For localized fires, it is necessary to consider the thermal and mechanical responses of building elements subject to uneven heating under the influence of wind. In this paper, the thermomechanical phenomena experienced by a ceiling jet and I-beam in a structural fire were simulated. Instead of applying the concept of adiabatic surface temperature (AST) to achieve fluid–structure coupling, this paper proposes a new computational fluid dynamics–finite element method numerical simulation that combines wind, fire, thermal, and structural analyses. First, to analyze the velocity and temperature distributions, the results of the numerical model and experiment were compared in windless conditions, showing good agreement. Vortices were found in the local area formed by the upper and lower flanges of the I-beam and the web, generating a local high-temperature zone and enhancing the heat transfer of convection. In an incoming-flow scenario, the flame was blown askew significantly; the wall temperature was bimodally distributed in the axial direction. The first temperature peak was mainly caused by radiative heat transfer, while the second resulted from convective heat transfer. In terms of mechanical response, the yield strength degradation in the highest-temperature region in windless conditions was found to be significant, thus explaining the stress distribution of steel beams in the fire field. The mechanical response of the overall elements considering the incoming flows was essentially elastic.

The present study describes a reliability analysis of the strength model for predicting concrete columns confinement influence with Fabric-Reinforced Cementitious Matrix (FRCM). through both physical models and Deep Neural Network model (artificial neural network (ANN) with double and triple hidden layers). The database of 330 samples collected for the training model contains many important parameters, i.e., section type (circle or square), corner radius r_c, unconfined concrete strength f_co, thickness n_t, the elastic modulus of fiber E_f , the elastic modulus of mortar E_m. The results revealed that the proposed ANN models well predicted the compressive strength of FRCM with high prediction accuracy. The ANN model with double hidden layers (APDL-1) was shown to be the best to predict the compressive strength of FRCM confined columns compared with the ACI design code and five physical models. Furthermore, the results also reveal that the unconfined compressive strength of concrete, type of fiber mesh for FRCM, type of section, and the corner radius ratio, are the most significant input variables in the efficiency of FRCM confinement prediction. The performance of the proposed ANN models (including double and triple hidden layers) had high precision with R higher than 0.93 and RMSE smaller than 0.13, as compared with other models from the literature available.

In this study, the mechanical properties of the composite plate were considered Gaussian random fields and their effects on the buckling load and corresponding mode shapes were studied by developing a semi-analytical non-intrusive approach. The random fields were decomposed by the Karhunen−Loève method. The strains were defined based on the assumptions of the first-order and higher-order shear-deformation theories. Stochastic equations of motion were extracted using Euler–Lagrange equations. The probabilistic response space was obtained by employing the non-intrusive polynomial chaos method. Finally, the effect of spatially varying stochastic properties on the critical load of the plate and the irregularity of buckling mode shapes and their sequences were studied for the first time. Our findings showed that different shear deformation plate theories could significantly influence the reliability of thicker plates under compressive loading. It is suggested that a linear relationship exists between the mechanical properties’ variation coefficient and critical loads’ variation coefficient. Also, in modeling the plate properties as random fields, a significant stochastic irregularity is obtained in buckling mode shapes, which is crucial in practical applications.

A numerical framework was proposed for the seismic analysis of underground structures in layered ground under inclined P-SV waves. The free-field responses are first obtained using the stiffness matrix method based on plane-wave assumptions. Then, the domain reduction method was employed to reproduce the wavefield in the numerical model of the soil–structure system. The proposed numerical framework was verified by providing comparisons with analytical solutions for cases involving free-field responses of homogeneous ground, layered ground, and pressure-dependent heterogeneous ground, as well as for an example of a soil–structure interaction simulation. Compared with the viscous and viscous-spring boundary methods adopted in previous studies, the proposed framework exhibits the advantage of incorporating oblique incident waves in a nonlinear heterogeneous ground. Numerical results show that SV-waves are more destructive to underground structures than P-waves, and the responses of underground structures are significantly affected by the incident angles.

