Smart Construction and Sustainable Cities

A detailed investigation was conducted to analyse the mechanical and durability features of a mixture of binary cement concrete modified with nanomaterials. In the context of the concrete matrix, the substitution of fractional cement content was carried out using Nano silica (NS) at concentrations of 1%, 2%, and 3%. Four distinct cementitious blends were subjected to a comprehensive match of tests, which encompassed compressive strength, flexural strength, split tensile strength, static modulus of elasticity, bulk density, water absorption, permeability, carbonation resistance, acid attack resistance, and rapid chloride penetration. The compositions of the mixes were investigated through the use of various microstructural analysis techniques, including scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (SEM-EDS), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR). The research revealed significant improvements in the mechanical and durability characteristics of the material. An increment in the mechanical and durability properties of mixtures were seen due to inclusion of marble power and Nano silica due to enhanced pozzolanic activities of composite and its filling effect. It is worth mentioning that Nano silica has shown the potential to mitigate the degradation caused by exposure to sulfuric acid. The SEM-EDX analysis demonstrated a decrease in the Ca/Si ratio when compared to the reference combination, suggesting an increase in the consumption of calcium hydroxide (CH) and the creation of a more compact calcium-silicate-hydrate (C-S-H) gel. The X-ray diffraction (XRD) findings indicate that NS has the ability to act as an accelerator for pozzolanic processes. This is achieved by consuming calcium hydroxide (CH) and promoting the creation of extra calcium silicate hydrate (C-S-H), which ultimately enhances the overall performance of the concrete mixture.

Wind-driven sand erosion is the leading primary reason of earth deterioration in dry lands and a major global issue. Desert dust emissions and topsoil degradation caused by wind pose a global danger to the ecosystem, economy, and individual health. The aim of the current study is to critically analyze the different types of biopolymers and their interaction mechanism with sands for desert sand stabilization. Extensive experimental data with different percentages of biopolymers has been presented on various wind erosion studies using wind tunnel testing and their control rate on desert sand stabilization. Also, studies related to evaluating the engineering properties of sand using biopolymers were analyzed. Other biological approaches, namely Microbial-induced calcite precipitation (MICP) and Enzyme-induced carbonate precipitation (EICP), have been discussed to regulate wind-driven sand erosion in terms of percentage calcite formation at different compositions of urea and calcium chloride. Comparative analysis of MICP and EICP with biopolymer treatment and their limitations have been discussed. Biopolymers are not only demonstrated adeptness in engineering applications but are also helpful for environment safety. Biopolymers are suggested to be novel and nature-friendly soil-strengthening material. This review focuses on the fundamental mechanisms of biopolymer treatment to reduce wind-driven sand loss and its future scope as a binder for sand stabilization. The mechanism of soil-biopolymer interaction under various soil conditions (water content, density, and grain size distribution) and climatic circumstances (drying-wetting cycles) needs to be explored. Furthermore, before applying on a large scale, one should evaluate sand-biopolymer interaction in terms of durability and viability.

Waterlogging in subway stations has a devastating impact on normal operation of important urban facilities and can cause harm to passengers and property. It is difficult to assess the vulnerability of metro stations to waterlogging because many complex factors are involved. This study proposes a hybrid model to assess the vulnerability of subway stations to waterlogging by integrating the entropy weight method (EWM) with a technique for order preference based on similarity to the ideal solution (TOPSIS) (the EWM-TOPSIS method). The model is based on analysis of factors influencing the vulnerability of subway stations to waterlogging. The proposed method was applied to a field case (Jinshahu station in Hangzhou, found to be vulnerable to waterlogging at level IV). The results from EWM-TOPSIS, EWM, and TOPSIS were compared. The results using the EWM-TOPSIS method were more accurate and reliable than those using EWM and TOPSIS. However, the reliability of EWM-TOPSIS was determined based on historical data, which cannot capture rapidly changing factors. Based on the assessment results, recommendations were made to promote the overall health and development of urban areas to satisfy the United Nations Sustainable Development Goal 11 (SDG11).

The frequent occurrence of building collapse accidents not only causes significant casualties, but also jeopardizes local economies. This paper adopts a combinatory assessment approach to showcase the lessons learned from a recent building collapse in Changsha, China. The proposed approach blends the system thinking approach and strategic environmental assessment (SEA) model. It delineates the causes of collapse and provide key leverage points for safety management. The results show that the primary causes for the collapse are the poor construction quality, illegal alterations, and lack of regulations enforcement. The management of rural housing construction in Hunan Province achieved a total score of 4 out of 30. It was also determined that the key prevention measures for abating these deleterious phenomena involve ensuring quality assurance/quality control, efficiently assessing safety risk, and timely performing structural health monitoring. This study is bound to enhance the understanding of collapse accidents and foster the achievement of sustainable cities and communities.

Due to global warming, considerable amounts of storm rain have occurred, causing urban water logging and flooding. The efficient scheduling of drainage systems among pumping stations is crucial to mitigating flash flooding in urban areas. This study introduces a Multi-Level Dynamic Priority and Importance Scheduling (MDPIS) algorithm as a proactive solution for addressing urban flooding through the optimization of drainage system discharge capacities. The algorithm's robustness is guaranteed through the integration of a multi-tier drainage system and dependency relationships. Additionally, the incorporation of an importance parameter is considered for facilitating the practical exploration of flooding risk evaluation. The proposed model was applied to simulate a drainage system in Haining City, and the results indicate that its accuracy, flexibility and reliability outperform that of existing algorithms such as fixed-priority scheduling. Moreover, the proposed approach enabled a considerable reduction in overflow loss and improved the efficiency of the sewage system. This method can improve the responses of cities to the rising problem of urban water logging.

In recent years, the comprehensive and extensive development of urban underground space (UUS) has gained substantial popularity with the efficient guidance of UUS planning. This study discussed the research trends and paradigm shift in UUS planning over the past few decades. Bibliometric and comparative studies were conducted to identify the contributions of the research in this field. The analysis identified the overall temporal development trend of UUS planning and the research hot spots, namely, the primary use of UUS and UUS planning technology. Additionally, the study identified academic collaborative relationships through country and institution co-occurrence network analysis. The diversified development philosophy, planning systems, key planning scenarios, and data-driven technology pertaining to UUS planning have been extracted through keyword co-occurrence network analysis. Moreover, the planning systems, planning management, and planning practices for UUS in various countries, including Singapore, Japan, Finland, Canada, and China, were also systematically reviewed. By doing so, the worldwide UUS planning evolution has been identified. The paradigm shift for UUS planning has been clarified, involving technical method, result form, control mode, and control elements. Furthermore, the conceptual data-driven framework for UUS planning, which orients multiple development concepts, has been proposed to meet the requirement of next frontier development.

Preventing/mitigating natural disasters in urban areas can indirectly be part of the 17 sustainable economic and social development intentions according to the United Nations in 2015. Four types of natural disasters—flooding, heavy rain-induced slope failures/landslides; earthquakes causing structure failure/collapse, and land subsidence—are briefly considered in this article. With the increased frequency of climate change-induced extreme weathers, the numbers of flooding and heavy rain-induced slope failures/landslides in urban areas has increased in recent years. There are both engineering methods to prevent their occurrence, and more effectively early prediction and warning systems to mitigate the resulting damage. However, earthquakes still cannot be predicted to an extent that is sufficient to avoid damage, and developing and adopting structures that are resilient against earthquakes, that is, structures featuring earthquake resistance, vibration damping, and seismic isolation, are essential tasks for sustainable city development. Land subsidence results from human activity, and is mainly due to excessive pumping of groundwater, which is a “natural” disaster caused by human activity. Countermeasures include effective regional and/or national freshwater management and local water recycling to avoid excessive pumping the groundwater. Finally, perspectives for risk warning and hazard prevention through enhanced field monitoring, risk assessment with multi-criteria decision-making (MCDM), and artificial intelligence (AI) technology.

Ensuring high-quality fill compaction is crucial for the stability and longevity of infrastructures and affects the sustainability of urban infrastructure networks. The purpose of this paper is to provide a refined analysis and insight understanding of the current practice, limitations, challenges, and future development trends of compaction methods from the perspective of the development stage. This paper offers a comprehensive overview of the evolution of compaction methods and classifies compaction quality control methods into four groups through quantitative analysis of literature: traditional compaction methods, digital compaction methods, automated compaction methods, and intelligent compaction methods. Each method's properties and issues are succinctly stated. Then, the research on three key issues in intelligent compaction including compaction quality evaluation algorithms, dynamic optimal path planning, and implementation of unmanned technology is summarized. Currently, the field of intelligent compaction is far from mature, a few challenges and limitations need further investigation: coupling problems of multiple indicators in intelligent evaluation algorithms, unmanned roller groups collaborative control problems, and intelligent decision-making and optimization problems of multi-vehicle compaction paths. This review serves as a valuable reference for systematically understanding the development of compaction methods.