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Abstract Determining rock mass mechanical parameters and accurately predicting tunnel deformation during tunnel construction remain challenging tasks. This study introduces a novel approach to calculate the Geological Strength Index by integrating indoor rock mechanics tests with geometric data from three-dimensional dense reconstruction. We utilized the Hoek-Brown strength criterion to develop a theoretical model for predicting tunnel deformation in fractured rock masses. Case studies reveal that the average value of Geological Strength Index for the Xiamen highway tunnel’s surrounding rock is 44. With support from the lining structure equivalent to 0.002–0.02 times the initial in-situ stress, the plastic zone thickness decreased by approximately 50%, and radial displacement was reduced by about 40%. Enhancing the lining structure’s support pressure significantly reduces the plastic zone radius and radial displacement. As the Geological Strength Index decreases, the nonlinearity between support pressure and plastic zone radius becomes more pronounced, with a similar trend observed for the relationship between support pressure and tunnel radial displacement. The relative deviation between predicted and measured values did not exceed 1.69%. The method accurately captures the effects of rock fragmentation and tunnel construction on plastic zone formation and displacement, offering an effective approach for the rapid and secure assessment of rock tunnel excavation stability using digital technology.

Considering the effect of surrounding rock on lining in the design of tunnel lining within fractured rock masses is challenging, particularly in accurately predicting the reserved deformation of the tunnel. This study bases a rock mass classification method and the established Hoek–Brown (H-B) strength criterion to assess the deformation characteristics of the surrounding rock. It establishes a more scientifically rigorous theoretical calculation method for the reserved deformation of tunnel linings that accounts for the rock–lining interaction. An optimization design approach for the lining structure, based on the synergistic effect and considering the stress safety of the concrete lining and the rock’s displacement release rate, is proposed. Case analysis is utilized to validate the safety of the lining design in the study section through computational verification. The recommended optimized lining parameters are identified: the support time is initiated when the tunnel wall’s surrounding rock deforms by 9 mm, and the lining thickness is optimized to 47 cm, which is approximately 36.5% less than the pre-optimization thickness. This precise optimization of support timing and lining thickness enhances both the safety and economic efficiency of the Wufengshan Tunnel. The method allows for the calculation of the optimal combination of support time and lining thickness tailored to different surrounding rock conditions, offering significant reference value for tunnel lining optimization.

Abstract U-Shaped Steel Sheet Piles (USSSP) have buckling and bending problems during construction. In this research, the structural measure of stiffened plates applied along the longitudinal direction of USSSP is analyzed and proposed. A theoretical calculation method of stiffening effect is proposed based on the dynamic correlation coefficient method and the formula for the critical buckling load of locally stiffened USSSP is derived. A parametric analysis of the number, width, and arrangement scheme of the stiffened plates on the USSSP with different lengths is examined. The empirical formula derived for the total stiffening area and the critical load of the axial compression members of the USSSP is compared with practical results from an engineering case study. The results show a quadratic function under the condition of arranging the different number of stiffened plates at equal intervals, which is accurate in deriving the critical load values USSSP after local stiffening, and provide a theoretical basis for the optimization design of local reinforcement of USSSP axial compression members in engineering projects.

Abstract Despite the extensive investigation on the stress and displacement distributions in tunnels, few have considered the influences of the damaged zone around a tunnel on the strength and stiffness parameters of the surrounding rock, including the gradual variation in the damaged factor D and dimensionless damaged radius $$\rho^{{\text{d}}}$$ ρ d , under the effect of excavation disturbance. In this paper, a numerical solution is presented for the stresses and displacement of a circular tunnel excavated in a Hoek–Brown rock mass considering the progressive destruction of the damaged zone. First, the results obtained using the proposed algorithm are compared with those obtained using other numerical solutions, demonstrating a high degree of accuracy through some examples. Second, the influences of the damaged factor $$D$$ D and dimensionless damaged radius $$\rho^{d}$$ ρ d on the stresses, radial displacement, plastic radii, and ground response curve are investigated. The results show that, as the damaged factor D increases, the radial displacement and plastic radius increase, whereas the tangential stress decreases. Both the plastic radius and displacement decrease with decreasing $$\rho^{{\text{d}}}$$ ρ d . This shows that the damaged factor D has a significant effect on tunnel convergence.

The computer vision inspection of surface cracks in concrete structures has the characteristics of convenient and efficient 24-h on-site inspection. In this paper, the instance segmentation method and semantic segmentation method are used to realize the surface crack recognition of concrete structures, and a concrete crack detection method based on two different deep learning methods is designed. Experiments show that in scenarios where detection accuracy is required, compared with the Mask Region with Convolutional Neural Network method, the U-Net model improves the model segmentation accuracy through up-sampling and skip connection, and its Recall, Kappa, and Dice are increased by 6.88, 1.94, and 7.72%, respectively. In the scene of positioning requirements, Mask Region with Convolutional Neural Network has a better detection effect than U-Net for very thin and inconspicuous cracks, effectively avoiding the situation of missing cracks.