Scouring is one of the primary triggers of failure for bridges across rivers or seas. However, research concerning the scour mechanism of multi-wall foundations (MWFs) remains scarce, hindering the further application of MWFs. In this study, for the first time, the scouring effect caused by unidirectional flow around MWFs was examined numerically using FLOW-3D involving a large-eddy simulation. Initially, the applicability of the scouring model and input parameters was validated using a case study based on published measured data. Subsequently, the scouring effects of four MWFs with different wall arrangements and inflow angles, including the flow field analysis and scour pit and depth, were investigated thoroughly. It was found that the maximum scour depth of MWFs with an inflow angle of 0° was smaller than that of those with an inflow angle of 45°, regardless of the wall arrangement. Meanwhile, changing the inflow angle significantly affects the scour characteristics of MWFs arranged in parallel. In practical engineering, MWFs arranged in parallel are preferred considering the need for scouring resistance. However, a comparative analysis should be performed to consider comprehensively whether to adopt the form of a round wall arrangement when the inflow angle is not 0° or the inflow direction is changeable.

The objective of the current study is to propose an expert system framework based on a supervised machine learning technique (MLT) to predict the seismic performance of low- to mid-rise frame structures considering soil-structure interaction (SSI). The methodology of the framework is based on examining different MLTs to obtain the highest possible accuracy for prediction. Within the MLT, a sensitivity analysis was conducted on the main SSI parameters to select the most effective input parameters. Multiple limit state criteria were used for the seismic evaluation within the process. A new global seismic assessment ratio was introduced that considers both serviceability and strength aspects by utilizing three different engineering demand parameters (EDPs). The proposed framework is novel because it enables the designer to seismically assess the structure, while simultaneously considering different EDPs and multiple limit states. Moreover, the framework provides recommendations for building component design based on the newly introduced global seismic assessment ratio, which considers different levels of seismic hazards. The proposed framework was validated through comparison using non-linear time history (NLTH) analysis. The results show that the proposed framework provides more accurate results than conventional methods. Finally, the generalization potential of the proposed framework was tested by investigating two different types of structural irregularities, namely, stiffness and mass irregularities. The results from the framework were in good agreement with the NLTH analysis results for the selected case studies, and peak ground acceleration (PGA) was found to be the most influential input parameter in the assessment process for the case study models investigated. The proposed framework shows high generalization potential for low- to mid-rise structures.

In recent years, tunnel boring machines (TBMs) have been widely used in tunnel construction. However, the TBM control parameters set based on operator experience may not necessarily be suitable for certain geological conditions. Hence, a method to optimize TBM control parameters using an improved loss function-based artificial neural network (ILF-ANN) combined with quantum particle swarm optimization (QPSO) is proposed herein. The purpose of this method is to improve the TBM performance by optimizing the penetration and cutterhead rotation speeds. Inspired by the regularization technique, a custom artificial neural network (ANN) loss function based on the penetration rate and rock-breaking specific energy as TBM performance indicators is developed in the form of a penalty function to adjust the output of the network. In addition, to overcome the disadvantage of classical error backpropagation ANNs, i.e., the ease of falling into a local optimum, QPSO is adopted to train the ANN hyperparameters (weight and bias). Rock mass classes and tunneling parameters obtained in real time are used as the input of the QPSO-ILF-ANN, whereas the cutterhead rotation speed and penetration are specified as the output. The proposed method is validated using construction data from the Songhua River water conveyance tunnel project. Results show that, compared with the TBM operator and QPSO-ANN, the QPSO-ILF-ANN effectively increases the TBM penetration rate by 14.85% and 13.71%, respectively, and reduces the rock-breaking specific energy by 9.41% and 9.18%, respectively.

