The fracture characteristics of the excavation damage zones (EDZs) of deeply buried tunnels are closely related to energy evolution, and they are highly valuable for support design. Advanced numerical simulation techniques have shown the potential for evaluating the EDZ properties. On the basis of the finite-discrete element method (FDEM) and Poisson’s random block generation technique, the virtual block model (VBM) is proposed to characterize the intact rock masses surrounding tunnels. Moreover, a virtual block upscale principle is proposed to determine the geometric and meso-mechanical parameters. The Canadian Underground Research Laboratory and China Jinping Underground Laboratory Phase II (CJPL-II) project excavations are simulated, and the excavation-induced fracture characteristics of the surrounding rock masses are analyzed in detail. The VBM captures the tensile, shear, and mixed fracture properties under excavation-induced confining pressure evolution. Then, the thicknesses of the spalling rock slabs in Lab #7 of the CJPL-II project are evaluated via the Otsu method. Combined with onsite monitoring data, the validity and advancement of the VBM are verified. This study expands the applicability of the FDEM and provides a new method for assessing the EDZs of surrounding rocks.
Singapore, a land- and resource-scarce nation, serves as a global example of how low-carbon initiatives can drive the sustainable development of underground space in densely populated urban environments. This critical review highlights major low-carbon efforts from both academia and the industry over the past decade, along with supportive policies that integrate these efforts into governance and decision-making processes. These efforts, including cutting carbon emissions through material efficiency, shaping carbon emissions through digitalized construction, and tracking carbon emissions through sustainable operation, not only reflect the national efforts to carbon reduction across the full lifecycle of underground infrastructure but also offer valuable insights for similar urban settings worldwide. Furthermore, the review identifies the development of a well-defined framework for lifecycle carbon assessment as an overarching trend to promote carbon reduction in underground space development. However, significant challenges remain, such as the need for comprehensive data collection and integration, as well as a deeper understanding of how human behavior interacts with operational efficiency. Addressing these challenges requires interdisciplinary collaborations among government agencies, academic researchers, and industry practitioners to develop robust frameworks and dynamic models that more reliably capture the impact of low-carbon strategies on urban underground environments.
Energy geostructures represent a novel building energy-saving technology derived from ground source heat pump technology. Heat transfer and thermo-mechanical response characteristics stand out as pivotal issues in the investigation and design of such energy geostructures. This paper provides an overview of the research on heat transfer models, factors influencing heat exchange performance, and thermo-mechanical behaviour concerning energy piles, energy walls, and energy tunnels. The future perspectives are also presented. Four types consisting of ten basic heat transfer models for energy piles were summarized, and their advantages, limitations, and applicable scenarios were comprehensively discussed from multiple aspects. The heat transfer models for energy walls and energy tunnels are scarce, and only one model was introduced for each of them. The influences of some controllable design parameters on the thermal performance of energy geostructures and the thermal-induced mechanical behaviour were summarized. The key conclusions are that the fluid flow rate should not be too high or too low, which is generally considered sufficient to ensure that the flow state is turbulent; and properly intermittent operation is beneficial to the recovery of geothermy, thereby improving the heat exchange performance. Due to the differing conditions considered, it is not possible to draw a definitive conclusion regarding whether heating can increase or decrease the shaft resistance or bearing capacity of energy piles. Generally, thermal effects within energy walls are unlikely to cause severe damage to structural stability. The issues related to thermal-induced ground deformation are considered more critical than those concerning the energy tunnel structure deformation. This paper highlights the aspects that require further research and the new aspects worth exploring in the future. Energy geostructures are not limited to new construction projects, and combining with other renewable energy utilization methods and integrating into district energy networks are the future development trends.
Water and soil gushing in shield tunnels pose a significant risk to tunnel structure safety. However, it is challenging to fully capture the evolution of the mechanical response of tunnel structures due to the limitations of conventional numerical methods in simulating large soil deformations around the tunnel due to gushing. This paper developed a coupled material point method (MPM) and finite element method (FEM) approach for water and soil gushing, where MPM was for modelling the soil deformation and FEM was for modelling the tunnel response. The developed approach was utilized to conduct the gushing-induced large deformation analyses and generate the varying soil and water pressures acting on the tunnel lining. Meanwhile, structural internal forces and joint deformations were identified based on the load-structure method. The findings suggest that the gushing process can be categorized into three stages: initial developing, rapid developing, and stable developing stages. The soil and water pressures around the gushing point decreased abruptly during the “rapid developing stage”, but the soil pressures on the tunnel crown and tunnel invert increase, causing a sharp rise in the bending moment of the lining and severe joint deformations, particularly at joints No. 2 and No. 3. Finally, the parametric analyses show that a lower gushing location, deeper tunnel depth, and higher soil shear strength will all exacerbate the influence of water-soil gushing on tunnel structural response, due to variations in the soil and water pressures acting on the tunnel lining throughout the whole process of gushing. These findings underscore the importance of revealing the evolution of tunnel responses to water-soil gushing for maintaining tunnel safety.
