Incorporating a paraffin-based phase-change material (PPCM) into core-wall clay (PCM-clay) enables the mixture to regulate the temperature during winter construction through latent-heat storage and release, offering a promising approach for mitigating freeze-thaw damage and extending the construction period of earth-rock dam core walls in cold regions. However, in practical applications, the potential loss of liquid PPCM under seepage pressure raises concerns regarding the impermeability and long-term integrity of the core walls. To address this critical issue, two seepage-loss test devices were developed in this study and systematic experiments were conducted to examine the characteristics, governing factors, and threshold of PPCM loss in clay. The results indicate that significant PPCM loss occurs only when the PPCM content exceeds the critical loss threshold. Following seepage, the remaining PPCM persists in two stable forms, adsorption/wrapping on soil particles and retention in pores via capillary forces, both of which resist further leakage. A higher PPCM content and greater clay density lead to a larger residual PPCM ratio, thereby helping to maintain the high impermeability of PPCM-mixed clay (PCMclay). Specifically, approximately 5 % and 6 % PPCM remained after seepage at a gradient of 25 for soil with initial contents of 6 % and 8 %, respectively. These findings clarify the mechanism and critical control factors of PPCM seepage loss, providing essential guidance for the core-wall material application of PPCM-mixed clay in cold regions and ensuring the operational safety of the novel core-wall earth-rock dams.

Accurate real-time monitoring of surrounding rock deformation during tunnel excavation is essential for ensuring construction safety. Conventional manual methods suffer from low efficiency and susceptibility to subjective factors, making it difficult to guarantee continuity and accuracy. Single non-contact approaches are constrained by incomplete observation dimensions and environmental sensitivity, which limits their ability to simultaneously achieve accuracy, robustness, and three-dimensional (3D) perception under complex conditions. To address these challenges, this study proposes a high-precision monitoring method that fuses monocular vision with millimeter-wave (MMW) radar. The method exploits vision for high-resolution geometric detail and MMW radar for robust radial displacement measurement in complex environments. A cross-modal geometric fusion model is constructed to realize complementary constraints and joint estimation, while an adaptive weighting mechanism based on error propagation analysis dynamically balances the uncertainties of different modalities under varying conditions. By further integrating nonlinear least-squares optimization with temporal filtering, the method achieves robust inversion and millimeter-level estimation of 3D displacement fields. Experimental results show that the average error remains at approximately 1 mm across various distances, displacement amplitudes, orientations, and dynamic tracking scenarios, demonstrating stable and high-precision performance. Field measurements in tunnel environments likewise exhibited smooth displacement curves, maintaining millimeter-level displacement outputs without noticeable drift or abrupt changes, thereby confirming the stability of the proposed method and its resistance to environmental disturbances. The findings demonstrate significant improvements in the real-time performance, reliability, and automation of tunnel construction monitoring, and provide a novel technical paradigm for multimodal structural health monitoring under complex conditions.

The paraffin-based phase change material (PPCM) has provided a novel solution to the antifreezing and temperature control of core wall soil. However, as a new filling material for dam core walls, the PPCM-mixed soil (PS) may increase the brittleness and the risk of hydraulic fracturing failure to the core wall. In this paper, a three/four-point bending test device with horizontal loading was developed to investigate the fracture characteristics and failure criteria of PS. The results show that the increase of PPCM content and the decrease of dry density will reduce the fracture toughness of PS. The elliptic equation with the fracture toughness of Mode I (open fracture) and Mode II (sliding fracture) as the axial length is more suited to describing the results of the fracture toughness test for PS with different PPCM contents. Combined with the relationship between the fracture angle and the ratio of the stress intensity factor, the fracture failure criterion of PS under different PPCM contents can be presented. These research results can provide a theoretical support for further analysis of core wall failure and hydraulic fracturing risk.

