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Advances in Deformation Control Technologies for Deep Excavations in Congested Urban Areas: 2nd Edition

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

Deadline for manuscript submissions: closed (31 October 2024) | Viewed by 2791

Special Issue Editors

School of Civil Engineering, Hefei University of Technology, Hefei 230009, China
Interests: geotechnical engineering; tunnelling; excavation; soil mechanics; rock mechanics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Deep excavations in congested urban areas in developing countries, which are carried out for various reasons, such as the construction of basements, parking garages, utilities, metro stations, and transportation tunnels, are becoming increasingly popular. Generally, in such urban areas, preexisting buildings and underground structures or utilities (e.g., piles, pipelines, and tunnels) are abundant, and they are susceptible to ground deformations induced by deep excavations adjacent to them. For the sake of the safety of the adjacent buildings and structures, as well as the stability of the excavation’s supporting system, it is vital to control the deformation of deep excavations in congested urban areas to achieve the best or most acceptable level of engineering cost. As for the technologies which control the deformation of deep excavations in these areas, long term-related research and engineering practice has accumulated much experience and effective technologies, especially for deformation control standard at the centimeter-level; however, when dealing with engineering cases involving the millimeter-level deformation control standard, challenges still remain.

The objective of this Special Issue is to collect new advances in deformation control technologies for deep excavations in congested urban areas and their many applications. Both original research and review articles are welcome. Potential topics include but are not limited to the following:

  • Mechanisms of deformations induced by the different construction phases of deep excavations;
  • Optimization and improvement of passive-type deformation control methods;
  • Analytical methods for predicting deformations induced by deep excavations;
  • Disposal measures for existing deformations;
  • Active-type deformation control methods;
  • The numerical modelling of three-dimensional behaviors of deep excavation;
  • The protection of adjacent buildings;
  • The performance of shelter piles or walls for reducing the adverse effects of excavation deformation;
  • The behavior or response of underground structures subject to excavation-induced ground deformations;
  • Case studies of deep excavations in congested urban areas.

Prof. Dr. Yixian Wang
Prof. Dr. Hang Lin
Prof. Dr. Yanlin Zhao
Dr. Panpan Guo
Guest Editors

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Keywords

  • deep excavation
  • deformation control
  • urban area
  • soil–structure interaction
  • soils
  • geotechnical engineering

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Published Papers (2 papers)

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Research

23 pages, 7403 KiB  
Article
Lateral Dynamic Response of Helical Pile in Viscoelastic Foundation Considering Shear Deformation
by Xiaoyan Yang, Chaozhe Wang, Sheng Cao, Fengxi Wang and Wenbing Wu
Appl. Sci. 2023, 13(22), 12220; https://doi.org/10.3390/app132212220 - 10 Nov 2023
Cited by 3 | Viewed by 1003
Abstract
Helical piles are a new type of pile that has good application prospects, and researchers have carried out an in-depth investigation into their vertical uplift and compressive bearing capacity. However, there is relatively little research on the dynamic bearing characteristics of helical piles. [...] Read more.
Helical piles are a new type of pile that has good application prospects, and researchers have carried out an in-depth investigation into their vertical uplift and compressive bearing capacity. However, there is relatively little research on the dynamic bearing characteristics of helical piles. Therefore, the lateral vibration of a helical pile embedded in the viscoelastic foundation is systematically studied in this article. Utilizing the equivalent stiffness method to transform a helical pile into a cylindrical pile of special diameter, the lateral vibration model of the helical pile considering shear deformation is established based on the Winkler foundation model and the Timoshenko beam theory. The analytical solutions for the lateral dynamic displacement, bending moment, and shear force of the helical pile are strictly derived, and the rationality of the present solutions is also verified by comparing them with existing solutions. Based on the present solutions, a parametric study is carried out to investigate the influence of the pile and soil properties on the lateral dynamic response of the helical pile. It is found that the load excitation frequency and pile–soil stiffness ratio have a significant influence on the lateral dynamic displacement, bending moment, and shear force of the helical pile with space and time response. Full article
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19 pages, 8482 KiB  
Article
Prediction of Maximum Tunnel Uplift Caused by Overlying Excavation Using XGBoost Algorithm with Bayesian Optimization
by Haolei Zhao, Yixian Wang, Xian Li, Panpan Guo and Hang Lin
Appl. Sci. 2023, 13(17), 9726; https://doi.org/10.3390/app13179726 - 28 Aug 2023
Cited by 4 | Viewed by 1205
Abstract
The uplifting behaviors of existing tunnels due to overlying excavations are complex and non-linear. They are contributed to by multiple factors, and therefore, they are difficult to be accurately predicted. To address this issue, an extreme gradient boosting (XGBoost) prediction model based on [...] Read more.
The uplifting behaviors of existing tunnels due to overlying excavations are complex and non-linear. They are contributed to by multiple factors, and therefore, they are difficult to be accurately predicted. To address this issue, an extreme gradient boosting (XGBoost) prediction model based on Bayesian optimization (BO), namely, BO-XGBoost, was developed specifically for assessing the tunnel uplift. The modified model incorporated various factors such as an engineering design, soil types, and site construction conditions as input parameters. The performance of the BO-XGBoost model was compared with other models such as support vector machines (SVMs), the classification and regression tree (CART) model, and the extreme gradient boosting (XGBoost) model. In preparation for the model, 170 datasets from a construction site were collected and divided into 70% for training and 30% for testing. The BO-XGBoost model demonstrated a superior predictive performance, providing the most accurate displacement predictions and exhibiting better generalization capabilities. Further analysis revealed that the accuracy of the BO-XGBoost model was primarily influenced by the site’s construction factors. The interpretability of the BO-XGBoost model will provide valuable guidance for geotechnical practitioners in their decision-making processes. Full article
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