An approach to control the profiles of interstory drift ratios along the height of building structures via topology optimization is proposed herein. The theoretical foundation of the proposed approach involves solving a min–max optimization problem to suppress the maximum interstory drift ratio among all stories. Two formulations are suggested: one inherits the bound formulation and the other utilizes a p-norm function to aggregate all individual interstory drift ratios. The proposed methodology can shape the interstory drift ratio profiles into inverted triangular or quadratic patterns because it realizes profile control using a group of shape weight coefficients. The proposed formulations are validated via a series of numerical examples. The disparity between the two formulations is clear. The optimization results show the optimal structural features for controlling the interstory drift ratios under different requirements.

Clear asphalt (CA) currently used in light-colored asphalt mixtures (LCAM) exhibits poor transparency and adhesion. Therefore, a highly transparent CA (HCA) modified using a silane coupling agent (KH550) was prepared. Furthermore, LCAM was prepared by mixing CA and limestone aggregates. The properties of the HCA and ordinary CA (OCA) were characterized using conventional asphalt tests, optical tests, pull-off tests, ultraviolet aging tests, dynamic shear rheometry, Fourier-transform infrared spectroscopy, differential scanning calorimetry, and scanning electron microscopy. Whereas Marshall, moisture resistance, wheel tracking, trabecular bending, and British pendulum tests were employed for the LCAM. The transmittance and spectral reflectance of the HCA were 123.30 and 3.74 times greater than those of the OCA, respectively. The complex modulus and viscosity-aging index of the HCA were 48% and 53% less than those of the OCA, respectively. After modification with KH550, the Marshall stability ratio, tensile strength ratio, and flexural strain of the HCA-prepared LCAM increased by 12.92%, 25.06%, and 23.90%, respectively. However, the rutting resistance of the HCA-prepared LCAM was 14.3% less than that of the OCA-prepared LCAM. The comprehensive performances of the HCA and HCA-prepared LCAM were 49.2% and 10.3% greater than those of the OCA and OCA-prepared LCAM, respectively, indicating a high application value in the future.

An analytical model is proposed to estimate the discontinuous mechanical behavior of an existing shield tunnel above a new tunnel. The existing shield tunnel is regarded as a Timoshenko beam with longitudinal joints. The opening and relative dislocation of the longitudinal joints can be calculated using Dirac delta functions. Compared with other approaches, our method yields results that are consistent with centrifugation test data. The effects of the stiffness reduction at the longitudinal joints (α and β), the shearing stiffness of the Timoshenko beam GA, and different additional pressure profiles on the responses of the shield tunnel are investigated. The results indicate that our proposed method is suitable for simulating the discontinuous mechanical behaviors of existing shield tunnels with longitudinal joints. The deformation and internal forces decrease as α, β, and GA increase. The bending moment and shear force are discontinuous despite slight discontinuities in the deflection, opening, and dislocation. The deflection curve is consistent with the additional pressure profile. Extensive opening, dislocation, and internal forces are induced at the location of mutation pressures. In addition, the joints allow rigid structures to behave flexibly in general, as well as allow flexible structures to exhibit locally rigid characteristics. Owing to the discontinuous characteristics, the internal forces and their abrupt changes at vulnerable sections must be monitored to ensure the structural safety of existing shield tunnels.

The horizontal bearing behavior of a single batter pile (SBP) is vital to its application in practical engineering; however, the horizontal responses of SBPs change with the directions of horizontal loads, and this phenomenon is rarely investigated. Therefore, the directional differences in the horizontal bearing behaviors of SBPs are investigated in this study. Four model tests are conducted to preliminarily examine the effects of the skew angle of horizontal loads on the horizontal bearing capacities and distributions of the bending moments of the SBPs. Subsequently, the differences in the responses of the SBPs under horizontal loads in various directions at full scale are analyzed comprehensively via finite-element (FE) analysis. The effects of the skew angle on SBP-soil interaction are discussed. Moreover, an empirical design method is proposed based on the FE analysis results to predict the bearing ratios of SBPs in medium-dense and dense sand while considering the effects of the skew angle, batter angle, and pile diameter. The method is confirmed to be effective, as confirmed by the close agreement between the predicting results with the model test (reported in this study) and centrifuge model test results (reported in the literature).

