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Signal noise removal is an indispensable and critical procedure in obtaining clean pavement texture data for reliable pavement evaluation and management. Nevertheless, the presently established denoising approaches to pavement texture data still rely on traditional techniques that have long struggled with removing noise accurately and consistently. This paper innovatively initiates a one-dimensional

Superabsorbent polymers (SAPs) are widely studied as internal curing agents in high-performance concrete, but their adverse effects on pore structure remain a challenge. This study introduces an innovative cement-integrated SAP (CiSAP) by modifying the interface, using KH570-modified cement (KMC) as the functional core. By optimizing KMC content, the microstructure was improved, leading to enhanced

The construction methods of Engineered Cementitious Composites (ECC) are crucial for ensuring the structural performance of ECC pavements, which have demonstrated superior fatigue life and heavy traffic capacity. However, the commonly used rolling compacted (RC) method for pavement has never been explored for RC-ECC pavement. In this study, RC-ECC was developed via theoretical and experimental methods

As a promising sustainable alternative to ordinary Portland cement (OPC), there are still doubts about the protective properties of belitic calcium sulfoaluminate (BCSA) cement to the embedded steel, especially for its low pore solution alkalinity and high sulfate concentration. To guarantee the corrosion resistance of steel reinforcement in BCSA cement, using corrosion-resistant steels, such as stainless

Soda residue, a by-product of the Na2CO3 industry, is recognized for its high alkalinity, which can lead to corrosion and the deposition of iron oxide (Fe2O3) from industrial procedures and lab infrastructure. This study delves into the effects of incorporating Fe2O3-rich soda residue (FSR) into alkali-activated materials (AAMs), specifically alkali-activated fly ash (FA) and/or slag powder (SP), on

Engineered Cementitious Composites (ECC) are high-performance cementitious materials that exhibit multiple cracking and self-controlled width under uniaxial loading, which can lead to a low permeability. Quantifying the water flow behavior of an ECC crack is a precondition for its practical application. However, the lack of characterization for internal crack profiles and advanced modeling for water

MgO-based cement offers a promising solution to lower the carbon footprint compared to that of Portland cement, where MgO is sourced from fossil-free minerals. The hydration of MgO plays a key role in these cements. However, MgO required higher water demand to achieve a workable mix, which poses drawbacks in microstructure and strength development. In this work, we investigated the effects of 7 polycarboxylate-based

Fly ash, a by-product of coal combustion, is a pozzolanic solid waste with annual production of 1.63 billion tonnes, which has been widely used to replace cement clinker to develop sustainable concrete. However, the incorporation of high volumes of inert fly ash significantly reduces the early mechanical strength of concrete due to its low pozzolanic activity. This study presents an innovative strategy

Recently, there has been a growing interest in the use of Artificial Ground Freezing (AGF) to temporarily stabilize unstable ground at tunnel construction sites. Recognizing that the effectiveness of this method is significantly influenced by groundwater flow, it is crucial to conduct a sophisticated thermal-hydraulic coupling analysis to assess the potential adverse effects of groundwater flow in

Hazard recognition is critical for construction safety, especially for accident prevention. Traditional methods often fail to capture the dynamic and interdependent nature of construction hazards. To address this issue, this paper proposes a network-based framework that conceptualizes construction hazards as dynamic interactions between objects with hazardous attributes. A link prediction model using

Healthcare facilities are complex systems where operational efficiency depends on space, processes, resources, and logistics. While many studies propose process-simulation-based improvements, few dynamically consider the built space’s effect on process efficiency. The critical challenge here is the effective integration of data from these disparate domains. This article addresses this challenge by

After the installation of rubber isolation layer in tunnels, surrounding rock convergence may apply permanent pressure on the tunnel, compressing the isolation material. This can reduce its elasticity, impairing its recovery capacity and potentially leading to failure. Therefore, this paper proposes a new type of pressure-resistant isolation layer that embeds the compressive layer into the energy dissipation

Fiber reinforcement has been demonstrated to mitigate soil liquefaction, making it a promising approach for enhancing the seismic resilience of tunnels in liquefiable strata. This study investigates the seismic response of a tunnel embedded in a liquefiable foundation locally improved with carbon fibers (CFs). Consolidated undrained (CU), consolidated drained (CD), and undrained cyclic triaxial (UCT)

