary and constantly evolving branch of geotechnical engineering analysis and design, employing computational methods, Internet of Things (IoT), Artificial intelligence (AI) and deep learning. Theoretical models, physical models, design procedures, and construction technologies have evolved through the knowledge gained by innovative information technology and computer science technology in geotechnical engineering worldwide. Therefore, this Special Issue intends to present novel scientific advances in intelligent design, testing methods, numerical simulations and case studies, and aims to significantly promote state-of-the-art research in these areas and assist geotechnical engineering practitioners and decision-makers.

Example topics of interest include, but are not limited to, the following:

  • computational methods in geotechnical engineering assessment and design;
  • advanced numerical modelling of geotechnical engineering;
  • intelligent geotechnical monitoring;
  • data mining and analysis of geotechnical engineering;
  • intelligent planning strategies and expert systems for geotechnical engineering;
  • intelligent field surveys;
  • underground construction techniques and applications;
  • retrofit strategies and technical solutions for smart geotechnical engineering;
  • recent developments in standards and codes;
  • Research and Practice on Engineering Disaster Assessment - Monitoring and Early Warning Methods;
  • intelligent mining blasting;
  • Intelligent reinforcement.

Dr. Jiwei Zhang
Prof. Dr. Hui Cao
Dr. Song Zhang
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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

  • geotechnical design
  • computational method
  • numerical model
  • intelligent geotechnical monitoring
  • data mining
  • expert system
  • intelligent field survey
  • theoretical model
  • physical model
  • construction technology
  • engineering disaster assessment
  • intelligent mining blasting
  • intelligent reinforcement

Published Papers (5 papers)

