Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.1
3.8
Journals
Buildings
Special Issues
Intelligent Risk Identification and Management in Urban Built Environment
share announcement

Intelligent Risk Identification and Management in Urban Built Environment

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: 28 September 2024 | Viewed by 4133

Special Issue Editors

Prof. Dr. Tianzheng Li

E-Mail Website
Guest Editor
Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
Interests: slope stability; underground construction; machine learning; reliability analysis; failure mechanism
Dr. Jingshu Xu

E-Mail Website
Guest Editor
Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Interests: slope stability; debris flow; chain-induced hazards; tunnelling engineering
Dr. Xiangfeng Guo

E-Mail
Guest Editor
Department of Civil and Environmental Engineering, National University of Singapore, Singapore 119077, Singapore
Interests: reliability analysis; structural health monitoring; machine learning; uncertainty quantification; dam engineering; geological mapping

Special Issue Information

Dear Colleagues,

Urban construction plays a crucial role in enhancing people’s well-being and driving urban competitiveness. The new city concept has been prevalent in recent years, where exploring underground spaces and integrating them with above-ground spaces have given birth to many innovative construction techniques, but also induced new geotechnical or geological risks. Identifying and managing these risks effectively in the unique context of the urban built environment is vital to safeguarding lives and properties. In recent years, the promotion and application of advanced technologies such as remote sensing image recognition, UAV aerial survey, and artificial intelligence have greatly improved the ability of engineers to predict various engineering risks in the process of urban construction. In addition, the introduction of advanced simulation methods also provides a strong theoretical guidance for the design of large-scale urban construction. The cross-integration of these methods not only ensures the safety and cost-effectiveness of urban construction, but also fosters interdisciplinary collaboration, driving technological innovation.

In view of these advancements, this special issue endeavors to delve into the most recent progress in geotechnical or geological risk analysis within the urban built environment. We cordially invite researchers and practitioners to submit their original research papers, theoretical and experimental works, case studies, or comprehensive review papers for potential publication in this special issue. This collective effort aims to enhance our comprehension of risk management in urban construction. Relevant topics, within the context of urban built environment, to this Special Issue include but are not limited to the following subjects:

  • New approaches for risk identification and management
  • Risk-based design/assessment of geo-structures
  • Risk assessment of geological hazards
  • Modelling of geological/geotechnical uncertainties
  • Remote sensing and surface subsidence analysis

Prof. Dr. Tianzheng Li
Dr. Jingshu Xu
Dr. Xiangfeng Guo
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. Buildings 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 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

  • slope stability
  • geotechnical risk analysis
  • landslide
  • geological hazards
  • remote sensing
  • uncertainty quantification

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

18 pages, 5164 KiB  
Article
Research on Prediction of EPB Shield Tunneling Parameters Based on LGBM
by Wei Wang, Huanhuan Feng, Yanzong Li, Quanwei You and Xu Zhou
Buildings 2024, 14(3), 820; https://doi.org/10.3390/buildings14030820 - 18 Mar 2024
Viewed by 558
Abstract
At present, the determination of tunnel parameters mainly rely on engineering experience and human judgment, which leads to the subjective decision of parameters and an increased construction risk. Machine learning algorithms could provide an objective theoretical basis for tunnel parameter decision making. However, [...] Read more.
At present, the determination of tunnel parameters mainly rely on engineering experience and human judgment, which leads to the subjective decision of parameters and an increased construction risk. Machine learning algorithms could provide an objective theoretical basis for tunnel parameter decision making. However, due to the limitations of a machine learning model’s performance and parameter selection methods, the prediction model had poor prediction results and low reliability for parameter research. To solve the above problems, based on a large number of construction parameters of a composite section subway in Shenzhen, this paper combined dimensionality reduction data with service analysis to optimize the selection process of shield tunneling parameters, and determined the total propulsion force, cutter head torque, cutter head speed, and advance rate as key tunneling parameters. Based on an LGBM algorithm and Bayesian optimization, the prediction model of key tunneling parameters of an earth pressure balance shield was established. The results showed that the average error of the LGBM model on the test set was 8.18%, the average error of the cutter head torque was 13.93%, the average error of the cutter head speed was 3.16%, and the average error of advance rate was 13.35%. Compared with the RF model, the prediction effect and the generalization on the test set were better. Therefore, an LGBM algorithm could be used as an effective prediction method for tunneling parameters in tunnel construction and provide guidance for the setting of tunneling parameters. Full article
(This article belongs to the Special Issue Intelligent Risk Identification and Management in Urban Built Environment)
►▼ Show Figures