Buried pipes are subjected to static and dynamic loads depending on their areas of use. To mitigate the risk of damage caused by these effects, various materials and reinforcement methods are utilized. In this study, five buried uPVC pipes designed in accordance with ASTM D2321 standards were reinforced with three different ground improvement materials: Geocell, Geonet, and Geocomposite, and experimentally

In deep underground engineering construction and resource exploitation, complex conditions such as high stress and strong disturbance are often encountered, and dynamic disasters such as rockburst and coal burst are prone to occur. As a common anchorage support form in deep underground engineering, bolts and cables are often applied with high prestress to improve the bearing capacity of surrounding

This paper presents a method for automatic detection and quantification of full cross-sectional dimensions of structural components using oblique photography and the SAM-dimension (Segment Anything Model-dimension) model. Unlike traditional methods that measure only a single cross-section, this approach enables full cross-sectional dimension detection across the entire component, enhancing efficiency

Engineering structural damage often exhibits diverse and complex features across multiple scales within small-scale regions of interest (ROI), complicating post-earthquake assessments. This paper proposes an interpretable deep learning (DL) framework for semantic segmentation of multicategory damage. Energy-derivative attention modules are integrated into convolutional neural networks (CNNs) to enhance

Recent urban revitalisation requires advanced utility management and innovative technology to achieve high-precision utility management. This paper introduces an automated framework that surpasses traditional methods of subsurface utility detection by integrating Ground Penetrating Radar (GPR), deep learning, and Augmented Reality (AR) to provide an advanced solution for subsurface detection and visualization

The measurement of ultrasonic surface velocity in concrete and the ultrasonic Time Of Flight method for estimating the depth of surface opening cracks in concrete are important techniques for maintenance of constructions, which are currently performed manually. This paper demonstrates the possibility to automate these measurements by means of an Unmanned Aerial Vehicle (UAV) equipped with a robotic

Ground‐penetrating radar (GPR) offers nondestructive subsurface imaging but suffers from a trade‐off between frequency and penetration depth: High frequencies yield better resolution with limited depth, while low frequencies penetrate deeper with reduced detail. This paper introduces a novel frequency enhancement method for GPR images using domain‐adaptive generative adversarial networks. The proposed

Failure of buried pipelines can result in serious impacts, such as explosions, environmental contamination, and economic losses. Early detection and location of unexpected events is crucial to prevent such events. However, conventional monitoring methods exhibit limited generalization performance under varying environmental and operational conditions. Furthermore, the cross‐correlation‐based time difference

Sulfuric acid corrosion poses a significant threat to urban ‘deep tunnel’ systems, exacerbating flood disasters and causing economic losses. Therefore, it is crucial to predict the deterioration process of steel fiber-reinforced concrete under sulfuric acid corrosion. This study developed four predictive models for the degradation process of steel fiber-reinforced concrete of ‘deep tunnel’ lining during

This study presents a novel method for identifying joints and automatically segmenting shield tunnels using light detection and ranging (LiDAR). In cylindrical coordinates, the Hough transform is used to extract feature LiDAR data corresponding to ring joints at different azimuths. This feature extraction using LiDAR data facilitates the computation of ring joint feature coordinates and average ring

Urban Heat Islands (UHIs) substantially alter local climates, yet their impacts on building energy performance remain inconsistently quantified and poorly integrated into simulation workflows, energy codes, and planning practice. This review critically synthesizes U.S.-based studies that model the impacts of the UHI effect on building heating and cooling loads, revealing substantial variability in

Matrix strength and interfacial bonding between aggregate and matrix are critical factors influencing the performance of lightweight cementitious composites (LCC). This study proposes an environmentally friendly and efficient strategy for developing high-performance fly ash cenospheres (FAC)-containing LCC by combining sodium sulfate (SS) and calcium-silicate-hydrate (C-S-H) seeds. Moreover, the roles

This study investigates the role of L-aspartic (L-Asp) in regulating the crystallisation of hydrated magnesium carbonates (HMCs) in carbonation-cured reactive MgO (RM). The effects of L-Asp on hydration kinetics, bulk density, compressive strength, phase composition, carbon sequestration, microstructure and morphology of RM composites were examined to understand its influence on the coupled hydration

The built environment is a key leverage point for policy intervention to combat climate change and the statutory reporting of financial and non-financial indicators over the asset lifecycle is increasingly required. This poses significant information management challenges in a sector characterised by complexity. Contributions to-date which address Life Cycle Asset Information Management (LCAIM) remain

Near‐fault pulse‐like ground motions can cause severe damage to long‐period engineering structures. A rapid and accurate identification method is essential for seismic design. Deep learning offers a solution by framing pulse‐like motion identification as an image classification task. However, the application of deep learning models faces multiple challenges from data and models for pulse‐like motion

While semi‐autonomous drones are increasingly used for road infrastructure inspection, their insufficient ability to independently handle complex scenarios beyond initial job planning hinders their full potential. To address this, the paper proposes a human–drone collaborative inspection approach leveraging flexible surface electromyography (sEMG) for conveying inspectors' speech guidance to intelligent

Traffic congestion has substantially induced significant mobility and energy inefficiency. Many research challenges are identified in traffic signal control and management associated with artificial intelligence (AI)‐based models. For example, developing AI‐driven dynamic traffic system models that accurately capture high‐resolution traffic attributes and formulate robust control algorithms for traffic

Although estimating the International Roughness Index (IRI) is crucial, previous studies have faced challenges in addressing IRI prediction for asphalt concrete (AC) overlays on Portland cement concrete (PCC) pavements. This study introduces machine learning to predict the IRI of AC overlays on PCC pavements, focusing on incorporating pre‐overlay treatments to reflect their composite characteristics

Chillers account for the majority of energy consumption in central air-conditioning refrigeration stations. However, conventional models lack strong out-of-sample generalization, making it difficult to accurately reflect chiller performance variations under multiple operating conditions. Consequently, there is a lack of reliable multi-condition performance data to support energy-efficient regulation

Semantic digital twinning has traditionally supported design coordination, documentation, and planning during the early stages of building projects. However, its application in building operation and maintenance—particularly in real time—remains limited. This study proposes a methodology for cost-optimal HVAC load management using an operational digital twin, and demonstrates its real-time application

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Limestone calcined clay cement (LC3), a low-carbon cementitious material, has demonstrated outstanding resistance to chloride ion penetration. However, the real environment is rich in many harmful ions beyond chloride ions, including sulfate and magnesium ions, making the interactions among these ions highly complex. This study systematically explores the impact of sulfate ions and the synergistic

As construction workflows become increasingly dynamic, there is a growing need for Digital Twins (DTs) to support integrated, real-time workflow monitoring. However, establishing DTs in construction remains challenging due to fragmented data sources and the lack of systematic semantic integration methods. This paper investigates how semantic web ontologies can be systematically applied to establish

Effective knowledge management in construction safety is essential yet challenging. Despite emerging technologies to collect valuable data automatically, it continues to rely on manual input. The heterogeneity of data sources in construction makes it additionally difficult, resulting in a high number of incidents due to late changes in the design. Presented is a unified ontology for construction safety

Vision‐based monitoring of construction equipment is limited in scalability due to the high resource demands of collecting and labeling large datasets across diverse environments. This study proposes a framework that employs Zero‐Shot Learning (ZSL) and Multimodal Large Language Model (MLLM) to recognize construction equipment tasks from video frames without additional training data. The framework

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The size distribution of rock chips can fully reflect the performance of shield machine, and existing size distribution indicators suffer from low efficiency and poor accuracy. Therefore, the aim is to find an accurate and rapid quantitative indicator to characterize the rock chips size distribution and address the engineering issues of shield machine rock-breaking efficiency analysis and tunneling

Concrete is widely used in infrastructure, and its waste heat recovery for thermoelectric power generation holds remarkable potential for energy utilization. However, optimizing the thermal conductivity of concrete to enhance thermoelectric conversion efficiency remains a critical challenge. This study investigates C40 concrete modified with bamboo fibers and fly ash, evaluating the thermal conductivity

Salt scaling damage peaks at a specific salt concentration, known as the pessimum concentration. However, reported pessimum concentrations vary widely, lacking a theoretical explanation. The microstructure of concrete is an important characteristic influencing the freezing behavior of pore solution, which is often neglected in salt scaling studies. This study investigates the effect of concrete microstructure

The unavoidable challenge of weakened interlayers in 3D Concrete Printing yields diminished mechanical performance due to compromised micro- and macrostructural properties that are a culmination of the material and process parameters, in conjunction with ambient environmental conditions. A bond enhancement technique is proposed that is characterised by the surface treatment of interlayer surfaces with

The performance of low-carbon cements prepared from different neat calcined clays (CCs) can be very inconsistent due to substantial variations in the composition of the CC samples. To gain a better understanding and further promote the practical application of such low-carbon cements incorporating CCs, the influence of calcined clays possessing different mineralogical compositions on the rheological

Construction site monitoring relies on robust image classification to enhance safety, track progress, and optimize resource management. However, the amount of clutter and the high cost of manual labeling pose significant challenges. This paper presents an approach to multi-object classification in construction sites using Adaptive Active Transfer Learning. The Weighted Active Transfer Learning with

Increasing the Degrees Of Freedom (DOFs) of Kinetic Fa?ade Systems (KFS) potentially enhances environmental adaptability but presents challenges in mechanical feasibility and optimization complexity due to high-dimensional design spaces. This paper investigates the mechanism design and optimization strategies for multi-DOF KFS, and assesses the performance trade-offs associated with increased motion

With the increasing demand for precise control in 3D concrete printing, coordinating material rheological properties and printing parameters has become a critical challenge. This paper addresses how to intelligently optimize printing parameters to adapt to varying concrete material attributes and improve printing quality. A dual-path framework co-driven by physical information equations (PIE) and machine

Wire-arc directed energy deposition (DED-Arc), also known as wire arc additive manufacturing (WAAM), brings about unprecedented opportunities in the construction sector to improve material efficiency, enhance automation and reduce embodied carbon. To address the current standardisation gap, a normative framework for the use of DED-Arc in construction is proposed in this paper. The current standardisation

The number and proportion of aging infrastructures are increasing, thereby necessitating accurate inspection to ensure safety and structural stability. While computer vision and deep learning have been widely applied to concrete cracks, domain shift issues often result in the poor performance of pretrained models at new sites. To address this, a self‐supervised domain adaptation method using generative

The assembly and production of sandwich panels for prefabricated components is crucial for the safety of modular construction. Although computer vision has been widely applied in production quality and safety monitoring, the large‐scale differences among components and numerous background interference factors in sandwich panel prefabricated components pose substantial challenges. Therefore, maintaining

The automatic identification of surrounding rock grade is a key challenge in the TBM construction of deep tunnels. This study aims to develop an automatic identification system based on TBM ascending section tunneling data to provide accurate guidance for stable section tunneling. A total of 6734 m of per-second TBM tunneling data was collected, and a preprocessing method for null and outlier values

During the engineering design stage, it is challenging to precisely identify the number and spatial distribution of joints within rock masses. To address this, joint orientations are assumed to be constant and evaluate all possible combinations of joints and excavation surfaces to identify the most critical scenario. The maximum key block serves as a vital indicator for tunnel alignment optimization

Urban heat island (UHI) has been one of the most prominent results of anthropogenic related land use change. To achieve accurate and computationally efficient spatiotemporal mapping of air temperature and UHI under typical climate conditions, in this study, a reference weather station-based framework is presented for high-resolution and representative urban temperature mapping in a cost-effective and

The 2024 F-GAS Regulation mandates the phase-out of fluorinated gases across multiple sectors, promoting the adoption of natural refrigerants like propane, which pose flammability risks. Simultaneously, the 2024 Energy Performance of Buildings Directive (EPBD) introduces stricter requirements for building thermophysical parameters, potentially reducing heating and cooling peak loads. Together, these

Achieving net-zero emissions in residential heating requires sustainable alternatives to gas-powered systems and effective use of existing gas infrastructure. This study introduces ice-source heat pumps, leveraging the latent heat of fusion for efficient heating combined with innovative water transmission methods.