• Computers and Concrete
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• v.29 no.2
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• pp.93-105
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• 2022

The degrees of freedom (DOFs) of high-rise structures increase rapidly due to the need for refined analysis, which poses a challenge toward a computationally efficient method for numerical analysis of high-rise structures using the finite element method (FEM). This paper presented an efficient iterative method, an algebraic multigrid (AMG) with a Jacobi overrelaxation smoother preconditioned conjugate gradient method (AMG-CG) used for solving large-scale structural system equations running on heterogeneous platforms with parallel accelerator graphics processing units (GPUs) enabled. Furthermore, an AMG-CG FEM application framework was established for the numerical analysis of high-rise structures. In the proposed method, the coarsening method, the optimal relaxation coefficient of the JOR smoother, the smoothing times, and the solution method for the coarsest grid of an AMG preconditioner were investigated via several numerical benchmarks of high-rise structures. The accuracy and the efficiency of the proposed FEM application framework were compared using the mature software Abaqus, and there were speedups of up to 18.4x when using an NVIDIA K40C GPU hosted in a workstation. The results demonstrated that the proposed method could improve the computational efficiency of solving structural system equations, and the AMG-CG FEM application framework was inherently suitable for numerical analysis of high-rise structures.

• Advances in concrete construction
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• v.15 no.5
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• pp.333-348
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• 2023

Fast infrastructure development boosts the demand for shotcrete. Despite sand and stone being the most common coarse and fine aggregates for shotcrete, excessive exploration of these materials challenges the ecological environment. This study utilized an industrial solid waste, high-titanium heavy slag, blended with steel fibers to form Wet Shotcrete of Steel Fiber-reinforced High-Titanium Heavy Slag (WSSFHTHS). It investigated its workability, shotcrete performance and mechanical properties under different water-to-cement ratios, fly ash content, superplasticizer dosage, and steel fiber content. The tunnel excavation and support were investigated by conducting finite element numerical simulation analysis and was used in 3 tunnel lining pipes in Zhonggouwan tailing pond. The major findings are as follows: (1) The water-to-cement ratio (w/c ratio) significantly impacted the compressive strength of WSSFHTHS. The highest 28-day compressive strength of 60 MPa was achieved when the w/c ratio was 0.38; (2) Adding fly ash improved the workability and shotcrete performance and strength development of WSSFHTHS. The best anti-permeability performance was achieved when the fly ash constituted 15%, with the lowest permeability coefficient of 4.596 × 10-11 cm/s; (3) The optimum superplasticizer dosage for WSSFHTHS is 0.8%. It provided the best workability and shotcrete performance. Excessive dosage resulted in water bleeding and poor aggregate encapsulation, while insufficient dosage decreased flowability and adversely affected shotcrete performance; (4) The dosage of steel fibers significantly impacted the flexural and tensile strength of WSSFHTHS. When the steel fiber dosage was 45 kg/m³, the 28-day flexural and tensile strengths were 8.95 MPa and 6.15 MPa, respectively; (5) By integrating existing shotcrete techniques, the optimal lining thickness was 80 mm for WSSFHTHS per simulation. The results revealed that after using WSSFHTHS, the displacement of the tunnel surrounding the rock significantly improved, with no cracks or hollows, similar to the simulation results.

• Computers and Concrete
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• v.29 no.2
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• pp.107-115
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• 2022

With the improvements in computer technologies, utilization of image processing techniques has increased in many areas (such as medicine, defence industry, other industries etc.) Many different image processing techniques are used for surface analysis, detection of manufacturing defects, and determination of physical and mechanical characteristics of composite materials. In this study, cementitious composites were obtained by addition of Grounded Granulated Blast-Furnace Slag (GGBFS), Styrene Butadiene polymer (SBR), and Grounded Granulated Blast-Furnace Slag and Styrene Butadiene polymer together (GGBFS+SBR). Expanded Polystyrene (EPS) beads were added to these cementitious composites in different ratios (20%, 40% and 60%). The mechanical and physical characteristics of the composites were determined, and homogeneity indexes of the composites were determined by image processing techniques to determine EPS distribution forms in them. Physical and mechanical characteristics of the produced samples were obtained by applying consistency, density, water absorption, compressive strength (7 and 28 days), flexural strength (7 and 28 days) and tensile splitting strength (7 and 28 days) tests on them. Also, visual examination by using digital microscope, and image analysis by using image processing techniques with open source coded ImageJ program were performed. As a result of the study, it is determined that GGBFS and SBR addition strengthens the adhesion sites formed as it increases the adhesion power of the mixture and helps to get rid of the segregation problem caused by EPS. As a result of the image processing analysis it is demonstrated that GGBFS and SBR addition has positive contribution on homogeneity index.

