Recent Advances in Sustainability Practice of Civil and Environmental Engineering in Regions with Challenging Geological and Climatic Conditions

Topic Information

Dear Colleagues,

In today's world, the theory and technology of civil and environmental engineering in typical regions have reached a mature stage. However, there remain numerous challenging issues related to the design, construction, and sustainable maintenance of infrastructures in regions with unique geological conditions and harsh climates. For instance, in **njiang Province, China, the sustainable development and operation of infrastructures face difficulties due to various inherent adverse local attributes, including frequent natural hazards such as avalanches, debris flows, earthquakes, saline and alkaline land, extreme cold and drought, significant temperature variations, high seismic intensity, and severe sandstorms. These adverse environmental and climatic conditions not only escalate construction and maintenance costs, but also result in substantial casualties and economic losses. On the other hand, these regions often boast abundant natural resources such as sunlight and wind, fostering the growth of new energy industries. However, these new energy facilities are typically located in desert areas where significant day and night fluctuations in temperature, shifting sands, and intense sandstorms occur alongside severe water scarcity. The construction of infrastructure in desert areas and the utilization of desert sand as a primary construction material represent crucial novel avenues for enhancing sustainability in civil and environmental engineering; however, these areas have been relatively unexplored. Furthermore, the challenging environment limits the use of conventional sensors. Hence, it is urgent that new sensors capable of withstanding adverse environmental conditions are designed and developed, while ensuring consistent performance. Additionally, remote sensing technologies such as InSAR will prove invaluable in monitoring terrestrial changes and infrastructure displacement in remote and inaccessible areas. However, existing methods, frameworks, tools, and platforms for processing satellite data, visualizing information, and integrating data from ground-based monitoring systems, which are well-established in conventional regions, must be modified or newly created to suit the demanding geological and climatic conditions of these areas.

The aim of this Topic is to highlight recent advancements in fundamental theories, analytical methodologies, intelligent frameworks, advanced numerical modeling, and innovative practical technologies in civil and environmental engineering and related disciplines such as architecture and surveying for regions with challenging geological and climatic conditions. We welcome submissions that address various topics including architectural design theory, remote sensing methodologies, green buildings, sustainable infrastructure management, construction technologies, novel structural patterns, waste material recycling and reuse, water treatment, pavement engineering, avalanche disaster prevention and mitigation, and disaster prevention early warning systems. We particularly encourage the submission of practical case studies that showcase the application of innovative technologies in the aforementioned fields and that contribute to enhancing sustainability and economics. Submissions should be original and not previously reported or published in other journals.

Dr. **n Huang
Dr. Qinghua Lei
Dr. Tao Zhao
Prof. Dr. Liangfu **e
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.5	5.3	2011	17.8 Days	CHF 2400	Submit
Remote Sensing remotesensing	4.2	8.3	2009	24.7 Days	CHF 2700	Submit
Technologies technologies	4.2	6.7	2013	24.6 Days	CHF 1600	Submit
Buildings buildings	3.1	3.4	2011	17.2 Days	CHF 2600	Submit
Sustainability sustainability	3.3	6.8	2009	20 Days	CHF 2400	Submit

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Published Papers (3 papers)

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17 pages, 3706 KiB  

Open AccessArticle

Inversion Study on Landslide Seepage Field Based on Swarm Intelligence Optimization Least-Square Support Vector Machine Algorithm

by Xuan Tang, Chong Shi and Yuming Zhang

Appl. Sci. 2024, 14(13), 5822; https://doi.org/10.3390/app14135822 - 3 Jul 2024

Viewed by 349

Abstract

The permeability coefficient of landslide mass, a key parameter in the study of reservoir landslides, is commonly obtained through in situ and laboratory tests; however, the tests are costly and subject to high variability, leading to potential biases. In this paper, a new [...] Read more.

The permeability coefficient of landslide mass, a key parameter in the study of reservoir landslides, is commonly obtained through in situ and laboratory tests; however, the tests are costly and subject to high variability, leading to potential biases. In this paper, a new method was proposed to inversely estimate the permeability coefficient of landslide layers using monitoring data of groundwater level (GWL). First, the landslide transient seepage simulation was conducted to generate sample data for permeability coefficients and GWL during a reservoir operation cycle. Second, using GWL data as input and permeability coefficient data as output, the least-square support vector machine (LSSVM) was trained with two optimization algorithms, the particle swarm optimization (PSO) algorithm and the whale optimization algorithm (WOA), to construct the nonlinear map** relationship between simulated GWL and permeability coefficients. Third, the accurate permeability coefficients for landslide seepage simulation were inverted or predicted based on the monitored GWL. Finally, using the inverted permeability coefficients for landslide seepage simulation, we compared simulation results with actual monitored GWL and achieved good consistency. In addition, this paper compared the inversion effects of three different algorithms: the standard LSSVM, PSO-LSSVM, and WOA-LSSVM. This study showed that these three algorithms had good nonlinear fitting effects in studying landslide seepage fields. Among them, using the inversion values from PSO-LSSVM for landslide seepage simulation resulted in the smallest relative error compared to actual monitoring data. Within a single reservoir operation cycle, the simulated water level changes were also largely consistent with the monitored water level changes. The results could provide a reference to determine landslide permeability coefficients and seepage. Full article