Masonry arch bridges serve as essential transport infrastructure and are often protected as cultural heritage sites. While most studies emphasize their response to vertical loading, limited attention has been given to their behavior under the influence of nearby tunnel excavation. This study investigates the interaction between tunnel-induced ground movement and masonry arch bridges through physical model tests and numerical simulations. Two typical arch bridge types are examined to assess deformation patterns caused by tunneling. A coupled discrete element and finite difference method is proposed to simulate soil-structure interactions, and the model is validated against experimental results. The results highlight that the arch span has a major impact on soil behavior. Larger spans lead to wider settlement zones and more uniform stress distribution but increase structural vulnerability. Semi-circular arches develop tensile strain at the crown and compressive strain at the foot under tunneling. Meanwhile, the joint displacements follow a three-dimensional Gaussian distribution, influenced by tunnel volume loss and burial depth, especially in circular arches. Increasing Young’s modulus and joint shear stiffness of masonry arch bridges through technical means, such as grouting, is helpful to reduce deformation and cracking. These findings support risk assessment and design improvements for masonry bridges in tunneling environments.
Recognizing the formidable challenge of achieving millimeter-level precision in controlling shield machine attitudes amidst thrust forces exceeding thousands of tons on a global scale, a thrust-vectoring automatic shield tunneling technology was introduced to effectively mitigate potential inaccuracies stemming from human intervention. Initially, a load-thrust “dual-vector” motion control mechanism was adopted, grounded in defining the shield thrust vector and establishing the interactive correlation between shield attitude deviation points and thrust action points in both horizontal and vertical orientations through comprehensive data assessments. Subsequently, a parallel proportional-integral-derivative control law was devised for stability control of shield machines, delineating the functional link between alterations in shield attitudes and displacements of thrust action points, with initial validation conducted via full-scale model trials. A motion trajectory for correcting shield attitudes was devised, and a thrust vector control approach was formulated by amalgamating feedforward calculations with feedback adjustments. The application of this thrust-vectoring automatic tunneling technology in a large-diameter shield tunneling endeavor yielded the subsequent key findings: a consistent deviation of approximately 2.5% was upheld between target and actual thrust forces, with actual shield velocity managed within a -1 to +1 mm/min range from the target value. To ensure robust steering capability of the shield machine, target thrust moments in both horizontal and vertical directions marginally exceeded actual values, with satisfactory execution. The interplay between shield attitudes and thrust action points in both horizontal and vertical dimensions exhibited a characteristic akin to “sugar-coated haws on a stick”. Despite notable “kowtow” occurrences during segment assembly, statistical analysis indicated that deviations in shield attitude in horizontal and vertical planes were ultimately contained within -20 to +5 mm and -45 to -28 mm ranges, respectively, markedly surpassing average manual control standards.
The unclear response law of rock-cutterhead interaction seriously limits the tunnel boring machine (TBM) efficiency. Various influencing factors make it difficult to illustrate the law using the TBM tunnelling results in the field. In the present study, we develop a novel TBM tunnelling test platform (DGTBM-A) to analyze rock-cutterhead interaction. The components and functions of the platform are introduced. The cubic sandstone specimens (500 mm ×500 mm × 500 mm) with three distinct uniaxial compressive strengths (low (24.94 MPa), medium (61.22 MPa), and high (95.04 MPa) are used for TBM tunnelling test. The effects of cutterhead thrust, rotational speed and rock strength on the rock-cutterhead interaction are examined. Key tunnelling parameters, TBM performance indices, and rock muck characteristics are analyzed to reflect their effects. The findings revealed significant impacts of cutterhead thrust, rotational speed and rock strength on torque, advance rate, penetration rate, specific energy, and field penetration index. Additionally, the characteristics of the produced rock muck varied with the applied tunnelling parameters, providing insights into the efficiency and effectiveness of rock breaking. Correlations between the TBM performance indices and the influencing factors are established. The results contribute to a better understanding of the mechanics involved in TBM tunnelling in sandstone, aiding in optimizing operational parameters for improved performance and cost-efficiency in engineering practice.
