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Big Data in Geoscience: Advances and Applications
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Big Data in Geoscience: Advances and Applications

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

Deadline for manuscript submissions: closed (20 January 2022) | Viewed by 5131

Special Issue Editors

Dr. Runhong Zhang

E-Mail Website
Guest Editor
School of Civil Engineering, Chongqing University, Chongqing, China
Interests: numerical modeling, braced excavation; reliability analysis; soil-structure interaction; applications of machine learning in geotechnical engineering
Dr. Lin Wang

E-Mail Website
Guest Editor
School of Civil Engineering, Chongqing University, Chongqing, China
Interests: geotechnical reliability analysis and risk assessment; Bayesian updating of geotechnical soil parameters; machine learning and its applications in geotechnical engineering
Prof. Dr. Wengang Zhang

E-Mail Website
Guest Editor
School of Civil Engineering, Chongqing University, Chongqing 400045, China
Interests: deep braced excavation; geotechnical reliability analysis; slope engineering; big data and machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This SI strives to review the latest development of big data and machine learning, as well as their key applications in geoscientific and/or geoengineering problems. The unique knowledge, ideas and insights presented can serve as a valid reference that provides all the details required for a successful application of big data and machine learning tactics. It is also suitable for advanced students who wish to use relevant papers of this SI as a basis to pursue further research in these areas. Moreover, educating the next generation of geoscientists and engineers is itself becoming a pressing issue.  Topics related to the scope of this Special Issue include, but are not limited to, the application of:

  • Statistical Analysis
  • Artificial Intelligence
  • Machine Learning
  • Pattern Recognition

in geoscientific issues and/or geoengineering problems.

Dr. Runhong Zhang
Dr. Lin Wang
Prof. Dr. Wengang Zhang
Guest Editors

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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

  • big data
  • machine learning
  • geoscience
  • geoengineering
  • statistical analysis
  • artificial intelligence

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Published Papers (2 papers)

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Research

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18 pages, 8090 KiB  
Article
CT Scanning of Structural Characteristics of Glacial Till in Moxi River Basin, Sichuan Province
by Yanfeng Zhang, Yongbo Tie, Luqi Wang and Jianfeng Liu
Appl. Sci. 2022, 12(6), 3040; https://doi.org/10.3390/app12063040 - 16 Mar 2022
Cited by 5 | Viewed by 2372
Abstract
Glacial till is a special soil in alpine mountainous areas, which often induces geohazards such as debris flows and landslides due to the influence of special geological environmental conditions in alpine mountainous areas. The change in the structure of glacial till is the [...] Read more.
Glacial till is a special soil in alpine mountainous areas, which often induces geohazards such as debris flows and landslides due to the influence of special geological environmental conditions in alpine mountainous areas. The change in the structure of glacial till is the main cause of geohazards. Glacial till structure is one of the important factors affecting the mechanical properties of soil. It can explain the mechanical phenomena of soil engineering and establish the quantitative relationship between soil structure and macro–mechanical properties. However, there are few systematic research results on its structure. For this reason, the intact glacial till in the Moxi River Basin, South of Kangding City, Tibetan Autonomous Prefecture of Garzê, Sichuan Province was taken as the research object, and the meso-structure and micro-structure of intact glacial till were studied using CT scanning and scanning electron microscopy (SEM). The meso-structure and micro-structure images of the interior of intact glacial till were obtained and the porosity, particle shape, directivity and structural unit were analyzed. The results show that: (1) the average porosity of longitudinal and transverse sections of intact glacial till are 24.92% and 24.35%, respectively, and the difference is not significant; (2) the average circularity of the particles in the longitudinal and transverse sections is 0.836 and 0.802, respectively, and the average aspect ratio is 2.5 and 3.7, respectively. The shape of the particles in the longitudinal section is more circular than in the transverse section, and the orientation of the particles in the transverse sectional direction is more obvious; (3) the main mineral components of the glacial till sample are mica, feldspar and quartz. In the process of transportation and deposition, the mineral particles undergo different degrees of grinding, crushing and dissolution. The particles are mainly formed by calcareous cementation, and the cementation is dense. The structure is mainly a skeleton structure composed of fine particles that are wrapped or filled. These findings provide the scientific basis for highway-, railway- and hydro-power-station construction and disaster prevention and mitigation in the alpine mountainous area. Full article
(This article belongs to the Special Issue Big Data in Geoscience: Advances and Applications)
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Other

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15 pages, 5891 KiB  
Technical Note
Formation and Failure Mechanism of the Xinfangzi Landslide in Chongqing City (China)
by Kaiqiang Zhang, Luqi Wang, Wengang Zhang, Zhihua Zhang and Hao Zhou
Appl. Sci. 2021, 11(19), 8963; https://doi.org/10.3390/app11198963 - 26 Sep 2021
Cited by 8 | Viewed by 1810
Abstract
At 2:00 a.m. on 1 July 2020, after several days of continuous heavy rainfall, the Xinfangzi landslide occurred in Zhengping Village, Ganshui Town, Qijiang District, Chongqing City, China. The area of the landslide was about 3.85 × 104 m2 and the [...] Read more.
At 2:00 a.m. on 1 July 2020, after several days of continuous heavy rainfall, the Xinfangzi landslide occurred in Zhengping Village, Ganshui Town, Qijiang District, Chongqing City, China. The area of the landslide was about 3.85 × 104 m2 and the volume was about 71.22 × 104 m3. The Xinfangzi landslide can be defined as a push-type landslide. Specifically, the main sliding area pushed the front squeezing area, causing it to slide laterally. The entire slip path of the landslide was a broken line, while the right edge and the front shear outlet position slipped loosely in a circular arc. In this study, finite element numerical calculations were used to compare and analyze the multisection plastic deformation of the landslide under natural and rainfall conditions based on field investigations. The formation and failure characteristics of the Xinfangzi landslide were further revealed. The results show that the cross and longitudinal sections of the landslide were in a critical state of instability under natural and rainfall conditions. A compound section was established along the slip path based on the cross and longitudinal sections. Due to the extrusion of the trailing edge of the landslide, the compound section’s leading edge was in a state of instability under natural conditions. Under rainfall conditions, the increase in the unit weight of the sliding mass was superimposed on the compound section, which amplified the thrust of the trailing edge and further accelerated the overall sliding process of the landslide. Based on the macroscopic deformation of the landslide, it was found that the sliding of the trailing edge of the landslide is the key factor promoting the failure of the front edge, and local slump is possible under rainfall conditions. Full article
(This article belongs to the Special Issue Big Data in Geoscience: Advances and Applications)
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