• Advances in concrete construction
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• v.13 no.5
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• pp.385-394
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• 2022

Recently, an increasing number of cutting-edged studies have shown that designing a smart active control for real-time implementation requires piles of hard-work criteria in the design process, including performance controllers to reduce the tracking errors and tolerance to external interference and measure system disturbed perturbations. This article proposes an effective artificial-intelligence method using these rigorous criteria, which can be translated into general control plants for the management of civil engineering installations. To facilitate the calculation, an efficient solution process based on linear matrix (LMI) inequality has been introduced to verify the relevance of the proposed method, and extensive simulators have been carried out for the numerical constructive model in the seismic stimulation of the active rigidity. Additionally, a fuzzy model of the neural network based system (NN) is developed using an interconnected method for LDI (linear differential) representation determined for arbitrary dynamics. This expression is constructed with a nonlinear sector which converts the nonlinear model into a multiple linear deformation of the linear model and a new state sufficient to guarantee the asymptomatic stability of the Lyapunov function of the linear matrix inequality. In the control design, we incorporated H Infinity optimized development algorithm and performance analysis stability. Finally, there is a numerical practical example with simulations to show the results. The implication results in the RMS response with as well as without tuned mass damper (TMD) of the benchmark building under the external excitation, the El-Centro Earthquake, in which it also showed the simulation using evolved bat algorithmic LMI fuzzy controllers in term of RMS in acceleration and displacement of the building.

• Smart Structures and Systems
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• v.30 no.1
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• pp.49-62
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• 2022

Experimental and discrete element methods were used to investigate the effects of triple joints lengths and triple joint angle on the failure behavior of rock mass under uniaxial compressive test. Concrete samples with dimension of 20 cm × 20 cm × 5 cm were prepared. Within the specimen, three imbedded joint were provided. The joint lengths were 2 cm, 4cm and 6 cm. In constant joint lengths, the angle between middle joint and other joints were 30°, 60°, 90°, 120° and 150°. Totally 15 different models were tested under compression test. The axial load rate on the model was 0.05 mm/min. Concurrent with experimental tests, the models containing triple joints, length and joint angle are similar to the experiments, were numerical by Particle flow code in two dimensions (PFC2D). Loading rate in numerical modelling was 0.05 mm/min. Tensile strength of material was 1 MPa. The results show that the failure behaviors of rock samples containing triple joints were governed by both of the angle and the length of the triple joints. The uniaxial compressive strengths (UCS) of the specimens were related to the fracture pattern and failure mechanism of the discontinuities. Furthermore, it was shown that the compressive behavior of discontinuities is related to the number of the induced tensile cracks which are increased by decreasing the joint length. Along with the damage failure of the samples, the acoustic emission (AE) activities are excited. There were only a few AE hits in the initial stage of loading, then AE hits rapidly grow before the applied stress reached its peak. In addition, every stress drop was accompanied by a large number of AE hits. Finally, the failure pattern and failure strength are similar in both methods i.e., the experimental testing and the numerical simulation methods.

• Steel and Composite Structures
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• v.44 no.1
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• pp.33-47
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• 2022

This paper presents a finite element model for predicting the monotonic behaviour of bolted endplate joints connecting steel-concrete composite walls and steel beams. The demountable Hollo-bolts are utilised to facilitate the quick installation and dismantling for replacement and reuse. In the developed model, material and geometric nonlinearities were included. The accuracy of the developed model was assessed by comparing the numerical results with previous experimental tests on hollow/composite column-to-steel beam joints that incorporated endplates and Hollo-bolts. In particular, the Hollo-bolts were modelled with the expanded sleeves involved, and different material properties of the Hollo-bolt shank and sleeves were considered based on the information provided by the manufacture. The developed models, therefore, can be applied in the present study to simulate the wall-to-beam joints with similar structural components and characteristics. Based on the validated model, the authors herein compared the behaviour of wall-to-beam joints of two commonly utilised composite walling systems (Case 1: flat steel plates with headed studs; Case 2: lipped channel section with partition plates). Considering the ease of manufacturing, onsite erection and the pertinent costs, composite walling system with flat steel plates and conventional headed studs (Case 1) was the focus of present study. Specifically, additional headed studs were pre-welded inside the front wall plates to enhance the joint performance. On this basis, a series of parametric studies were conducted to assess the influences of five design parameters on the behaviour of bolted endplate wall-to-beam joints. The initial stiffness, plastic moment capacity, as well as the rotational capacity of the composite wall-to-beam joints based on the numerical analysis were further compared with the current design provision.