Tunnel lining seismic performance is significantly influenced by the spatial variability of geological parameters and the uncertainty of earthquake excitation factors, which are conventionally treated in isolation. This study proposes a novel probabilistic framework that integrates random field theory with an enhanced Clough-Penzien spectrum to concurrently model both uncertainty sources. The approach offers a more realistic and integrated assessment of seismic risk for tunnels under complex geological and loading conditions. The case analysis of a railway project reveals that considering both spatial variability of rock mass and uncertainty in seismic excitation leads to significant increases in internal forces and their variability, with mean values rising up to 278.9% and coefficients of variation (COV) up to 262.8%, compared to single-factor random analyses. The non-normal distribution of responses under seismic uncertainty, combined with the broader dispersion from rock variability, necessitates integrating both random factors for reliable seismic performance assessment of tunnels. Parametric studies demonstrate spectral parameters, including initial circular frequency (ω0), equivalent damping ratio (ξ0), and peak acceleration (amax), significantly influence results: increasing ω0 and ξ0 markedly reduces both the mean and COV of lining mechanical response-by up to 83.5% and 82.5%, respectively-potentially underestimating failure risk and underscoring the need to adopt lower-bound values in design for enhanced safety. Meanwhile, amax positively correlates with mean structural response, while variability in internal forces follows distinct trajectories; moreover, the interaction between rock spatial variability and seismic uncertainty raises failure probabilities by 3%-38%, emphasizing the necessity of integrating both randomness sources, especially in high-intensity seismic regions.
Joint deformation is a key factor controlling the mechanical behavior of discontinuous rock strata under changing stress conditions, including dominating the elastic deformation in near-surface excavations and serving as a major component of settlement under higher stress. This study, focusing on joint deformation behavior, investigates the effect of joint roughness on the peak stress and failure modes of specimens under uniaxial compression. Rock-like specimens with two layers of parallel, nonpersistent joints, one rough, were fabricated using 3D printing technology. Digital image correlation was used to capture real-time surface displacement fields, and a joint deformation analysis method was developed. The results show that joints exhibit staged, non-uniform closure and slip behavior, influenced by joint roughness, distribution of primary and secondary joints, and layered arrangement. Rough joints accelerate closure but hinder slip coordination, resulting in a three-stage loading process. In stage I, primary closure and layer-coordinated slip occur, accompanied by crack initiation, joint coalescence, and steady stress growth. Stage II involves secondary closure and overall coordinated slip, leading to localized failure and stress stabilization. Stage III is characterized by complete closure, uncoordinated slip, intensified crack propagation, and specimen failure, accompanied by stress hardening. The study reveals that joint deformation serves as a bridge linking roughness and peak strength. The average joint closure level and slip coordination are linearly negatively correlated with roughness but nonlinearly positively correlated with peak strength. Roughness restricts slip coordination, limiting crack propagation and delaying failure, which slows stress growth. Redistribution of joint aperture during slip reduces joint closure, weakens wall contact, and diminishes stress hardening.
The exponential increase in the number of new tunnels, their length, and complexity makes safe and comfortable driving in these infrastructures a must. Among all the technical characteristics necessary to achieve this target, accurate lighting is the most important. However, the peculiarities of driving in tunnels, narrowly linked to the infrastructure itself, but also to physiological and psychological characteristics of drivers, make good lighting complex and highly consuming in terms of energy, financial resources, use of raw materials, environmental impact, and maintenance. The relatively recent introduction of LEDs in tunnels and the new strategies to decrease energy demands and profit from sunlight, whose energy savings can reach 40% in a wide variety of cases, together with the progressive aging of drivers, are challenges for researchers in this field, that currently seek new perspectives affecting the tunnel, the roads before and after, and the portal surroundings. This work approaches the principles of tunnel lighting, its singularities, open points with difficult solutions, and some others that are already contributing to safer and more sustainable tunnels and underground roads.
