• KCI Concrete Journal
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• v.12 no.2
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• pp.55-72
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• 2000

This paper proposes a mechanical model to describe the load-deformation responses of the reinforced concrete plate members under service load state. An Analytical method is introduced on the basis of the rotating crack model which considers equilibrium, compatibility conditions, load-strain relationship of cracked member, and constitutive law for materials. The tension stiffening effect in reinforced concrete structures is taken into account by the average tensile stress-strain relationship from the load-strain relationship for the cracked member and the constitutive law for material. The strain compatibility is used to find out the crack direction because the crack direction is an unknown variable in the equilibrium and compatibility conditions. The proposed theory is verified by the numerous experimental data such as the crack direction, moment-steel strain relationship, moment-crack width relationship. The present paper can provide some basis for the provision of the definition of serviceability for plate structures of which reinforcements are deviated from the principal stresses, because the present code defines the serviceability by the deflection, crack control, vibration and fatigue basically for the skeletal members. The proposed theory is applicable to predict the service load state behavior of a variety of reinforced concrete plate structures such as skew slab bridges, the deck of skew girder bridges.

• Computers and Concrete
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• v.21 no.4
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• pp.399-406
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• 2018

The present study focuses on the performance of basalt fiber reinforced concrete (BFRC) lining in tunnel situated in sandstone rock when subjected to internal blast loading. The blast analysis of the lined tunnel is carried out using the three-dimensional (3-D) nonlinear finite element (FE) method. The stress-strain response of the sandstone rock is simulated using a crushable plasticity model which can simulate the brittle behavior of rock and that of BFRC lining is analyzed using a damaged plasticity model for concrete capturing damage response. The strain rate dependent material properties of BFRC are collected from the literature and that of rock are taken from the authors' previous work using split Hopkinson pressure bar (SHPB). The constitutive model performance is validated through the FE simulation of SHPB test and the comparison of simulation results with the experimental data. Further, blast loading in the tunnel is simulated for 10 kg and 50 kg Trinitrotoluene (TNT) charge weights using the equivalent pressure-time curves obtained through hydrocode simulations. The analysis results are studied for the stress and displacement response of rock and tunnel lining. Blast performance of BFRC lining is compared with that of plain concrete (PC) and steel fiber reinforced concrete (SFRC) lining materials. It is observed that the BFRC lining exhibits almost 65% lesser displacement as compared to PC and 30% lesser displacement as compared to SFRC tunnel linings.

• Steel and Composite Structures
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• v.26 no.1
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• pp.115-123
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• 2018

Steel-concrete composite structure is widely applied to bridge engineering due to their outstanding mechanical properties and economic benefit. This paper studied a new type of steel-concrete composite anchorage system for a self-anchored suspension bridge and focused on the mechanical behavior and force transferring mechanism. A model with a scale of 1/2.5 was prepared and tested in ten loading cases in the laboratory, and their detailed stress distributions were measured. Meanwhile, a three-dimensional finite element model was established to understand the stress distributions and validated against the experimental measurement data. From the results of this study, a complicated stress distribution of the steel anchorage box with low stress level was observed. In addition, no damage and cracking was observed at the concrete surrounding this steel box. It can be concluded that the composite effect between the concrete surrounding the steel anchorage box and this steel box can be successfully developed. Consequently, the steel-concrete composite anchorage system illustrated an excellent mechanical response and high reliability.

• Computers and Concrete
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• v.25 no.1
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• pp.29-36
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• 2020

This work presents a numerical modeling procedure to simulate the refractory concrete lining in fluid catalytic cracking units of oil refineries. The model includes the simulation of the anchors that reinforce the contact between the refractory concrete and the steel casing. For this purpose, the constitutive relations of an interface finite element are set to values that represent the homogenized behavior of the anchored interface. The parameters of this constitutive relation can be obtained by experimental tests. The model includes also multi-surface plasticity, in order to represent the behavior of the refractory concrete lining. Since the complexity of real case applications leads to high computational costs, the models presented here were implemented in a high-performance parallelized finite element platform. A case study representing a riser similar to the ones used by the refinery industry demonstrates the potential of the model.

• Structural Engineering and Mechanics
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• v.37 no.2
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• pp.215-231
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• 2011

As a brittle and heterogeneous material, concrete behaves differently under different stress conditions and its bulk strength is loading rate dependent. To a large extent, the varying behavioural properties of concrete can be explained by the mechanical failure processes at a mesoscopic level. The development of a computational mesoscale model in a general finite element environment, as presented in the preceding companion paper (Part 1), makes it possible to investigate into the underlying mechanisms governing the bulk-scale behaviour of concrete under a variety of loading conditions and to characterise the variation in quantitative terms. In this paper, we first present a series of parametric studies on the behaviour of concrete material under quasi-static compression and tension conditions. The loading-face friction effect, the possible influences of the non-homogeneity within the mortar and ITZ phases, and the effect of randomness of coarse aggregates are examined. The mesoscale model is then applied to analyze the dynamic behaviour of concrete under high rate loading conditions. The potential contribution of the mesoscopic heterogeneity towards the generally recognized rate enhancement of the material compressive strength is discussed.

