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The filter paper (FP) method, a cost-effective, versatile, and convenient approach, has found extensive application in analyzing fine-grained soils, enabling the successful measurement of a broad spectrum of total and matric suctions. However, using the FP method in sand with a limited range of suction profiles has been notably underrepresented in the existing literature. Therefore, this study investigated the applicability of the contact FP method in establishing soil water retention curves (SWRCs) using five distinct FP calibration curves for 10 poorly graded sands. Among these calibration curves, the one presented by Chandler yielded the highest suction values, which were followed by those of ASTM. Furthermore, the FP results were subjected to fitting with a mathmatical model, which led to the observation that the overall trends in the obtained SWRCs displayed smooth sigmoidal shapes, resulting in a complete and coherent SWRCs. The SWRC results of five sand samples were assessed through validation against the hanging column technique (HCT) results, indicating a high degree of concordance and affirming the suitability of the FP method for sands characterized by a limited suction profile. Notably, the entire range of suction values fell within the 0.01–20 kPa range based on the calibration curves presented by Chandler and ASTM for all the examined sand samples, except sands 9 and 10. Furthermore, the suction values were unobtainable using the two aforementioned calibration curves within the ranges of 0.01–1.47 kPa and 0.01–0.172 kPa. [ABSTRACT FROM AUTHOR]

The article discusses the importance of reproducibility in academic research, particularly in the field of structural engineering. It acknowledges the challenges in achieving reproducibility, such as data storage and computing requirements, as well as proprietary issues. The authors argue for the development of a reproducibility policy in the Journal of Structural Engineering and the Journal of Bridge Engineering, taking into account the nature and culture of research in these subdisciplines. They propose a classification system that emphasizes the availability of data and metadata, and encourage authors to go beyond data availability by making models and other materials accessible. To incentivize research and data availability, the journals will provide a visible recognition badge for papers with open data/models/codes and may consider special recognition for these papers. The authors also outline the review process for data-verified papers, which involves three associate editors verifying the availability and representativeness of the data. [Extracted from the article]

The Journal of Construction Engineering & Management has announced the recipients of the 2023 Best Paper Award. The winning paper, titled "Deep Learning Image Captioning in Construction Management: A Feasibility Study," explores the automation of deep learning for image captioning in the construction management field. The authors present a systematic approach that includes developing a linguistic schema, creating a dataset of manually captioned images, and evaluating six deep-learning methods using eight metrics. The paper concludes that a method combining two advanced deep learning processes performed the best, and that automatic captioning in construction management is feasible. The article provides valuable insights and suggestions for future development in this area. [Extracted from the article]

This study deals with the recovery of deinking sludge (DS) generated during waste paper recycling. The aim is to integrate this sludge in the fired-bricks formulation with different percentages. These mixtures are fired, and the study of the general aspect, loss on fire, and water absorption enables characterization of this material. Different compression tests are carried out on studied samples to characterize the strength and compare its performance to the standard. The mixtures' optimization and the elaboration conditions are the main objectives to obtain a new construction material with competitive performances conforming to the standards. [ABSTRACT FROM AUTHOR]

The emphasis of the current study was on the calcination of lime sludge, performed at different temperatures from 650°C to 750°C, which consumes less energy as compared to the industrial process of calcination. Different proportions of calcined lime sludge and raw lime sludge were used with cement to form cementitious binders. M25 grade concrete was prepared with the application of the prepared binders and tested for strength properties at 7 and 28 days of curing. The binder consisted of 10% substitution of cement with as-received lime sludge and 30% substitution with calcined lime sludge and produced a compressive strength of concrete approximately similar to the control concrete. Reactive lime and metakaolinite performed an active role after the calcination of lime sludge at 650°C, which worked as pozzolana. This effect is also confirmed with isothermal calorimetry of the prepared binder. The prepared binder was sustainable with approximately 20% less production cost and 55% less emission of greenhouse gases as compared to ordinary portland cement. [ABSTRACT FROM AUTHOR]

The aim of this paper is to propose a step by step method to establish and validate a relevant, dynamical model of the activated sludge process for the paper mill industry. The model is established by considering the specificities of the effluent to be treated. It uses the biochemical oxygen demand (BOD) measurement, which allows a direct correlation between the state variables of the model and the measurements. This model is validated on a pilot plant of semi-industrial size fed with industrial paper mill effluents. The parameter estimation is based on an analysis of the sensitivities. The results are compared with a model based on chemical oxygen demand (COD) partitioning which is issued from the simplification of the activated sludge model number 1 (ASM1) model. Finally, the model dealing with BOD measurements not only shows the best performances, but is also the easiest to implement, overcoming one main obstacle to efficient monitoring and control in paper mill wastewater treatment plants. [ABSTRACT FROM AUTHOR]

Cement stabilization is a widely applied technique in improving the workability and geotechnical properties of soft clay. This paper investigated the influence of cement stabilization on the soil–water characteristic curve (SWCC) and the deformation behavior of unsaturated cement–stabilized soft clay. The combined effect of cementation and partial saturation on the hydromechanical behavior of cement-stabilized soils was discussed. The SWCC of stabilized soil was measured in the full suction range under drying and wetting paths using the pressure plate method, the filter paper method, and the vapor equilibrium technique. The deformation behaviors of cement-stabilized soft soil were investigated by conducting suction-controlled oedometer tests. Furthermore, scanning electron microscope micrographs and mercury intrusion porosimetry tests were performed to investigate the effects of cement content on the evolution of soil pore structures. The test results showed that the water retention capacity of the stabilized soft clay increased with increasing cement content. The SWCC showed a significant hysteretic behavior in the boundary effect zone and transition zone, whereas the hysteretic effect was unapparent in the residual zone. The increased cement content had a more significant hysteretic effect on the SWCC. The deformation resistance capacity increased as the cement content and matric suction increased. However, the effect of matric suction on deformation resistance capacity decreased as the cement content increased. With the increase in cement content, the macropores were converted to small interaggregate pores, the pore spaces were distributed more uniformly, and the particle surface became rougher, resulting in higher water retention capacity and significant hysteresis of the SWCC. [ABSTRACT FROM AUTHOR]

She holds a B.Eng. in building engineering from Tongji University (2001), a M.S. in civil engineering from the University of Massachusetts (2005), and a Ph.D. in geotechnical engineering from the Georgia Institute of Technology (2010). Dr. Tan's areas of specialization include deep excavation and tunnelling, foundation engineering, forensic geotechnical engineering, and engineering failures associated with climate change. He received his B.Eng. in building engineering from Tongji University (1999), M.Eng. in Geotechnical Engineering from Tongji University (2002), and Ph.D. in civil engineering from the University of Massachusetts (2005). [Extracted from the article]

The current cases and studies show that the aerosol propagation of COVID-19 is possible in the office buildings. The paper explored the ventilation level and monitoring methods for indoor infection risk in office buildings, improved the Wells-Riley equation and ventilation rate equation, providing the possibility of real-time monitoring of the transmission risk of COVID-19 in office buildings. Then, the main influencing factors of the exposure risk of SARS-CoV-2, including working density, dwell time, and fresh air volume per person, were field measured in three office areas and three conference rooms of an office building in Shenzhen, China. In addition, the field monitored carbon dioxide (CO2) data were used to estimate the possibility of COVID-19 infection in offices and conference rooms. The results show that the number of staff, ventilation rate, and office hours are all important factors affecting the infection risk of workers in the office building environment, but the existing literature rarely considers these three points at the same time. In addition, the paper adopted the method of assessing the infection risk from place to place, time to time, and person to person in the building environment, providing early warning for office buildings and helping to control the spread of airborne diseases. The results can be beneicial to understanding and taking necessary safety considerations against the infection risk in closed public or governmental environments. The paper explored the ventilation level and monitoring methods for indoor infection risk in office buildings and improved the Wells-Riley equation and ventilation rate equation, providing the possibility of real-time monitoring of the transmission risk of COVID-19 in office buildings. The results showed that the number of staff, ventilation rate, and office hours are all important factors affecting the infection risk of workers in the office building environment, but the existing literature has rarely considered these three points at the same time. Meanwhile, research has further demonstrated the connection between the risk of virus infection and indoor monitoring environmental indicators, providing a new path for further accurate prediction of indoor infection risk. The results can be beneficial to understanding and taking necessary safety considerations against the infection risk in closed public or governmental environments. Therefore, evaluating indoor transmission risks through monitoring environmental indicators is feasible and could be used as a reference basis for practical applications. [ABSTRACT FROM AUTHOR]