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Research

19 pages, 15332 KiB  
Article
Optimization Study of Water Interval Charge Structure Based on the Evaluation of Rock Damage Effect in Smooth Blasting
by Sijie Wang, Min Gong, Haojun Wu, Xiaodong Wu and Xiangyu Liu
Appl. Sci. 2024, 14(7), 2868; https://doi.org/10.3390/app14072868 - 28 Mar 2024
Viewed by 330
Abstract
In tunnel smooth blasting, optimizing the water interval charging structure of peripheral holes is of great significance in improving the effect of smooth blasting and reducing the unit consumption of explosives. Addressing the issue of a single traditional evaluation standard, this paper proposes [...] Read more.
In tunnel smooth blasting, optimizing the water interval charging structure of peripheral holes is of great significance in improving the effect of smooth blasting and reducing the unit consumption of explosives. Addressing the issue of a single traditional evaluation standard, this paper proposes a composite index evaluation method for rock blasting damage in different zones, and the best charging structure is optimized according to the evaluation results. Taking Liyue Road Tunnel Light Smooth Blasting Project in Chongqing as the Research Background, the numeric models were established with ten kinds of charge structures, the charge structures and explosive quantity were optimized according to the evaluation results, and then the field tests were conducted. The results show that when the length of the water medium at the bottom of the hole is 20 cm, the damage range of the retained rock mass can be controlled while ensuring rock fragmentation. If the length of the water medium at the orifice and in the center of the hole is more than 30 cm, it will affect the superposition effect of the blast stress wave, resulting in under-excavation; in the preferred charge structure, the ratio of the length of the upper and lower explosives reaches 1:3, and the ratio of the length of the water medium is 2:2:1, which achieves a better rock-breaking effect in the field test. Full article
(This article belongs to the Special Issue Smart Geotechnical Engineering)
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20 pages, 4595 KiB  
Article
A Numerical Bio-Geotechnical Model of Pressure-Responsive Microbially Induced Calcium Carbonate Precipitation
by Jianye Wang, Helen Mitrani, Anil Wipat, Polly Moreland, Jamie Haystead, Meng Zhang and Martyn Dade Robertson
Appl. Sci. 2024, 14(7), 2854; https://doi.org/10.3390/app14072854 - 28 Mar 2024
Viewed by 475
Abstract
The employment of Microbially Induced Calcium Carbonate Precipitation (MICP) is of increasing interest as a technique for environmentally sustainable soil stabilisation. Recent advancements in synthetic biology have allowed for the conception of a pressure-responsive MICP process, wherein bacteria are engineered to sense environmental [...] Read more.
The employment of Microbially Induced Calcium Carbonate Precipitation (MICP) is of increasing interest as a technique for environmentally sustainable soil stabilisation. Recent advancements in synthetic biology have allowed for the conception of a pressure-responsive MICP process, wherein bacteria are engineered to sense environmental loads, thereby offering the potential to stabilise specific soil regions selectively. In this study, a 2D smart bio-geotechnical model is proposed based on a pressure-responsive MICP system. Experimentally obtained pressure-responsive genes and hypothetical genes with different pressure responses were applied in the model and two soil profiles were evaluated. The resulting model bridges scales from gene expression within bacteria cells to geotechnical simulations. The results show that both strata and gene expression–pressure relationships have a significant influence on the distribution pattern of calcium carbonate precipitation within the soil matrix. Among the evaluated experimental genes, Gene A demonstrates the best performance in both of the two soil profiles due to the effective stabilisation in the centre area beneath the load, while Genes B and C are more effective in reinforcing peripheral regions. Furthermore, when the hypothetical genes are utilised, there is an increasing stabilisation area with a decreased threshold value. The results show that the technique can be used for soil reinforcement in specific areas. Full article
(This article belongs to the Special Issue Smart Geotechnical Engineering)
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19 pages, 2815 KiB  
Article
Finite Element Analysis of Load-Bearing Characteristics and Design Method for New Composite-Anchor Uplift Piles
by Jiaqi Jiang, Zongyuan Mao, Lihong Chen and Yongkang Wu
Appl. Sci. 2024, 14(5), 2100; https://doi.org/10.3390/app14052100 - 02 Mar 2024
Viewed by 572
Abstract
This paper introduces a new type of uplift pile known as the composite-anchor pile, which employs a composite anchor composed of steel strands, grouting materials, and steel pipes as the main reinforcement. This paper extensively analyzes this pile’s load-bearing capacity and deformation characteristics [...] Read more.
This paper introduces a new type of uplift pile known as the composite-anchor pile, which employs a composite anchor composed of steel strands, grouting materials, and steel pipes as the main reinforcement. This paper extensively analyzes this pile’s load-bearing capacity and deformation characteristics through full-scale field tests and three-dimensional finite element numerical simulations. The results show that the composite-anchor pile has a more even distribution of stress, and its endurance and mechanics performance are better than others. Furthermore, this study utilizes a three-dimensional finite element refined model that has been validated using on-site test results to examine the influence of key parameters, such as the pile diameter, the number of composite-anchor cables, and the diameter of steel strands, on the load-bearing capacity of uplift piles. Building upon these findings, this paper introduces a calculating method to determine the bearing capacity of composite-anchor piles, thereby addressing the existing gap in this field. Full article
(This article belongs to the Special Issue Smart Geotechnical Engineering)
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31 pages, 13498 KiB  
Article
A Novel Approach to Swell Mitigation: Machine-Learning-Powered Optimal Unit Weight and Stress Prediction in Expansive Soils
by Ammar Alnmr, Richard Ray and Mounzer Omran Alzawi
Appl. Sci. 2024, 14(4), 1411; https://doi.org/10.3390/app14041411 - 08 Feb 2024
Cited by 1 | Viewed by 702
Abstract
Expansive soils pose significant challenges to structural integrity, primarily due to volumetric changes that can lead to detrimental consequences and substantial economic losses. This study delves into the intricate dynamics of expansive soils through loaded swelling pressure experiments conducted under diverse conditions, encompassing [...] Read more.
Expansive soils pose significant challenges to structural integrity, primarily due to volumetric changes that can lead to detrimental consequences and substantial economic losses. This study delves into the intricate dynamics of expansive soils through loaded swelling pressure experiments conducted under diverse conditions, encompassing variations in the sand content, initial dry unit weight, and initial degree of saturation. The findings underscore the pronounced influence of these factors on soil swelling. To address these challenges, a novel method leveraging machine learning prediction models is introduced, offering an efficient and cost-effective framework to mitigate potential hazards associated with expansive soils. Employing advanced algorithms such as decision tree regression (DTR), random forest regression (RFR), gradient boosting regression (GBR), extreme gradient boosting (XGBoost), support vector regression (SVR), and artificial neural networks (ANN) in the Python software 3.11 environment, this study aims to predict the optimal applied stress and dry unit weight required for soil swelling mitigation. Results reveal that XGBoost and ANN stand out for their precision and superior metrics. While both performed well, ANN demonstrated exceptional consistency across training and testing phases, making it the preferred choice. In the tested dataset, ANN achieved the highest R-squared values (0.9917 and 0.9954), lowest RMSE (7.92 and 0.086), and lowest MAE (5.872 and 0.0488) for predicting optimal applied stress and dry unit weight, respectively. Full article
(This article belongs to the Special Issue Smart Geotechnical Engineering)
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18 pages, 6997 KiB  
Article
Quantitative Characterization and Disturbance Law of Key Parameters Influencing Deformation of Overlying Strata during Strip Filling in a Goaf
by Zenghui Zhao, Zhe Meng, Longfei Li, Hao Liu, Jiaze Du and Tianyu Li
Appl. Sci. 2024, 14(3), 996; https://doi.org/10.3390/app14030996 - 24 Jan 2024
Viewed by 428
Abstract
Strip filling mining in a goaf is of great significance for solving the ‘three under’ coal-pressure and mining-area ecological environment problems in Central and Eastern China, but the disturbance characteristics of filling parameters on overlying rock are not clear at present. Taking the [...] Read more.
Strip filling mining in a goaf is of great significance for solving the ‘three under’ coal-pressure and mining-area ecological environment problems in Central and Eastern China, but the disturbance characteristics of filling parameters on overlying rock are not clear at present. Taking the geological conditions of the CT30101 working face in Mahuangliang coal mine and the short-wall interval strip filling as a background, the strength parameters (cohesion and friction angle), deformation parameters (elastic modulus and Poisson’s ratio), and structural parameters (strip width and spacing) of the filling body were selected as experimental factors, and the maximum settlement of the direct roof and the ground surface was taken as the evaluation index. The influence degree of each factor was quantitatively characterized via a variance analysis and an F test, and the main control factors of the strip filling overburden settlement were proposed. The roof and surface displacement, the stress evolution law of the filling body, and the shape change of the surrounding rock plastic zone under different levels of main control factors in the entire process of mining filling coupling were analyzed in detail. The results showed that the cohesion of the backfill had a highly significant impact on the direct roof settlement, the strip spacing and the friction angle of backfill had a significant impact on it, the cohesion of the backfill and the strip spacing had a certain impact on the surface settlement, and the two had a cross-coupling effect. In the process of mining and filling, the stress evolution of the filling body was extremely complex, and it finally presented a saddle shape that was high on both sides and low in the middle; the majority of the strata and the filling body primarily exhibited shear damage, with a small amount of tensile failure zones appearing only in the direct roof and mid-section of the filling body. The above conclusions have a certain guiding significance for the optimal design of strip filling in a goaf. Full article
(This article belongs to the Special Issue Smart Geotechnical Engineering)
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