• Structural Engineering and Mechanics
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• v.73 no.5
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• pp.515-527
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• 2020

This paper presents a stress field approach for the shear capacity of stirrup-reinforced concrete beams that explicitly incorporates the contribution of principal tensile stresses in concrete. This formulation represents an extension of the variable strut inclination method adopted in the Eurocode 2. In this model, the stress fields in web concrete consist of principal compressive stresses inclined at an angle θ combined with principal tensile stresses oriented along a direction orthogonal to the former (the latter being typically neglected in other formulations). Three different failure mechanisms are identified, from which the strut inclination angle and the corresponding shear strength are determined through equilibrium principles and the static theorem of limit analysis, similar to the EC-2 approach. It is demonstrated that incorporating the contribution of principal tensile stresses of concrete slightly increases the ultimate inclination angle of the compression struts as well as the shear capacity of reinforced concrete beams. The proposed stress field approach improves the prediction of the shear strength in comparison with the Eurocode 2 model, in terms of both accuracy (mean) and precision (CoV), as demonstrated by a broad comparison with more than 200 published experimental results from the literature.

• Structural Engineering and Mechanics
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• v.29 no.3
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• pp.259-278
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• 2008

This paper presents a nonlinear finite element procedure accounting for the effects of geometric as well as material nonlinearities for reinforced concrete bridge piers supported by laminated rubber bearings. Reinforced concrete bridge piers supported by laminated rubber bearings and carrying a cyclic load were analyzed by using a special purpose, nonlinear finite element program, RCAHEST. For reinforced concrete, the proposed robust nonlinear material model captures the salient response characteristics of the bridge piers under cyclic loading conditions and addresses with the influence of geometric nonlinearity on post-peak response of the bridge piers by transformations between local and global systems. Seismic isolator element to predict the behaviors of laminated rubber bearings is also developed. The seismic performance of reinforced concrete bridge piers supported by laminated rubber bearings is assessed analytically. The results show good correlation between the experimental findings and numerical predictions, and demonstrate the reliability and robustness of the proposed analytical model. Additionally, the studies and discussions presented in this investigation provide an insight into the key behavioral aspects of reinforced concrete bridge piers supported by laminated rubber bearings.

• Journal of Industrial Technology
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• v.41 no.1
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• pp.1-6
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• 2021

Fly ash and silica fume belong to industry by-products that can be used to produce concrete. This study shows the model of a neural network to evaluate the strength development of blended concrete containing fly ash and silica fume. The neural network model has four input parameters, such as fly ash replacement content, silica fume replacement content, water/binder ratio, and ages. Strength is the output variable of neural network. Based on the backpropagation algorithm, the values of elements in the hidden layer of neural network are determined. The number of neurons in the hidden layer is confirmed based on trial calculations. We find (1) neural network can give a reasonable evaluation of the strength development of composite concrete. Neural network can reflect the improvement of strength due to silica fume additions and can consider the reductions of strength as water/binder increases. (2) When the number of neurons in the hidden layer is five, the prediction results show more accuracy than four neurons in the hidden layer. Moreover, five neurons in the hidden layer can reproduce the strength crossover between fly ash concrete and plain concrete. Summarily, the neural network-based model is valuable for design sustainable composite concrete containing silica fume and fly ash.

• Steel and Composite Structures
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• v.44 no.3
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• pp.389-406
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• 2022

Recycling concrete construction waste is an encouraging step toward green and sustainable building. A lot of research has been done on recycled aggregate concretes (RACs), but not nearly as much has been done on concrete made with recycled aggregate. Recycled aggregate concrete, on the other hand, has been found to have a lower mechanical productivity compared to conventional one. Accurately estimating the mechanical behavior of the concrete samples is a most important scientific topic in civil, structural, and construction engineering. This may prevent the need for excess time and effort and lead to economic considerations because experimental studies are often time-consuming, costly, and troublous. This study presents a comprehensive data-mining-based model for predicting the splitting tensile strength of recycled aggregate concrete modified with glass fiber and silica fume. For this purpose, first, 168 splitting tensile strength tests under different conditions have been performed in the laboratory, then based on the different conditions of each experiment, some variables are considered as input parameters to predict the splitting tensile strength. Then, three hybrid models as GWO-RF, GWO-MLP, and GWO-SVR, were utilized for this purpose. The results showed that all developed GWO-based hybrid predicting models have good agreement with measured experimental results. Significantly, the GWO-RF model has the best accuracy based on the model performance assessment criteria for training and testing data.

• Advances in concrete construction
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• v.14 no.1
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• pp.15-34
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• 2022

The use of waste rubber in concrete can reduce natural aggregate consumption and improve some technical properties of concrete. Although there are several equations for estimating the mechanical properties of concrete containing waste rubber, limited numbers of machine learning-based models have been proposed to predict the mechanical properties of rubbercrete. In this study, an extensive database of the mechanical properties of rubbercrete was gathered from a comprehensive survey of the literature. To model the mechanical properties of rubbercrete, M5P tree and linear gene expression programming (LGEP) methods as two machine learning techniques were employed to achieve reliable mathematical equations. Two procedures of input variable selection were considered in this study. The crucial component ratios of rubbercrete and concrete age were assumed as the input variables in the first procedure. In contrast, the volumes of the coarse and fine waste rubber and the compressive strength of concrete without waste rubber were considered the second procedure of the input variables. The results show that the models obtained by LGEP are more accurate than those achieved by the M5P model tree and existing traditional equations. Besides, the volumes of the coarse and fine waste rubber and the compressive strength of concrete without waste rubber are better predictors of the mechanical properties of rubbercrete compared to the first procedure of input variable selection.