To ensure the safety of tunnel construction, it is necessary to accurately and timely measure the deformation of the shotcrete liner during the management of the construction process. The light detection and ranging (LiDAR) technique, known as the reality reproduction technology, provides a new solution for deformation measurement. However, the nonsmooth defects of shotcrete liner and the scattered noise points caused by the nearby dust, as well as a large number of nontunnel structures such as pipes, construction machinery, and vehicles in the obtained tunnel point cloud datasets, hinder the application of point clouds in deformation measurement of shotcrete liner. In this paper, a ring simulation sampling (RSS) method for automatic sampling and deformation measurement of shotcrete liner using the multiepoch LiDAR point clouds is proposed. This method constructs the virtual ring according to shape of the tunnel cross section and emits the rays from the ring to the center of each tunnel cross section. The length difference of the rays arriving at the outer wall of the multiepoch tunnel point clouds is calculated to achieve the analysis of overall and local deformations of the shotcrete liner. The shotcrete liner point clouds generated by the manual modeling and terrestrial laser scanning are tested to validate the effectiveness of the method in extracting the deformation of shotcrete liner. Compared with the conventional total station monitoring, the mean absolute deviation and root mean square error are 1.39 and 1.93 mm, respectively, which indicates that the RSS method could be effectively applied to the deformation measurement of tunnel shotcrete liner. Deformation measurement of tunnel shotcrete liner is crucial to safety of tunnel construction and implementation of dynamic parameter design. This study recommends the light detection and ranging (LiDAR) technique. The main work of this paper is to determine whether the tunnel shotcrete lining has been deformed as a whole or locally by comparing the obtained multiepoch high-precision 3D point clouds. Furthermore, the authors propose a method for automatic sampling and deformation measurement of shotcrete liner using the multiepoch LiDAR point clouds. Compared with conventional deformation measurement methods (i.e., the total station and fiber optics) that capture deformation information from a limited number of monitoring points, LiDAR technology enables the high-precision, omnidirectional, and noncontact acquisition of spatial data within tunnels. This serves as a complementary and enhanced tool to tunnel safety monitoring techniques and methodologies. In addition, the adoption of the method proposed in this paper facilitates the quality check of shotcrete liner, including thickness assessment and smoothness detection. [ABSTRACT FROM AUTHOR]

Complex risk factors make metro construction safety accidents prone to occur, and there are various types of accidents. Accident reports record detailed information about different types of accidents in text form. However, effectively utilizing such unstructured data presents a significant challenge. Text mining (TM) provides a viable foundation for addressing this challenge, but related studies have limitations in risk feature extraction and lack of in-depth analysis capability. To address the deficiencies of existing studies and provide a feasible strategy for identifying key risk factors in the metro construction domain, this paper proposes an integrated model combining TM and machine learning–based Bayesian networks. Firstly, the term frequency-inverse document frequency (TF-IDF) algorithm in TM was used to separately extract the direct and indirect cause factors from the accident reports, with the missing factors supplemented using the TextRank algorithm. Then, depending on the assumption of whether to consider the conditional independence between factors, an improved naive Bayesian network (NBN) and a tree-augmented naive Bayesian network (TAN) were built based on the extracted factors and the corresponding accident types, respectively, for further in-depth analysis. Finally, the training set was divided to train the two network models, and sensitivity analysis was used to identify the key risk factors. Using 162 accident reports from China as an application example, the results showed that TAN exhibited a higher average accuracy (79.62%) in the test set compared with the improved NBN (71.75%), and the importance of risk factors for different accident types was successfully ranked from multiple perspectives using TAN. Meanwhile, some new insights into metro accidents in China were obtained, which can support decision-making for accident prevention and control. In conclusion, this paper effectively addresses the relevant limitations of accident text utilization and presents a novel approach for metro construction safety management. Analyzing accident texts can help gain insights from objective historical data to support safety management efforts. However, accident texts are often unstructured and contain a lot of irrelevant content. How to quickly extract valid information from accident text and use it to analyze accidents in depth is of continuous interest to safety managers. In particular, those models that have real-time decision support capabilities in addition to theoretical insights. This paper proposes an integrated model that combines text mining and machine-learning Bayesian networks. This model achieves comprehensive textual feature extraction, multifaceted accident causation analysis, and allows safety managers to input current accident information into the model to obtain real-time decision support for accident prevention and control. Although the proposed model is developed for metro construction, it can be slightly adapted by incorporating the characteristics of accident texts from similar domains to obtain an integrated model suitable for these domains, so as to effectively control the occurrence of safety accidents. [ABSTRACT FROM AUTHOR]

Global warming is causing unprecedented changes to permafrost regions with amplified effects in the Arctic through a phenomenon known as Arctic amplification. This intensified climate warming thaws both the discontinuous and continuous permafrost resulting in changes in the mechanical properties of the soils found in these regions. Since permafrost regions constitute nearly 24% of the Northern Hemisphere, understanding the strength of soils in thawed conditions is essential to analyze the stability of existing structures, and to design safer and more economical infrastructure in these regions. Specifically, thawing of the permafrost is causing considerable reductions in its strength of soils, which may lead to massive landslides, foundation failures, and so forth. Since frozen soil is a multiphase structure that consists of soil particles, unfrozen water, ice, and air, each constituent will influence the mechanical properties. This paper reviews the current state of knowledge of the impact of temperature, volumetric ice content, unfrozen water content, and frozen density on the compressive strength, peak shear strength, residual shear strength, undrained shear strength, and tensile strength of soils. The undrained shear strength of soil is said to have a linear correlation with temperature. In addition, the undrained cohesion of soil was found to depend on the temperature, whereas the undrained friction angle of soil was significantly influenced by volumetric ice content. An increase in the volumetric ice content up to 80% to 90% will cause a reduction in the peak and residual deviatoric stresses. In addition, an increase in volumetric ice content resulted in an increase in the compressive strength of the soil. The tensile and compressive strengths were found to be functions of the unfrozen water content. Global warming is causing the temperature of the permafrost, which is permanently frozen ground, to rise. This paper provides valuable insights into the impact of the changes in this ambient temperature on the strength of frozen soils in permafrost regions for a wide range of applications. Such insights are crucial for the design of resilient and stable infrastructure, such as foundations, embankments, and retaining walls, in which consideration of the reduced strength of thawed soils due to climate change will be necessary. In addition, the knowledge will allow for better management of vulnerable areas prone to landslides and erosion caused by the weakened soil strength permitting the implementation of mitigation measures before lives are lost and costly economic damages are incurred. Finally, this information will aid in early warning systems, emergency planning, and decision making to minimize the impact of hazards on human settlements and infrastructure. In this paper, a review of the current state of knowledge regarding the strength of frozen soils and the associated fluctuations in these strengths because of a rise in temperature are presented. Guidelines on the best practices for sample preparation and testing along with correlations to estimate various strength parameters are also provided. [ABSTRACT FROM AUTHOR]

Ultrahigh-performance concrete (UHPC) is a new class of concrete with far superior mechanical and durability properties compared to conventional concrete. Recently, its use has been growing in both civil and architectural applications, especially in the precast industry. This paper presents the application of UHPC to the production of precast concrete sandwich wall panels commonly used in Northern regions and known as insulated wall panels. Using UHPC in the panel wythes allows for a significant reduction in wythe thickness and, consequently, panel weight, in addition to the elimination of longitudinal and transverse reinforcement, which simplifies production. In this study, four 2.44 m × 1.22 m × 203 mm composite UHPC sandwich wall panels were fabricated by a local precast producer using a nonproprietary UHPC mixture. Panels were tested in flexure to evaluate the degree of composite action when wythe thickness of 32 mm and glass fiber–reinforced polymer (GFRP) shear connectors are used. These panels do not contain any conventional rebars or prestressing strands as they are fully dependent on the presence of random steel fibers in UHPC to provide the tensile resistance. Test results have shown that this new system can achieve a flexural capacity of 92% of that of a fully composite panel while being more flexible and lighter than conventional concrete sandwich wall panels. The composite UHPC sandwich wall panels have a great potential in architectural and structural applications, such as exterior load-bearing walls and cladding panels. This paper investigates the structural behavior of a new system of sandwich wall panels utilizing reduced wythe thicknesses made of ultrahigh-performance concrete (UHPC) and achieving high degree of composite action. Structural performance and production efficiency of this system can have significant impacts on energy-efficient building construction. This new system can achieve a degree of composite action up to 92%, which makes the design efficient for large cladding panels and load bearing exterior walls. A design example is presented comparing a conventional concrete sandwich wall panel made of two 76-mm-thick concrete wythes and 51-mm-thick insulation to a UHPC panel with the same overall thickness of 203 mm but with 32-mm-thick concrete wythes and 140-mm-thick insulation. Both panels are 2.44-m wide and 9.14-m tall and subjected to unfactored wind pressure of 1.44-kPa, which is considerably higher than the typical values used in wall design for midwest states. The significant increase in the insulation thickness of the UHPC panel results in significantly less weight and higher R-value than those of the conventional concrete panel. In addition, the UHPC panel does not have either longitudinal prestressing strands or transverse reinforcing bars, which simplifies panel fabrication. [ABSTRACT FROM AUTHOR]

