Compressive Strength Of Concrete Columns Research Articles

Data‐driven investigation of compressive strength of FRP‐confined concrete columns using a unified model based on RSM considering interactions between parameters

AbstractIn this study, a data‐driven model was developed to predict compressive strength of concrete columns after confining with Fiber‐Reinforced Polymer (FRP). Through application of Response Surface Method (RSM), interactions of input parameters are investigated in addition to their individual influence. Moreover, RSM is utilized in conjunction with unification to enhance model's accuracy. Furthermore, sensitivity analysis is employed together with RSM, to determine the effect size of statistically significant parameters. It is revealed that the real behavior of FRP confined concrete cannot be predicted by single‐parameter studies. Therefore, interaction terms should be included in the model to yield a more accurate prediction. Moreover, the model shows the highest sensitivity to FRP failure strength which this sensitivity decreases as corner radius increases. Therefore, regarding rounded‐corner sections, high improvements are achievable even by utilizing low strength FRPs. It is also shown that higher improvement may be limited due to premature debonding which elastic modulus mismatch between different phases is supposed to be responsible for it.

Machine Learning Based Compressive Strength Prediction Model for CFRP-confined Columns

The study described in the paper focuses on the compressive strength of concrete columns that are reinforced with carbon fiber reinforced polymer (CFRP). The researchers aimed to identify the main parameters that affect the compressive strength of these confined columns. They used models to analyze and study the relationship between these parameters and the compressive strength. The study found that certain parameters had an inverse relationship with compressive strength. These parameters include the column diameter, CFRP fracture strain, and modulus of elasticity. On the other hand, the CFRP thickness and concrete strength exhibited a positive relationship with the compressive strength. The study also determined that the influence of column diameter and CFRP thickness was greater compared to the influence of CFRP fracture strain and elastic modulus on the compressive strength. To predict the compressive strength, the researchers developed a machine learning algorithm-based compressive strength prediction model. They found that a backpropagation (BP) neural network model showed high prediction accuracy and robustness in predicting the strength. Additionally, the researchers' model was analyzed, and it was found that while the calculated values from their model aligned well with the experimental results, there were some issues with overestimating or conservatively estimating the compressive strength in certain cases.

Compressive strength of concrete cylindrical columns confined with fabric-reinforced cementitious matrix composites under monotonic loading: Application of machine learning techniques

The reinforcement of concrete columns with fabric reinforced cementitious matrix (FRCM) is one of the most challenging issues in the construction of concrete structures, as there is still an absence of a promising model to assess their performance. This is because the behavior of such elements is complex and accompanied by a high margin of uncertainty. To address this issue, this study compiles a large dataset of the performance of FRCM-reinforced concrete columns under monotonic load. The obtained dataset is then used to train an artificial neural network (ANN) as a promising method for predicting the compressive strength of concrete columns with acceptable accuracy. Afterward, using a genetic algorithm (GA)-based regression model, a simplified formula is developed as an explicit model for predicting the compressive strength of FRCM-confined concrete columns. Additionally, a reliability model is established and solved by the Monte Carlo sampling method to capture the uncertainty and provide the results probabilistically. The results indicate that with the increase of fcc, the probability of exceedance is sharply reduced, so that the failure probability of fcc greater than 68 MPa falls below 2%. Moreover, a reliability sensitivity analysis is performed to measure the effects of input parameters on the resulting exceedance probability. The results reveal that the greatest impact of column diameter and height falls within the small range of fcc between 25 and 35 MPa. The maximum effect of temperature and unconfined concrete compressive strength, however, happens in the medium range of fcc between 35 and 45 MPa. Additionally, the percentage of fiber mostly affects the large range of fcc between 45 and 49 MPa.

Estimating the compressive strength of rectangular fiber reinforced polymer–confined columns using multilayer perceptron, radial basis function, and support vector regression methods

Recently, there has been a tendency to use machine learning (ML)–based methods, such as artificial neural networks (ANNs), for more accurate estimates. This paper investigates the effectiveness of three different machine learning methods including radial basis function neural network (RBNN), multi-layer perceptron (MLP), and support vector regression (SVR), for predicting the ultimate strength of square and rectangular columns confined by various FRP sheets. So far, in the previous study, several experiments have been conducted on concrete columns confined by fiber reinforced polymer (FRP) sheets with the results suggesting that the use of FRP sheets enhances the compressive strength of concrete columns effectively. Also, a wide range of experimental data (including 463 specimens) has been collected in this study for square and rectangular columns, confined by various FRP sheets. The comparison of ML-derived results with the experimental findings, which were in a very good agreement, demonstrated the ability of ML to estimate the compressive strength of concrete confined by FRP; the correlation coefficient (R2) for MLP, RBFNN, and SVR methods was equal to 0.97, 0.97, and 0.90, respectively. Similar accuracy was obtained by MLP and RBFNN, and they provided better estimates for determining the compressive strength of concrete confined by FRP. Also, the results showed that the difference between statistical indicators for training and testing specimens in the RBFNN method was greater than the MLP method, and this difference indicated the poor performance of RBFNN.