• Smart Structures and Systems
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• v.32 no.1
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• pp.9-21
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• 2023

The parameters of civil engineering structures have time-variant characteristics during their service. When extremely large external excitations, such as earthquake excitation to buildings or overweight vehicles to bridges, apply to structures, sudden or gradual damage may be caused. It is crucially necessary to detect the occurrence time and severity of the damage. The unscented Kalman filter (UKF), as one efficient estimator, is usually used to conduct the recursive identification of parameters. However, the conventional UKF algorithm has a weak tracking ability for time-variant structural parameters. To improve the identification ability of time-variant parameters, an adaptive UKF with forgetting factor (AUKF-FF) algorithm, in which the state covariance, innovation covariance and cross covariance are updated simultaneously with the help of the forgetting factor, is proposed. To verify the effectiveness of the method, this paper conducted two case studies as follows: the identification of time-variant parameters of a simply supported bridge when the vehicle passing, and the model updating of a six-story concrete frame structure with field test during the Yangbi earthquake excitation in Yunnan Province, China. The comparison results of the numerical studies show that the proposed method is superior to the conventional UKF algorithm for the time-variant parameter identification in convergence speed, accuracy and adaptability to the sampling frequency. The field test studies demonstrate that the proposed method can provide suggestions for solving practical problems.

• Computers and Concrete
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• v.32 no.2
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• pp.217-232
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• 2023

Numerous studies have been performed on the behavior of pile foundations in cold regions. This study first attempted to employ artificial neural networks (ANN) to predict pile-bearing capacity focusing on pile data recorded primarily on cold regions. As the ANN technique has disadvantages such as finding global minima or slower convergence rates, this study in the second phase deals with the development of an ANN-based predictive model improved with an Elephant herding optimizer (EHO), Dragonfly Algorithm (DA), Genetic Algorithm (GA), and Evolution Strategy (ES) methods for predicting the piles' bearing capacity. The network inputs included the pile geometrical features, pile area (m²), pile length (m), internal friction angle along the pile body and pile tip (Ø°), and effective vertical stress. The MLP model pile's output was the ultimate bearing capacity. A sensitivity analysis was performed to determine the optimum parameters to select the best predictive model. A trial-and-error technique was also used to find the optimum network architecture and the number of hidden nodes. According to the results, there is a good consistency between the pile-bearing DA-MLP-predicted capacities and the measured bearing capacities. Based on the R2 and determination coefficient as 0.90364 and 0.8643 for testing and training datasets, respectively, it is suggested that the DA-MLP model can be effectively implemented with higher reliability, efficiency, and practicability to predict the bearing capacity of piles.

• Steel and Composite Structures
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• v.46 no.1
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• pp.75-92
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• 2023

The novel composite cold-formed steel (CFS)/engineered cementitious composites (ECC) beams have been recently presented. The new composite section exhibited superior structural performance as a flexural member, benefiting from the lightweight thin-walled CFS sections with improved buckling and torsional properties due to the restraints provided by thinlayered ECC. This paper investigated the shear performance of the new composite CFS/ECC section. Twenty-eight simply supported beams, with a shear span-to-depth ratio of 1.0, were assembled back-to-back and tested under a 3-point loading scheme. Bare CFS, composite CFS/ECC utilising ECC with Polyethylene fibres (PE-ECC), composite CFS/MOR, and CFS/HSC utilising high-strength mortar (MOR) and high-strength concrete (HSC) as replacements for PE-ECC were compared. Different failure modes were observed in tests: shear buckling modes in bare CFS sections, contact shear buckling modes in composite CFS/MOR and CFS/HSC sections, and shear yielding or block shear rupture in composite CFS/ECC sections. As a result, composite CFS/ECC sections showed up to 96.0% improvement in shear capacities over bare CFS, 28.0% improvement over composite CFS/MOR and 13.0% over composite CFS/HSC sections, although MOR and HSC were with higher compressive strength than PE-ECC. Finally, shear strength prediction formulae are proposed for the new composite sections after considering the contributions from the CFS and ECC components.