Figure 1

17 pages, 6388 KiB  
Article
A Multiscale Method to Develop Three-Dimensional Anisotropic Constitutive Model for Soils
by Yu Tian, Hao Chen, Zijun Yao and Yufei Fang
Buildings 2024, 14(2), 307; https://doi.org/10.3390/buildings14020307 - 23 Jan 2024
Viewed by 534
Abstract
A multiscale method is presented to develop a constitutive model for anisotropic soils in a three-dimensional (3D) stress state. A fabric tensor and its evolution, which quantify the particle arrangement at the microscale, are adopted to describe the effects of the inherent and [...] Read more.
A multiscale method is presented to develop a constitutive model for anisotropic soils in a three-dimensional (3D) stress state. A fabric tensor and its evolution, which quantify the particle arrangement at the microscale, are adopted to describe the effects of the inherent and induced anisotropy on the mechanical behaviors at the macroscale. Using two steps of stress mapping, the deformation and failure of anisotropic soil under the 3D stress state are equivalent to those of isotropic soil under the triaxial compression stress state. A series of discrete element method (DEM) simulations are conducted to preliminarily verify this equivalence. Based on the above method, the obtained anisotropic yield surface is continuous and smooth. Then, a fabric evolution law is established according to the DEM simulation results. Compared with the rotational hardening law, the fabric evolution law can also make the yield surface rotate during the loading process, and it can grasp the microscopic mechanism of soil deformation. As an example, an anisotropic modified Cam-clay model is developed, and its performance validates the ability of the proposed method to account for the effect of soil anisotropy. Full article
(This article belongs to the Special Issue Intelligent Risk Identification and Management in Urban Built Environment)
►▼ Show Figures

Figure 1

17 pages, 13357 KiB  
Article
Experimental Study on the Evolution Law of the Mechanical and Pore Characteristic Parameters of Set Cement under High- and Ultra-High-Temperature Treatments
by Yan Xi, Junhao Xing, Jiajia Feng, Congming Ma, Xiutian Yang, Yudong Tian and Xin Liu
Buildings 2024, 14(1), 303; https://doi.org/10.3390/buildings14010303 - 22 Jan 2024
Viewed by 694
Abstract
Cement has been widely used as a structural material in many underground projects, and these projects often face high- or ultra-high-temperature environments, leading to the deterioration of the mechanical, porosity, and permeability properties of set cement, thereby increasing the risk of instability of [...] Read more.
Cement has been widely used as a structural material in many underground projects, and these projects often face high- or ultra-high-temperature environments, leading to the deterioration of the mechanical, porosity, and permeability properties of set cement, thereby increasing the risk of instability of underground structures. In response to this, two new temperature-resistant cement slurry systems were designed. Experiments were conducted on the changes in porosity and permeability of set cement after thermal treatment using low-field nuclear magnetic resonance technology (NMR), visual studies of pore and crack development were carried out using the argon-ion polishing field emission scanning electron microscopy (FE-SEM) and computed tomography (CT) methods. The research results show that as the thermal treatment temperature continued to rise, the compressive strength first increased (25 °C–200 °C) and then decreased (200 °C–600 °C). The porosity of the set cement first decreased (25 °C–115 °C) and then increased (115 °C–600 °C), and the penetration first slowly increased (25 °C–400 °C) and then rapidly increased (400 °C–600 °C). Visualization experiments were conducted on micro-cracks and the pore distribution of the set cement under high- and ultra-high-temperatures, which proved the evolution law of these characteristic parameters. The research results have vital reference significance for the protection of the structural stability of cement components when encountering high-temperature environments. Full article
(This article belongs to the Special Issue Intelligent Risk Identification and Management in Urban Built Environment)
►▼ Show Figures