Past studies on deep-lying tunnels under the assumption of plane strain have generally neglected the influence of intermediate principal stress even though this affects the surrounding rocks in the plastic zone. This study proposes a finite difference method to compute the stress strain plastic region and displacement of a tunnel based on the Drucker–Prager (D–P) yield criterion and non-associated flow rule and considering the influences of intermediate principal stress and the strain-softening behavior of surrounding rock. The computed results were compared with those of other well-known solutions and the accuracy and validity of the method were confirmed through some examples. Parameter analysis was conducted to investigate the effects of intermediate principal stress on stress-strain, the plastic region, the ground response curve, and the dilatability of surrounding rock. The results showed that the plastic radius Rp, the residual radius Rd, and radial displacement of surrounding rock first decreased and then increased with increasing intermediate principal stress coefficient b from 0 to 1, with the minimums occurring at b = 0.75. On the contrary, the peak and rate of variation of the dilatancy coefficient first increased and then decreased with increasing b and the dilatancy coefficient Kψ gradually transitioned from nonlinear to linear variation. Meanwhile, the inhibition of the plastic radius and radial displacement gradually weakened with increasing support pressure, whereas the dilatancy coefficient of the tunnel opening gradually increased.

In the existing research studies of hydraulic conductivity, most of them assume that soil consists of spheroidal particles and the value of hydraulic conductivity can be designated by the particle size. In the actual soil layers, the shape of soil particles is mostly ellipsoid or rod-like rather than ideal sphere. Therefore, the prediction of soil permeability using current method often deviates from the actual situation and cannot capture the anisotropy nature of soil without consideration of the effect of the axis size of soil particles in two different directions. To solve this problem, a new theoretical model with three different soil particle arrangements is introduced to derive a new hydraulic conductivity-particle size relationship considering the size difference in two directions. This model, from a microscopic perspective, divides pores into numerous pore units and obtains hydraulic conductivity of each tube unit, eventually predicting the permeability of soil layer based on an equivalence principle. The proposed equation is validated in comparison with experimental data from the existing literature and is proved to have a satisfied accuracy to predict hydraulic conductivity for a wide range of soils, from bentonite-silt mixed soils to sandy soils. The proposed model provides a new perspective for accurately predicting the hydraulic conductivity.

Leakage channels in tunnel lining and surrounding rock can lead to water seepage on tunnel walls, significantly posing risks to the safety and stability of tunnel operations. Accurate detection of these leakage channels is important to block them and maintain safe operations of tunnels. Based on the theory of natural potential field detection, the potential distribution on the tunnel wall is studied. An improved particle swarm optimization algorithm is applied to invert the spatial charge distribution inside the tunnel lining and surrounding rock. The distribution of spatial charges is used to infer the location and direction of leakage channels within the tunnel lining and surrounding rock. The research results show that the variance of charge distribution is 1.58% in the forward modeling inversion and 7.6% in the inversion of measured data. The inverted result shows an area of charge anomaly consistent with the actual position of the leakage channel. [ABSTRACT FROM AUTHOR]

When a biological public health event breaks out, due to the characteristics of their work, doctors and nurses must face risks directly when the situation is unknown. Their difficulties and psychological pressure are unimaginable. However, few studies have investigated the difficulties encountered by those doctors and nurses and their requirements for psychological interventions. This study aimed to explore the difficulties and psychological intervention needs of doctors and nurses during the new biological public health events in China in 2019. We carried out a qualitative study using a phenomenological approach. We used convenience sampling to identify participants who provided direct care and treatment for patients with biological events such as coronavirus disease 2019 (COVID-19). They participated in semi-structured, in-depth face-to-face interviews. The interviews were transcribed and analyzed using Colaizzi's seven-step method. Analysis of this study was divided into the difficulties encountered by doctors and nurses and their mental health need. The difficulties encountered by doctors and nurses included four themes: being worried about the impact on others, lack of knowledge and skills, difficult patients, being socially isolated, and the feeling of uncertainty. The mental health need was summarized into two parts, needs expressed by doctors and nurses and needs observed by researchers. Doctors and nurses mostly did not feel that they needed any psychological support, but the researchers noticed several signs of stress or potential mental health problems among interviewees. Doctors and nurses faced significant complex and multidimensional difficulties. Many denied needing psychological support, even though the researchers noted signs that it might be helpful. Interventions and support strategies that involve mental health promotion activities should consider individual needs related to doctors and nurses' situation.

Background It is essential to investigate the experiences behind why adolescents start and continue to self-harm in order to develop targeted treatment and prevent future self-harming behaviours. Aims The aims of this study are to understand the motivations for initiating and repeating nonfatal self-harm, the different methods used between first-time and repeated self-harm and the reasons that adolescents do not seek help from health services. Methods Adolescents with repeated nonfatal self-harm experiences were recruited to participate in individual, semi-structured qualitative interviews. The interviews were analysed with interpretative phenomenological analysis. Results We found that nonfatal self-harm among adolescents occurred comparatively early and was often triggered by specific reasons. However, the subsequent nonfatal self-harm could be causeless, with repeated self-harm becoming a maladaptive coping strategy to handle daily pressure and negative emotions. The choice of tools used was related to the ease of accessibility, the life-threatening risk and the size of the scars. Adolescents often concealed their scars on purpose, which made early identification insufficient. Peer influence, such as online chat groups encouraging self-harm by discussing and sharing self-harm pictures, could also lead to increased self-harm. The results also included participants’ opinions on how to stop nonfatal self-harm and their dissatisfaction with the current healthcare services. Conclusions The current study provides important implications both for early identification and interventions for adolescents who engage in repeated nonfatal self-harm, and for individualising treatment planning that benefits them. It is also worthwhile to further investigate how peer influence and social media may affect self-harm in adolescents.