• Structural Engineering and Mechanics
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• v.85 no.4
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• pp.469-484
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• 2023

A deep recursive bidirectional Cuda Deep Neural Network Long Short Term Memory (Bi-CuDNNLSTM) layer is recruited in this paper to predict the entire force time histories, and the corresponding hysteresis and backbone curves of reinforced concrete (RC) bridge piers using experimental fast and slow cyclic tests. The proposed stacked Bi-CuDNNLSTM layers involve multiple uncertain input variables, including horizontal actuator displacements, vertical actuators axial loads, the effective height of the bridge pier, the moment of inertia, and mass. The functional application programming interface in the Keras Python library is utilized to develop a deep learning model considering all the above various input attributes. To have a robust and reliable prediction, the dataset for both the fast and slow cyclic tests is split into three mutually exclusive subsets of training, validation, and testing (unseen). The whole datasets include 17 RC bridge piers tested experimentally ten for fast and seven for slow cyclic tests. The results bring to light that the mean absolute error, as a loss function, is monotonically decreased to zero for both the training and validation datasets after 5000 epochs, and a high level of correlation is observed between the predicted and the experimentally measured values of the force time histories for all the datasets, more than 90%. It can be concluded that the maximum mean of the normalized error, obtained through Box-Whisker plot and Gaussian distribution of normalized error, associated with unseen data is about 10% and 3% for the fast and slow cyclic tests, respectively. In recapitulation, it brings to an end that the stacked Bi-CuDNNLSTM layer implemented in this study has a myriad of benefits in reducing the time and experimental costs for conducting new fast and slow cyclic tests in the future and results in a fast and accurate insight into hysteretic behavior of bridge piers.

• Structural Engineering and Mechanics
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• v.85 no.4
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• pp.485-500
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• 2023

The non-linear static analysis of reinforced concrete (RC) structures using the three-dimensional (3D) finite element method is a time-consuming and challenging task. Moreover, this type of analysis encounters numerical problems such as the lack of convergence of results in the stages of growth and propagation of cracks in the structure. The time integration analysis along with the mass scaling (MS) technique is usually used to overcome these limitations. Despite the use of this method in the 3D finite element analysis of RC structures, a comprehensive study has not been conducted so far to assess the effects of the MS method on the accuracy of results. This study aims to evaluate the accuracy of the MS method in the non-linear quasi-static finite element analysis of RC structures. To this aim, different types of RC structures were simulated using the finite element approach based on the implicit time integration method and the mass scaling technique. The influences of effective parameters of the MS method (i.e., the allowable values of increase in the mass of the RC structure, the relationship between the duration of the applied load and fundamental vibration period of the RC structure, and the pattern of applied loads) on the accuracy of the simulated results were investigated. The accuracy of numerical simulation results has been evaluated through comparison with existing experimental data. The results of this study show that the achievement of accurate structural responses in the implicit time integration analyses using the MS method involves the appropriate selection of the effective parameters of the MS method.

• Computers and Concrete
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• v.32 no.1
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• pp.61-74
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• 2023

This article investigates the wave propagation analysis of the imperfect functionally graded (FG) sandwich plates based on a novel simple four-variable integral quasi-3D higher-order shear deformation theory (HSDT). The thickness stretching effect is considered in the transverse displacement component. The presented formulation ensures a parabolic variation of the transverse shear stresses with zero-stresses at the top and the bottom surfaces without requiring any shear correction factors. The studied sandwich plates can be used in several sectors as areas of aircraft, construction, naval/marine, aerospace and wind energy systems, the sandwich structure is composed from three layers (two FG face sheets and isotropic core). The material properties in the FG faces sheet are computed according to a modified power law function with considering the porosity which may appear during the manufacturing process in the form of micro-voids in the layer body. The Hamilton principle is utilized to determine the four governing differential equations for wave propagation in FG plates which is reduced in terms of computation time and cost compared to the other conventional quasi-3D models. An eigenvalue equation is formulated for the analytical solution using a generalized displacements' solution form for wave propagation. The effects of porosity, temperature, moisture concentration, core thickness, and the material exponent on the plates' dispersion relations are examined by considering the thickness stretching influence.

• Computers and Concrete
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• v.32 no.1
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• pp.75-85
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• 2023

This work utilizes simplified higher-order shear deformation beam theory (HSDBT) to investigate the vibration response for functionally graded carbon nanotube-reinforced composite (CNTRC) beam. Novel to this work, single-walled carbon nanotubes (SWCNTs) are distributed and aligned in a matrix of polymer throughout the beam, resting on a viscoelastic foundation. Four un-similar patterns of reinforcement distribution functions are investigated for the CNTRC beam. Porosity is another consideration taken into account due to its significant effect on functionally graded materials (FGMs) properties. Three types of uneven porosity distributions are studied in this study. The damping coefficient and Winkler's and Pasternak's parameters are considered in investigating the viscosity effect on the foundation. Moreover, the impact of different parameters on the vibration of the CNTRC beam supported by a viscoelastic foundation is discussed. A comparison to other works is made to validate numerical results in addition to analytical discussions. The findings indicate that incorporating a damping coefficient can improve the vibration performance, especially when the spring constant factors are raised. Additionally, it has been noted that the fundamental frequency of a beam increases as the porosity coefficient increases, indicating that porosity may have a significant impact on the vibrational characteristics of beams.