• Steel and Composite Structures
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• v.43 no.2
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• pp.165-183
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• 2022

Most transportation departments have recognized and developed procedures to address the ever-increasing weights of trucks traveling on bridges in a service today. Transportation agencies also recognize the issues with overheight vehicles' collisions with bridges, but few stakeholders have definitive countermeasures. Bridges are becoming more vulnerable to collisions from overheight vehicles. The exact response under lateral impact force is difficult to predict. In this paper, nonlinear impact analysis shows that the degree of deformation recorded through the modeling of the unprotected vehicle-girder model provides realistic results compared to the observation from the US-61 bridge overheight vehicle impact. The predicted displacements are 0.229 m, 0.161 m, and 0.271 m in the girder bottom flange (lateral), bottom flange (vertical), and web (lateral) deformations, respectively, due to a truck traveling at 112.65 km/h. With such large deformations, the integrity of an impacted bridge becomes jeopardized, which in most cases requires closing the bridge for safety reasons and a need for rehabilitation. We proposed different sacrificial cushion systems to dissipate the energy of an overheight vehicle impact. The goal was to design and tune a suitable energy absorbing system that can protect the bridge and possibly reduce stresses in the overheight vehicle, minimizing the consequences of an impact. A material representing a Sorbothane high impact rubber was chosen and modeled in ANSYS. Out of three sacrificial schemes, a sandwich system is the best in protecting both the bridge and the overheight vehicle. The mitigation system reduced the lateral deflection in the bottom flange by 89%. The system decreased the stresses in the bridge girder and the top portion of the vehicle by 82% and 25%, respectively. The results reveal the capability of the proposed sacrificial system as an effective mitigation system.

• Structural Engineering and Mechanics
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• v.83 no.4
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• pp.551-561
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• 2022

In this paper, the effect of fire conditions according to ISO 834 standard on the behavior of carbon fibre-reinforced plastic (CFRP) reinforced steel beams coated with gypsum-based mortar has been investigated numerically. To study the efficiency of these beams, 3D coupled temperature-displacement finite element analyzes have been conducted. Mechanical and thermal characteristics of three different parts of composite beams, i.e., steel, CFRP plate, and fireproof coating, were considered as a function of temperature. The interaction between steel and CFRP plate has been simulated employing the adhesion model. The effect of temperature, CFRP plate reinforcement, and the fireproof coating thickness on the deformation of the beams have been analyzed. The results showed that within the first 120 min of fire exposure, increasing the thickness of the fireproof coating from 1 mm to 10 mm reduced the maximum temperature of the outer surface of the steel beam from 380℃ to 270℃. This increase in the thickness of the fireproof layer decreased the rate of growth in the temperature of the steel beam by approximately 30%. Besides excellent thermal resistance and gypsum-based mortar, the studied fireproof coating method could provide better fire resistance for steel structures and thus can be applied to building materials.

• Structural Engineering and Mechanics
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• v.83 no.4
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• pp.515-535
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• 2022

The strength models for fiber-reinforced polymer (FRP)-confined normal strength concrete (NC) cylinders available in the literature have been suggested based on small databases using limited variables of such structural members portraying less accuracy. The artificial neural network (ANN) is an advanced technique for precisely predicting the response of composite structures by considering a large number of parameters. The main objective of the present investigation is to develop an ANN model for the axial strength of FRP-confined NC cylinders using various parameters to give the highest accuracy of the predictions. To secure this aim, a large experimental database of 313 FRP-confined NC cylinders has been constructed from previous research investigations. An evaluation of 33 different empirical strength models has been performed using various statistical parameters (root mean squared error RMSE, mean absolute error MAE, and coefficient of determination R²) over the developed database. Then, a new ANN model using the Group Method of Data Handling (GMDH) has been proposed based on the experimental database that portrayed the highest performance as compared with the previous models with R²=0.92, RMSE=0.27, and MAE=0.33. Therefore, the suggested ANN model can accurately capture the axial strength of FRP-confined NC cylinders that can be used for the further analysis and design of such members in the construction industry.

• Structural Engineering and Mechanics
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• v.84 no.5
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• pp.685-697
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• 2022

Nanotechnology has become one of the interesting technique used in material science and engineering. However, it is low used in civil engineering structures. The purpose of the present study is to investigate the static behavior of concrete plates reinforced with silica-nanoparticles. Due to agglomeration effect of silica-nanoparticles in concrete, Voigt's model is used for obtaining the equivalent nano-composite properties. Furthermore, the plate is simulated mathematically with higher order shear deformation theory. For a large use of this study, the concrete plate is assumed resting on a Pasternak elastic foundation, including a shear layer, and Winkler spring interconnected with a Kerr foundation. Using the principle of virtual work, the equilibrium equations are derived and by the mean of Hamilton's principle the energy equations are obtained. Finally, based on Navier's technique, closed-form solutions of simply supported plates have been obtained. Numerical results are presented considering the effect of different parameters such as volume percent of SiO₂ nanoparticles, mechanical loads, geometrical parameters, soil medium, on the static behavior of the plate. The most findings of this work indicate that the use of an optimum amount of SiO₂ nanoparticles on concretes increases better mechanical behavior. In addition, the elastic foundation has a significant impact on the bending of concrete slabs.

