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Constructing large-section underground structures using the pipe jacking technique presents challenges, including the insufficient size of the rectangular pipe-jacking machine and the transportation and hoisting of large prefabricated ring structures. This paper introduces and investigates the construction, challenges, and key techniques involved in jacking a super-large rectangular prefabricated tunnel underpass a rainwater box culvert. The adoption of an assembly concept for manufacturing both the super-large rectangular pipe-jacking machine and ring structures, along with innovative in-shaft assembly and jacking techniques, effectively addresses issues in super-large section pipe-jacking engineering. The on-site monitoring data analysis reveals that the jacking force for the super-large rectangular tunnel significantly exceeds the estimated value. This is primarily attributed to excessive resistance during jacking in the reinforcement areas of the launching and receiving shafts, constituting 55 % of the total jacking force. Additionally, the jacking resistance from the soil chamber pressure accounts for approximately 22 % of the total force. The frictional resistance of the ring structures represents only 23 % of the total jacking force, with the average surface friction force approximately at 12.4 kPa. Vertical and horizontal relative deviations of the tunnel were controlled at 32 mm and 22 mm, respectively. The settlements of the ground surface and box culvert induced by pipe-jacking were vulnerable to the grouting pressure of lubricants, with maximum values of 35.9 mm and 39.1 mm, respectively. The experience learnt from this project can provide valuable insights for the application of large-section rectangular pipe-jacking technology in underground space development. [ABSTRACT FROM AUTHOR]

[Display omitted] • The study proposed YOLOv8-CM, a novel framework that integrates YOLOv8 and CBAM to accurately detect 10 different defects/objects and segment 9 different tunnel defects, excluding small cracks and critical maintenance objects. • A hybrid approach, integrating the strengths of YOLOv8-CM and U-Net, was specifically engineered to address the challenges of pixel-wise segmentation of crack features in environments characterized by low resolution or complex backgrounds. • YOLOv8-CM achieved a mean average precision (mAP) of 0.908 for detection and 0.890 for segmentation across all 10 objects, with an IoU of 0.712, outperforming YOLOv8, YOLOv7, YOLOv5, and Detectron2. Tunnel maintenance is essential for ensuring the safety and health of urban transportation systems. However, traditional inspection methods are labor-intensive, time-consuming, and prone to human errors. In this paper, a YOLOv8-CM framework is proposed, which integrates You Only Look Once v8 (YOLOv8) and Convolutional Block Attention Module (CBAM) to automate the detection and segmentation of various defects and other critical objects in tunnels. Segment Anything Model (SAM) was used to generate accurate polygon masks for annotated features. U-shaped Network (U-net) was adopted to segment pixel-wise features of cracks in low-resolution images by processing split images detected by YOLOv8-CM. Common tunnel defects like cracks, water seepage, spalling, and rebar exposure, alongside essential maintenance objects such as repaired spalling, seam joints, bolted connections, stains, markings, and pipelines, all of which are primary concerns for tunnel maintenance personnel, are successfully detected and segmented. Results show that YOLOv8-CM outperforms YOLOv8, YOLOv7, and YOLOv5 in terms of mean average precision (mAP), achieving 0.908 for detection and 0.890 for segmentation of all objects. The highest predicted detection and segmentation accuracies are achieved by bolted connections, reaching 0.976 and 0.990, respectively. While cracks exhibit the lowest prediction precision, the attained accuracies of 0.746 for detection and 0.747 for segmentation remain noteworthy. Additionally, YOLOv8-CM exhibits higher detection and segmentation accuracy than Detectron2, particularly in detecting intricate defects like water seepage and spalling. The proposed YOLOv8-CM framework demonstrates effective capabilities in detecting and segmenting vital maintenance defects, showing its promising potential as a tool for intelligent tunnel monitoring. [ABSTRACT FROM AUTHOR]

