• Steel and Composite Structures
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• v.51 no.6
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• pp.679-695
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• 2024

This paper presents a novel technique that combines machine learning (ML) with moth-flame optimization (MFO) methods to predict the axial compressive strength (ACS) of concrete filled double skin steel tubes (CFDST) columns. The proposed model is trained and tested with a dataset containing 125 tests of the CFDST column subjected to compressive loading. Five ML models, including extreme gradient boosting (XGBoost), gradient tree boosting (GBT), categorical gradient boosting (CAT), support vector machines (SVM), and decision tree (DT) algorithms, are utilized in this work. The MFO algorithm is applied to find optimal hyperparameters of these ML models and to determine the most effective model in predicting the ACS of CFDST columns. Predictive results given by some performance metrics reveal that the MFO-CAT model provides superior accuracy compared to other considered models. The accuracy of the MFO-CAT model is validated by comparing its predictive results with existing design codes and formulae. Moreover, the significance and contribution of each feature in the dataset are examined by employing the SHapley Additive exPlanations (SHAP) method. A comprehensive uncertainty quantification on probabilistic characteristics of the ACS of CFDST columns is conducted for the first time to examine the models' responses to variations of input variables in the stochastic environments. Finally, a web-based application is developed to predict ACS of the CFDST column, enabling rapid practical utilization without requesting any programing or machine learning expertise.

• Computers and Concrete
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• v.33 no.1
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• pp.103-119
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• 2024

In this paper, the non-linear behavior of masonry-infill and bare steel frames using different beam-column connections under monotonic static loading was investigated through a parametric study. Numerical models were carried out using one- and two-dimensional modelling to validate the experimental results. After validating the experimental results by using these models, a parametric study was carried out to model the behavior of these frames using flushed, extended, and welded connections. The results showed that using the welded or extended connection is more efficient than using the flushed type in masonry-infilled steel frames, since the lateral capacities, initial stiffness, and toughness have been increased by 155%, 601%, and 165%, respectively in the case of using welded connections compared with those used in bare frames. The FE investigation was broadened to study the influence of the variation of the uniaxial column loads on the lateral capacities of the bare/infill steel frames. As the results showed when increasing the amount of uniaxial loading on the columns, whether in tension or compression, causes the lateral load capacity of the columns to decrease by 26% for welded infilled steel frames. Finally, the influence of using different types of beam-to-column connections on the vertical capacities of the bare/infill steel frames under settlement effect was also studied. As a result, it was found that, the vertical load capacity of all types of frames and with using any type of connections is severely reduced, and this decrease may reach 62% for welded infilled frames. Furthermore, the flushed masonry-infilled steel frame has a higher resistance to the vertical loads than the flushed bare steel frame by 133%.

• Steel and Composite Structures
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• v.51 no.5
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• pp.509-527
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• 2024

Bonding carbon fiber-reinforced polymer (CFRP) laminates have been extensively employed in the restoration of steel constructions. In addition to the mechanical properties of the CFRP, the bond strength (P_U) between the CFRP and steel is often important in the eventual strengthened performance. Nonetheless, the bond behavior of the CFRP-steel (CS) interface is exceedingly complicated, with multiple failure causes, giving the P_U challenging to forecast, and the CFRP-enhanced steel structure is unsteady. In just this case, appropriate methods were established by hybridized Random Forests (RF) and support vector regression (SVR) approaches on assembled CS single-shear experiment data to foresee the P_U of CS, in which a recently established optimization algorithm named Aquila optimizer (AO) was used to tune the RF and SVR hyperparameters. In summary, the practical novelty of the article lies in its development of a reliable and efficient method for predicting bond strength at the CS interface, which has significant implications for structural rehabilitation, design optimization, risk mitigation, cost savings, and decision support in engineering practice. Moreover, the Fourier Amplitude Sensitivity Test was performed to depict each parameter's impact on the target. The order of parameter importance was t_c> L_c > E_A > t_A > E_c > b_c > f_c > f_A from largest to smallest by 0.9345 > 0.8562 > 0.79354 > 0.7289 > 0.6531 > 0.5718 > 0.4307 > 0.3657. In three training, testing, and all data phases, the superiority of AO - RF with respect to AO - SVR and MARS was obvious. In the training stage, the values of R² and VAF were slightly similar with a tiny superiority of AO - RF compared to AO - SVR with R² equal to 0.9977 and VAF equal to 99.772, but large differences with results of MARS.