An innovative composite deck system has recently been proposed for improved structural performance. To study the fatigue behavior of a steel-concrete composite bridge deck, we took a newly-constructed rail-cum-road steel truss bridge as a case study. The transverse stress history of the bridge deck near the main truss under the action of a standard fatigue vehicle was calculated using finite element analysis. Due to the fact that fatigue provision remains unavailable in the governing code of highway concrete bridges in China, a preliminary fatigue evaluation was conducted according to the fib Model Code. The results indicate that flexural failure of the bridge deck in the transverse negative bending moment region is the controlling fatigue failure mode. The fatigue life associated with the fatigue fracture of steel reinforcement is 56 years. However, while the top surface of the bridge deck concrete near the truss cracks after just six years, the bridge deck performs with fatigue cracks during most of its design service life. Although fatigue capacity is acceptable under design situations, overloading or understrength may increase its risk of failure. The method presented in this work can be applied to similar bridges for preliminary fatigue assessment.

This paper numerically studied the effect of uncertainty and random distribution of concrete strength in beams failing in shear and flexure using lattice modeling, which is suitable for statistical analysis. The independent variables of this study included the level of strength reduction and the number of members with reduced strength. Three levels of material deficiency (i.e., 10%, 20%, 30%) were randomly introduced to 5%, 10%, 15%, and 20% of members. To provide a database and reliable results, 1000 analyses were carried out (a total of 24000 analyses) using the MATLAB software for each combination. Comparative studies were conducted for both shear- and flexure-deficit beams under four-point loading and results were compared using finite element software where relevant. Capability of lattice modeling was highlighted as an efficient tool to account for uncertainty in statistical studies. Results showed that the number of deficient members had a more significant effect on beam capacity compared to the level of strength deficiency. The scatter of random load-capacities was higher in flexure (range: 0.680–0.990) than that of shear (range: 0.795–0.996). Finally, nonlinear regression relationships were established with coefficient of correlation values (R²) above 0.90, which captured the overall load–deflection response and level of load reduction.

A fictitious soil pile (FSP) model is developed to simulate the behavior of pipe piles with soil plugs undergoing high-strain dynamic impact loading. The developed model simulates the base soil with a fictitious hollow pile fully filled with a soil plug extending at a cone angle from the pile toe to the bedrock. The friction on the outside and inside of the pile walls is distinguished using different shaft models, and the propagation of stress waves in the base soil and soil plug is considered. The motions of the pile−soil system are solved by discretizing them into spring-mass model based on the finite difference method. Comparisons of the predictions of the proposed model and conventional numerical models, as well as measurements for pipe piles in field tests subjected to impact loading, validate the accuracy of the proposed model. A parametric analysis is conducted to illustrate the influence of the model parameters on the pile dynamic response. Finally, the effective length of the FSP is proposed to approximate the affected soil zone below the pipe pile toe, and some guidance is provided for the selection of the model parameters.

This study aimed to investigate a novel slender buckling-restrained knee brace damper (BRKB) for welded and weld-free steel framing systems. The proposed BRKB adopts steel bar cores connected by a central coupler and restrained by tube buckling restrainers with a cover tube supporter. The advantages of the proposed damper include easy assembly compared to conventional buckling restrained braces, and high architectural flexibility for the retrofitting of large-span weld-free or welded steel moment-resisting systems. Specifically, by increasing the number of contraction allowances, undesirable failure mechanisms that are global instability and local buckling of the restrainer ends can be effectively suppressed because the more uniform plastic deformation of the core bar can be achieved longitudinally. In this study, displacement-controlled compression and cyclic loading tests were carried out to investigate the deformation capacities of the proposed BRKBs. Structural performance metrics associated with both loading tests, such as strength capacities, strains at the cover tubes and buckling restrainers, and hysteretic behaviors of the proposed damper under cyclic loads, were measured and discussed. Test results revealed that the geometrical characteristics of the cover tubes and adopted contraction allowances at the dampers play essential roles in their load-bearing capacities.

The research and development of high-performance pavement materials has been intensified owing to the demand for long-life pavements. This study is performed to develop a novel pavement material using waste rubber powder, waste lubricating by-product (LBP), and asphalt. Subsequently, the aging properties and aging mechanism of activated waste rubber powder modified asphalt (ARMA) are investigated based on its rheological properties and micro-characterization. The rheological results show that, compared with waste rubber powder modified asphalt (RMA), ARMA offers a higher aging resistance and a longer fatigue life. A comparison and analysis of the rheological aging parameters of ARMA and RMA show that LBP activation diminishes the aging sensitivity of ARMA. The micro-characterization result shows that the aging of ARMA may be caused by the fact that LBP-activated waste rubber powder is more reactive and can form a dense colloidal structure with asphalt. Therefore, the evaporation loss of asphalt light components by heat and the damage to the colloidal structure by oxygen during the aging process are impeded, and the thermal-oxidative aging resistance of ARMA is improved.

Thermal energy storage recycled powder mortar (TESRM) was developed in this study by incorporating paraffin/recycled brick powder (paraffin/BP) composite phase change materials (PCM). Fourier transform infrared and thermogravimetric analysis results showed that paraffin/BP composite PCM had good chemical and thermal stability. The onset melting temperature and latent heat of the composite PCM were 46.49 °C and 30.1 J·g⁻¹. The fresh mortar properties and hardened properties were also investigated in this study. Paraffin/BP composite PCM with replacement ratio of 0%, 10%, 20%, and 30% by weight of cement were studied. The results showed that the static and dynamic yield stresses of TESRM were 699.4% and 172.9% higher than those of normal mortar, respectively. The addition of paraffin/BP composite PCM had a positive impact on the mechanical properties of mortar at later ages, and could also reduce the dry shrinkage of mortar. The dry shrinkage of TESRM had a maximum reduction about 26.15% at 120 d. The thermal properties of TESRM were better than those of normal mortar. The thermal conductivity of TESRM was 36.3% less than that of normal mortar and the heating test results showed that TESRM had good thermal energy storage performance.

Owing to long-distance advancement or obstacles, shield tunneling machines are typically shut down for maintenance. Engineering safety during maintenance outages is determined by the stability of the tunnel face. Pressure maintenance openings are typically used under complicated hydrogeological conditions. The tunnel face is supported by a medium at the bottom of the excavation chamber and compressed air at the top. Owing to the high risk of face failure, the necessity of support pressure when cutterhead support is implemented and a method for determining the value of compressed air pressure using different support ratios must to be determined. In this study, a non-fully chamber supported rotational failure model considering cutterhead support is developed based on the upper-bound theorem of limit analysis. Numerical simulation is conducted to verify the accuracy of the proposed model. The results indicate that appropriately increasing the specific gravity of the supporting medium can reduce the risk of collapse. The required compressed air pressure increases significantly as the support ratio decreases. Disregarding the supporting effect of the cutterhead will result in a tunnel face with underestimated stability. To satisfy the requirement of chamber openings at atmospheric pressure, the stratum reinforcement strength and range at the shield end are provided based on different cutterhead aperture ratios.

Blasting engineering in complex urban environments is considered to influence the safety and stability of the overlying drainage box culvert structure owing to vibration. Therefore, field blasting and vibration tests were performed on the blasting engineering of the Wuhan Metro Line 8 connected aisle, and the LS-DYNA software was used to analyze the dynamic response characteristics of an underground drainage box culvert during the blasting test. The vibration response evolution law of the buried drainage box culvert under blasting vibration was investigated, and a safe surface control standard for the blast vibration of a drainage box culvert is proposed. The results reveal that the maximum tensile stress of the box culvert structure was 0.33 MPa. The peak particle velocity (PPV) and peak tensile stress (PTS) of the drainage box culvert decreased as the water level in the box culvert increased. Based on the relationship between the tensile stress of the box culvert, PPV of the box culvert, and PPV of the surface, it is proposed that the surface control velocity of the buried drainage box culvert is 1.36 cm/s.