• Investigate platform-based stable truck matching problem with trailer-swapping mode. • Construct preference list based on chain-data structure to obtain stable matching scheme. • Develop iterative preference-list-trim heuristic to efficiently solve problem. • Evaluate the efficiency, applicability, and sensitivity of the trailer-swapping mode. This study investigates the platform-based stable truck-matching problem with trailer-swapping mode (STMP-TSM). The TSM is a novel collaborative transportation approach in which trucks participate in trailer swapping, significantly decreasing the rate of empty trucks and reducing transportation costs. In the STMP-TSM, a platform delivers a trailer-swapping scheme that satisfies all participating trucks. Correspondingly, an integer linear programming model is developed to maximize the total truck utility of the STMP-TSM. A specific preference list based on a chain-data structure is meticulously constructed to obtain a stable matching scheme. The preference list enables more generalized truck matching. In addition, a series of acceleration strategies is proposed to expedite the generation of a preference list while effectively reducing its length. An iterative preference-list-trim heuristic algorithm is designed, which strategically trims chains in the preference list to solve the STMP-TSM efficiently. As a benchmark, an integer linear programming model is developed based on the preference list to solve the truck-matching problem using the TSM. Finally, a series of numerical experiments are conducted to evaluate the performance of the proposed algorithm, assess the practicality of the TSM, and analyze the influences of the key parameters. [ABSTRACT FROM AUTHOR]

The oldest salpingid beetle is discovered from the mid-Cretaceous Myanmar amber: Cretoprostominia myanmarensis Jiang, Liu and Chen gen. et. sp. nov. The new genus is most similar to the extant genus Prostominia Reitter, 1889 and differs from the latter by the narrowly separated procoxae. The new discovery enriches our knowledge of the evolutionary history of the family Salpingidae. [ABSTRACT FROM AUTHOR]

• Prefabrication restoration was proposed for ocean engineering resilience. • Full-scale experiments were conducted on pile-beam joints. • Pile-beam joint showed semi-rigid with an interface weak link. • Joint model (PJAM) was developed for parametric quantitative mechanical assessment. • PJAM has a promising parameter decision-making capability for actual project. Ocean engineering structures are susceptible to severe damage caused by adverse weather conditions. The question of accelerating post-disaster restoration is the focus for ocean engineering resilience. In this regard, this study proposed the prefabrication restoration technology and investigated the mechanical properties of the key pile-beam joint. Full-scale experiments are conducted to analyze the pile-beam joint, followed by the development of the Pile-beam Joint Assessment Model (PJAM) for mechanical assessment. PJAM is subsequently applied to evaluate a restoration case at Shantou Port, facilitating informed decision-making. The main findings are as follows: (1) The flexural performance of the pile-beam joint is crucial in prefabrication restoration as it influences the assembly performance and impact resilience of the new-old structure. (2) Stiffness reduction in the pile-beam joint is primarily attributed to interface weakness, resulting in stiffness and bearing capacity values of 64.3 % and 95.5 %, respectively, compared to the cast- in-situ joint. (3) Elastic and plastic properties of the pile-beam joint are governed by the compression interface and rebar properties, respectively. The compression interface size significantly enhances joint performance, while rebar properties affect ultimate bearing capacity and ductility. (4) PJAM enables a parametric quantitative assessment of pile-beam joints. In the case study, a 31 % size enlargement scheme combined with a 51 % rebar arrangement is identified as achieving performance comparable to the cast- in-situ joint. This research addresses the critical joint challenge in prefabrication restoration, providing a theoretical basis and practical demonstration to enhance post-disaster resilience in ocean engineering structures. [ABSTRACT FROM AUTHOR]

