• Computers and Concrete
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• v.27 no.2
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• pp.153-162
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• 2021

This paper aims to simulate the isotropic elastic damage theory of Liu Jun (2012) using the self-programmed UMAT subroutine in the interface of ABAQUS. Liu Jun (2012)'s method based on the mechanic theory can not be used interactively with the currently commonly used finite element software ABAQUS. The advantage of this method in the paper is that it can interact with ABAQUS and provide a constitutive program framework that can be modified according to user need. The model retains the two scalar damage variables and the corresponding two energy dissipation mechanisms and damage criteria for considering the tensile and compressive asymmetry of concrete. Taking C45 concrete as an example, the relevant damage evolution parameters of its tensile and compressive constitutive model are given. The study demonstrates that the uniaxial tensile stress calculated by the subroutine is almost the same as the Chinese Concrete Design Specification (GB50010) before the peak stress, but ends soon after the peak stress. The stress-strain curve of uniaxial compression calculated by the subroutine is in good agreement with the peak stress in Chinese Concrete Design Specification (GB50010), but there is a certain deviation in the descending stage. In addition, this paper uses the newly compiled subroutine to simulate the shear bearing capacity of the shear key in a new structural system, namely the open-web sandwich slab. The results show that the damage constitutive subroutine has certain reliability.

• Advances in concrete construction
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• v.13 no.1
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• pp.11-23
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• 2022

Conventional concrete needs some improvement in the mechanical properties, which can be obtained by different admixtures. However, making concrete samples costume always time and money. In this paper, different types of hybrid algorithms are applied to develop predictive models for forecasting compressive strength (CS) of concretes containing metakaolin (MK) and fly ash (FA). In this regard, three different algorithms have been used, namely multilayer perceptron (MLP), radial basis function (RBF), and support vector machine (SVR), to predict CS of concretes by considering most influencers input variables. These algorithms integrated with the grey wolf optimization (GWO) algorithm to increase the model's accuracy in predicting (GWMLP, GWRBF, and GWSVR). The proposed MLP models were implemented and evaluated in three different layers, wherein each layer, GWO, fitted the best neuron number of the hidden layer. Correspondingly, the key parameters of the SVR model are identified using the GWO method. Also, the optimization algorithm determines the hidden neurons' number and the spread value to set the RBF structure. The results show that the developed models all provide accurate predictions of the CS of concrete incorporating MK and FA with R² larger than 0.9972 and 0.9976 in the learning and testing stage, respectively. Regarding GWMLP models, the GWMLP1 model outperforms other GWMLP networks. All in all, GWSVR has the worst performance with the lowest indices, while the highest score belongs to GWRBF.

• Computers and Concrete
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• v.28 no.5
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• pp.441-450
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• 2021

This study presents the first analysis system and fast-access cloud database for shrinkage and creep of concrete in the world, named "shrinkage and creep database in Taiwan", SCDT. SCDT not only has the most comprehensive experimental data, including NU, JSCE, Europe, and TW databases, but provides a design tool for researchers and engineers. It can further facilitate the development of prediction models for localized concrete. Users can obtain the shrinkage and creep curves based on their selected prediction models in SCDT. Comparisons of the predicted results of selected models and test results in the chosen database can be generated in seconds. One example of the development of basic creep prediction model in Taiwan based on model B4 by using SCDT to reflect concrete characteristics in Taiwan is also presented in this study. Users anywhere in the world can easily access SCDT to browse and upload data, receive predictive results, or develop predictive models.

• Computers and Concrete
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• v.31 no.4
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• pp.307-314
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• 2023

In this paper we back-analyze a failure event of a 9 m high concrete cantilever wall subjected to earth loading. Granular soil was deposited into the space between the wall and a nearby rock slope. The wall segments were not designed to carry lateral earth loading and collapsed due to excessive bending. As many geotechnical programs rely on the Mohr-Coulomb (MC) criterion for elastoplastic analysis, it is useful to apply this failure criterion to the concrete material. Accordingly, the back-analysis is aimed to search for the suitable MC parameters of the concrete. For this study, we propose a methodology for accelerating the back-analysis task by automating the numerical modeling procedure and applying a machine-learning (ML) analysis on FE model results. Through this analysis it is found that the residual cohesion and friction angle have a highly significant impact on model results. Compared to traditional back-analysis studies where good agreement between model and reality are deemed successful based on a limited number of models, the current ML analysis demonstrate that a range of possible combinations of parameters can yield similar results. The proposed methodology can be modified for similar calibration and back-analysis tasks.

• Steel and Composite Structures
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• v.47 no.5
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• pp.645-661
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• 2023

Concrete-filled steel tubular columns with double inner steel tubes (CFST-DIST) are a novel type of composite members developed from conventional concrete-filled steel tubular (CFST) columns. This paper investigates the structural performance of circular CFST-DIST stub columns using nonlinear finite element (FE) analysis. A numerical model was developed and verified against existing experimental test results. The validated model was then used to compare circular CFST-DIST stub columns' behavior with their concrete-filled double skin steel tubular (CFDST) and CFST counterparts. A parametric study was performed to ascertain the effects of geometric and material properties on the axial performance of CFST-DISTs. The FE results and the available test data were used to assess the accuracy of the European and American design regulations in predicting the axial compressive capacity of circular CFST-DIST stub columns. Finally, a new design model was recommended for estimating the compressive capacity of CFST-DISTs. Results clarified that circular CFST-DIST columns had the advantages of their CFST counterparts but with better ductility and strength-to-weight ratio. Besides, the investigated design codes led to conservative predictions of the compressive capacity of circular CFST-DIST columns.