Limited research has been directed toward coastal protection infrastructure compared to other types of infrastructure, despite the increasing global population in low-elevated coastal regions and the threats posed by climate change. This paper presents a risk-based asset management framework for coastal protection structures that improves accuracy with each inspection. The framework consists of five components: the Coastal Asset Inventory (CAI), Inspection and Condition Assessment (ICA) module, Backward Markovian Deterioration Model (BMDM), Forward Markovian Deterioration Model (FMDM), and Intervention Policy Engine (IPE). The framework addresses challenges in accurately predicting coastal structure deterioration due to uncertainties in wave loading conditions and the need for frequent inspections. It is applied to rubble-mound breakwaters in Alexandria, Egypt. The BMDM and FMDM models are developed based on inspection data, and the IPE optimizes interventions considering structural condition, risk thresholds, and budget constraints. Results showed that long-term deterioration estimates occur at an accelerated rate with an increase in inspection points, triggering earlier interventions. However, the framework proves reliable even with only two inspection points, allowing asset managing agencies to implement the model based on the structural condition at the year of construction and a minimum of two inspections. The proposed risk-based asset management framework provided a comprehensive approach to managing coastal protection infrastructure, reducing risks to life and property. By accurately predicting deterioration and optimizing intervention decisions, the framework can greatly assist in the effective management and maintenance of coastal assets. This is vital in ensuring the safety of coastal populations facing global climate change and demographic growth. Coastal protection structures are crucial for safeguarding coastal populations in the face of climate change and demographic growth. This research paper introduces a risk-based asset management framework for coastal protection structures, with practical applications for coastal management agencies and practitioners. The framework addresses the challenges of predicting coastal structure deterioration and optimizing intervention decisions. The framework consists of five components: the Coastal Asset Inventory (CAI), Inspection and Condition Assessment (ICA), Backward Markovian Deterioration Model (BMDM), Forward Markovian Deterioration Model (FMDM), and Intervention Policy Engine (IPE). It has been successfully applied to rubble-mound breakwaters in Alexandria, Egypt. The practical implications are significant: The framework enables asset managers to make informed decisions on coastal infrastructure maintenance and interventions, reducing risks to life and property. It provides a comprehensive approach to managing coastal protection infrastructure and ensuring the safety of coastal populations. By accurately predicting deterioration and optimizing interventions, the framework supports effective management and maintenance of coastal assets. Its reliability and flexibility make it a valuable tool for coastal management practitioners, promoting sustainable development and safeguarding coastal areas. With its potential for broader application, this risk-based asset management framework offers practical solutions for coastal protection worldwide. [ABSTRACT FROM AUTHOR]

To solve the problem where the prediction formula for vibration velocity by dynamic compaction cannot fully reflect the elevation amplification effect, the elevation amplification effect of vibration velocity by dynamic compaction was studied theoretically, and the factors that influence the elevation amplification effect of vibration velocity by dynamic compaction were systematically analyzed in this paper. The elevation amplification effect of a loess high slope under dynamic compaction is coformed by the refraction and reflection superposition effect of dynamic compaction vibration waves at the soil layer interface and the diffraction effect of dynamic compaction vibration waves. The propagation path of dynamic compaction vibration waves in soil was analyzed, and the elevation amplification effect was verified theoretically. The related physical quantities that affected the dynamic compaction vibration velocity of a loess high slope were analyzed based on the dimensional analysis method, and the calculation and improved calculation formulas that considered the elevation amplification effect of dynamic compaction vibration velocity were obtained. The multiple regression analysis of the calculation and improved calculation formula that considered the elevation amplification effect of the dynamic compaction vibration velocity was carried out using MATLAB with engineering examples. The results show that the relative error of the two formulas is small when the elevation difference is small; when the elevation difference is large, the calculation accuracy of the improved calculation formula that considered the elevation difference is higher, and it is more in line with the actual situation. Finally, according to the selected maximum allowable value of the slope particle velocity (e.g., 1.5, 2.0, and 2.5 cm/s), the allowable safe distance for dynamic compaction on a loess high slope is proposed area of northern Shaanxi Province, China. The results of this paper could provide a reliable basis for predicting vibration velocity by dynamic compaction in the Loess Plateau area of northern Shaanxi Province, China. They might have a reference value for dynamic compaction vibration control under similar terrain environments with large elevation differences and provide a safe guide for a dynamic compaction construction site in the Loess Plateau area of northern Shaanxi Province, China. [ABSTRACT FROM AUTHOR]

This study focuses on the area of large deformation of soft rocks across the fault in Dongmachang China to investigate support methods for fractured surrounding rocks Negative Poisson's Ratio (NPR) anchor cable support. The research employs field monitoring, 3D physical model experiments, and numerical simulations. The results show that: (1) the maximum settlement displacement of the Dongmachang Tunnel section with original support can reach about 476 mm and has an upward trend, the limit of initial branch intrusion is 41.2 cm, and the width of invert joint is 5–50 mm; (2) the dynamic impact experiment of NPR anchor cable shows that the NPR anchor can withstand several impacts, the maximum cumulative impact deformation within the range of constant resistance is 500–1,000 mm, and the impact resistance is strong; and (3) NPR anchor cable can effectively control the large deformation disaster of surrounding rock in the fault fracture zone of Dongmachang Tunnel, basically ensuring that the deformation of the surrounding rock is below 300 mm, and the control effect is good. These findings suggest that NPR anchor cables are effective for controlling large deformations in tunnels constructed through soft rock across faults and provide a scientific basis for implementing new support systems for other similar tunnels. At present, the international support of deep-buried underground engineering still takes the new Austrian method as the mainstream, but the core idea of the new Austrian method is passive support, which often cannot effectively support the deep-buried soft rock with high stress and large deformation. This paper takes the anchor cable with high preload (350 kN) as the core and the excavation compensation method proposed by Academician He Manchao as the starting point, and innovatively supports the deep-buried soft rock large deformation tunnel, which provides a new idea for the support of other deep-buried underground projects. Although this paper studies the support effect of negative Poisson's ratio (NPR) cable compensation mechanics from the perspectives of laboratory test, physical model experiment, and numerical simulation, because the tunnel has not yet been started, it has not been studied from the perspective of field application. The support effect of NPR anchor cables on surrounding rock in the fracture zone needs further study. [ABSTRACT FROM AUTHOR]

In the twenty-first century, with the development of urbanization, large-scale mine wastelands in peri-urban areas have become increasingly closely related to the daily lives of urban and rural residents. Adopting a reuse method that meets the health needs of these residents, restoration, construction of mine wastelands in the suburbs of cities, and the formation of high-quality healthy environments and service supply are in line with the demands of healthy city construction and sustainable development. In addition, they have received increasing attention from all sectors of society. Based on the main criteria for constructing a healthy urban environment, this paper takes the comprehensive remediation and construction project of mine wastelands in the Taiyuan Xishan Ecological and Cultural Tourism Demonstration Area as a case study. It uses on-site surveys and an open-ended web-based questionnaire. It focuses on researching the perceived health needs of urban and rural residents in Taiyuan City, Shanxi Province, China concerning the main elements that determine health, such as the natural ecological environment, the construction of facilities and activities, and the local economic and industrial development. The results of 748 questionnaires that were completed by participants who effectively participated in the survey show that most participants preferred a comprehensive development model (86.6%) to reuse these areas. In addition, the specific needs of urban and rural residents for health safety, equity and quality, and healthy low-carbon industries should be considered. The differences in demand among groups of citizens due to different ages, living distances, levels of education, and occupations should be comprehensively considered. This paper demonstrates that a full understanding of the health needs of residents has great practical significance when improving the healthy environment and service supply level in mine wasteland restoration and construction and promoting the development of regional healthy city construction. Recently, the healthy environment and sustainable development of areas that host large-scale mine wastelands on the outskirts of cities have received increasing attention from all sectors of society. This paper suggests that during the reuse and construction of these areas, government management, development, and construction companies, planning and design organizations, and other departments that are involved in policy formulation and construction implementation should give full consideration to the perceived health needs of urban and rural residents in the host city, and to groups of residents of different ages, living distances, occupations, and educational levels, to form a high-quality and equitable health environment and services in the area. In addition, active public participation, on-site research, and interviews are essential for relevant departments to improve their understanding of resident health needs. [ABSTRACT FROM AUTHOR]

Industrialization and urbanization are significant facets of modernization. The asynchronous development of the two is closely related to the agglomeration of producer services. This paper constructed an asynchrony index to describe the development gap between industrialization and urbanization. Various spatial weight matrices were introduced to test the spatial autocorrelation of the asynchrony index. Applying spatial econometric models, we explored the impact of agglomeration of producer services on the asynchrony index from two aspects: diversified agglomeration (DA) and specialized agglomeration (SA). The following conclusions are drawn from the empirical findings, which are based on data from 31 Chinese provinces between 2008 and 2019: (1) the asynchrony of industrialization and urbanization exhibits the spatial autocorrelation increasing over time; (2) SA exacerbates the asynchrony, while DA alleviates the asynchrony; (3) SA exerts greater impacts in highly industrialized and urbanized regions, while DA exerts greater effects in lowly industrialized and urbanized regions; and (4) agricultural dependence and infrastructure level weaken the impacts of SA and strengthen the impacts of DA. Income level weakens the impacts of both SA and DA. The results of this study provide a reference for policymakers to adjust the industrial layout in a targeted manner to regulate the asynchronous nature of modernization development. Peace and development are the themes of the world today. Most developing countries are experiencing or about to experience industrialization and urbanization. The world reality indicates that the two are not always synchronized in countries due to resource and cultural differences. Producer services not only improve agricultural and industrial production efficiency but also bring population agglomeration effects like other industries. In the era of informatization, the producer services exert a profound impact on industrialization and urbanization through two agglomeration modes. This technical paper quantifies the asynchrony between industrialization and urbanization using data from 31 provinces in China and verifies the opposite effects of two agglomeration modes on asynchrony. In cities with different levels of industrialization and urbanization, cities with higher or lower agricultural dependence, and cities with higher or lower infrastructure levels, the impact direction of the two agglomeration modes shows stability, while the magnitude varies. Cities with higher per capita income tend to develop into consumer cities, where industrialization should lag behind urbanization. [ABSTRACT FROM AUTHOR]