The interactions between reinforced concrete (RC) frames and infill walls play an important role in the seismic response of frames, particularly for low-rise frames. Infill walls can increase the overall lateral strength and stiffness of the frame owing to their high strength and stiffness. However, local wall-frame interactions can also lead to increased shear demand in the columns owing to the compressive diagonal strut force from the infill wall, which can result in failure or in serious situations, collapse. In this study, the effectiveness of a design strategy to consider the complex infill wall interaction was investigated. The approach was used to design example RC frames with infill walls in locations with different seismicity levels in Thailand. The performance of these frames was assessed using nonlinear static, and dynamic analyses. The performance of the frames and the failure modes were compared with those of frames designed without considering the infill wall or the local interactions. It was found that even though the overall responses of the buildings designed with and without consideration of the local interaction of the infill walls were similar in terms the overall lateral strength, the failure modes were different. The proposed method can eliminate the column shear failure from the building. Finally, the merits and limitations of this approach are discussed and summarized.

An algorithm based on deep semantic segmentation called LC-DeepLab is proposed for detecting the trends and geometries of cracks on tunnel linings at the pixel level. The proposed method addresses the low accuracy of tunnel crack segmentation and the slow detection speed of conventional models in complex backgrounds. The novel algorithm is based on the DeepLabv3+ network framework. A lighter backbone network was used for feature extraction. Next, an efficient shallow feature fusion module that extracts crack features across pixels is designed to improve the edges of crack segmentation. Finally, an efficient attention module that significantly improves the anti-interference ability of the model in complex backgrounds is validated. Four classic semantic segmentation algorithms (fully convolutional network, pyramid scene parsing network, U-Net, and DeepLabv3+) are selected for comparative analysis to verify the effectiveness of the proposed algorithm. The experimental results show that LC-DeepLab can accurately segment and highlight cracks from tunnel linings in complex backgrounds, and the accuracy (mean intersection over union) is 78.26%. The LC-DeepLab can achieve a real-time segmentation of 416 × 416 × 3 defect images with 46.98 f/s and 21.85 Mb parameters.

Owing to advancement in advanced manufacturing technology, the reinforcement design of concrete structures has become an important topic in structural engineering. Based on bi-directional evolutionary structural optimization (BESO), a new approach is developed in this study to optimize the reinforcement layout in steel-reinforced concrete (SRC) structures. This approach combines a minimum compliance objective function with a hybrid truss-continuum model. Furthermore, a modified bi-directional evolutionary structural optimization (M-BESO) method is proposed to control the level of tensile stress in concrete. To fully utilize the tensile strength of steel and the compressive strength of concrete, the optimization sensitivity of steel in a concrete–steel composite is integrated with the average normal stress of a neighboring concrete. To demonstrate the effectiveness of the proposed procedures, reinforcement layout optimizations of a simply supported beam, a corbel, and a wall with a window are conducted. Clear steel trajectories of SRC structures can be obtained using both methods. The area of ​​critical tensile stress in concrete yielded by the M-BESO is more than 40% lower than that yielded by the uniform design and BESO. Hence, the M-BESO facilitates a fully digital workflow that can be extremely effective for improving the design of steel reinforcements in concrete structures.

