Frontiers of Structural and Civil Engineering最新文献

For real-time classification of rock-masses in hard-rock tunnels, quick determination of the rock lithology on the tunnel face during construction is essential. Motivated by current breakthroughs in artificial intelligence technology in machine vision, a new automatic detection approach for classifying tunnel lithology based on tunnel face images was developed. The method benefits from residual learning for training a deep convolutional neural network (DCNN), and a multi-scale dilated convolutional attention block is proposed. The block with different dilation rates can provide various receptive fields, and thus it can extract multi-scale features. Moreover, the attention mechanism is utilized to select the salient features adaptively and further improve the performance of the model. In this study, an initial image data set made up of photographs of tunnel faces consisting of basalt, granite, siltstone, and tuff was first collected. After classifying and enhancing the training, validation, and testing data sets, a new image data set was generated. A comparison of the experimental findings demonstrated that the suggested approach outperforms previous classifiers in terms of various indicators, including accuracy, precision, recall, F1-score, and computing time. Finally, a visualization analysis was performed to explain the process of the network in the classification of tunnel lithology through feature extraction. Overall, this study demonstrates the potential of using artificial intelligence methods for in situ rock lithology classification utilizing geological images of the tunnel face.

Real-time perception of rock conditions based on continuously collected data to meet the requirements of continuous Tunnel Boring Machine (TBM) construction presents a critical challenge that warrants increased attention. To achieve this goal, this paper establishes real-time prediction models for fractured and weak rock mass by comparing 6 different algorithms using real-time data collected by the TBM. The models are optimized in terms of selecting metric, selecting input features, and processing imbalanced data. The results demonstrate the following points. (1) The Youden’s index and area under the ROC curve (AUC) are the most appropriate performance metrics, and the XGBoost Random Forest (XGBRF) algorithm exhibits superior prediction and generalization performance. (2) The duration of the TBM loading phase is short, usually within a few minutes after the disc cutter contacts the tunnel face. A model based on the features during the loading phase has a miss rate of 21.8%, indicating that it can meet the early warning needs of TBM construction well. As the TBM continues to operate, the inclusion of features calculated from subsequent data collection can continuously correct the results of the real-time prediction model, ultimately reducing the miss rate to 16.1%. (3) Resampling the imbalanced data set can effectively improve the prediction by the model, while the XGBRF algorithm has certain advantages in dealing with the imbalanced data issue. When the model gives an alarm, the TBM operator and on-site engineer can be reminded and take some necessary measures for avoiding potential tunnel collapse. The real-time predication model can be a useful tool to increase the safety of TBM excavation.

The accreted ice on wind turbine blades significantly deteriorates the blade aerodynamic performance and consequently the power production. The existing numerical simulations of blade icing have mostly been performed with the Eulerian approach for two-dimensional (2D) blade profiles, neglecting the possible three-dimensional (3D) rotating effect. This paper conducts a numerical simulation of rime ice accretion on a 3D wind turbine blade using the Lagrangian approach. The simulation results are validated through previously published experimental data. The icing characteristics along the blade radial direction are then investigated in detail. Significant radial airflow along the blade is observed, which demonstrates the necessity of 3D simulation. In addition, more droplets are found to impinge on the blade surface near the tip region, thereby producing severer ice accretion there. The accreted ice increases almost linearly along the blade radial direction in terms of both ice mass and maximum ice thickness.

A concrete-filled double-skin tube (CFDST) is a new type of composite material. Experimental studies have been conducted to investigate the axial compression behavior of CFDST members for approximately 30 years. This paper provides a review of the status of axial compression bearing capacity tests conducted on circular CFDST stub columns as well as a summary of test data for 165 circular CFDST stub columns reported in 22 papers. A relatively complete high-quality test database is established. Based on this database, the main factors affecting the axial compression bearing capacity of the CFDST stub columns are analyzed. The prediction accuracy and robustness of an existing theoretical prediction model, which is a data-driven model, are evaluated, and a numerical simulation of the axial compression bearing capacity of the CFDST stub columns is conducted. In addition, the differences between the basic theory and experimental results of various models are compared, and the possible sources of prediction errors are analyzed. The current model for predicting the axial compression capacity of CFDST stub columns cannot simultaneously satisfy the requirements of high accuracy and confidence, and the stress independency assumption introduced in the test is not valid. The main error source in the theoretical prediction model is the non-simultaneous consideration of the effects of the void ratio and inner steel tube.