• Computers and Concrete
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• v.32 no.1
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• pp.1-13
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• 2023

This paper discusses a framework for predicting the flexural strength of prestressed and non-prestressed FRP reinforced T-shaped concrete beams using soft computing techniques. An analysis of 83 tests performed on T-beams of varying widths has been conducted for this purpose with different widths of compressive face, beam depth, compressive strength of concrete, area of prestressed and non-prestressed FRP bars, elasticity modulus of prestressed and non-prestressed FRP bars, and the ultimate tensile strength of prestressed and non-prestressed FRP bars. By analyzing the data using two soft computing techniques, named artificial neural networks (ANN) and gene expression programming (GEP), the fundamental parameters affecting the flexural performance of prestressed and non-prestressed FRP reinforced T-shaped beams were identified. The results showed that although the proposed ANN model outperformed the GEP model with higher values of R and lower error values, the closed-form equation of the GEP model can provide a simple way to predict the effect of input parameters on flexural strength as the output. The sensitivity analysis results revealed the most influential input parameters in ANN and GEP models are respectively the beam depth and elasticity modulus of FRP bars.

• Advances in nano research
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• v.13 no.4
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• pp.369-378
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• 2022

Dynamic study of concrete plates under impact load is presented in this article. The main objective of this work is presenting a mathematical model for the concrete plates under the impact load. The concrete plate is reinforced by carbon nanoparticles which the effective material proprieties are obtained by mixture's rule. Impacts are assumed to occur normally over the top layer of the plate and the interaction between the impactor and the structure is simulated using a new equivalent three-degree-of-freedom (TDOF) spring-mass-damper (SMD) model. The structure is assumed viscoelastic based on Kelvin-Voigt model. Based on the classical plate theory (CPT), energy method and Hamilton's principle, the motion equations are derived. Applying DQM, the dynamic deflection and contact force of the structure are calculated numerically so that the effects of mass, velocity and height of the impactor, volume percent of nanoparticles, structural damping and geometrical parameters of structure are shown on the dynamic deflection and contact force. Results show that considering structural damping leads to lower dynamic deflection and contact force. In addition, increasing the volume percent of nanoparticles yields to decreases in the deflection.

• Geomechanics and Engineering
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• v.10 no.1
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• pp.49-57
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• 2016

The high permeability-high strength concrete belongs to the typical of porous materials. It is mainly used in underground engineering for cold area, it can act the role of heat preservation, also to be the bailing and buffer layer. In order to establish a suitable model to predict the thermal conductivity and directly applied for engineering, according to the structure characteristics, the thermal conductivity predicting model was built by resistance network model of parallel three-phase medium. For the selected geometric and physical cell model, the thermal conductivity forecast model can be set up with aggregate particle size and mixture ratio directly. Comparing with the experimental data and classic model, the prediction model could reflect the mixture ratio intuitively. When the experimental and calculating data are contrasted, the value of experiment is slightly higher than predicting, and the average relative error is about 6.6%. If the material can be used in underground engineering instead by the commonly insulation material, it can achieve the basic requirements to be the heat insulation material as well.

• Structural Engineering and Mechanics
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• v.7 no.4
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• pp.413-432
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• 1999

A macro-element model is developed to account for shear deformation and bond slip of reinforcement bars in the beam-column joint region of reinforced concrete structures. The joint region is idealized by two springs in series, one representing shear deformation and the other representing bond slip. The softened truss model theory is adopted to establish the shear force-shear deformation relationship and to determine the shear capacity of the joint. A detailed model for the bond slip of the reinforcing bars at the beam-column interface is presented. The proposed macro-element model of the joint is validated using available experimental data on beam-column connections representing exterior joints in ductile and nonductile frames.

• Computers and Concrete
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• v.16 no.1
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• pp.37-48
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• 2015

Alkali aggregate reaction affects numerous civil engineering structures and causes irreversible expansion and cracking. This work aims at developing model to predict the potential expansion of concrete containing alkali-reactive aggregates. First, the paper presents the experimental results concerning the influence of particle size of an alkali-reactive aggregate on mortar expansion studied at 0.15-0.80 mm, 1.25-2.50 mm and 2.5-5.0 mm size fractions and gives data necessary for model development. Results show that no expansion was measured on the mortars using small particles (0.15-0.80 mm) while the particles (1.25-2.50 mm) gave the largest expansions. Finally, model is proposed to simulate the experimental results by studying correlations between the measured expansions and the size of aggregates and to calculate the thickness of the porous zone necessary to take again all the volume of the gel created by this chemical reaction.