With the rapid development of high-speed railways (HSR) in China, the level of travel accessibility for residents has improved. While previous research has predominantly concentrated on the accessibility of HSR networks, it is imperative to recognize that the accessibility of HSR services is intrinsically intertwined with the spatial arrangement of HSR stations. The unreasonable location of HSR stations can lead to inequitable problems in service facilities within metropolitan areas. When investigating the accessibility of HSR stations, the road network emerges as the primary conduit for residents' mobility. The spatial variance of the road network manifests not only in divergent spatial densities but also in the traffic conditions across distinct temporal and spatial intervals. Based on the road network and dynamic road conditions, this study proposed a modified two-step floating catchment area method (M2SFCA) by using high-speed railway station location data, the subdistrict office (village and town) data, road network data, and floating car data (FCD). Taking the XZQ Metropolitan Core Area (the metropolitan core area of Xiamen, Zhangzhou, and Quanzhou, China) as an example, this paper analyzed the impact of a newly planned HSR station on the spatial distribution of accessibility in the metropolitan core area. The findings revealed that the newly planned HSR station has led to a substantial 68.18% elevation in overall regional accessibility. Notably, approximately 35% of the population has transitioned from locales with diminished accessibility to regions with heightened accessibility. Furthermore, the HSR station has ameliorated the hitherto uneven spatial distribution of accessibility advantages across the region. Under the limitation of travel time in metropolitan areas, this study explored an accessibility evaluation model based on dynamic traffic data, providing a method for an impartial and equitable evaluation of transportation infrastructure placement within the metropolitan core area. This study shows that the new high-speed railway station will not only improve regional accessibility but also affect the equilibrium degree of the spatial distribution of regional accessibility benefits. It is suggested that the metropolitan area should further build high-grade roads, strengthen transportation network links between urban areas, and improve regional accessibility. At the same time, for areas where the degree of accessibility fairness has declined, it is suggested to increase the energy level and scale of their high-speed railway stations to reduce the dependence of local residents on external high-speed railway stations and improve the convenience of local residents' travel. In addition, this paper improves the accessibility measurement method—2SFCA method. By improving the search carrier of the spatial action domain, the calculation method of road traffic state, and the selection of time threshold, the improved 2SFCA method is more in line with the actual situation, which expands the dynamic space–time analysis ability, improves the accuracy of accessibility calculation, and can more accurately judge the fairness of high-speed railway station construction. [ABSTRACT FROM AUTHOR]

This paper describes the experimental methods developed to understand the piping erosion of impervious core and its interaction with downstream filters in embankment dams. Concentrated leaks through a dam core-filter system are simulated experimentally in the hole erosion filter test (HEFT). The mass rate of erosion in the base soil, the eroded soils entrapped in the downstream filters, and the eroded soil particles passed through the filters that settled in the test unit and suspended in the effluent were derived throughout the test. An interpretation method of test results and determination of the rate of erosion of the dam core with downstream filters are proposed for which no methods are reported in the current literature. Results of experimental investigations indicated that the mechanism of erosion in a soil-filter system and the rate of erosion are influenced dominantly by the relative particle size distribution of base soils and filters, applied hydraulic gradient, coefficient of soil erosion, and dry density of base soil. For the soils and filters tested, the average erosion rate of a specimen compacted to 88% of the standard maximum dry density of soil compacted at standard optimum moisture content, Mdd, is about 4.1 times that of specimen with 97% Mdd. The average erosion rate for soil with erosion coefficient 1.54×10−5 s·m−1 is about 15.4 times of that for soil with erosion coefficient 3.8×10−6 s·m−1 for the same downstream filter and hydraulic gradient. The average erosion rate for a hydraulic gradient of 27.17 is about 2.2 times that for a hydraulic gradient 18.9 for the same soil and filter tested. Application of the HEFT for assessing the piping risk rating of embankment dams is presented. The practical applications of the HEFT presented in this paper extend to the assessment of the piping risk rating of embankment dams. These findings provide a valuable foundation for improving dam safety protocols and the design and maintenance of embankment dams. By gaining a deeper understanding of the factors influencing piping erosion, dam engineers and geotechnical professionals can make informed decisions to enhance the resilience and safety of embankment dam structures, ultimately minimizing the risks associated with this critical geotechnical issue. [ABSTRACT FROM AUTHOR]

During the last decades, liquefaction damages induced by earthquakes have underlined the importance of identifying effective soil improvement techniques for mitigation purposes. Vibratory methods, such as rammed aggregate piers, are commonly used to densify sands and silty sands, erroneously neglecting the influence of the lateral stress. This paper presents the results of a series of liquefaction mitigation case studies carried out using rammed aggregate piers in Christchurch (New Zealand), Boca de Briceño (Ecuador), and Bondeno (Italy) following the 2010–2011 Canterbury seismic sequence, the 2016 Muisne earthquake, and the 2012 Emilia seismic sequence, respectively. The availability of coupled piezocone and seismic dilatometer tests before and after treatment enabled a geotechnical characterization of the three sandy sites to be made, along with estimating the at-rest lateral earth pressure coefficient, and comparing the effectiveness of the treatment at the trial sites. Finally, the paper proposes an updated procedure for liquefaction assessment that takes into account both the increase in soil density and lateral stress produced by ground improvement. [ABSTRACT FROM AUTHOR]

Flood bypasses are used in regional flood management to reduce flood risk and damage by routing substantial flood flows to a supplementary river channel to lower flood stages in the usual river mainstem. Design, operations, and modifications to flood bypasses commonly employ hydraulic analysis and evaluation. Economics of flood bypasses is usually considered only in terms of feasibility, and bypass design is rarely optimized economically. The literature lacks formal integration of economics, engineering, and hydrology for flood bypasses. Economically analyzed flood bypass systems better incorporate bypasses into flood management, reflecting and balancing the range of costs, impacts, and opportunities of bypasses. This paper presents a method to integrate economics, hydrology, and engineering for flood bypass planning. An economic optimization model is developed based on a cost–benefit analysis. The optimization suggests and explores a preferred economic flood bypass capacity. A preliminary analysis is developed, with a base case that includes benefits from flood risk reduction only. Costs include for a levee setback, weir widening, and land use. The optimization model is applied preliminarily to California's Yolo Bypass. With the simplification of unlimited land availability, the model results suggest an optimal Yolo Bypass capacity expansion of approximately 5,800 m3/s. The expansion suggested is close to the Department of Water Resources (DWR) stated objective in their 2017 Central Valley Flood Protection Plan and part of the Basin-Wide Feasibility Studies Sacramento River Basin, part of the Central Valley Flood Management Program of 2017. The model is also applied to the Mississippi River Basin's, New Madrid Birds Point Bypass and Morganza Floodway. In all cases, actual and theoretically optimal bypass capacities agree in their general behavior. This paper provides a framework for decision analysis. This method can better inform policymakers and stakeholders on bypass design and structural modifications and long-term flood management strategy. [ABSTRACT FROM AUTHOR]

In the context of the Internet of Things, there is a growing demand for real-time monitoring of water distribution systems (WDS). Among the various leak detection methods, acoustic leak detection is considered to be a suitable method. However, existing methods are not very effective in environments with high daytime ambient noise. To address this issue, this paper conducted on-site data collection experiments and designed a monitoring system that combines traditional nighttime monitoring with daytime monitoring, combining water company pipeline inspections and repair work. A large number of daytime audio samples were collected. In this paper, the logarithmic spectrogram (log spectrogram) was used to represent the features of the leak signal. By comparing the features of the signal during day and night, noisy and quiet environments, and leak and normal signals, we identified the interfering frames that required noise reduction, and applied frame-level noise reduction processing to the signal. Based on this, a log PS-ResNet18 model was developed to identify leaks, and its performance was compared with other classification models [including traditional nighttime detection methods, random forests, XGBoost, and convolutional neural network (CNN)]. The results showed that the log PS-ResNet18 model had the best performance, with an all-day accuracy rate of 99.4% and a daytime accuracy rate of 99.3%. In addition, by conducting ablation experiments to explore the role and contribution of the log PS-ResNet18 and noise reduction methods in the model, the results showed that the log spectrogram and noise reduction methods increased the all-day accuracy rate by 18.8% and 23.2%, respectively, and by 24.7% when used together. In another practical application, the log PS-ResNet18 model achieved an all-day detection accuracy rate of 99.6%. This study demonstrated the applicability of the log spectrogram and CNN combination in daytime leak detection, overcoming research limitations in the field. This research presents the log PS-ResNet18 framework, which combines deep learning models and denoised logarithmic spectrograms to improve leak detection in water supply pipelines under daytime environmental noise. The research focuses on field data collection and analysis of cast iron pipes with different diameters in Hangzhou (HZ). The model was tested on cast iron pipes in Lishui (LS) and proved to be effective. The proposed method is highly versatile and can be applied to different regions and pipe materials after sufficient sample collection and model training validation. The research recommends a comprehensive leak monitoring solution that involves initial intelligent detection using front-end noise meters and secondary identification of suspicious audio signals using the log PS-ResNet18 model in the cloud. This enables water utility operators to respond quickly to pipeline leaks, leading to more efficient water resource conservation and improved water supply service quality. [ABSTRACT FROM AUTHOR]