Ensuring the compaction quality of soil materials is essential for controlling post-construction settlement in dams and high-fill embankments. As moisture content is a key factor affecting soil compaction quality, its rapid and accurate detection during rolling is of great practical importance. However, conventional methods, such as oven drying and alcohol combustion, rely on limited-point sampling and cannot provide rapid full-field detection of in situ moisture content, which varies significantly with time, material source, and paving position. To address this limitation, this study proposed a real-time method for detecting the overall soil moisture content during rolling based on near-infrared (NIR) technology. A compactor-mounted real-time detection device was first developed to measure the soil surface moisture content by integrating intelligent compaction technology with NIR sensing. A thermo-hydraulic coupled migration model considering air temperature, wind speed, and light intensity was established to relate the NIR-detected surface moisture content to moisture content at different depths within the compacted layer. On this basis, an efficient surrogate model, namely a goose algorithm-optimized back-propagation neural network (GOA-BPNN), was constructed to rapidly predict soil moisture content at different depths. A calculation method was further proposed to estimate the overall moisture content within the paving layer. Finally, a real-time soil moisture detection system was developed to achieve rapid and comprehensive detection of the overall soil moisture content during rolling. Field application results show that the mean absolute error between the detected and actual overall soil moisture content is 0.86%, demonstrating high detection accuracy. The proposed method provides an efficient approach for real-time detection of the overall soil moisture content during rolling and offers more precise and comprehensive moisture information for intelligent compaction-based assessment of soil compaction quality.

Phase-change-material-mixed clay (PCM-clay) effectively regulates temperature fluctuations and prevents freezing in the core walls of dams, canals, embankments, and pavements in cold regions. Despite the potential of PCM-clay, limited research has conducted on its damage mechanisms when subjected to freeze-thaw (F-T) cycles. In this study, discrete element method (DEM) was established to numerically simulate and analyze the progressive damage mechanism of PCM-clay during F-T cycles. Fundamental assumptions, were made regarding filling configurations, and contact model selection. Laboratory experiments were conducted to calibrate the model parameters and evaluate simulation accuracy. The progression of crack development, force chain networks, and particle displacement throughout the entire F-T cycle are examined and discussed. The results indicate high accuracy of the model, with an efficiency of 0.82 and 0.78 for untreated soil and PCM-clay, respectively. Compared to untreated soil, the F-T-induced cracks in the PCM-clay model were mainly tensile and more evenly distributed across the PCM-clay sample. Post-cycle analysis revealed a relatively continuous internal force chain network and minimal particle displacement, while maintaining structural integrity. This study elucidates the mesoscopic behavior and mechanism underlying F-T damage in PCM-clay, thereby contributing to a clearer understanding of its performance and functional principles in cold-region engineering applications.

To systematically investigate the mechanical behaviors of rockfill materials under the combined influence of particle shape and sample size, a stochastic algorithm that incorporates three-dimensional shape parameters such as elongation, flatness, sphericity, and convexity, was employed to generate irregularly shaped rockfill particles. A triaxial numerical simulation method was proposed for rockfill materials, which comprehensively accounts for both particle shape and sample size. Discrete element numerical simulations of rockfill materials with varying particle shapes and sample sizes were conducted to investigate the effects of these two factors on the mechanical properties and nonlinear constitutive models from both macroscopic and microscopic perspectives. The evolution of microscopic characteristics including coordination number, Euler angles, and fabric anisotropy of rockfill bodies were examined, and the stress–strain and volumetric strain responses of various particle samples were analyzed, revealing the correlation mechanisms of particle shape and sample size on their macro- micro properties of rockfill materials. Based on these findings, a novel constitutive model that integrates both particle shape and sample size was presented, aiming to offer a more accurate and comprehensive theoretical framework for understanding the mechanical behavior of rockfill materials.

Accurate backfill grouting plays a critical role in treating soil karst cave foundations. However, the inherent concealment of underground construction complicates the assessment of actual grouting and filling conditions. Digital construction technology facilitates the dynamic monitoring of grouting parameters, including slurry flow, pressure, and water-cement ratio, providing essential field data for analyzing grout diffusion within soil karst caves. By leveraging these digital monitoring data, a computational-fluid-dynamics-based numerical simulation was conducted to investigate grout flow, diffusion, and filling patterns during the grouting process. A foundational three-dimensional geological model for soil karst cave foundation treatment was developed by integrating subsurface geology, dynamic grouting hole data, and topography. By coupling this geological model with real-time grouting monitoring data and employing the Bingham constitutive model for cement grout, an integrated digital simulation method for the coupling of two stages of low-grade concrete pouring and sleeve-valve pipe grouting under digital construction was proposed. This methodology utilizes the finite difference method, true volume of fluid technique, and porous media theory. A sensitivity analysis was also performed to examine the influence of grouting pressure and water-cement ratio on the grout diffusion time and injection volume during filling. The findings demonstrate strong agreement between the simulated values of grout flow, filling, and diffusion within the karst cave and on-site measurements (the errors in the two-stage infusion volume were 6.4% and 5.0%, respectively). This integrated approach provides an effective means of optimizing grouting parameters and enables comprehensive quality control throughout the soil karst cave foundation grouting process.