• Geomechanics and Engineering
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• v.36 no.2
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• pp.167-181
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• 2024

The soil-structure relative stiffness is a key factor affecting the seismic response of underground structures. It is of great significance to study the soil-structure relative stiffness for the soil-structure interaction and the seismic disaster reduction of subway stations. In this paper, the dynamic shear modulus ratio and damping ratio of an inhomogeneous soft soil site under different buried depths which were obtained by a one-dimensional equivalent linearization site response analysis were used as the input parameters in a 2D finite element model. A visco-elasto-plastic constitutive model based on the Mohr-Coulomb shear failure criterion combined with stiffness degradation was used to describe the plastic behavior of soil. The damage plasticity model was used to simulate the plastic behavior of concrete. The horizontal and vertical relative stiffness ratios of soil and structure were defined to study the influence of relative stiffness on the seismic response of subway stations in inhomogeneous soft soil. It is found that the compression damage to the middle columns of a subway station with a higher relative stiffness ratio is more serious while the tensile damage is slighter under the same earthquake motion. The relative stiffness has a significant influence on ground surface deformation, ground acceleration, and station structure deformation. However, the effect of the relative stiffness on the deformation of the bottom slab of the subway station is small. The research results can provide a reference for seismic fortification of subway stations in the soft soil area.

• Geomechanics and Engineering
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• v.36 no.6
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• pp.563-573
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• 2024

In this study, various countermeasures used to mitigate tunnel deformations due to nearby multi-propped basement excavation in soft clay are explored by three-dimensional numerical analyses. Field measurements are used to calibrate the numerical model and model parameters. Since concrete slabs can constrain soil and retaining wall movements, tunnel movements reach the maximum value when soils are excavated to the formation level of basement. Deformation shapes of an existing tunnel due to adjacent basement excavation are greatly affected by relative position between tunnel and basement. When the tunnel is located above or far below the formation level of basement, it elongates downward-toward or upward-toward the basement, respectively. It is found that tunnel movements concentrate in a triangular zone with a width of 2 H_e (i.e., final excavation depth) and a depth of 1 D (i.e., tunnel diameter) above or 1 D below the formation level of basement. By increasing retaining wall thickness from 0.4 m to 0.9 m, tunnel movements decrease by up to 56.7%. Moreover, tunnel movements are reduced by up to 80.7% and 61.3%, respectively, when the entire depth and width of soil within basement are reinforced. Installation of isolation wall can greatly reduce tunnel movements due to adjacent basement excavation, especially for tunnel with a shallow burial depth. The effectiveness of isolation wall to reduce tunnel movement is negligible unless the wall reaches the level of tunnel invert.

• Steel and Composite Structures
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• v.50 no.6
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• pp.659-674
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• 2024

Casting Ultra High-Performance Concrete (UHPC) on an orthotropic steel deck and forming a composite action by connectors could improve the steel deck fatigue performance. This study presents the mechanical performance of a proposed post-combination connection between UHPC and steel, which had a low constraint effect on UHPC shrinkage. A total of 10 push-out tests were conducted for static and fatigue performance investigations. And the test results were compared with evaluation methods in codes to verify the latter's applicability. Meanwhile, nonlinear simulation and parametric works with material damage plasticity models were also conducted for the static and fatigue failure mechanism understanding. The static and fatigue test results both showed that fractures at stud roots and surrounding local UHPC crushes were the main failure appearances. Compared with normally arranged studs, group arrangement could result in reductions of static stud shear stiffness, strength, and fatigue lives, which were about 18%, 12%, and 27%, respectively. Compared with the test results, stud shear capacity and fatigue lives evaluations based on the codes of AASHTO, Eurocode 4, JSCE and JTG D64 could be applicable in general while the safety redundancies tended to be smaller or even insufficient for group studs. The analysis results showed that arranging studs in groups caused obviously uneven strain distributions. The severer stress concentration and larger strain ranges caused the static and fatigue performance degradations of group studs. The research outcome provides a very important basis for establishing a design method of connections in the novel post-combination steel-UHPC composite deck.

• Computers and Concrete
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• v.33 no.4
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• pp.425-443
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• 2024

Floods are among the most common natural hazards in urban areas. To mitigate the problems caused by flooding, unstructured data such as images and videos collected from closed circuit televisions (CCTVs) or unmanned aerial vehicles (UAVs) have been examined for flood management (FM). Many computer vision (CV) techniques have been widely adopted to analyze imagery data. Although some papers have reviewed recent CV approaches that utilize UAV images or remote sensing data, less effort has been devoted to studies that have focused on CCTV data. In addition, few studies have distinguished between the main research objectives of CV techniques (e.g., flood depth and flooded area) for a comprehensive understanding of the current status and trends of CV applications for each FM research topic. Thus, this paper provides a comprehensive review of the literature that proposes CV techniques for aspects of FM using ground camera (e.g., CCTV) data. Research topics are classified into four categories: flood depth, flood detection, flooded area, and surface water velocity. These application areas are subdivided into three types: urban, river and stream, and experimental. The adopted CV techniques are summarized for each research topic and application area. The primary goal of this review is to provide guidance for researchers who plan to design a CV model for specific purposes such as flood-depth estimation. Researchers should be able to draw on this review to construct an appropriate CV model for any FM purpose.