Cost estimating in the construction industry is challenging due to the high uncertainty associated with the supply chain, especially after the COVID-19 pandemic. Some research studies have addressed such problems by developing models that predict material cost. In fact, all material can be interconnected and interrelated with lead-lag relationships such that any inflation in one material's price can be associated with inflation in other materials' prices, referred to as transmission of inflation. Despite the latter, none of the existing studies have investigated inflation transmission among all construction materials. This paper fills this knowledge gap. The authors used a multistep research methodology. First, Producer Price Index (PPI) data for 16 construction materials were collected and sorted. Second, the vector autoregression technique was used to model the relationships between each pair of material and subsequently validate the associations using the Granger causality test. Third, network analysis was performed to identify the inflation transmission capacity (out-degree centrality), inflation susceptibility (in-degree centrality), and inflation intermediatory capacity (betweenness centrality) for each material. Finally, modularity-based clustering was conducted to categorize the materials based on their price indices' interconnections and examine inflation transmission path among different sectors of construction-related material. The results show that metals and plastic products are generally the highest transmitters of inflation to other construction material including "Fabricated structural metal products" and "Plastic construction products." Furthermore, the results show that "Concrete products," "Flat glass," "Brick and structural clay tile," and "Architectural coatings" are also high transmitters of inflation and thus can be key indicators of increase in the overall construction cost. This paper provides the industry stakeholders with leading indicators and early warning signs for the inflated material prices. Contractors and owners can utilize those warning signs to enhance their procurement plans and budgeting decisions. [ABSTRACT FROM AUTHOR]

The construction is one of the key contributing sectors in the U.S. economy. For operational purposes, the construction sector uses inputs from other producing sectors. That dependence makes the construction sector vulnerable to shocks in other sectors. This paper has quantified that vulnerability measured in terms of the annual percentage production loss due to shocks in other sectors. As such, this paper has collected 25 years of historical data from the U.S. Bureau of Economic Analysis and used them in an input–output model to derive the intersectoral relationships, which were further used to calculate the impact of exogenous shocks on the construction sector. It has been found that a 1% annual production loss in the (1) finance, insurance, real estate, rental, and leasing sector; (2) government sector; and (3) manufacturing sector will cause an annual production loss of 0.16%, 0.11%, and 0.05% in the construction sector, respectively. These three sectors exert the most significant influence on the construction sector's annual production. The outcomes of this paper can also be used to measure the cumulative impact of multiple exogenous shocks originating in different sectors, which could ultimately help to make the U.S. construction sector resilient to external shocks. [ABSTRACT FROM AUTHOR]

Despite the critical role of boards and their significant interest in Diversity, Equity, and Inclusion, there is a scarcity of studies on board diversity within the architecture, engineering, and construction (AEC) industry. This paper aims to investigate board gender diversity in the AEC industry and provide a comprehensive overview of its progression over time, comparing it with non-AEC industry. The findings reveal that, on average, the AEC industry exhibits lower board gender diversity compared with non-AEC industry, although the gap between the two industries has significantly narrowed over time. The professional characteristics of female directors suggest that board gender diversity in the AEC industry seems to not yet fully embrace an inclusive and equitable work environment. Notably, female directors in the AEC industry have a shorter tenure, hold a higher number of outside board positions, display a relatively worse board meeting attendance rate, and tend to concentrate on professional positions related to finance, in comparison with male directors in the same industry or female directors in non-AEC industry. This paper contributes to the literature by shedding light on the specific dynamics and challenges related to board gender diversity in the AEC industry using comprehensive and up-to-date data. Diversity, equity, and inclusion (DEI) is a hot topic everywhere, and the AEC industry is no exception. Due to its reputation as a male-dominated field, DEI issues within the AEC industry have garnered more attention than other industries. Yet, a notable gap in understanding persists. Board diversity, particularly in the AEC context, remains relatively unexplored compared with worker and top management diversity. This study provides a fresh perspective on board gender diversity, an aspect of board diversity, utilizing comprehensive and current US. AEC industry data. The findings hint at a narrower quantitative gender diversity discrepancy between the AEC and non-AEC industries. Nevertheless, qualitatively, it appears that female directors within the AEC sector may not experience a fully inclusive and equitable work environment. This implies that although AEC firms outwardly significantly improved board gender diversity, they might not fully embrace equity and inclusion on their boards. These findings align with the idea that recent improvements in board gender diversity could be influenced by external factors, such as evolving societal perceptions and legislative actions. However, the AEC firms might struggle to tackle deep-rooted challenges, thereby limiting the realization of the complete benefits of authentic board diversity. [ABSTRACT FROM AUTHOR]

A pipeline is critical in conveying water, oil, gas, petrochemicals, and slurry. As the pipeline ages and corrodes, it becomes susceptible to deterioration, resulting in wastage and hazardous damages depending on the material it transports. To mitigate these risks, implementing a suitable monitoring system becomes essential, enabling the early identification of damage and minimizing waste and the potential for hazardous incidents. The pipeline monitoring system can be exterior, visual/biological, and computational. This paper surveys state-of-the-art approaches and also performs experimental analyses with a few methods in signal/data-driven approaches within computational methods. More precisely, signal processing-based leak localization methods, artificial intelligence-based leak detection methods, and combined approaches are given. This paper implements five signal processing-based methods and 17 artificial intelligence-based methods. This implementation helps to compare and understand the significance of appropriate noise removal and feature extraction. The data for this analysis is collected using acousto-optic sensors from an experimental setup. After implementation, the highest observed leak localization accuracy is 99.14% with the wavelet packet adaptive independent component analysis-based generalized cross correlation, and the highest leak detection accuracy is 98.32% with the one-dimensional convolutional neural network. [ABSTRACT FROM AUTHOR]

This paper studies the design of foundations built on thick compressible soft soil layers that are reinforced by floating columns. Based on a recent methodology, the suggested design combines the bearing capacity and settlement verifications to provide an optimized improvement area ratio (IAR). Then, an optimized length for the floating columns is obtained by introducing the admissible long-term settlement of the unreinforced compressible sublayers and assuming that the total short-term settlement vanishes at the end of project construction. This paper focuses on the variation in the consolidation settlement of the unreinforced compressible sublayer versus the length of the floating columns. The discussion of this design methodology highlights the feasibility of a potential reinforcement solution when producing a cost-effective design, which assures an optimized IAR within the reinforced upper layer and an optimized length for the floating columns. Using typical case history data, a parametric study showed that reinforcement with end-bearing columns is not required to control the admissible long-term settlement. Instead, the suggested design method enables the determination of the optimized length of the floating columns, which satisfies the admissible residual settlement and consolidation time. The comparison between the proposed results and numerical predictions by Plaxis 2D shows good agreement, which confirms the feasibility of an optimized length for floating columns and avoids the systematic adoption of end-bearing reinforcement in columns. [ABSTRACT FROM AUTHOR]

Understanding the moisture migration of unsaturated soil in response to temperature changes is essential in soil science and geosystems applications. The coupling of thermohydro (TH) processes is a result of changes in fluid density and viscosity; however, gravity can disrupt the moisture migration of unsaturated sand initiated by a thermal gradient when the sand is considerably porous. Moreover, the moisture redistribution caused by the gravity effect is influenced by the imposed boundary temperature and initial moisture content of the unsaturated sand. Therefore, this paper presents heating tests performed on sand specimens of different gradations and subjected to various thermal gradients in a modified and well-controlled soil testing cell to evaluate the coupling behavior of TH processes in unsaturated sand. Two sands were tested in the soil testing cell, which was equipped with thermocouples (TCs) to measure the temperature and time-domain reflectometry (TDR) sensors to measure the apparent dielectric constant (Ka); three temperature boundary conditions were imposed on the soil testing cell to create two thermal gradients. This study shows that gravity, thermal boundary conditions, initial moisture content, and matric suction influence the migration of moisture: the silty sand, as compared with pure sand, more properly displayed the phenomenon of coupled TH processes in unsaturated soil when tested at a temperature gradient of 200°C/m and initial moisture content of 6%. The study provides an advanced understanding of the paired migration of heat and moisture in porous media under various conditions, including thermal gradient, initial moisture content, and gradation. When unsaturated soils are under a temperature gradient, the pore water tends to move from the heat source to a cooler end in search of moisture equilibrium. Temperature-driven moisture flow is commonly investigated in soil science, agriculture, and geosystems. For example, the soil surrounding a geosystem (electrical cables and ground heat exchangers) experiences heating and cooling cycles when heat energy is exchanged from buildings to the soil via the geosystem. This heat exchange can effectively cool the buildings in the summer and heat the buildings in the winter. To maintain effective heat transfer in the soil, it is necessary to investigate the temperature-driven moisture flow, as it has been established that redistributed moisture also significantly impacts heat transport. At the same time, the moisture flow is also influenced by gravity, particularly for coarse sands. Moisture flow in coarse sands is more prone to the effect of gravity than that in fine sands. This paper evaluates how the physical and hydraulic properties of the soil, such as gradation and suction, can affect the coupled thermal and hydraulic processes. The gravitational effect can dominate the moisture redistribution depending on the direction of the temperature gradient. [ABSTRACT FROM AUTHOR]