This work investigates the temperature increase effect of heating gravel-clay mixed with phase change material (GC-PCM) via air circulation during large-scale production. Due to the low initial temperature of clay stockpiled outdoors during winter, the anti-freezing performance of GC-PCM is limited and cannot prevent GC-PCM from freeze-thaw damage. Thus, it is important to increase the temperature of GC-PCM to meet the initial temperature requirement for core wall construction in winter. In this work, the equivalent physical and thermal parameters of GC-PCM are derived considering its loose coefficient. In addition, a numerical simulation method for the heating process via air circulation during large-scale production of GC-PCM is proposed according to the indoor test results. Then, numerical models for the indoor test and a GC-PCM strip are established, and various heating processes of a GC-PCM strip under different temperatures of the hot air blower and bottom heat source are simulated. Finally, a factor analysis method for heating GC-PCM via air circulation during large-scale production is proposed and a multiple regression model is established for the heating time with initial clay temperature, hot air blower temperature and bottom heat source temperature. The RMSE between the numerical and measured temperature values in the indoor test of heating GC-GCM was 0.16 degrees C 0.55 degrees C and the R2 of the multiple regression model was 0.99 with a relative deviation of -3.4% 9.8%. The results show that the numerical simulation method for heating GC-PCM via air circulation is validated by the indoor test results, and the heating time is mostly affected by the initial clay temperature, hot air blower temperature, and bottom heat source temperature. This work provides a basis to determine the specific heating procedure in the large-scale application of GC-PCM for the core-wall construction in winter.

An ellipsoid element method was used to construct irregular polyhedral rockfill particles of arbitrary shapes, and a flexible boundary method was adopted to simulate the flexible membranes of triaxial specimens. A discrete element method (DEM) was proposed for triaxial wetting tests of rockfills. Based on the DEM, a numerical study was conducted to investigate the wetting mechanical behavior of rockfill under different compaction quality (porosity or dry density) levels, and the influence of compaction quality on macroscopic characteristics, such as axial wetting deformation and volumetric wetting deformation, was analyzed. Furthermore, the evolution law of the microscopic characteristics, including the coordination number, Euler angles, and contact fabric within the rockfill during different wetting stages, was analyzed to provide a micromechanical explanation for the wetting deformation source of the rockfill. Thus, a new wetting deformation constitutive model considering the compaction quality was proposed, which significantly improved the accuracy of the wetting deformation representation compared with the traditional model. This study provides prerequisites and technical support for the precise simulation and prediction of the wetting behavior of dam structures during reservoir impoundment.

With the construction of asphalt concrete faced rockfill dams gradually expanding into high-altitude and cold regions, these dams are increasingly challenged by harsh winter conditions during service. Hydraulic Electrically Conductive Asphalt Concrete (HECAC) is a type of hydraulic asphalt concrete modified with conductive materials to enhance its functionality and the requirements for the mechanical properties and anti-seepage performance of HECAC are different from those of conventional pavement asphalt concrete. In this study, the engineering and electrothermal properties of HECAC were experimentally investigated to assess its feasibility as a novel dam construction material. The test results indicated that HECAC meets the impermeability requirements specified in current technical standards. In terms of mechanical performance, the incorporation of steel fibers and steel slag improved the flexural and compressive strength of the asphalt concrete. However, the addition of graphite was found to weaken its mechanical properties. The addition of steel slag can enhance the strength of the specimen's framework and the bonding strength. When the content of steel slag increases from 18 % to 72 %, the compressive strength of the specimen rises from 2.156 MPa to 3.418 MPa, with an increase of 59 %. With increasing content of conductive materials, specimens with excellent electrical conductivity were produced, exhibiting a minimum resistivity of 5.11 Omega & sdot;m. Under a -25 degrees C ambient temperature, the specimen with the optimal electrical conductivity reached center and surface temperatures of 33.1 degrees C and 16.3 degrees C, respectively, after 2.5 h of power supply. Furthermore, an electro-thermal coupling simulation analysis of HECAC panel shows electric heating effectively raise the panel temperature by 9.5 degrees C under a typical 7-day low ambient temperature condition, thereby preventing frost cracking.

