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Failure and Multiphysical Fields in Geo-Energy
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Failure and Multiphysical Fields in Geo-Energy

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 5041

Special Issue Editor

Dr. Yongliang Wang

E-Mail Website
Guest Editor
School of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing 100083, China
Interests: mining engineering; petroleum engineering; civil engineering; computational mechanics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Failures (e.g., instability, damage, and fracture) and multiphysical fields coupling (thermal, hydro, mechanical, and chemical fields) problems exist in the in situ occurrence and exploitation process of geo-energy, and they have become the key factors affecting the disasters in the exploitation process. Without understanding of the involved mechanisms, it is challenging to exploit energy safely and efficiently. The goal of this Special Issue is to review the novel theories and methods concerning failure and multiphysical fields in geo-energy problems including new applications in related fields. The aim is to define the state-of-the-art of the subject and the recently proposed methods, as well as future directions of research in this area. Another goal—which we hope will be beneficial for the community of failure and multiphysical fields—is to connect participants so that international collaborations can take place for advanced research and study of relevant applications.

Dr. Yongliang Wang
Guest Editor

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. Energies 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 2600 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

  •  pipeline failure
  •  wellbore stability
  •  damage and fracture
  •  hydraulic fracturing
  •  multiphysical fields coupling
  •  rock engineering
  •  geo-energy and geo-resources
  •  computational mechanics
  •  numerical models
  •  experimental tests

 

Published Papers (3 papers)

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Research

12 pages, 2411 KiB  
Article
Real-Time Experimental Monitoring for Water Absorption Evolution Behaviors of Sandstone in Mogao Grottoes, China
by Nai Hao, Yongliang Wang, Xiaochong Wu, Yifeng Duan, Panshun Li and Manchao He
Energies 2022, 15(22), 8504; https://doi.org/10.3390/en15228504 - 14 Nov 2022
Cited by 3 | Viewed by 1176
Abstract
Rock mass has typical pore structure, and the induced coupling effects of fluid and solid matrix appear in the disaster evolution process of deep energy exploitation and overground rock hydration. As a representative case, influenced by the water absorption environment, the surrounding rock [...] Read more.
Rock mass has typical pore structure, and the induced coupling effects of fluid and solid matrix appear in the disaster evolution process of deep energy exploitation and overground rock hydration. As a representative case, influenced by the water absorption environment, the surrounding rock and murals of Mogao Grottoes produce hydration diseases, which may be related to unclear interaction mechanisms between the surrounding rock and water. In this study, the self-developed physical experimental system for real-time experimental monitoring was applied to test the water absorption evolution behaviors of sandstone. The experimental results showed that the water evaporation of the rock sample during the process of water absorption could be measured through this well-designed physical experimental system, and the actual water absorption of the rock sample is the difference between the decrease of water in the water storage bucket, measured by the balance and the water evaporation in the process of experiment; by drawing the actual water absorption curve of the rock sample, the time when the water absorption of the rock sample reaches saturation could be determined accurately; and the curve of water absorption with time could be expressed as an exponential function. The experimental techniques and methods in this study provide a feasible research idea for studying the water absorption evolution behaviors and mechanisms of the surrounding rock weathering when it meets water, and have significance for revealing the disease mechanisms of the surrounding sandstone in Mogao Grottoes, China. Full article
(This article belongs to the Special Issue Failure and Multiphysical Fields in Geo-Energy)
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15 pages, 7349 KiB  
Article
Deflection of Hydraulic Fractures and Shear Stress Disturbance Considering Thermal Effects: A Numerical Case Study
by Nana Liu and Yongliang Wang
Energies 2022, 15(13), 4888; https://doi.org/10.3390/en15134888 - 04 Jul 2022
Cited by 1 | Viewed by 1280
Abstract
Quantitative characterization of propagation behaviors and morphology of hydraulic fractures is crucial for controlling and optimizing hydrofracturing effects. To study the disturbance deflection behaviors of multiple hydraulic fractures, a three-dimensional field-scale numerical model for multistage fracturing is established to study the shear stress [...] Read more.
Quantitative characterization of propagation behaviors and morphology of hydraulic fractures is crucial for controlling and optimizing hydrofracturing effects. To study the disturbance deflection behaviors of multiple hydraulic fractures, a three-dimensional field-scale numerical model for multistage fracturing is established to study the shear stress disturbance and unstable propagation behavior of hydraulic fractures under different perforation cluster spacing. In the model, the thermal diffusion, fluid flow and deformation in reservoirs are considered to describe the thermal-hydro-mechanical coupling. In the numerical case study, the derived results show that the thermal effect between fracturing fluid and rock matrix is an important factor affecting fracture propagation, and thermal effects may increase the extent of fracture propagation. The size of stress shadow areas and the deflection of hydraulic fractures will increase with a decrease in multiple perforation cluster spacing in horizontal wells. The shear stress disturbance caused by fracture propagation is superimposed in multiple fractures, resulting in the stress shadow effect and deflection of fractures. Full article
(This article belongs to the Special Issue Failure and Multiphysical Fields in Geo-Energy)
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15 pages, 3524 KiB  
Article
Self-Supervised Railway Surface Defect Detection with Defect Removal Variational Autoencoders
by Yongzhi Min and Yaxing Li
Energies 2022, 15(10), 3592; https://doi.org/10.3390/en15103592 - 13 May 2022
Cited by 9 | Viewed by 2061
Abstract
In railway surface defect detection applications, supervised deep learning methods suffer from the problems of insufficient defect samples and an imbalance between positive and negative samples. To overcome these problems, we propose a lightweight two-stage architecture including the railway cropping network (RC-Net) and [...] Read more.
In railway surface defect detection applications, supervised deep learning methods suffer from the problems of insufficient defect samples and an imbalance between positive and negative samples. To overcome these problems, we propose a lightweight two-stage architecture including the railway cropping network (RC-Net) and defects removal variational autoencoder (DR-VAE), which requires only normal samples for training to achieve defect detection. First, we design a simple and effective RC-Net to extract railway surfaces accurately from railway inspection images. Second, the DR-VAE is proposed for background reconstruction of railway surface images to detect defects by self-supervised learning. Specifically, during the training process, DR-VAE contains a defect random mask module (D-RM) to generate self-supervised signals and uses a structural similarity index measure (SSIM) as pixel loss. In addition, the decoder of DR-VAE also acts as a discriminator to implement introspective adversarial training. In the inference stage, we reduce the random error of reconstruction by introducing a distribution capacity attenuation factor, and finally use the residuals of the original and reconstructed images to achieve segmentation of the defects. The experiments, including core parameter exploration and comparison with other models, indicate that the model can achieve a high detection accuracy. Full article
(This article belongs to the Special Issue Failure and Multiphysical Fields in Geo-Energy)
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