Underground land and property information is currently recorded, registered, and managed using two-dimensional (2D) datasets provided in survey plans. There are significant communication challenges associated with fragmented 2D land and property data in complex underground projects. On the other hand, building information modelling (BIM) has been adopted for three-dimensional (3D) digital management of the lifecycle of built assets, including those of underground infrastructure. BIM can potentially provide a fully integrated 3D representation of rights, restrictions, and responsibilities for underground assets. Therefore, this study investigates the potential of BIM to support the development of 3D underground land administration (ULA) through an integrated data modelling approach. By reviewing the current body of knowledge, research challenges, and future pathways for adopting BIM-based approaches for 3D ULA data management are identified, specifically across legal, institutional, and technical dimensions. One key finding is the critical transition from current 2D approaches to BIM environments. This will lead to integrated and smooth information flow, which is critically important for more efficient ULA practices, enhancing communication among various stakeholders, improving decision-making in ULA, and contributing to sustainable underground space planning and development.
Urban underground space (UUS) development, guided by prudent planning, has emerged as a vital solution to the increasingly complex issues of urban built environments globally. Driven by the growing needs for human-centric urban design, low-carbon development, enhanced urban resilience, and alignment with sustainable development goals, UUS planning is rapidly shifting from experience-based approaches to evidence-based and data-driven methodologies. Yet, the broader landscape of this research field remains ambiguous, with the characteristics and future trajectories of such emerging planning technologies still to be clearly delineated. To this end, this systematic review delves into the burgeoning field of data-informed planning technologies for underground space (DIPTUS), examining how data-driven methods are revolutionizing the planning, design, and management of underground environments. Through a comprehensive bibliometric analysis of 134 articles published from 2014 to 2024, we identified key trends and mapped research themes within DIPTUS. Our narrative synthesis evaluated DIPTUS advancements across three dimensions: sensing and measurement, pattern and model, and planning and governance. The results indicate that DIPTUS exploits diverse data streams to quantitatively analyze UUS development. Utilizing advanced analytical tools such as spatial statistics, machine learning, and causal inference, these technologies uncover utilization patterns and planning optimization strategies. The review also underscores the increasing integration of planning and governance within DIPTUS, merging resource evaluation and demand forecasting, layout planning optimization, development benefits and spatial performance evaluation into a cohesive framework. Enhancements in 3D cadastral systems, innovative management models, and digital twin technologies further bolster this integrated approach. Despite significant strides, challenges in data integration, model complexity, and practical application persist. Lastly, we proposed a visionary framework to address these issues through interdisciplinary research and robust model development, aiming to fully harness DIPTUS’s transformative potential for sustainable, resilient, and human-centered urban environments.
Predicting the three-dimensional (3D) distributions of discontinuities within rock masses is crucial for evaluating tunnel stability. However, this task is challenging due to the inherent opacity of rock, which prevents the direct observation of discontinuities. Most current methods for predicting discontinuities are based on extracting the two-dimensional intersection lines of spatial discontinuities. In this paper, we propose a novel, purely visual approach to analyze and predict the 3D distributions of discontinuities in rock masses. In this method, a 3D model of the tunnel face is constructed based on motion prediction and multi-view stereo vision, and the development of discontinuities is then predicted. Each set of discontinuities is projected onto the virtual tunnel face using a convex hull algorithm, creating a virtual trace. A newly developed algorithm for predicting spatiotemporal sequences, which incorporates a self-attention mechanism and a zigzag recurrent transition mechanism, is then applied to predict the evolution of discontinuities. For testing and verification, we used smartphones to collect surface data on multiple sets of excavated rock from the Bimoyuan Tunnel in Sichuan, China. Extensive experiments involving these surface data demonstrated the effectiveness of our proposed method. The findings provide technical support for predicting tunnel collapse and ensuring tunnel safety.