The study proposes a method for the trajectory tracking control of a fixed-wing unmanned aerial vehicle (UAV) based on the deep deterministic policy gradient (DDPG). First, the problem of controlling the trajectory of a fixed-wing UAV is combined with the reinforcement learning framework and transformed into a Markov decision process, and a DDPG agent is established in the framework of TensorFlow. Second, we conducted simulations to train and optimize the model in a 3D environment of trajectory tracking control and obtained an integrated DDPG-based trajectory tracking controller that can regulate functions ranging from the state of flight of the UAV to rudder control. Third, we constructed a digital simulation system to verify the proposed method while considering the influence of parametric uncertainties, measurement-induced noise, and delays in the response of the control system. The effectiveness and robustness of the proposed DDPG controller were verified by comparing its performance with that of traditional proportional-integral-derivative (PID) control. Unmanned aerial vehicles have gained widespread use across numerous sectors of society. However, the control process for fixed-wing UAVs is more intricate and challenging than that for rotor type UAVs due to the coupled and nonlinear nature of their dynamic models. To address this issue, decoupling and splitting hierarchical control methods are commonly employed. However, these methods can introduce errors and affect flight performance. In contrast, artificial intelligence, particularly deep learning and reinforcement learning, has made significant advancements and found successful applications in areas such as robot control and gaming. To address the challenges posed by complex forms, excessive measurement information, and manual parameter tuning associated with traditional control approaches for fixed-wing UAVs, this paper introduces a deep reinforcement learning algorithm, i.e., the deep deterministic policy gradient, into the control process of fixed-wing UAVs. The paper presents a trajectory tracking control policy for UAVs, which efficiently achieves the task of tracking a desired trajectory without the need for selecting multiple working state nodes or designing linear control laws. Further, through simulation verification, the proposed policy demonstrates adaptability to interference caused by parameter bias, measurement noise, and control system response delays while achieving control accuracy comparable with classical control methods. [ABSTRACT FROM AUTHOR]

Fault detection is an important part of aeroengine health management. Intelligent fault detection methods represented by machine learning have been widely studied. However, most studies assume that training and test data follow the same distribution, which is unrealistic. Due to the degradation of engine performance or change of engine operating environment, the historical operation data of aeroengines are different from the current operation data of the engine. If the engine history operation data are directly used to train a fault detection model, the fault detection of the current engine may lead to low efficiency and affect the reliability of fault detection. In order to overcome this problem, transfer learning is introduced into aircraft engine fault detection in this paper. This paper combines transfer learning with support vector data description (SVDD), a common fault detection algorithm, and proposes SVDD-based transfer learning (SVDD-TL). This algorithm takes the spherical center of the SVDD as the knowledge structure to transfer from the source domain to the target domain, which can improve the detection accuracy of the model in the target domain. A fault detection experiment for an aeroengine was designed. Single and mixed fault data were used in the experiment, and the variation of fault data quantity was considered. Experimental results showed that the proposed method can improve the fault detection accuracy of the model in the target domain and still have good detection performance when the amount of fault data changes. [ABSTRACT FROM AUTHOR]

This paper aims to study the influence of novel macro encapsulated phase change materials (PCMs) on the mechanical and thermal properties of concretes. Thermal energy storage aggregates (TESAs) were prepared using vacuum impregnation. The PCMs were a lauric-myristic acid (LA-MA) eutectic mixture and coconut oil, pure or mixed, and are impregnated in diatomite as a supporting material. Thermal energy storage concrete (TESC) was made by replacing gravel in ordinary concrete with TESAs. Thermal and mechanical properties of prepared TESC were studied using differential scanning calorimetry, thermogravimetric analysis, Fourier transform infrared spectroscopy, compressive strength, and thermal performance analysis. The results showed that the melting temperature of coconut oil and the eutectic mixture of LA-MA were 25.2°C and 34.5°C, respectively. TESC with 80 wt.% of gravel replaced with TESA had a compressive strength of higher than 17 MPa, which indicates its usability as structural concrete. The results of thermal performance analysis also revealed that prepared TESC had the capability of storing thermal energy and can reduce energy consumption by damping temperature fluctuations caused by the outside environment. In this paper, a thermal energy storage concrete (TESC) was prepared by embedding phase change materials (PCMs) in diatomite used in TESC. Using this type of concrete in the building will reduce the energy consumption of the building and increase its thermal comfort. The produced concrete containing 80 wt.% of gravel replaced with diatomite saturated with PCM had a desirable 28-day cylindrical sample strength of 21 MPa. In the designed thermal test, the time required for this concrete to reach 40°C is almost twice that of concrete without PCM. The results show a reduction of the influence of outside temperature on the temperature inside the buildings made with this type of concrete. [ABSTRACT FROM AUTHOR]

One of the greatest challenges faced when using gravity settling is achieving efficient particle removal and retention rates under high inflow rates. This paper proposes a new method for enhancing sedimentation and protecting the settled particle. This is accomplished by placing one layer of the virtual bed above the real bed to divide the water body into hydraulically different upper and lower regions. The normal structure of the newly-proposed virtual bed is a flat plate with many small perforations. When the water flows along the top surface of the virtual bed, it creates two effects: (1) it isolates and protects water in the area below the virtual bed from being disturbed by the fast and turbulent flows above, which enhances sedimentation of the particles in the lower region and protects the sediment which could be eroded; and (2) the vertical vortex generated by the surficial flows passing over the openings helps the nearby suspended particles to enter the quiescent water region below. To assess the performance of the newly-proposed virtual bed, a rectangular settling tank was used to conduct comparison tests of particle removal with three particle size ranges, four inflow rates, five virtual bed structural designs, and multiple experimental conditions. The results clearly showed that, compared with a traditional settling tank (without the virtual bed), the addition of the proposed settling structure notably enhanced the particle settling rate by 10%–15% for the particles tested and experimental conditions assessed. The virtual bed method easily can be applied to various water treatment devices and facilities to enhance the suspended particle removal efficiencies in treatments of storm runoff, wastewater, and many other kinds of water without the need for chemical additions or energy-intensive processes. This paper proposes and tested an innovative method for increasing the removal of suspended particles using a virtual bed. A virtual bed is composed of a plate with numerous holes through it suspended above particle-settling facilities. It enhances particle settling by providing a less disturbed region for settling particles, protecting already-settled particles, and encouraging the suspended particles to move toward the real bed. Laboratory tests in a rectangular tank with different particle sizes and flow rates showed that the virtual bed effectively improved particle removal rates. Various possible virtual bed structure designs are proposed and were examined. The best-performing virtual bed was identified, and possible reasons for its performance were discussed based on hydraulics and physics principles. Experiments with different tank configurations and virtual bed position arrangements were conducted, and based on the experimental results, general suggestions for using the virtual bed in practice more effectively are given. In principle, the proposed virtual bed can be applied to any particle-separation facilities. [ABSTRACT FROM AUTHOR]

Construction competitive bidding has been studied by many researchers; however, their focus was mainly on certain bidding aspects. Thus, despite their value, existing bidding models have limited applicability for various reasons including the noninclusion of some real-life factors that impact bidding-related decisions. As such, there is a need for identifying a comprehensive list of bidding factors that impact construction bidding–related decisions, studying their associations, and identifying understudied factors to direct future research efforts. This paper fills this knowledge gap. First, the authors conducted a systematic selection of 124 construction bidding–related articles published within the past 40 years. Second, the authors identified a list of 43 bidding factors from the contractor's perspective and divided them into four groups (project, bidding environment, economy, and company) based on their characteristics and relevance. Thereafter, the authors implemented cluster analysis and social network analysis (SNA) to quantitatively analyze the level of inclusion, co-occurrence, and interconnectivity among the bidding factors and identify the gaps in the literature. Results of cluster analysis revealed that previous studies focused mainly on company-related factors, while economy-related factors were the least studied. Also, SNA outcomes highlighted that experience in similar project and availability and costs of rental labor/equipment/material are the most studied factors in theoretical discussions, while number of competitors and size of the project are the most investigated factors in developed models. Consequently, this paper identified understudied bidding factors, including company reputation level in the market, bidding method, bidding stages, and contractor's risk attitude. Thus, this paper contributes to the body of knowledge by promoting a comprehensive understanding of bidding-related factors and providing a road map for incorporating critical understudied bidding-related factors. This would minimize redundancies and maximize the effectiveness of future bidding-related research. Ultimately, this should provide better decision-making for all associated stakeholders. [ABSTRACT FROM AUTHOR]