Pre-Load Effect on CFRP-Confinement of Concrete Columns: Experimental and Theoretical Study

The axial compression strength of concrete columns has been proved to be significantly enhanced by external confinement. In this perspective, the use of Fiber-Reinforced Polymers (FRPs) has been extensively studied. In practical applications, the FRP-confinement is installed on loaded columns, which can already be significantly deformed, while theoretical models neglect this aspect. This paper concerns a new experimental investigation on the possibility that a pre-existing axial load affects the FRP-confinement of concrete. The research program also aimed at the development of a new analysis-oriented-model for the prediction of the compressive strength of FRP-jacketed concrete columns, depending on the level of the axial load, acting before the confinement. For this purpose, series of small-scale concrete cylinders were first loaded, then confined with Carbon FRP, and finally subjected to destructive pure axial compression tests. Four different levels of pre-existing loads were simulated, including the un-loaded condition.

Experimental determination of the residual compressive strength of concrete columns subjected to different fire durations and load ratios

Purpose At elevated temperatures, concrete undergoes changes in its mechanical and thermal properties, which mainly cause degradation of strength and eventually may lead to the failure of the structure. Retrofitting is a desirable option to rehabilitate fire damaged concrete structures. However, to ensure safe reuse of fire-exposed buildings and to adopt proper retrofitting methods, it is essential to evaluate the residual load-bearing capacity of such fire-damaged reinforced concrete structures. The focus of the experimental study presented in this paper aims to investigate the fire performance of concrete columns exposed to a standard fire, and then evaluate its residual compressive strengths after fire exposure of different durations. Design/methodology/approach To effectively study the fire performance of such columns, eight identical 200 × 200 × 1,500-mm high reinforced concrete columns test specimens were subjected to two different fire exposure (1- and 2-h) while being loaded with two different load ratios (20% and 40% of the column ultimate design axial compressive load). In a subsequent stage and after complete cooling down, residual compressive strength capacity tests were performed on each fire exposed column. Findings Experimental results revealed that the columns never regain its original capacity after being subjected to a standard fire and that the residual compressive strength capacity dropped to almost 50% and 30% of its ambient temperature capacity for the columns exposed to 1- and 2-h fire durations, respectively. It was also noticed that, for the tested columns, the applied load ratio has much less effect on the column’s residual compressive strength compared to that of the fire duration. Originality/value According to the unique outcomes of this experimental study and, as the fire-damaged concrete columns possessed considerable residual compressive strength, in particular those exposed to shorter fire duration, it is anticipated that with proper retrofitting techniques such as fiber-reinforced polymers (FRP) wrapping, the fire-damaged columns can be rehabilitated to regain at least portion of its lost load-bearing capacities. Accordingly, the residual compressive resistance data obtained from this study can be effectively used but not directly to adopt optimal retrofitting strategies for such fire-damaged concrete columns, as well as to be used in validating numerical models that can be usefully used to account for the thermally-induced degradation of the mechanical properties of concrete material and ultimately predict the residual compressive strengths and deformations of concrete columns subjected to different load intensity ratios for various fire durations.

Analysis of Compressive Strength of Existing Higher Educational Institutions (HEI) Concrete Column using a Schmidt Rebound Hammer

The Schmidt rebound hammer is principally a surface hardness tester with an apparent theoretical relationship between the strength of hardened concrete block and the rebound number of the hammer. This study analysed compressive strength of some selected concrete columns of Civil Engineering block at Covenant University Ota, using the Schmidt rebound hammer. It is aimed at determining variation in the concrete column strength of the HEI building in relation to standard compressive strength required of a concrete column. Data for the study was collected by carrying our Schmidt rebound hammer test (non-destructive test) on the concrete column within the study area and the rebound value (R) was measured to determine the present compressive strength of the concrete column. In carrying out this experiment, the standard experiment procedure of the Schmidt hammer test was followed. The analysis of the performed nondestructive test on the HEI concrete column was presented through tables and figures. The result of the study shows that there is variation in the compressive strength of the HEI concrete columns sampled using Schmidt rebound hammer test. The result indicated that the average compressive strength gotten through the rebound values of the sampled concrete columns compressive strength falls within the minimum required strength between 25N/mm2 and 30N/mm2 expected of a concrete column of an existing structure. The study therefore, concluded that the concrete columns of the HEI building sampled is safe, stable and it can satisfy the need for which it was built. Furthermore, because of it stability it can resist the load coming to it and this make it habitable for learning.