To investigate surface settlement under the combined effect of foundation pit dewatering and excavation, a series of experiments was conducted using a scaled model of a deep foundation pit at a metro station. During experimental simulations of the dry excavation and dewatering processes, data were collected on surface settlement, water heads outside the pit, and deflection of the diaphragm wall. The characteristics of surface settlement were compared and analyzed under different conditions with a focus on the development of surface settlement during dewatering and excavation at key locations outside the pit. The combined effect of dewatering and excavation was found to increase surface settlement outside the pit and expand its area of influence. The insertion ratio of the diaphragm wall (n) significantly affected surface settlement; as the insertion ratio increased, surface settlement, along with its area of influence, decreased. For n < 1.25, the area beyond twice the excavation depth was considered a minor area of settlement influence. In contrast, for n ≥ 1.25, this area wasn’t classified as a minor area of settlement influence. As excavation depth increased, the surface settlement pattern outside the pit transitioned from triangle-type to groove-type, groove-type settlement occurred when As ≥ 1.6Ac, whereas triangle-type settlement occurred under other conditions (As represents the area of the deep inward part of the convex deformation of the diaphragm wall; Ac refers to the cantilever part of the diaphragm wall). This study provides insights into the development of surface settlement during dewatering and excavation and serves as a valuable reference for innovations in sustainable and resilient underground design.
Tunnelling is a challenging task due to a lack of full understanding of the surrounding rock quality. This study proposes a solution driven by a refined computer vision (CV) method, complemented by rock mass drilling tests and Bayesian networks, to address this issue through a multi-source heterogeneous data approach. Initially, improvements are made to the popular Swin Transformer to improve the recognition and segmentation of intricate rock features. Notably, refined smart CV, owing to its U-shaped architecture and smart window self-attention computation, exhibits segmentation performance superior to that of conventional CV methods such as Swin Transformer, Deeplab V3+, and UNet. Building upon the segmentation outcomes of the refined CV, a parameter set comprising apparent rock parameters is established. Then, two datasets encompassing rock internal drilling parameters and mechanics, as well as design parameters, are curated. The combination of the aforementioned parameter sets is referred to as the rock quality comprehensive evaluation dataset. However, analysis reveals data incompleteness issues within these datasets. To mitigate this problem, a novel tree-augmented Bayesian network is designed, and a prediction accuracy of 91% is realized, surpassing popular decision trees, ensemble learning, and deep learning methods. Furthermore, evaluation services are provided in mountain and submarine tunnels, suggesting that drilling parameters significantly enhance the evaluation performance. Moreover, employing two sensitivity analysis metrics underscores the prominent influence of rotating pressure and drilling speed parameters. This study endeavor presents diverse solutions for achieving precise and expeditious predictions of rock quality through various parameter sets, tailored to cater to diverse requirements of tunnels.
The urban metro system is a crucial infrastructure for sustainable urban development. However, ground engineering disturbances, such as foundation pit excavations and overloading, can cause damage to the metro structure, including cracks and water leakage. By integrating small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) technology, this study develops a preliminary risk assessment methodology for metro lines that are subjected to ground engineering disturbances. A relevant case from Changsha was proposed, spanning from January 2017 to July 2023, using a dataset of 147 Sentinel satellite images. Key findings include: (1) InSAR technology effectively monitors ground settlement, the areas with significant construction activities, the average annual settlement rate typically exceeds −6 mm/yr, with some regions reaching up to −10 mm/yr. In contrast, most areas without ground disturbance usually experience surface settlement not exceeding −2 mm/yr. (2) Satellite imagery analysis of metro areas with settlement differences greater than 20 mm revealed that most of these regions are influenced by foundation pit excavation, and some regions may be influenced by soil consolidation. (3) Overall, metro lines in Changsha have a low risk level, with certain areas classified as “high risk”. In the high-risk sections, Line 2 and Line 6 account for 32.7% and 20%, respectively, and regular inspections are required. This study would be beneficial to sustainable urban transportation.
Research into the mechanical behaviour of rock surrounding the deep-buried tunnel under multi-source dynamic disturbance is key to the safety of underground engineering operations. Based on a dynamic true-triaxial testing apparatus, the present study examined the mechanical behaviours and fracture mechanisms of deep granite under the coupled effects of intermediate-frequency dynamic disturbance (f = 300 Hz) and low-frequency dynamic disturbance (f = 5-20 Hz). Intermediate-frequency dynamic disturbance markedly initiates the genesis of tensile micro-cracks within rock, while low-frequency dynamic disturbance exacerbates the propagation and interconnection of cracks, ultimately leading to the formation of a tensile-shear mixed failure mode. The severity of the influence of intermediate-frequency disturbance on the peak strength of rock is the initial crack compaction σcc (decreased by 8.1%), the damage stress σcd (decreased by 6.4%), and the crack initiation stress σci (decreased by 4.7%) under different disturbance timings. This changes the characteristic stress of the rock and significantly decreases its brittleness index. Meanwhile, the low-frequency f of weak disturbance significantly affects the failure mode and peak strength of the rock. The peak strength σp exhibits U-shaped variation, with the maximum decrease reaching 15 MPa, which indicates the presence of a resonance effect between the external disturbance and the natural frequency of the rock. The timing of intermediate-frequency disturbance alters the natural frequency of the rock. Analysis of the fracture surface shows that cracks induced by intermediate-frequency disturbance primarily propagate along the σ1-direction, while low-frequency disturbance promotes propagation of shearing cracks along the σ3-direction. Brittle failure occurs due to the through-going shearing cracks. The results further reveal the synergistic mechanism of action of multi-source dynamic disturbance on rock failure, indicating that the coupled effects of multi-source dynamic disturbances significantly increase the risk of brittle failure in the rock mass.