• Smart Structures and Systems
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• v.30 no.6
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• pp.601-612
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• 2022

The prediction of structural mechanical behaviors is vital important to early perceive the abnormal conditions and avoid the occurrence of disasters. Especially for underground engineering, complex geological conditions make the structure more prone to disasters. Aiming at solving the problems existing in previous studies, such as incomplete consideration factors and can only predict the continuous performance, the deep attention fused temporal convolution network (DATCN) is proposed in this paper to predict the spatial mechanical behaviors of structure, which integrates both the temporal effect and spatial effect and realize the cross-time prediction. The temporal convolution network (TCN) and self-attention mechanism are employed to learn the temporal correlation of each monitoring point and the spatial correlation among different points, respectively. Then, the predicted result obtained from DATCN is compared with that obtained from some classical baselines, including SVR, LR, MLP, and RNNs. Also, the parameters involved in DATCN are discussed to optimize the prediction ability. The prediction result demonstrates that the proposed DATCN model outperforms the state-of-the-art baselines. The prediction accuracy of DATCN model after 24 hours reaches 90 percent. Also, the performance in last 14 hours plays a domain role to predict the short-term behaviors of the structure. As a study case, the proposed model is applied in an underwater shield tunnel to predict the stress variation of concrete segments in space.

• Steel and Composite Structures
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• v.45 no.6
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• pp.797-818
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• 2022

Steel-precast ultra-high-performance concrete (UHPC) composite beams with demountable high-strength friction-grip bolt (HSFGB) shear connectors can be used for accelerated bridge construction (ABC) and achieve excellent structural performance, which is expected to be dismantled and recycled at the end of the service life. However, no investigation focuses on the demountability and reusability of such composite beams, as well as the installation difficulties during construction. To address this issue, this study conducted twelve push-out tests to investigate the effects of assembly condition, bolt grade, bolt-hole clearance, infilling grout and pretension on the crack pattern, failure mode, load-slip/uplift relationship, and the structural performance in terms of ultimate shear strength, friction resistance, shear stiffness and slip capacity. The experimental results demonstrated that the presented composite beams exhibited favorable demountability and reusability, in which no significant reduction in strength (less than 3%) and stiffness (less than 5%), but a slight improvement in ductility was observed for the reassembled specimens. Employing oversized preformed holes could ease the fabrication and installation process, yet led to a considerable degradation in both strength and stiffness. With filling the oversized holes with grout, an effective enhancement of the strength and stiffness can be achieved, while causing a difficulty in the demounting of shear connectors. On the basis of the experimental results, more accurate formulations, which considered the effect of bolt-hole clearance, were proposed to predict the shear strength as well as the load-slip relationship of HSFGBs in steel-precast UHPC composite beams.

• Computers and Concrete
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• v.30 no.2
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• pp.99-111
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• 2022

In this study, deep learning and k-Nearest Neighbor (kNN) models were used to estimate the sorptivity and freeze-thaw resistance of self-compacting mortars (SCMs) having binary and ternary blends of mineral admixtures. Twenty-five environment-friendly SCMs were designed as binary and ternary blends of fly ash (FA) and silica fume (SF) except for control mixture with only Portland cement (PC). The capillary water absorption and freeze-thaw resistance tests were conducted for 91 days. It was found that the use of SF with FA as ternary blends reduced sorptivity coefficient values compared to the use of FA as binary blends while the presence of FA with SF improved freeze-thaw resistance of SCMs with ternary blends. The input variables used the models for the estimation of sorptivity were defined as PC content, SF content, FA content, sand content, HRWRA, water/cementitious materials (W/C) and freeze-thaw cycles. The input variables used the models for the estimation of sorptivity were selected as PC content, SF content, FA content, sand content, HRWRA, W/C and predefined intervals of the sample in water. The deep learning and k-NN models estimated the durability factor of SCM with 94.43% and 92.55% accuracy and the sorptivity of SCM was estimated with 97.87% and 86.14% accuracy, respectively. This study found that deep learning model estimated the sorptivity and durability factor of SCMs having binary and ternary blends of mineral admixtures higher accuracy than k-NN model.