• Steel and Composite Structures
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• v.47 no.2
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• pp.147-165
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• 2023

The paper contrasts conventional seismic design with a design that incorporates buckling-restrained bracing in three-dimensional reinforced concrete buildings (BRBs). The suboptimal structures may be found using the multi-objective chimp optimization algorithm (MEN-ChOA). Given the constraints and dimensions, ChOA suffers from a slow convergence rate and tends to become stuck in local minima. Therefore, the ChOA is improved by niching and evolutionary operators to overcome the aforementioned problems. In addition, a new technique is presented to compute seismic and dead loads that include all of a structure's parts in an algorithm for three-dimensional frame design rather than only using structural elements. The performance of the constructed multi-objective model is evaluated using 12 standard multi-objective benchmarks proposed in IEEE congress on evolutionary computation. Second, MEN-ChOA is employed in constructing several reinforced concrete structures by the Mexico City building code. The variety of Pareto optimum fronts of these criteria enables a thorough performance examination of the MEN-ChOA. The results also reveal that BRB frames with comparable structural performance to conventional moment-resistant reinforced concrete framed buildings are more cost-effective when reinforced concrete building height rises. Structural performance and building cost may improve by using a nature-inspired strategy based on MEN-ChOA in structural design work.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.255-264
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• 2023

As the demand for urban underground space increases recently, urban tunnel planning is actively progressing. In the urban area, a underground station is planned in consideration of the living environment of residents, and 2-arch tunnel is applied for the stability of existing structures and reduction of environmental damage. However, since the depth of weak rock mass is deeply distributed in the urban area due to severe weathering, careful planning is required to secure tunnel stability. In addition, if TBM mechanical excavation is applied as the main tunnel excavation method considering the composite ground in urban area, the construction connectivity with the 2-arch tunnel of the NATM concept may be deteriorated. In this study, the design case of applying TBM pre-excavation type 2-arch tunnel for the first time in Korea was mainly described. The main considerations for the segment design of TBM pre-excavation type 2-arch tunnel were explained for side tunnels. Also, a stability analysis was conducted to verify the effectiveness and adequacy of the TBM pre-excavation type 2-arch tunnel.

• Composites Research
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• v.36 no.5
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• pp.377-382
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• 2023

To enhance the performance of graphene-based devices, it is of great importance to better understand the interfacial interaction of graphene with its underlying substrates. In this study, the adhesion energy of monolayer graphene placed on dielectric substrates was characterized using mode I fracture tests. Large-area monolayer graphene was synthesized on copper foil using chemical vapor deposition (CVD) with methane and hydrogen. The synthesized graphene was placed on target dielectric substrates using polymer-assisted wet transfer technique. The monolayer graphene placed on a substrate was mechanically delaminated from the dielectric substrate by mode I fracture tests using double cantilever beam configuration. The obtained force-displacement curves were analyzed to estimate the adhesion energies, showing 1.13 ± 0.12 J/m² for silicon dioxide and 2.90 ± 0.08 J/m² for silicon nitride. This work provides the quantitative measurement of the interfacial interactions of CVD-grown graphene with dielectric substrates.

• 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.

• Structural Engineering and Mechanics
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• v.63 no.3
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• pp.361-370
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• 2017

Through the use of finite element analysis and acoustic emission techniques we have evaluated the interfacial failure of a carbon fiber reinforced polymer (CFRP) repair patch on a notched aluminum substrate. The repair of cracks is a very common and widely used practice in the aeronautics field to extend the life of cracked sheet metal panels. The process consists of adhesively bonding a patch that encompasses the notched site to provide additional strength, thereby increasing life and avoiding costly replacements. The mechanical strength of the bonded joint relies mainly on the bonding of the adhesive to the plate and patch stiffness. Stress concentrations at crack tips promote disbonding of the composite patch from the substrate, consequently reducing the bonded area, which makes this a critical aspect of repair effectiveness. In this paper we examine patch disbonding by calculating the influence of notch tip stress on disbond area and verify computational results with acoustic emission (AE) measurements obtained from specimens subjected to uniaxial tension. The FE results showed that disbonding first occurs between the patch and the substrate close to free edge of the patch followed by failure around the tip of the notch, both highest stress regions. Experimental results revealed that cement adhesion at the aluminum interface was the limiting factor in patch performance. The patch did not appear to strengthen the aluminum substrate when measured by stress-strain due to early stage disbonding. Analysis of the AE signals provided insight to the disbond locations and progression at the metal-adhesive interface. Crack growth from the notch in the aluminum was not observed until the stress reached a critical level, an instant before final fracture, which was unaffected by the patch due to early stage disbonding. The FE model was further utilized to study the effects of patch fiber orientation and increased adhesive strength. The model revealed that the effectiveness of patch repairs is strongly dependent upon the combined interactions of adhesive bond strength and fiber orientation.

• Composites Research
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• v.30 no.5
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• pp.323-330
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• 2017

In this study, multiscale analysis in which the information obtained from molecular dynamics simulation is applied to the continuum mechanics level is conducted to investigate the effects of clustering of silicon carbide nanoparticles reinforced into polypropylene matrix on mechanical behavior of nanocomposites. The elastic behavior of polymer nanocomposites is observed for various states of nanoparticulate agglomeration according to the model reflecting the degradation of interphase properties. In addition, factors which mainly affect the mechanical behavior of the nanocomposites are identified, and new index 'clustering density' is defined. The correlation between the clustering density and the elastic modulus of nanocomposites is understood. As the clustering density increases, the interfacial effect decreased and finally the improvement of mechanical properties is suppressed. By considering the random distribution of the nanoparticles, the range of elastic modulus of nanocomposites for same value of clustering density can be investigated. The correlation can be expressed in the form of exponential function, and the mechanical behavior of the polymer nanocomposites can be effectively predicted by using the nanoparticulate clustering density.