The dynamic stress response of the surrounding rock in deep tunnels during contour blasting is first derived using elastic statics and dynamics theory alongside Fourier transform methods. This solution uniquely accounts for the effects of lateral stress coefficient, blasting loading, two-dimensional unloading, and the redistribution of static stress fields induced by internal free surfaces. Discrete element numerical simulations are also performed and cross-validated with the theoretical model. The study analyzes and discusses the effects of in-situ stress levels, lateral stress coefficients $k$, and internal radius ratio $\tilde{r} _0$ (ratio of internal free surface radius to tunnel radius) on the failure characteristics and mechanisms of surrounding rocks. The results indicate that increasing $\tilde{r} _0$ can reduce the unloading amplitude, thereby decreasing the dynamic circumferential compressive stress and circumferential cracking induced by unloading, especially under high in-situ stress. Under low stress levels, the maximum dynamic radial compressive stress during blasting decreases, reducing radial compression-shear failure. Simultaneously, the dynamic circumferential tensile stress is also reduced, thereby minimizing blasting-induced radial fractures. However, under extreme lateral stress conditions (k < 0.2), adjusting $\tilde{r} _0$ cannot cause the circumferential stress to exceed the radial stress at the tunnel contour along the maximum principal stress direction. As a result, an ideal contour blasting effect cannot be achieved, and failure continues to propagate radially. In conclusion, the derived dynamic blasting-unloading stress response, in relation to the internal radius ratio, provides theoretical analysis tools for understanding the failure characteristics and mechanisms of surrounding rock during contour blasting, serving as a foundation for optimizing blasting and support design.
Optimizing shield tunnel joints is essential to meet the evolving demands of modern construction, where balancing structural performance, environmental impact, and cost efficiency is increasingly important. Traditional cast iron joint (CIJ) has been widely used, but there remains significant room for improvement in terms of both their mechanical efficiency and sustainability. This study addresses these challenges by investigating two alternative designs: the single row sleeve joint (SRSJ) and the double row sleeve joint (DRSJ). The research focuses on evaluating their mechanical performance and potential to reduce carbon emissions and costs, offering a more comprehensive and future-forward solution compared to the traditional CIJ. Through experimental testing, key performance factors such as joint deflection, rotational angle, concrete strain, and bolt strain were analyzed alongside joint toughness, ductility, cracking patterns, embodied carbon, and material cost. Key findings revealed that SRSJ achieved 97% of CIJ’s ultimate bearing capacity, while DRSJ reached only 75%. In the elastic phase, SRSJ performed significantly better, supporting twice the load of CIJ. Bolt strain analysis showed that DRSJ experienced greater stress concentration, while SRSJ maintained balanced strain distribution. SRSJ also outperformed CIJ and DRSJ in toughness and ductility, particularly in rotational flexibility, exceeding CIJ by 76%. SRSJ and DRSJ all demonstrated lower embodied carbon and costs compared to CIJ, with reductions of up to 7.21% in emissions and 6.42% in costs. Overall, SRSJ emerged as a viable alternative, balancing mechanical performance, sustainability, and cost efficiency. In contrast, DRSJ’s stress concentration issues limited its effectiveness, making it less advantageous compared to CIJ.