• Advances in concrete construction
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• v.14 no.2
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• pp.103-113
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• 2022

On the basis of fabrication, the utilization of nano material in numerous industrial and technological system, obtained the utmost significance in current decade. Therefore, the current investigation presents a theoretical disposition regarding the flow of electric conducting Williamson nanoliquid over a stretchable surface in the presence of the motile microorganism. The impact of thermal radiation and magnetic parameter are incorporated in the energy equation. The concentration field is modified by adding the influence of chemical reaction. Moreover, the splendid features of nanofluid are displayed by utilizing the thermophoresis and Brownian motion aspects. Compatible similarity transformation is imposed on the equations governing the problem to derive the dimensionless ordinary differential equations. The Homotopy analysis method has been implemented to find the analytic solution of the obtained differential equations. The implications of specific parameters on profiles of velocity, temperature, concentration and motile microorganism density are investigated graphically. Moreover, coefficient of skin friction, Nusselt number, Sherwood number and density of motile number are clarified in tabular forms. It is revealed that thermal radiation, thermophoresis and Brownian motion parameters are very effective for improvement of heat transfer. The reported investigation can be used in improving the heat transfer appliances and systems of solar energy.

• Steel and Composite Structures
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• v.44 no.3
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• pp.437-450
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• 2022

When the vertical load-bearing members in high-rise structures fail locally, the beam-column joints play an important role in the redistribution of the internal forces. In this paper, a static laboratory test of three full-scale flush flange beam-reinforced connections with side and cover plates (CP-FBSP connection) with double half-span steel beams and single L-shaped columns composed of concrete-filled steel tubes (L-CFST columns) was conducted. The influence of the side plate width and cover plate thickness on the progressive collapse resistance of the substructure was thoroughly analyzed. The failure mode, vertical force-displacement curves, strain variation, reaction force of the pin support and development of internal force in the section with the assumed plastic hinge were discussed. Then, through the verified finite element model, the corresponding analyses of the thickness and length of the side plates, the connecting length between the steel beam flange and cover plate, and the vertical-force eccentricity were carried out. The results show that the failure of all the specimens occurred through the cracking of the beam flange or the cover plate, and the beam chord rotations measured by the test were all greater than 0.085 rad. Increasing the length, thickness and width of the side plates slightly reduced the progressive collapse resistance of the substructures. The vertical-force eccentricity along the beam length reduced the progressive collapse resistance of the substructure. An increase in the connecting length between the beam flange and cover plate can significantly improve the progressive collapse resistance of substructures.

• Computers and Concrete
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• v.29 no.3
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• pp.187-199
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• 2022

The usability of waste materials as raw materials is necessary for sustainable production. This study investigates the effects of different powder materials used to replace cement (0%, 5% and 10%) and standard sand (0%, 20% and 30%) (basalt, limestone, and dolomite) on the compressive strength (f_c), flexural strength (f_r), and ultrasonic pulse velocity (UPV) of mortars exposed to freeze-thaw cycles (56, 86, 126, 186 and 226 cycles). Furthermore, the usability of artificial intelligence models is compared, and the prediction accuracy of the outputs is examined according to the inputs (powder type, replacement ratio, and the number of cycles). The results show that the variability of the outputs was significantly high under the freeze-thaw effect in mortars produced with waste powder instead of those produced with cement and with standard sand. The highest prediction accuracy for all outputs was obtained using the adaptive-network-based fuzzy inference system model. The significantly high prediction accuracy was obtained for the UPV, f_c, and f_r of mortars produced using waste powders instead of standard sand (R² of UPV, f_c and f_f is 0.931, 0.759 and 0.825 respectively), when under the freeze-thaw effect. However, for the mortars produced using waste powders instead of cement, the prediction accuracy of UPV was significantly high (R²=0.889) but the prediction accuracy of f_c and f_r was low (R²f_c=0.612 and R²f_f=0.334).

• Earthquakes and Structures
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• v.21 no.5
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• pp.551-562
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• 2021

In this study, the generalized intensity measure (IM) named I_Npg is analyzed. The recently proposed proxy of the spectral shape named N_pg is the base of this intensity measure, which is similar to the traditional N_p based on the spectral shape in terms of pseudo-acceleration; however, in this case the new generalized intensity measure can be defined through other types of spectral shapes such as those obtained with velocity, displacement, input energy, inelastic parameters and so on. It is shown that this IM is able to increase the efficiency in the prediction of nonlinear behavior of structures subjected to earthquake ground motions. For this work, the efficiency of two particular cases (based on acceleration and velocity) of the generalized I_Npg to predict the peak floor acceleration demands on steel frames under 30 earthquake ground motions with respect to the traditional spectral acceleration at first mode of vibration Sa(T₁) is compared. Additionally, a 3D reinforced concrete building and an irregular steel frame is used as a basis for comparison. It is concluded that the use of velocity and acceleration spectral shape increase the efficiency to predict peak floor accelerations in comparison with the traditional and most used around the world spectral acceleration at first mode of vibration.