Crane-lift planning is critical but challenging to ensure construction safety and efficiency for the installation of heavy components. It engages a group decision-making process that involves various stakeholders to exchange knowledge of crane capabilities, site characteristics, and operational feasibility. However, conventional planning methods based on drawings, animations, and standalone virtual prototypes are inefficient in enabling collaborative decision-making due to rigid visualization and inflexible interactions among different stakeholders. This paper aims to develop a collaborative heavy lift planning (Co-HeLP) system that engages crane suppliers, site managers, and crane operators in an immersive and shared environment for crane layout optimization and lifting simulation. Specifically, the system incorporates a multiuser networking unit to enable stakeholders to design crane-lift layouts concurrently and synchronize changes in real time for facilitating information-sharing and collaborative planning. In addition, a cross-platform virtual reality (VR) unit is developed to provide stakeholders with role-tailored interactions of crane allocation and first-person operation. Automatic feasibility checking is also formulated to assist stakeholders in appraising jib reach limits and loading capacities more efficiently. The system is demonstrated using a real-life modular building project that involves the installation of multiple bulky modules. To evaluate the system, two groups of industry practitioners from crane suppliers and main contractors conducted heavy lift planning using Co-HeLP, where their responses were collected using questionnaire-based surveys and interviews. Results show that the system is rated highly on automatability (0.77/1), collectiveness (0.81/1), and applicability (0.85/1), with the advantages of full-scale visualization and multirole interactions. This paper opens up new possibilities for stakeholders to jointly manage crane-lift constraints and build consensus on layout plans through a mutually interactive and role-independent shared environment. More broadly, the paper derives a generic multiuser VR mechanism to address fragmented coordination and inefficient knowledge transfer, thereby facilitating collective planning and management in construction. [ABSTRACT FROM AUTHOR]

This paper implements a two-staged ensemble learning model for traffic forecasting, focusing on the interpretability of predictions. The stacking model leverages the advantages of its diverse component learning models. Experiments on high-dimensional and sparse data validate the stacking model's superior predictive accuracy compared to baseline models, including LightGBM and XGBoost. In addition to validating the stacking model's outstanding predictive performance, this paper emphasizes the interpretability of its predictions by proposing an innovative explanation model based on feature contributions. This explanation model addresses the high dimension and sparsity in data prevalent in transportation engineering with its integration of resampling and consensus clustering, offering a scalable, stable, and computationally efficient solution ideal for real-time and large-scale applications. The paper presents theoretical justification, experimental results, and empirical validation of the interpretation model. Extensive experiments demonstrate the model's enhanced stability compared to traditional shapley additive explanations (SHAP) implementations such as kernel SHAP. Investigating trade-offs between stability and computational efficiency of resampling provides insights for optimal configuration choices. This paper contributes to traffic flow prediction with broad applicability in real-time and large-scale traffic management scenarios, underscoring the vital role of ensemble learning and interpretable machine learning in contemporary data-driven decision making processes. [ABSTRACT FROM AUTHOR]

In view of the low identification accuracy of the crack-detection technology of asphalt pavement under the current conditions of complex pavement (subject to strong light, water on the road, debris, and so on), an asphalt pavement crack-detection algorithm based on improved YOLOv5s was proposed by building the data set for asphalt pavement cracks. The first step was to make the following improvements to the original YOLOv5s model according to the characteristics of the asphalt pavement crack data set: The k -means++ algorithm was used to recluster the anchor points of the crack data set, and the initial anchor frame matching the crack characteristics of the asphalt pavement was obtained to replace the default initial anchor frame in the YOLOv5 original model. In the prediction part of the original model, the Convolutional Block Attention Module (CBAM) was added in the order of first channel and then space to improve the detection ability of the model to small cracks. The CIoU_Loss function was used as the regression loss function of the model to replace the GIoU_Loss function in the original model to improve the positioning accuracy of the anchor frame. The second step was to perform an ablation experiment on the improved YOLOv5s model. This would prove that each improvement scheme could increase detection ability without conflict. The final step was to compare the improved YOLOv5s model with various classic target detection models in the data set of this paper: the Crack Forest Data set (CFD), the Crack500 data set, and the Crack200 data set. The results showed that the detection of the improved YOLOv5s model on each data set was better than other target detection models. The mAP@0.5 and mAP@[0.5:0.95] of this model on the data set of this paper were 90.58% and 56.08%, respectively, which were much higher than other target detection models. These findings indicate that the improved YOLOv5s model had better detection under complex pavement conditions and could provide a theoretical basis for the automatic detection of asphalt pavement cracks. [ABSTRACT FROM AUTHOR]

The detection and evaluation of internal corrosion of concrete bridge decks is of critical importance for bridge structure safety. Ground penetrating radar (GPR) is a nondestructive testing technique that has been used widely for corrosion assessment of RC bridge decks. However, the recognition accuracy of traditional automatic data processing methods for blurred hyperbolic features is insufficient, which leads to a decrease in the accuracy of bridge deck corrosion assessment. To address this problem, this paper proposes an automatic rebar picking algorithm based on gradient information and a migration method for bridge deck corrosion assessment with GPR data. This method can be divided into three steps: thresholding processing based on B-scan gradient information, a limited hyperbolic summation-based recognition (LHSR) algorithm, and rebar localization. First, the GPR B-scan is transformed into its gradient image and thresholded to enhance hyperbolic features. The LHSR algorithm then is applied to the binarized gradient B-scan to identify the hyperbolas, locate the rebar, and extract the rebar reflection amplitude. Finally, the corrosion map of the bridge deck is generated based on the rebar position and the rebar reflection amplitude after depth-correction. A case study with GPR data from two tested bridges was employed to validate the feasibility of the proposed method. The results show that the precision and recall of automatic rebar picking by this method for poor-quality GPR data were 91.27% and 93.56%, which are significantly higher than those of the traditional methods. Moreover, the accuracy of the bridge deck corrosion map obtained by the proposed method also is significantly better than that of the traditional methods. It can be concluded that the proposed method can be used for rebar picking and corrosion assessment of RC bridge decks with GPR data. Ground penetrating radar is a nondestructive testing technology that has been used widely for corrosion assessment of concrete bridge decks. However, the traditional automatic processing method of GPR data has insufficient recognition accuracy for blurred features of rebars, resulting in a decrease in the accuracy of bridge deck corrosion assessment. To address this problem, this paper proposes an automatic method that can be used for feature identification and location of rebars. The corrosion map generated by the position and reflection amplitude of rebars could help engineers to conduct corrosion assessment and repair of concrete bridge decks. The feasibility of the proposed method was validated through a case study with GPR data form two actual bridges. Especially for poor-quality GPR data, the accuracy of rebar picking and corrosion maps of this method is significantly higher than that of traditional methods. It can be concluded that the proposed method can be used for rebar positioning and corrosion assessment of concrete bridge decks based on GPR inspection data. [ABSTRACT FROM AUTHOR]

The geometric properties of the pore space govern the electrical and hydraulic properties of soils. Recognizing this commonality, this paper proposes a new approach to determine permeability from high-frequency electromagnetic (HF–EM) measurements on geomaterials undergoing evaporative dewatering. Two materials have been used; (1) kaolin, a reference geomaterial; and (2) a dredged sediment sample from the Port of Brisbane (PoB) reclamation site (Queensland, Australia). Based on a dielectric mixture equation that integrates Archie's parameters, the evolution of formation factors as a functions of porosity have been derived. Several models that are available in the literature have been used to estimate proxies for geometric length scales for pore radii. With knowledge of the formation factors and proxies for pore radii as functions of porosity, permeabilities of the materials under saturated conditions have been estimated. The results have been compared with experimentally obtained permeabilities. Using the formation factors from HF–EM measurements and two of the proxies for pore radii (hydraulic and characteristic pore radii, as defined in this paper), a good degree of agreement with the experimental data has been obtained within a variation in one-order of magnitude for kaolin. For the PoB material, the use of hydraulic pore radius yielded the best estimation of permeability. [ABSTRACT FROM AUTHOR]

This paper aims at proposing a calculation model to deal with the face stability of shield tunnels in unsaturated soil. Based on the existing results of centrifugal test and numerical simulation, a new failure mechanism is proposed, which combines the logarithmic spiral with upper loosening arch mechanisms. The failure mechanism considers the influence of the soil arching effect and the logarithmic spiral height coefficient. Formulas for calculating the loosening earth pressure of unsaturated soil are deduced. Subsequently, this model of loosening earth pressure is introduced into an analytical model to compute the limit support pressure on the tunnel face. Compared with other height coefficients and the degree of soil arching effect, when the height coefficient is 0.95 and the degree of soil arching effect is 10%–30%, the limit support pressure proposed in this paper is in good agreement with the centrifugal test results. Finally, comparisons are performed with the proposed model and classical models as well as typical centrifuge model tests. The comparative analysis shows that the proposed theoretical model is in good agreement with the numerical simulation. The outline of the failure zone by the theoretical model in this paper is in good agreement with the centrifuge results. [ABSTRACT FROM AUTHOR]

This document discusses a research paper on the discharge coefficient of Type-A piano key weirs. The discussers appreciate the authors' efforts but suggest further analysis for one equation in the original paper. They conducted simulations and analysis, providing graphs and tables to support their findings. The document also includes a sensitivity analysis of input parameters affecting the discharge coefficient, showing the varying effects of different parameters. The study provides insights into estimating the discharge coefficient and was supported by funding from the Water Resources Department of Jiangxi Province and the Natural Science Foundation of Jiangxi Province in China. [Extracted from the article]