Tunnels are critical transportation infrastructure, with >80% of their lifecycle carbon emissions from the design phase. Therefore, low-carbon design is a pathway to achieving “zero carbon” goals. However, multi-source and heterogeneous design information creates challenges because of tunnel carbon emission data silos. This study proposes a carbon emissions-structure-design framework with a multi-layered integrated structure for tunnel carbon footprint assessment, clarifying the relationships among design parameters, structural characteristics, and carbon emissions. Additionally, a design structure matrix-carbon footprint model is established to analyze the relationships between low-carbon design elements (LDEs) and the lifecycle carbon footprint. A model is developed to examine the nonlinear mechanisms by which LDEs affect carbon emissions. Case studies indicate that carbon emissions during the construction phase primarily arise from tunnel boring machine excavation, slag transportation, shotcreting, and tunnel lining. They are significantly influenced by LDEs, such as the surrounding rock grade, tunnel radius, advance rate, and slope, which exhibit threshold effects. In the operational phase, carbon emissions are dominated by train traction energy consumption, which increases with speed and decreases with radius. This is in contrast to the construction phase, where larger radii lead to higher emissions. This study integrates tunnel design parameters with lifecycle carbon emissions to overcome the limitations of traditional segmented approaches. The findings provide a decision-support framework for source-level emission reduction during the design phase, enabling engineers to predict carbon emissions for parameter combinations and offer a new strategy for achieving carbon neutrality in transportation infrastructure.
Automated subsurface utility detection systems in construction rely heavily on the quality of ground-penetrating radar (GPR) profiles, which are often degraded by high-amplitude horizontal interference. Existing low-rank decomposition methods lack the intelligence and flexibility required for multi-site data processing and involve labor-intensive parameter tuning, impeding their integration into intelligent construction workflows. To address these challenges, this paper proposes a horizontal interference suppression algorithm based on a diffusion model, termed GPR-HIDiff. The proposed model replaces conventional sequential convolutional operators with ResBlocks throughout the encoder, intermediate layer, and decoder of the UNet architecture, enhancing training stability. Lightweight agent attention modules are embedded between ResBlocks at each level to improve global information modeling capability. A spatial attention mechanism is deployed between the encoder and decoder to achieve adaptive spatial feature optimization. Furthermore, the forward diffusion phase adopts a cos$\theta $ schedule-based strategy to ensure a smooth temporal variation of noise variance. A standardized dataset comprising real-world measured samples and finite difference time domain simulation samples of urban road models has also been constructed. The effectiveness of the hybrid dataset, the introduced modules, the robustness analysis, and the cos$\theta $ schedule is validated through training with single/mixed datasets, ablation studies, evaluation of metric variations before and after the introduction of different noise levels, and comparative experiments with constant, linear, and cos$\theta $ schedules. Experimental results demonstrate that GPR-HIDiff significantly outperforms both traditional methods and state-of-the-art deep learning models on both simulated and real-world test samples. It effectively suppresses horizontal artifacts, preserves target hyperbolic contours, and avoids excessive reduction of target scattering, showcasing its exceptional performance. This method provides a powerful algorithmic foundation for high-resolution GPR imaging and target detection.
Driven by the “dual carbon” strategy, the functionality of coal mine underground reservoirs is transitioning toward multimedia collaborative storage, such as CO2 geological sequestration and strategic energy reserves. The microscopic structures of the coal pillar dams, which are subjected to mining-induced damage and long-term infiltration erosion by highly mineralized mine water, continuously deteriorate over time, posing significant risks to the long-term safety and stability of the reservoirs. This study, based on the Lingxin Coal Mine Underground Reservoir Demonstration Project, employs a multi-technique characterization approach including X-ray diffraction (XRD), scanning electron microscope, nuclear magnetic resonance, and computed tomography to systematically reveal the multiscale collaborative erosion mechanisms of highly mineralized mine water on the mineral composition, crystal structure, and pore development of coal pillar dams. The results indicate: (1) significant concentration-dependent deterioration of mineral composition and crystal structure; kaolinite hydrolysis had a weakening effect on XRD peaks while quartz remained inert; (2) initiation of progressive microstructural damage at boundaries via dissolution/loosening; this damage advanced through layered mineral delamination and pore development (evidenced by NMR T2 broadening), resulting in irreversible void formation with chloride precipitation; (3) formation of pore-throat halite crystals, primarily due to chloride ions (Cl-); these crystals propagated microfractures through salt-expansion stress, establishing a cyclic dissolution-migration-crystallization-cracking process; (4) triggering of accelerated deterioration of the coal matrix owing to prolonged retention; this induced time- and concentration-dependent expansion and interconnection of pore-fracture networks, resulting in geomechanical deterioration.