This study uses iso-geometric investigation, which is based on the non-uniform rational B-splines (NURBS) basis function, to investigate natural oscillation of bi-directional functionally graded porous (BFGP) doubly-curved shallow microshells placed on Pasternak foundations with any boundary conditions. The characteristics of the present material vary in both thickness and axial directions along the x-axis. To be more specific, a material length-scale coefficient of the microshell varies in both thickness and length directions as the material’s mechanical properties. One is able to develop a differential equation system with varying coefficients that regulate the motion of BFGP double-curved shallow microshells by using Hamilton principle, Kirchhoff–Love hypothesis, and modified couple stress theory. The numerical findings are reported for thin microshells that are spherical, cylindrical, and hyperbolic paraboloidal, with a variety of planforms, including rectangles and circles. The validity and effectiveness of the established model are shown by comparing the numerical results given by the proposed formulations with previously published findings in many specific circumstances. In addition, influences of length scale parameters, power-law indexes, thickness-to-side ratio, and radius ratio on natural oscillation responses of BFGP microshells are investigated in detail.

This paper presents a rapid and effective calibration method of mesoscopic parameters of a three-dimensional particle flow code (PFC3D) model for sandy cobble soil. The method is based on a series of numerical tests and takes into account the significant influence of mesoscopic parameters on macroscopic parameters. First, numerical simulations are conducted, with five implementation steps. Then, the multi-factor analysis of variance method is used to analyze the experimental results, the mesoscopic parameters with significant influence on the macroscopic response are singled out, and their linear relations to macroscopic responses are estimated by multiple linear regression. Finally, the parameter calibration problem is transformed into a multi-objective function optimization problem. Numerical simulation results are in good agreement with laboratory results both qualitatively and quantitatively. The results of this study can provide a basis for the calibration of microscopic parameters for the investigation of sandy cobble soil mechanical behavior.

With the development of self-healing technology, the overall properties of the microcapsule-enabled self-healing concrete have taken a giant leap. In this research, a detailed assessment of current research on the microcapsule-enabled self-healing concrete is conducted, together with bibliometric analysis. In the bibliometric analysis, various indicators are considered. The current state of progress regarding self-healing concrete is assessed, and an analysis of the temporal distribution of documents, organizations and countries of literature is conducted. Later, a discussion of the citations is analyzed. The research summarizes the improvements of microcapsule-enabled self-healing cementitious composites and provides a concise background overview.

Three-dimensional concrete printing (3DCP) is increasingly being applied in harsh environments and isolated regions. However, the effective utilization of aeolian sand (AS) resources and by-products derived from arid zones for 3DCP is yet to be fully realized. This study developed a three-dimensional (3D) printing composite using AS and magnesium oxychloride cement (MOC) from local materials. The effects of the mole ratio of MgO/MgCl₂ and sand/binder (S/B) ratio on the mechanical properties such as water resistance, drying shrinkage strain, rheology, and printability, were investigated systematically. The results indicated that the optimal mole ratio of MgO/MgCl₂ was 8, which yielded the desired mechanical performance and water resistance. Furthermore, the S/B ratio can be increased to three within the desired printability to increase the AS utilization rate. The rheological recovery and buildability of the 3D-printed MOC with AS were verified. These findings provide a promising strategy for construction in remote deserts.

Three-dimensional printable concrete requires further development owing to the challenges encountered, including its brittle behavior, high cement requirement for the buildability of layers, and anisotropic behavior in different directions. The aim of this study is to overcome these challenges. First, three-dimensional printable concrete mixtures were prepared using silica fume, ground blast furnace slag, and metakaolin, instead of cement, to reduce the amount of cement. Subsequently, the rheological and mechanical behaviors of these concretes were investigated. Second, three-dimensional printable concrete mixtures were prepared using 6-mm-long steel and synthetic fibers to eliminate brittleness and determine the effect of those fibers on the anisotropic behavior of the concrete. As a result of this study, it is understood that printable concretes with extremely low permeability and high buildability can be achieved using mineral additives. In addition, results showed that three-dimensional concrete samples containing short steel fibers achieve fracture energies up to 36 times greater than that of plain concrete. Meanwhile, its characteristic length values, as indicators of ductility, are 22 times higher than those of plain concrete. The weakest strength was recorded at the interfaces between layers. The bending and splitting tensile strengths of three-dimensional printed plain concrete samples were 15% and 19% lower than those of casted samples, respectively. However, the addition of fibers improved the mechanical strength of the interfaces significantly.

Balance of the groundwater and ecology is crucial for controlled discharge. However, regarding the segments of tunnel boring machines (TBMs) under high water pressure, the stability of the lining structure is often reduced by excessive drain holes required to achieve this balance. The large discharge of pinholes can easily have severe consequences, such as the lowering of the groundwater table, drying of springs, and vegetation wilting. Thus, in this study, according to the fluid-structure coupling theory, a new drainage design for TBM segments was developed by considering a mountain tunnel subject to a high water pressure as a case study. The evolution characteristics, including the external water pressure of the lining, discharge volume of the segment, and groundwater-table drawdown, were investigated via numerical modeling with drain holes and pinholes. The results indicated that the optimal design parameters of drainage segments for the project case were as follows: a circumferential spacing angle and longitudinal number on one side of a single ring of 51° and 2, respectively, for the drain holes and an inclination angle and length of 46.41° and 0.25 times the grouting thickness, respectively, for the pin holes.