Figure 1

17 pages, 3495 KiB  
Article
Effect of Rock Mass Disturbance on Stability of 3D Hoek–Brown Slope and Charts
by Jingshu Xu, Xinrui Wang, Pengfei Xie, Ruotong Wang and Dianchun Du
Buildings 2024, 14(1), 114; https://doi.org/10.3390/buildings14010114 - 31 Dec 2023
Viewed by 720
Abstract
The present study performs a stability analysis of a three-dimensional (3D) rock slope in disturbed rock masses following the Generalized Hoek–Brown (GHB) failure criterion. The factor of safety (FoS) of the slope is derived and the optimal solution is captured combining [...] Read more.
The present study performs a stability analysis of a three-dimensional (3D) rock slope in disturbed rock masses following the Generalized Hoek–Brown (GHB) failure criterion. The factor of safety (FoS) of the slope is derived and the optimal solution is captured combining the limit analysis method and the strength reduction technique. It is indicated by the parametric analysis that the 3D geometric characteristics have a significant impact on slope stability such that FoS decreases sharply with the increase in the width-to-height ratio B/H within 0<B/H≤2.0 and thereafter reaches a constant value asymptotically. The FoS decreases more than 60% linearly when the disturbance factor D increases from 0 to 1.0. Stability charts and slope angle weight factor fβ_3D for 3D slopes are proposed to provide a convenient and straightforward approach to obtain the FoS solutions of 3D slopes. A case study was carried out to apply the stability charts on practical engineering cases, which showed that slope stability under two-dimensional (2D) plane strain will lead to conservative results, and a 3D stability analysis of slope is more appropriate, especially for a slope with a limited width. Full article
(This article belongs to the Special Issue Intelligent Risk Identification and Management in Urban Built Environment)
►▼ Show Figures

Figure 1

18 pages, 6440 KiB  
Article
Risk-Informed, Reliability-Driven Decision Support for Building Basement Systems
by Ashan Senel Asmone, Helapura Nuwanshi Yasodara Senarathne and Michael Yit Lin Chew
Buildings 2023, 13(11), 2737; https://doi.org/10.3390/buildings13112737 - 30 Oct 2023
Viewed by 674
Abstract
A lack of consideration for maintainability at the planning/design stage of a construction project often results in inadequate decision-making and selection of design alternatives, which will likely lead to unproductive operational regimes riddled with frequent defects. This paper attempts to anchor the quantitative [...] Read more.
A lack of consideration for maintainability at the planning/design stage of a construction project often results in inadequate decision-making and selection of design alternatives, which will likely lead to unproductive operational regimes riddled with frequent defects. This paper attempts to anchor the quantitative risk analysis technique, Bayesian networks, as apt in predicting future operational defects based on the initial design alternatives by looking at specific case studies in building basement systems. Therefore, this paper aims to develop a comprehensive risk-informed, reliability-driven decision-making system. Central to this process is the implementation of a setup wherein a Bayesian Belief Network (BBN) operates as a powerful reliability engine. Concurrently, a risk matrix serves as a vital tool for facilitating risk-informed decision-making. This approach empowers stakeholders to make informed decisions regarding design choices while keeping maintainability at the forefront. It allows for maintainability to be practically used as an effective tool in buildings to lower the lifecycle cost. Furthermore, it is envisaged that this approach can be adopted in the construction industry globally for the prediction and diagnosis of defects, thereby facilitating risk-informed decision support. This study provides significant contributions to the building industry by providing a novel approach to a basement defect analysis, encouraging interdisciplinary collaboration among construction stakeholders, and assisting facility engineers and managers in properly determining maintenance requirements. Full article
(This article belongs to the Special Issue Intelligent Risk Identification and Management in Urban Built Environment)
►▼ Show Figures

Figure 1

17 pages, 16018 KiB  
Article
Buckling Analysis of a New Type of Double-Steering Prestressed Plate Column
by Yanying Li, Bailong Li, Xinsheng Yin and Zhiying Han
Buildings 2023, 13(10), 2574; https://doi.org/10.3390/buildings13102574 - 12 Oct 2023
Cited by 1 | Viewed by 545
Abstract
A new type of dual-steering prestressed plate column is introduced. Compared to the previous prestressed strut column, this proposed column considers both bending and constraints at ends. The calculation results indicated that the support plate significantly improves the stable bearing capacity and buckling [...] Read more.
A new type of dual-steering prestressed plate column is introduced. Compared to the previous prestressed strut column, this proposed column considers both bending and constraints at ends. The calculation results indicated that the support plate significantly improves the stable bearing capacity and buckling performance of the core steel column. When compared to the proposed column, the bearing capacity of the three-transverse prestressed beam column is 1.51 times smaller, the single-transverse prestressed beam column is 2.43 times lower, and the non-prestressed column is 4.51 times smaller. Moreover, this study examines the influences of effective length, buckling mode, stress nephogram detail, and prestress value. It explores the possibility of implementing this new type of dual-steering prestressed plate column in practical engineering. In addition, the variety and mechanical models of prestressed columns are expanded and refined. Full article
(This article belongs to the Special Issue Intelligent Risk Identification and Management in Urban Built Environment)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop