Electrochemical impedance spectroscopy (EIS) and linear polarization resistance (LPR) are widely adopted to measure steel/concrete corrosion. However, the variation in electrode configurations often lead to inconsistent results. In this study, different reference electrode (RE) and counter electrode (CE) configurations were adopted on the same steel/mortar specimen to investigate their influence on

Alkali-activated aluminosilicates (AAA) are considered a potential environmentally friendly alternative to traditional concrete. Previous studies also showed their better high-temperature performance as compared with cement-based composites. In this paper, a comprehensive assessment of AAA's behavior at high temperatures is presented. A detailed analysis of physical and chemical processes taking place

Bacteria-based self-healing concrete is promising in sustainable constructions, while the germination of carbonate precipitating bacterial spores in crack zone is the start of the healing process, and hence has great impact on crack healing efficiency. In this study, the Ca-alginate hydrogel sheets encapsulated spores were pre-embedded at specific crack depths, and the in-situ germination behavior

Click on the article title to read more.

Phosphogypsum (PG)-based cementitious materials often suffer from low strength and poor water resistance, especially when incorporating a high volume of PG. This issue arises mainly from the high solubility of CaSO4·2H2O. This study develops a novel CO2-assisted alkali activation method for phosphogypsum-based cementitious materials (HPCM), improving compressive strength to 49.3 MPa (+50.83%) and enhancing

Steel slag with high aluminum (Al) content significantly delays the early hydration of cement when used as a supplementary cementitious material (SCM). To address this challenge, this study investigates the effects of gypsum (Gy) and sodium sulfate (SS) additions on the performance of cement pastes with 30 % high-Al ladle metallurgy furnace (LMF) slag. The mechanical properties, hydration kinetics

Controlling autogenous shrinkage is one of the challenges for alkali-activated slag application. This paper reports a pair of approaches targeting the autogenous shrinkage mitigation: one is to use sodium desulfurization ash (SDA) and calcium carbide residue (CCR) as combined solid activators, rather than using sodium silicate solution; and another is to facilitate the formation of U-phase crystals

The diffusion coefficient of unsaturated cementitious materials is a crucial factor in assessing their transport-related properties for durability evaluation. However, predicting the diffusion coefficient of unsaturated cementitious media through mathematical modeling is challenging due to the variability of fitting parameters in existing models. This work explores the impact of pore structure and

Incorporating construction and demolition waste aggregate (DW) into concrete addresses environmental concerns by reducing the demand for virgin materials and diverting waste from landfills. However, the high porosity of DW negatively impacts the durability of concrete. In this work, DW was functionalized by impregnating it with paraffin to fill its inherent pores. Additionally, the phase change characteristics

Accurate long‐term deformation prediction is essential to ensure the structural security and ongoing stability of large water‐related concrete structures like ultra‐high arch dams. Traditional statistical regression and shallow machine learning approaches, due to their algorithmic constraints, often fail to comprehensively capture the complex temporal and spatial dependencies inherent in high‐dimensional

The prediction of freezing depth and thawing time of unbound pavement layers in cold regions is a critical task in pavement design and management. This study developed long short‐term memory (LSTM)‐based encoder–decoder models to accurately predict freezing depth and thawing time, with air temperature as the sole input variable. The models, which aim to offer a 14‐day advance prediction of the thawing

The influence of slaking on the properties of natural hydraulic limes (NHL) has been little studied so far. Laboratory-manufactured limes have been produced to investigate the mineralogical changes that occur during the slaking process. Two different hydration methods have been compared: conventional slaking, by adding water in a 1:1 water:CaO ratio, and passive slaking, by exposure of the quicklimes

The post-heating flexural performance of carbon fiber-reinforced polymer (CFRP) bars after thermal exposure plays a critical role in determining whether concrete members should be demolished or strengthened. This study investigates post-heating flexural performance of a CFRP bar in ultra-high-performance fiber-reinforced concrete (UHPFRC) after thermal exposure. A total of six UHPFRC members were prepared

Computer vision‐based ship detection using extensively labeled images is crucial for visual maritime surveillance. However, such data collection is labor‐intensive and time‐demanding, which hinders the practical application of newly built ship inspection systems. Additionally, well‐trained detectors are usually deployed on resource‐constrained edge devices, highlighting the lowered complexity of deep

As a fundamental driving behavior, the accurate modeling of car‐following (CF) dynamics is essential for improving traffic flow and advancing autonomous driving technologies. Due to the stochastic nature of CF behaviors, the CF model parameters often exhibit heterogeneity (multimodal trends), distribution uncertainty, and parameter correlations. Most studies have examined correlations among CF model

Safe, efficient, and comfortable autonomous driving is essential for high‐quality transport service in an open road environment. However, most existing driving strategy learning approaches for autonomous driving struggle with varying driving environments, only working properly under certain scenarios. Therefore, this study proposes a novel hierarchical continual reinforcement learning (RL) framework

Real‐time prediction of subgrade settlement caused by shield tunneling is crucial in engineering applications. However, data‐driven methods are prone to overfitting, while physical methods rely on certain assumptions, making it difficult to select satisfactory parameters. Although there are currently physics‐data‐driven methods, they typically require extensive iterative calculations with physical

This study aimed to investigate the phase assemblages of Portland cement (PC) samples and eluate compositions for various water compositions and liquid/solid (L/S) ratios using thermodynamic equilibrium calculations. Specifically, diverse groundwater and seawater compositions were selected as eluates to represent practical leaching conditions. Samples made of PC with carbonation degrees of 0, 10, 20

Floor heave is a typical form of roadway damage in underground mining, often causing transportation and ventilation issues, as well as restricted access. While shear-induced slip is universally acknowledged as the predominant failure mode in roadway surrounding rock, existing research has not recognized the mechanism from the perspective of full-range surrounding rock movement source identification

Reuse is not commonly adopted in practice, despite its acknowledged benefits, partly due to the complexity of the design process, considering geometric constraints and fluctuating stock availability. A multi-objective optimization framework for algorithm-based stock assignment and path generation is developed, specifically for one-dimensional material systems (e.g., piping, timber, steel), to maximize

There is substantial potential for future underground construction operations to be performed by autonomous robots. This paper proposes a 360-degree digital reconstruction framework for robotic-built underground structures using in-pipe rotating ground penetrating radar (GPR). Unlike conventional ground-level applications, placing GPR inside pipes significantly reduces signal attenuation by shortening

Machine learning (ML), graph deep learning (GDL), natural language processing (NLP), generative, and image deep learning (IDL) methods are promising for automating space function and space access element classification for building analysis. Benchmarking these five methods is currently infeasible primarily due to a lack of datasets with diverse data representation formats. This paper introduces SFC-A68

Energy tunnels represent a promising innovation in the integration of tunnel structures with shallow geothermal energy applications. However, the thermo-hydro-mechanical behaviour of energy tunnels in stiff ground conditions, particularly in rock formations, remains largely understudied. This research addresses this gap by employing a thoroughly validated finite element modelling approach, incorporating

The development of not-toxic retarders with a high retardation efficiency is crucial for a sustainable development of high-performance magnesium potassium phosphate (MKP) cement-based materials. Zinc acetate is such a promising new set retarder for MKP cements. The impact of zinc acetate on the properties and hydration of the MKP cements at a Mg/PO4 molar ratio of 8 was investigated up to 5 years.

The integration of ultra-high-performance concrete (UHPC) with 3D printing technology introduces the revolutionary potential, offering exceptional mechanical properties, enhanced design flexibility, and automated construction processes. However, without additional reinforcement, the fracture performance of 3D-printed UHPC (3DP-UHPC) becomes critical to the crack resistance structures. To address the

In order to improve the high temperature resistance of building materials and develop a material that does not need to be repaired after fire, this paper develops a novel high temperature resistant geopolymer with metakaolin-fly ash blended precursor and corundum aggregates, characterized by thermal enhanced ultra-high residual strength. The surface morphology, mass loss, volume shrinkage, compressive