• Computers and Concrete
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• v.34 no.2
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• pp.151-168
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• 2024

This research aimed to appraise the effectiveness of four optimization approaches - cuckoo optimization algorithm (COA), multi-verse optimization (MVO), particle swarm optimization (PSO), and teaching-learning-based optimization (TLBO) - that were enhanced with an artificial neural network (ANN) in predicting the bearing capacity of shallow foundations located on cohesionless soils. The study utilized a database of 97 laboratory experiments, with 68 experiments for training data sets and 29 for testing data sets. The ANN algorithms were optimized by adjusting various variables, such as population size and number of neurons in each hidden layer, through trial-and-error techniques. Input parameters used for analysis included width, depth, geometry, unit weight, and angle of shearing resistance. After performing sensitivity analysis, it was determined that the optimized architecture for the ANN structure was 5×5×1. The study found that all four models demonstrated exceptional prediction performance: COA-MLP, MVO-MLP, PSO-MLP, and TLBO-MLP. It is worth noting that the MVO-MLP model exhibited superior accuracy in generating network outputs for predicting measured values compared to the other models. The training data sets showed R² and RMSE values of (0.07184 and 0.9819), (0.04536 and 0.9928), (0.09194 and 0.9702), and (0.04714 and 0.9923) for COA-MLP, MVO-MLP, PSO-MLP, and TLBO-MLP methods respectively. Similarly, the testing data sets produced R² and RMSE values of (0.08126 and 0.07218), (0.07218 and 0.9814), (0.10827 and 0.95764), and (0.09886 and 0.96481) for COA-MLP, MVO-MLP, PSO-MLP, and TLBO-MLP methods respectively.

• Computers and Concrete
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• v.34 no.2
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• pp.179-193
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• 2024

The bending and buckling effect for carbon nanotube-reinforced composite (CNTRC) beams can be evaluated by developing the theory of third shear deformation (TSDT). This study examines beams supported by viscoelastic foundations, where single-walled carbon nanotubes (SWCNTs) are dispersed and oriented within a polymer matrix. Four patterns of reinforcement are used for the CNTRC beams. The rule of mixtures is assessed for the material properties of CNTRC beams. The effective functionally graded materials (FGM) properties are studied by considering three different uneven distribution types of porosity. The damping coefficient is considered to investigate the viscosity effect on the foundation in addition to Winkler's and Pasternak's parameters. The accuracy of the current theory is inspected with multiple comparison works. Moreover, the effects of different beam parameters on the CNTRC beam bending and buckling over a viscoelastic foundation are discussed. The results demonstrated that the O-beam is the weakest type of CNTRC beam to resist buckling and flexure loads, whereas the X-beam is the strongest. Moreover, it is indicated that the presence of porosity in the beams decreases the stiffness and increases deflection. In comparison, the deflection was reduced in the presence of a viscoelastic foundation.

• Steel and Composite Structures
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• v.52 no.2
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• pp.237-248
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• 2024

In order to make the dynamic analysis and design of improved composite beam with corrugated steel web (CBGSCC) bridge more efficient and economical, the parametric self-cyclic analysis model (SCAM) was written in Python on Anaconda platform. The SCAM can call ABAQUS finite element software to realize automatic modeling and dynamic analysis. For the CBGSCC bridge, parameters were set according to the general value range of CBGSCC bridge parameters in actual engineering, the SCAM was used to calculate the large sample model generated by parameter coupling, the optimal value range of each parameter was determined, and the sensitivity of the parameters was analyzed. The number of diaphragms effects weakly on the dynamic characteristics. The deck thickness has the greatest influence on frequency, which decreases as the deck thickness increases, and the deck thickness should be 20-25 cm. The vibration frequency increases with the increase of the bottom plate thickness, the web thickness, and the web height, the bottom plate thickness should be 17-23mm, the web thickness should be 13-17 mm, and the web height should be 1.65-1.7 5 m. Web inclination and Skew Angle should not exceed 30°, and the number of diaphragms should be 3-5 pieces. This method can be used as a new method for structural dynamic analysis, and the importance degree and optimal value range of each parameter of CBGSCC bridge can be used as a reference in the design process.