Due to recent advances in the field of artificial neural networks (ANN) and the global sensitivity analysis (GSA) method, the application of these techniques in structural analysis has become feasible. A connector is an important part of a composite beam, and its shear strength can have a significant impact on structural design. In this paper, the shear performance of perfobond rib shear connectors (PRSCs) is predicted based on the back propagation (BP) ANN model, the Genetic Algorithm (GA) method and GSA method. A database was created using push-out test test and related references, where the input variables were based on different empirical formulas and the output variables were the corresponding shear strengths. The results predicted by the ANN models and empirical equations were compared, and the factors affecting shear strength were examined by the GSA method. The results show that the use of ANN model optimization by GA method has fewer errors compared to the empirical equations. Furthermore, penetrating reinforcement has the greatest sensitivity to shear performance, while the bonding force between steel plate and concrete has the least sensitivity to shear strength.

The analysis of the bearing capacity of strip footings sited near an excavation is critical in geotechnics. In this study, the effects of the geometrical features of the excavation and the soil strength properties on the seismic bearing capacity of a strip footing resting on an excavation were evaluated using the lower and upper bounds of the finite element limit analysis method. The effects of the setback distance ratio (L/B), excavation height ratio (H/B), soil strength heterogeneity (kB/c_u), and horizontal earthquake coefficient (k_h) were analyzed. Design charts and tables were produced to clarify the relationship between the undrained seismic bearing capacity and the selected parameters.

Interdisciplinary research is considered a source of innovativeness and creativity, serving as a key mechanism for creating recombination necessary for the evolution of science systems. The aim of this study is to quantitatively establish the connection between interdisciplinary research and the research fronts that have recently emerged in civil engineering. The degree of interdisciplinarity of the research fronts was measured by developing metrics from bibliographic analyses. As indicated by the consistent increase in the metrics of interdisciplinarity over time, research fronts tend to emerge in studies with increasing diversity in the disciplines involved. The active disciplines involved in the fronts vary over time. The most active disciplines are no longer fundamental but those associated with energy, environment, and sustainable development, focusing on solutions to climate change and integrating intelligence technologies.

In this study, the flexural and longitudinal shear performances of two types of precast lightweight steel–ultra-high performance concrete (UHPC) composite beams are investigated, where a cluster UHPC slab (CUS) and a normal UHPC slab (NUS) are connected to a steel beam using headed studs through discontinuous shear pockets and full-length shear pockets, respectively. Results show that the longitudinal shear force of the CUS is greater than that of the NUS, whereas the interfacial slip of the former is smaller. Owing to its better integrity, the CUS exhibits greater flexural stiffness and a higher ultimate bearing capacity than the NUS. To further optimize the design parameters of the CUS, a parametric study is conducted to investigate their effects on the flexural and longitudinal shear performances. The square shear pocket is shown to be more applicable for the CUS, as the optimal spacing between two shear pockets is 650 mm. Moreover, a design method for transverse reinforcement is proposed; the transverse reinforcement is used to withstand the splitting force caused by studs in the shear pocket and prevent the UHPC slab from cracking. According to calculation results, the transverse reinforcement can be canceled when the compressive strength of UHPC is 150 MPa and the volume fraction of steel fiber exceeds 2.0%.

The disc cutters of shield machines exhibit unsatisfactory adaptability and performance during the soft–hard varied strata tunneling process. To analyze the rotation state, cutting performance, and adaptability of disc cutters during shield tunneling in soft–hard varied strata, the Holmquist Johnson Cook and Federal Highway Administration constitutive models are introduced to numerically simulate the failure process of materials on the excavation face and to calculate the load of disc cutters. Additionally, the parameters of the models are modified based on laboratory disc cutter excavation test results. The results of numerical calculation can reflect the load level and the behavior of the disc cutters during operation. The tangential loads of the disc cutters during the cutting of four typical soft-strata excavation face models are numerically calculated, thus providing reference values for the starting torque of the disc cutters. A greater penetration is suggested for soft-strata tunneling to allow the disc cutters to rotate smoothly and continuously as well as to guarantee a better cutting effect. The disc cutters in the center of the cutterhead should be specified with a lower starting torque to prevent uneven wear, rotation stagnation, cutterhead clogging, and other adverse phenomena.