Material transportation and on-site assembly are the building lifecycle phases that produce significant carbon emissions. However, traditional methods for capturing and recording these emissions lack automation, traceability, and immutability. This limitation hinders project stakeholders from data-driven decision-makings to promote sustainable construction practices and effectively implement regulations

This paper addressed the challenge of inverse design in structural engineering, focusing on predicting reinforcement and thickness parameters for piecewise developable reinforced concrete shells. Specifically, it investigates whether pre-trained machine learning models can more effectively predict rebar directions and thicknesses from displacement data compared to models trained from scratch. To answer

Industrialised construction, through the offsite manufacturing of standardised components, is emerging as a response to the growing demand for the mass production of high-performance buildings. A review of existing research and projects reveals a significant gap in the development of façade systems compatible with Prefabricated Prefinished Volumetric Construction (PPVC)—the most advanced form of offsite

Infrastructure facilities require proper maintenance, including diagnosing structural durability and determining appropriate repair methods. Structural analysis is widely used to assess structural conditions, necessitating three‐dimensional (3D) data that accurately reflect the locations of deterioration. Therefore, we investigate a method to generate 3D data of manholes from single‐shot panoramic

Previous analytical models of fault-crossing tunnels have predominantly been based on the assumption of the tunnel being continuous, which is barely present in practical engineering projects. In this study, a theoretical model for the mechanical analysis of segmental tunnels subjected to reverse fault dislocation is proposed, wherein the interactions between the segmental lining and joints are incorporated

To address the complexity of using multiple binders in a single system, the present study was designed as part of an initiative to blend commercially available Portland cement (PC) and calcium sulfoaluminate (CSA) clinker with supplementary cementitious materials (SCMs). Blast furnace slag and limestone or gypsum were selected as the SCMs in the experimental program to study the compound effect of

Alkali-activated materials offer a low-carbon and cost-effective approach for heavy metal immobilization. In this study, alkali-activated phosphorus slag (AA-PS) mixtures were designed to immobilize Cr(VI). This research integrates thermodynamic modelling and experiments to investigate the reaction processes, immobilization mechanisms, and leaching behaviors. The results show that the hydration products

Road intersections are critical components of urban infrastructure networks, ensuring safe and efficient traffic flow. However, their construction frequently experiences delays and cost overruns, often due to inadequate schedule planning. To mitigate these issues, the integration of Building Information Modeling (BIM) and Lean Construction has emerged as a promising strategy. Despite the recognized

The Architecture, Engineering, and Construction (AEC) industry faces data integration challenges due to fragmented silos and diverse data representations, hindering cross-domain queries and early detection of design constraints. Semantic Web Technologies (SWTs) address data integration challenges.

Traffic signal timing and vehicle routing have been empirically demonstrated as the two most promising paradigms for network‐level urban road traffic management. However, mainstream studies based on Wardrop's theory continues to treat these two modules separately without achieving effective coupling. Optimization‐based methods face the challenge of increasing computational complexity as urban scales

Three‐dimensional (3D) digital design is extensively adopted in the architecture, engineering, consulting, operations, and maintenance (AECOM) industry to enhance collaboration among stakeholders. Although recommendation systems are commonly employed to facilitate purchasing in e‐commerce websites, none involves recommending online products to users from 3D building design models due to dimensional

Carbon fiber-reinforced polymer (CFRP) bars exhibit superior mechanical and chemical properties compared to conventional steel reinforcement, making them a promising alternative for reinforced concrete structures. In FRP-reinforced members, bond cracking may still occur even when reinforcement spacing meets the minimum requirements commonly applied to RC structures, potentially leading to sudden brittle

Sustainable building materials are developed using recycled aggregate (RA) and desert sand (DS), in accordance with green, low-carbon, and environmentally conscious development principles. However, the effects of DS incorporation on the pore characteristics and interfacial properties of recycled aggregate concrete (RAC) exposed to salt freezing and thawing environments has remained insufficiently understood