Construction workers of long tunnel projects are confronted with numerous safety hazards such as fall from height (FFH) and object strike due to the harsh jobsite environment, limited space, and complex working conditions. And the absence of protective guardrails is identified as the primary cause of falling accidents from height. In order to automatically detect the safety protection status of working-at-high workers, a computer vision-based recognition method for working-at-high operation safety protection according to target detection and spatial relationship was proposed in this study. Firstly, the Cycle-consistent Generative Adversarial Networks (CycleGAN) was used to preprocess construction site images to enhance the image quality. Secondly, a YOLOv8 model integrated with the coordinate attention (CA) module was established to rapidly detect targets such as workers, trolleys, and guardrails in the tunnel. Furthermore, an identification method for working-at-high operation safety protection is proposed based on the detected targets and their spatial relationships. Finally, a case study was conducted, revealing that the model achieves an accuracy and recall rate of 95.89% and 97.22%, respectively, in identifying the safety protection status of working-at-high workers. The result indicates that the proposed method provides a new way for intelligent identification of working-at-high operation safety protection and assisting on-site management personnel to prevent the risk of FFH in the tunnel.

A numerical method is proposed to analyze the long-term structural behavior of concrete face rockfill dams (CFRDs), considering fluid-solid coupling and the spatial variability of model parameters. Initially, a method was explored for calculating the wetting deformation of rockfill within a CFRD, considering an effective stress framework and fluid-solid coupling. Subsequently, the wetting model was implemented into a FEM subroutine. Next, volumetric and axial creep curves were derived from triaxial creep tests conducted at varying porosities. Based on these test results, an enhanced creep model with higher accuracy was formulated and integrated into a finite-element calculation program. Furthermore, regression models were developed to assess the relationship between rockfill compaction quality and improved creep model parameters. The Particle Swarm Optimization (PSO)-Kriging method was employed to estimate the dam's global compaction quality. Moreover, spatial estimation of improved creep model parameters and refined assignment of FEM parameters were achieved. This refinement led to an enhanced simulation of CFRD, accounting for the wetting effect of dam materials and the spatial variability of model parameters under fluid-solid coupling. Finally, verification using a specific engineering case study demonstrated that the wetting effect of rockfill caused by impoundment and the spatial variability of creep model parameters can substantially enhance calculation accuracy. Consequently, the proposed method significantly contributes to predicting the long-term deformation of CFRD and ensuring the service safety of antiseepage concrete faces. In addition, it provides a more dependable technical method for analyzing the structural performance of CFRDs throughout their entire life cycle.

Construction quality is of upmost importance for delivering well-performed civil structures. Inspection offers critical means to ensure construction quality. However, its effective implementation relies on an excess of domain knowledge that usually takes years to accumulate, making inspection expensive and challenging to conduct. This paper introduces a construction quality inspection knowledge base that empowers inspectors with easily accessible and intuitive construction requirement information. Natural language processing (NLP) is applied to automatically extract knowledge from construction documents such as specification and regulatory files. The extracted knowledge is linked to the building information model (BIM) using proposed association methods and semantic similarity matching. The natural language-extracted and BIM-referenced knowledge base (NLBIM-KB) is integrated into an augmented reality (AR) interface, which provides a freehand tool to assist inspectors' decision-making via on-demand construction knowledge extraction.

Based on actual environmental temperature changes and the influence of concrete hydration heat release, a model for the temperature field during the construction of concrete face rockfill dams (CFRDs) was developed. Considering the influence of elastic modulus changes, dry shrinkage, creep, and other factors on the initial concrete pouring stage, a thermal-mechanical coupling model of the concrete face was established through secondary program development. Additionally, a finite element method (FEM)-extended finite element method (XFEM) model coupled with a multi-crack simulation considering the temperature change and long-term deformation of the rockfill was proposed. Through the verification of engineering examples, the performance response of the concrete face under the influence of multiple complex factors, such as ambient temperature changes, concrete face characteristics variations, and rockfill creep, was analyzed. The crack formation mechanism in a concrete face during construction was revealed, and specific engineering measures for the crack resistance of the concrete face were proposed. The findings of this study provide a more reliable technical approach for the accurate analysis of the structural behavior of CFRDs and crack prevention in concrete faces.