This paper presents a novel approach for simulating the localized leakage behavior of segmentally lined tunnels based on a cohesive zone model. The proposed approach not only simulates localized leakage at the lining segment, but also captures the hydromechanically coupled seepage behavior at the segmental joints. It is first verified via a tunnel drainage experiment, which reveals its merits over the existing local hydraulic conductivity method. Subsequently, a parametric study is conducted to investigate the effects of the aperture size, stratum permeability, and spatial distribution of drainage holes on the leakage behavior, stratum seepage field, and leakage-induced mechanical response of the tunnel lining. The proposed approach yields more accurate results than the classical local hydraulic conductivity method. Moreover, it is both computationally efficient and stable. Localized leakage leads to reduced local ground pressure, which further induces outward deformation near the leakage point and slight inward deformation at its diametrically opposite side. A localized stress arch spanning across the leakage point is observed, which manifests as the rotation of the principal stresses in the adjacent area. The seepage field depends on both the number and location of the leakage zones. Pseudostatic seepage zones, in which the seepage rate is significantly lower than that of the adjacent area, appear when multiple seepage zones are considered. Finally, the importance of employing the hydromechanical coupled mechanism at the segment joints is highlighted by cases of shallowly buried tunnels subjected to surface loading and pressure tunnels while considering internal water pressure.

The prediction of structural performance plays a significant role in damage assessment of glass fiber reinforcement polymer (GFRP) elastic gridshell structures. Machine learning (ML) approaches are implemented in this study, to predict maximum stress and displacement of GFRP elastic gridshell structures. Several ML algorithms, including linear regression (LR), ridge regression (RR), support vector regression (SVR), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), category boosting (CatBoost), and light gradient boosting machine (LightGBM), are implemented in this study. Output features of structural performance considered in this study are the maximum stress as f₁(x) and the maximum displacement to self-weight ratio as f₂(x). A comparative study is conducted and the Catboost model presents the highest prediction accuracy. Finally, interpretable ML approaches, including shapely additive explanations (SHAP), partial dependence plot (PDP), and accumulated local effects (ALE), are applied to explain the predictions. SHAP is employed to describe the importance of each variable to structural performance both locally and globally. The results of sensitivity analysis (SA), feature importance of the CatBoost model and SHAP approach indicate the same parameters as the most significant variables for f₁(x) and f₂(x).

Externally bonded (EB) and near-surface mounted (NSM) bonding are two widely adopted and researched strengthening methods for reinforced-concrete structures. EB composite substrates are easy to reach and repair using appropriate surface treatments, whereas NSM techniques can be easily applied to the soffit and concrete member sides. The EB bonded fiber-reinforced polymer (FRP) technique has a significant drawback: combustibility, which calls for external protective agents, and textile reinforced mortar (TRM), a class of EB composites that is non-combustible and provides a similar functionality to any EB FRP-strengthened substrate. This study employs a finite element analysis technique to investigate the failing failure of carbon textile reinforced mortar (CTRM)-strengthened reinforced concrete beams. The principal objective of this numerical study was to develop a finite element model and validate a set of experimental data in existing literature. A set of seven beams was modelled and calibrated to obtain concrete damage plasticity (CDP) parameters. The predicted results, which were in the form of load versus deflection, load versus rebar strain, tensile damage, and compressive damage patterns, were in good agreement with the experimental data. Moreover, a parametric study was conducted to verify the applicability of the numerical model and study various influencing factors such as the concrete strength, internal reinforcement, textile roving spacing, and externally-applied load span. The ultimate load and deflection of the predicted finite element results had a coefficient of variation (COV) of 6.02% and 5.7%, respectively. A strain-based numerical comparison with known methods was then conducted to investigate the debonding mechanism. The developed finite element model can be applied and tailored further to explore similar TRM-strengthened beams undergoing debonding, and the preventive measures can be sought to avoid premature debonding.