Pile installation leads to significant changes in soil state (i.e., void ratio and effective stress) around the pile, which affects stiffness and bearing capacity. Currently, the driveability of piles is analyzed using empirical methods, and the ultimate bearing capacity is estimated without considering the installation effects. This paper presents simulations of the entire installation and subsequent axial bearing capacity of a close-ended pile using a single numerical tool based on the material point method (MPM). A lab-scale experiment is used as a validation case, where the pile is first impact-driven in dry sand, with different initial relative densities (from loose to very dense), and then axially loaded. A state-dependent constitutive model (DeltaSand) is used in the numerical simulations to predict the mechanical behavior of the sand at different relative densities with a single set of input parameters. The paper also illustrates several enhancements needed to obtain more accurate results: (1) an improved contact algorithm that allows gap closure; (2) a rigid-body formulation for the pile body; and (3) a general analytical solution for calculation of energy-consistent impact forces in uncoupled hammer-pile systems. [ABSTRACT FROM AUTHOR]

This paper presents a new discretize-then-optimize (DTO) method for dynamic force inversion in a two-dimensional (2D) linear elastic, damped solid based on Runge–Kutta (RK) explicit time integration. Previous literature on DTO modeling for force or material inversion has predominantly focused on inversion methods based on Newmark implicit time integration. However, because implicit time integration may not be suitable for a problem with a large number of degrees of freedom [e.g., third-dimensional (3D) wave problems], there is a need to study an alternative DTO force-inversion formulation that centers around the RK explicit time integration, leveraged by a diagonal mass matrix. This paper attempts to fill this gap and present the full detail of the new RK-DTO formulation for dynamic force inversion. Our computational examples demonstrate that the new RK-DTO inversion simulator effectively reconstructs moving dynamic forces on the upper surface of the solid. It excels in efficiency when dealing with a higher number of degrees of freedom (DOFs) and maintains accuracy even with increased DOFs and observation durations. A smaller sensor spacing enhances the accuracy of the inverted force profile in the RK-based inversion. The presented inversion method can effectively identify the profiles of dynamic moving loads even when measurement data include noise or when the values of material properties are not deterministic. [ABSTRACT FROM AUTHOR]

Modeling the pipe failure phenomenon is essential for any water utility. The linear extension of the Yule process (LEYP), proposed in 2009, was intended to be a synthesis of the pipe failure models available at the time. Since then, two major improvements have been proposed. First, in 2012 and 2014, several papers introduced time-dependent factors into the LEYP model. Second, in 2016, the LEYP with Selective Survival (LEYP2s) was proposed to deal with the selective survival bias. The objectives of this paper were (1) from a theoretical point of view, to show how temporal covariates also can be introduced into the LEYP2s model; and (2) from a practical point of view, to prove the feasibility and interest of a LEYP2s model with time-dependent variables, using a case study. The mathematical consequences of taking into account temporal factors within the LEYP2s model are presented, together with the solutions found that allow the calculation of the model likelihood and thus the estimation of the model parameters. These solutions were applied to the black polyethylene service line network of the city of Bordeaux, France. Three time-dependent covariates were considered: air temperature, pressure regime, and type of disinfectant. This case study proved the feasibility of a LEYP2s model with temporal variables. The results showed that the time-dependent factors considered did not improve the ranking of the service lines, but did improve the annual prediction of the network failure rate. [ABSTRACT FROM AUTHOR]

The localization of sources of pressure transients is essential for proactively managing and reducing the adverse effects of these transients in water supply networks (WSNs). This paper addresses the issue of localizing transient sources in a WSN where there is uncertainty about the network connectivity. If closed valves or blockages in the pipes are not accounted for, it can result in inaccurate knowledge of the network connectivity, leading to incorrect estimations about the sources of pressure transients. The problem is challenging due to the added uncertainties in estimating the velocity of pressure waves and determining their arrival times at pressure monitoring sites. In order to systematically investigate this problem, the paper presents a novel theoretical framework for localizing the source of pressure transients in WSNs with uncertain connectivity. The problem is formulated as a mixed-integer quadratic program, which consists of minimizing the difference between analytical and measured pressure wave arrival times for multiple pairs of time-synchronized sensors. Unlike previous approaches, the k-shortest path (with respect to time) routing problem is incorporated into the problem formulation to account for multiple potential wave propagation paths. The optimization problem is then solved using an off-the-shelf solver, and a methodology is developed to ensure the reliability of the optimization approach. We apply the proposed methodology to numerically simulated pressure transient data for a benchmark WSN and compare it against a previously published method. The results show a notable improvement in accurately localizing the source of a transient in the presence of unknown closed valves or pipe blockages. Provided pressure wave speeds are predetermined, the proposed methodology is able to simultaneously localize the source of a pressure transient and validate the assumed hydraulic connectivity of a WSN. In this way, any irregularities or uncertainties in network connectivity can also be periodically detected and validated. [ABSTRACT FROM AUTHOR]

This document is a discussion of the original paper titled "Coastal Defense Megaprojects in an Era of Sea-Level Rise: Politically Feasible Strategies or Army Corps Fantasies?" by D. J. Rasmussen, Robert E. Kopp, and Michael Oppenheimer. The authors review coastal defense megaprojects with storm surge barriers in the United States and discuss their feasibility. They compare the findings of the original paper with experiences from the implementation of coastal megaprojects in the Netherlands and identify key factors crucial for their feasibility and realization. The document concludes that coastal megaprojects with barriers are feasible and will be needed for future coastal protection and adaptation. [Extracted from the article]

The Le Chatelier-Anstett test was used to study the sulfate resistance of cement pastes containing calcined paper sludge waste (MC). MC was blended with two types of portland cement (PC): P1 with and P2 without C3A (ordinary portland cement, OPC, and sulfateresistant portland cement, SRPC, respectively). The study of thaumasite formation required the utilization of a third PC, P3. The results showed that sulfate resistance always decreased at higher ratios of PC replacement by MC. This behavior was attributable to the expansive synergic effect (ESE), originated by the coprecipitation of ettringite from two resources in a gypsum and water medium. Part of the ettringite formed rapidly from the Al2O3r- in MC, and rapidly or slowly from the C3A in P1, depending on whether its early pozzolanic activity was sufficient or not. Rapid-forming ettringite of both origins was induced by the sufficient specific, fast, and early pozzolanic activity resulting in the indirect stimulation of sulfate-mediated P1 hydration (its C3A content especially) by the metakaolin present in the MC. Where such activity was insufficient, however, slow-forming ettringite was generated, reducing the ESE. The substantial calcite content in MC also played a very significant role in ESE, the result of the stimulation of such hydration, concomitant sulfate attack, and thaumasite formation. Stimulation was both direct (due to initial particle moistening by the mixing water) and nondirect (due, at the very outset, to the positive and negative electrostatic charge acquired by their particles during grinding and/or mixing, and subsequently, to the zeta potential originated as PC hydration progressed). Lastly, calcite (natural or synthesized in portlandite carbonation) was shown to be needed for thaumasite to form, a process not confined solely to low-temperature environments. [ABSTRACT FROM AUTHOR]

The paper recycling process generates a sludge characterized by a high content of cellulose fiber. To understand the behavior of this fibrous material, this article presents an interpretation of the geotechnical behavior of a waste sludge from a paper recycling plant situated in southern Brazil using data from laboratory tests. Engineering properties of compacted paper mill sludges are similar to those of most fibrous organic soils: low hydraulic conductivity upon compression and high compressibility. The waste studied has a water content of approximately 250%, organic content of 48%, mineral charges, and water. The one-dimensional compressibility parameters are indicative of high compressibility. For the determination of the strength parameters of the material, undrained triaxial tests were carried out. An incredibly high effective friction angle ([lowercase_phi_synonym]′=53°) was found, probably because of the fibrous nature of the paper sludge. In addition, hydraulic conductivity tests were performed on a flexible wall permeameter. The hydraulic conductivity of the fibrous paper sludge reached values near10-9 m/s. The results showed that the paper mill sludge is a ductile material with reduced hydraulic conductivity and elevated shear strength that could have multiple applications, such as in the construction of bottom liners, cover liners, and steep side-slope liners for solid-waste landfills. [ABSTRACT FROM AUTHOR]

Paper mill sludge is often incinerated for heat recovery and volume reduction. In Italy, about 600,000 t of paper mill sludge is produced yearly. About 6 kg of sludge is produced per ton of paper produced. The paper mill sludge is recovered from a primary mechanical separation process. When it is combusted as a single fuel source, it produces paper mill sludge ash (PA). In this project, PA was studied to evaluate its use as a supplementary cementitious material in mortars and concrete manufacturing. On the basis of the data collected, it was concluded that PA, if used to replace up to 10% of the portland cement, shows a positive effect on the mechanical performance of mortars. On the other hand, because of its high fineness and consequently high water absorption, it required a higher amount of water. It was concluded that the use of PA should not be higher than 10% by weight of the cement replaced, unless mortar mixtures are judiciously proportioned. [ABSTRACT FROM AUTHOR]