Limestone is widely utilized in tunnel construction and underground engineering structures. To investigate the corrosion damage of limestone exposed to acidic groundwater, scanning electron microscopy (SEM), nuclear magnetic resonance (NMR), uniaxial compression tests, and digital image correlation (DIC) were performed on limestone specimens immersed to varying pH solutions. Results indicated that

The increasing number of deep-buried tunnel projects has made high-temperature water inrush disasters a severe challenge for tunnel construction. Grouting has been proven to be one of the most effective measures against such disasters, with quick-setting slurry being the most commonly used grouting material. Nevertheless, time-dependent characteristics of quick-setting slurry rheological parameters

The aggregate distribution in concrete significantly influences the location of Interfacial Transition Zones (ITZs), impacting the initiation and propagation paths of cracks and complicating the prediction of concrete’s cracking behavior. To figure out the effects of aggregate distribution on concrete crack features, this study constructs a porosity-based heterogeneous model using the Discrete Element

The velocity properties of concrete are highly sensitive to the changes of concrete structure after high temperatures. Experimental and theoretical data indicate a reduction in velocities and a decrease in the Vp/Vs ratio with temperature. After the heated concrete is saturated with water, the dependence of velocities on temperature shows a different trend compared with the dry specimen. The Vp/Vs

This paper presents an approach to enhance the interlayer properties of 3D-printed concrete (3DPC) by synchronously spraying CO2-activated interface enhancer (CIE) onto the surface of printed concrete filament during the printing process, thus overcoming the inherent limitation of weak interlayer properties and unlocking new possibilities for automation construction. The CIE was developed by using

The real-time control of concrete's stiffening allows users to better control pumping and extrusion during 3D-printing processes. Here, a portlandite-based cementitious formulation (i.e., slurry or suspension) that features the potential for rapid CO2 uptake is adapted for 3D-printing applications. In particular, we showcase a portlandite-fly ash binder system combined with a thermoresponsive polymer

Elastic modulus is one of the key parameters of recycled concrete for its application as structural concrete. The effect of recycled coarse aggregate characteristics on concrete elastic modulus needs to be clarified to enhance concrete performance. This study investigated the effect of the properties of recycled coarse aggregate, new mortar, and interfacial transition zone (ITZ) on concrete elastic

The emergence of 3D computer vision presents a promising paradigm for structural health monitoring of segmental tunnel linings. For automated inspection and analysis, it is first necessary to segment the associated point clouds into individual tunnel segments. Whilst 3D deep learning (DL) networks are suitable for such tasks, the similarity of segment geometries renders generic 3D DL network architectures

While model generalization and specialization are a critical concern in computer vision, balancing them in data-scarce construction settings remains challenging due to their unique nature. This paper proposes a multi-domain learning approach where a model acquires domain-generic visual knowledge from various domain datasets, while maintaining domain-specific predictabilities for each individual domain

Digital Twin (DT) technology has emerged as a next-generation smart building management solution, seamlessly bridging traditional Building Automation Systems (BAS) with Industry 4.0 innovations such as Building Information Modelling (BIM), artificial intelligence (AI), big data, Internet of Things (IoT), and Extended Reality (XR). However, current DT applications in building operations remain nascent

This paper focuses on the cost minimization of the multi-mode resource-constrained repetitive project scheduling problem with multiple crews, crew interruptions, and soft logic. The resource allocation of each crew is considered. To explore the impact of different construction strategies on project costs, mixed-integer linear programming (MILP) and constraint programming (CP) models are developed representing

Real-time monitoring is critical for smart construction management, yet environmental complexities degrade surveillance video quality. Traditional visual information fidelity (VIF) algorithms depend on reference images, which limits their use in no-reference scenarios such as autonomous systems and industrial inspection. Grounded in information theory, this paper proposes an algorithm that integrates

Accurately predicting metro commuter flows under changing urban conditions is essential for guiding infrastructure investments and service planning. However, existing methods show limited adaptability to evolving urban conditions. To address this, we propose an adaptive graph sharing embedding cascade interaction network (AGSECIN), which establishes a dynamic mapping relationship between changing urban