Study of the influence of compressive strength concrete on columns during the design of a multi-floor building

Abstract This work aims to analyze the influence of the compressive strength of concrete columns in the design of a multi-floor building using the CAD/TQS computational tool. The strengths of the columns varied in increments of 5 MPa, from 35 MPa to 90 MPa, with a 35 MPa resistance in the remaining structural elements. Analyses of the horizontal deformability, stability parameters, and optimized sections, as well as quantities and cost of the main materials used (concrete, steel, and formwork), were performed. As a result, a 32% reduction to the total area of the columns was achieved; consequently, a reduction in material quantities and the total cost of the building was also achieved. Thus, greater durability was provided without major costs or loss in structural safety.

Increasing the Contribution of GFRP Bars on the Compressive Strength of Concrete Columns with Circular Cross Section

Corrosion of steel in concrete elements is a major issue in concrete structures. In order to overcome this matter, Glass Fiber Reinforced Polymer (GFRP) reinforcement is being used in concrete members from almost 20 years ago. Although it has been used and developed in recent years, there are still some uncertainties for the application of FRP reinforcement, especially in concrete columns. Most codes such as ACI, CSA, JSCE & etc. neglects the effect of these reinforcements or they do not permit them in compressive concrete elements. In this essay, it has been shown that these rebar can contribute significantly in compressive strength of concrete columns if the column confinement is provided sufficiently. In order to achieve the required confinement to reach a sharp contribution of GFRP longitudinal rebar in concrete columns, the spiral of FRP rebar with small pitches around longitudinal rebar is taken into account. This leads to higher strains of concrete which can result in a higher contribution of FRP longitudinal rebar. Foremost, equations related to the compressive strength of concrete columns considering the influence of spiral confinement will be carried out. Then, a parametric study will be performed, and the effects of pitch, concrete strength, column diameter, the quantity of longitudinal rebar and concrete cover will be investigated.

New models for estimating compressive strength of concrete confined with FRP sheets in circular sections

Models for determining the compressive strength of concrete columns confined by FRP have been presented in previous studies. In this study, a large set of experimental data regarding circular colum...

Compressive behaviour of concrete columns confined with steel-reinforced grout jackets

Abstract This paper investigates the compressive strength of concrete columns confined with a new jacketing system using high strength steel reinforced fabrics embedded in an inorganic matrix (SRG). A comprehensive experimental programme was conducted on 52 cylindrical columns with SRG jackets and 15 control specimens under monotonic uniaxial compression load. The test specimens were designed to investigate the influence of different design parameters including the density of the fabric (1, 1.57, 4.72 cords/cm), number of layers (1, 2), overlap length (24, 36 cm), bonding agent (4 different types of mortar) and the concrete strength (16–30 MPa). The test results highlight the efficiency of the proposed method, where one-layered and two-layered SRG jackets could increase the strength capacity of the unconfined specimens by up to 122% and 193%, respectively.

Multiscale modeling for compressive strength of concrete columns with circular cross-section

In order to construct a multiscale model for the compressive strength of plain concrete columns with circular cross section subjected to central longitudinal compressive load, a column failure mechanism is proposed based on the theory of internal instability. Based on an energy analysis, the multiscale model is developed to describe the failure process and predict the column's compressive strength. Comparisons of the predicted results with experimental data show that the proposed multiscale model can accurately represent both the compressive strength of the concrete columns with circular cross section, and the effect of column size on its strength.

Compressive strength of reinforced concrete column confined by composite material

Thus study has two parts. The first describes experiments and the second presents a model to accurately predict the compressive strength of concrete columns confined by composite materials. FRP is wrapped around concrete columns and RC columns to determine the difference between their behaviors under uniaxial compression. Experimental results indicate that the FRP confinements of the two specimen types are similar. Accordingly, a method for analyzing the behavior of an FRP-wrapped concrete column can be used also to analyze that of an FRP-wrapped RC column. When an RC column takes a uniaxial load, the concrete is first shear-fractured. Then, the steel is buckled and finally the FRP breaks. Confinement using FRP is a good ideal because FRP can be wrapped all around an RC column. Its stress–strain plot is bilinear. This study presents a theoretical stress–strain model. Some comparisons between experimental stress and the stress predicted using a model indicate that the present model is good to predict the fracture stress of FRP-wrapped concrete column.