[Display omitted] • Full-scale experiments were conducted on precast hollow components (PHC). • Large cavity setting may result in insufficient performance redundancy. • Hollow-section effect only manifested in the PHCs with robust joint. • The proposed mechanical model agreed with the tests. • The actual project with final optimal parameters achieved promising benefits. Full-assembled underground station (FUS) is a novel prefabricated underground station that fully uses assembled precast hollow components (PHC). The PHC with joint constraint and hollow-section effects determines the performance of the FUS. This study foremost conducted a multigroup full-scale experimental study on PHCs. A finite element analysis was performed to analyzed the relationship between joint constraint effect and hollow-section effect. A mechanical model of the assembled PHC was proposed. The hollow-section effect of PHC was assessed, and the results were applied to FUS. The main conclusions are as follows. (1) The performance of the PHC with the proper hollow-section size ratio (SR) meets the design requirements, whereas one with large SR may cause insufficient performance redundancy. (2) The bending performance of assembled PHC strengthens with the increase of joint constraint. The hollow-section effect only manifests in the PHCs with robust joint. (3) An SR ≤ 0.5 has a limited effect on PHC performance, whereas an SR ≥ 0.5 accelerates performance degradation. Furthermore, the hollow-section distribution rate (DR) presents a competing relationship between the PHC performance and weight reduction. (4) The application of the mechanical model on Shenzhen Metro FUS achieved promising benefits. The mechanical properties of PHC were comparable to those of solid components with sufficient weight reduction. This study provides technical guidance for the development of Shenzhen Metro and facilitates FUS application in low-carbon cities. [ABSTRACT FROM AUTHOR]

Prefabricated buildings (PBs) have attracted significant attention in the global construction field due to their remarkable environmental and social benefits. How to internalize the carbon emission reduction benefits brought by PBs into economic benefits, and then transform the PB promotion from government departments or state-owned enterprises to the whole market is an urgent problem to be solved. To find a market-oriented tool for internalizing the carbon emission reduction benefits, and to explore the impact of the current prevailing carbon emission trading scheme (ETS) on the construction industry, this study establishes a tripartite evolutionary game model for PB adoption and simulates the dynamic strategy evolution of the government and heterogeneous developers through numerical simulation. Findings indicate that low-carbon market demand, low-carbon synergy and carbon price have a positive impact on PB adoption. Meanwhile, it is recommended to include the construction industry in the ETS when carbon prices reach 110 RMB/t. Under the ETS, while the government could eliminate subsidies for PBs to alleviate financial pressure, the behavior of developers participating in the ETS needs to be monitored. Research findings provide insights for developers to participate in carbon trading markets and for governments to develop carbon trading mechanisms applicable to PBs. [Display omitted] • A tripartite evolutionary game model is established to promote PB adoption under ETS. • Low carbon market could foster PB adoption, especially for strong prefabrication developers. • Optimal time to integrate the construction industry into CTM: Carbon price ≥110 RMB/t. • Under ETS, government could discontinue subsidies and strengthen CTM for PB adoption. [ABSTRACT FROM AUTHOR]

• An automatic monitoring-control framework for excavation is proposed. • An automatic monitoring-control system is established with the IoT technology. • Successful application to an ultra-deep excavation extremely adjacent to the tunnels. • A well-documented field data is presented. This paper proposes an automatic monitoring and control system to control the construction disturbances of an ultra-deep foundation pit extremely adjacent to the operational metro tunnels. By real-time monitoring the structural response of tunnels and foundation pits, the reinjection wells and servo support system were automatically controlled to change the groundwater level and support axial force, respectively. All the relevant monitoring and control equipment was integrated into the system through Internet of Things technology. The field observations revealed that the proposed automatic monitoring-control system and framework can well control the excavation disturbance in adjacent metro tunnels. Under the ultra-deep excavation depth of 42.25 m and ultra-close spacing of 3.0 m, the maximum absolute value of the observed tunnel displacement was less than 5 mm. All the relevant structural responses of the tunnel and foundation pit were within limits. The wall deformation of the servo side is different from the common bulging deformation curve and is approximately 2 times smaller compared to the non-servo side. The observed tunnel deformation mainly changed at the excavation stage within the buried depth of tunnels. The presented system, data, advised control index and framework can provide useful guidance for similar scenarios. [ABSTRACT FROM AUTHOR]