(This article belongs to the Topic Recent Advances in Sustainability Practice of Civil and Environmental Engineering in Regions with Challenging Geological and Climatic Conditions)

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16 pages, 1232 KiB  

Open AccessArticle

Experimental Study on Key Techniques for the Construction of High Asphalt Concrete Core Rockfill Dam under Unfavorable Geological Conditions

by Hao Li, Jianxin He, Shihua Zhong, Liang Liu and Wu Yang

Buildings 2024, 14(7), 1968; https://doi.org/10.3390/buildings14071968 - 28 Jun 2024

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Abstract

Asphalt concrete core dams (ACCDs) have been widely constructed in **njiang, yet the design of materials and structures has mainly relied on empirical knowledge without substantial theoretical grounding. In this study, we carried out a large-scale relative density test of gravel material in [...] Read more.

Asphalt concrete core dams (ACCDs) have been widely constructed in **njiang, yet the design of materials and structures has mainly relied on empirical knowledge without substantial theoretical grounding. In this study, we carried out a large-scale relative density test of gravel material in Bamudun dam, studied the compaction characteristics of gravel material, and determined the relative density characteristic index, in order to provide a basis for the subsequent dam material rolling test and construction quality inspection. Furthermore, in order to improve the efficiency of dam construction in narrow valleys, we optimized the connection type between asphalt concrete core wall and bedrock, and proposed a rapid construction method of paving core wall after pouring mass concrete base on bedrock. Finally, we established a three-dimensional finite element model to systematically analyze the stress and deformation patterns of the dam body, core wall, and base of the ACCD at Bamudun. The results show that the maximum compressive stress suffered by the core wall during the full storage period is 1.62 MPa, there is no tensile stress, and the risk of hydraulic splitting is small. The stress and deformation levels of each part are within the safe range. This verifies the rationality of the rapid construction method. The research findings can provide a great theoretical significance and engineering value for the safe design and construction of ACCDs. Full article

(This article belongs to the Topic Recent Advances in Sustainability Practice of Civil and Environmental Engineering in Regions with Challenging Geological and Climatic Conditions)

19 pages, 7713 KiB  

Open AccessArticle

The Fractal Characteristics of Ground Subsidence Caused by Subway Excavation

by Yongjun Qin, Peng He, Jiaqi Zhang and Liangfu **e

Appl. Sci. 2024, 14(12), 5327; https://doi.org/10.3390/app14125327 - 20 Jun 2024

Viewed by 316

Abstract

The issue of uneven ground settlement caused by the excavation of subway tunnels represents a significant challenge in the design and construction of subway projects. This paper examined the fractal characteristics of surface settlement caused by subway excavation, employing wavelet transform and fractal [...] Read more.

The issue of uneven ground settlement caused by the excavation of subway tunnels represents a significant challenge in the design and construction of subway projects. This paper examined the fractal characteristics of surface settlement caused by subway excavation, employing wavelet transform and fractal theory. Firstly, the noise reduction effects of different wavelet functions, decomposition levels, threshold functions, and threshold selection rules were evaluated using the SNR and RMSE. Subsequently, 291 data points were derived from 18 interpolation points through fractal interpolation, representing a utilization of only 18% of the original data, to enhance the original monitoring data information by a factor of 2.94. The average relative error between the fractal interpolation results and the monitoring data was approximately 13%, which was indicative of a high degree of accuracy. Finally, the fractal dimension of the monitoring curves under different monitoring frequencies was calculated using the box-counting method. The denoising effect of the dbN wavelet function was found to be superior to that of the symN wavelet function in the denoising process of subway construction surface deformation monitoring data. Furthermore, the hard threshold method was observed to be more effective than the soft threshold method. As the monitoring frequency decreased, the fractal dimension of the deformation curves showed an overall decreasing trend. This indicated that high-frequency monitoring could capture more details and complexity of the surface settlement, while low-frequency monitoring led to a gradual flattening of the curves and a decrease in details. Full article

(This article belongs to the Topic Recent Advances in Sustainability Practice of Civil and Environmental Engineering in Regions with Challenging Geological and Climatic Conditions)

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