Long-distance tunnel construction involves a sequence of construction operations that are influenced by various uncertain factors. Accurate operation duration prediction is critical to inform long-distance tunnel construction management and decision-making. In this study, a novel operation duration prediction method called random forest improved by whale optimization algorithm (WOA-RF) is proposed by considering geological conditions-the most significant uncertain factor in long-distance tunnel construction. Firstly, a geological uncertainty prediction model was established to estimate probability of geological conditions along the tunnel. Secondly, factors influencing the durations of five key construction operations, i.e., drilling, charge blasting, mucking, supporting steel frame, and shotcrete were analyzed. A prediction model for the concerned operation durations was established using the WOA-RF. Furthermore, considering the uncertainty of tunnel geological conditions, a method for calculating the expected operation duration related to a certain geological condition was proposed. Effectiveness of the proposed WOA-RF model is demonstrated in a case study, showing better performance in terms of average absolute error, root mean square error, and determination coefficient than RF model. The proposed approach can be used to inform the arrival time of the subsequent team in real time during construction, and predict the construction progress to provide a scientific basis for scheduling and timely controlling the long-distance tunnel construction progress under geological uncertainties.

The cross-scale approach based on the finite element method (FEM) and discrete element method (DEM) was employed to investigate the effects of different particle shapes and stress conditions on axial deviatoric stress during wetting. A DEM modeling framework was proposed to simulate the wetting tests considering different particle shapes. The Effect of varying particle shapes on the stress-strain and volumetric strain behavior of rockfill materials during the wetting process was investigated. Moreover, the study analyzed macroscopic characteristics such as axial and volumetric wetting deformation under triaxial test conditions. Furthermore, the mesoscopic mechanisms influencing the wetting behavior of rockfill materials were investigated using internal sample features such as Euler angles, coordination number, and contact fabric distribution. Finally, a wetting constitutive model incorporating particle shape characterization indices was proposed and validated across multiple scales. This study provides a novel approach for the accurate evaluation and safety control of the structural behavior of high rockfill dams.

Thermal vacuum environment simulation device has high requirements for safety control, real-time and accurate analysis of stress and deformation of the device is an important prerequisite to ensure its safe operation. Aiming at the problems of the high time cost required for physics-driven models and the difficulty to reflect the physical mechanism of data-driven models, a physical-data-driven analysis method of thermal vacuum environment simulation device safety behavior was proposed. Firstly, based on the thermo-mechanical coupling theory, a physical-driven numerical simulation model of the vacuum device was established to simulate the stress and deformation. Furthermore, a data-driven deep learning model (GNN-LSTM) was established and the safety behavior of the vacuum device was analyzed in combination with the measured data. Finally, the fusion analysis results were obtained by assigning dynamic weights to physical-driven and data-driven results based on the Improved Particle Swarm Optimization algorithm (IPSO). The results show that the predictions of stress and axial deformation obtained by the proposed method have higher accuracy compared to traditional physical-driven or data-driven methods, which can provide a basis for the safety control of vacuum device operations.

During winter construction of earthworks such as earth dams and embankments, the structural properties of the soil may deteriorate due to freeze-thaw cycles. A new measure to combat freeze-thaw damage, incorporating phase change materials (PCMs) into the soil to regulate temperature, has been verified and applied in roadbed and pavement engineering. However, the law of deterioration from freeze-thaw cycles for this novel construction material is not clear yet. This study investigated the characteristics and mechanism of deterioration of clay mixed with paraffin-based PCM (PPCM-clay) through freezing and thawing using freeze-thaw tests, unconfined compression tests, permeability tests, and macro-micro structural analysis. The results show that the freeze-thaw resistance of PPCM-clay is better than that of pure soil. The amount of PPCM added is proportional to the effect of inhibiting soil strength and permeability degradation. Under the same number of freeze-thaw cycles, the compressive strength of PPCM-clay is greater than that of pure soil. Micropore expansion and frost heave are also not significant in PPCM-clay. This indicates that the low initial water content, relatively large porosity, thermal hysteresis, frost contraction, hydrophobicity, and high viscosity of PPCMs are the main reasons for the improvement in PPCM-clay freeze-thaw resistance. These findings provide a theoretical basis for the potential application of PPCM-clay as a dam or embankment material for weakening soil frost damage in winter construction in cold regions.