Basalt Fiber Reinforced Concrete Research Articles

Empirical models for compressive and tensile strength of basalt fiber reinforced concrete

When molten magma solidifies, basalt fiber (BF) is produced as a byproduct. Due to its remaining pollutants that could affect the environment, it is regarded as a waste product. To determine the compressive strength (CS) and tensile strength (TS) of basalt fiber reinforced concrete (BFRC), this study will develop empirical models using gene expression programming (GEP), Artificial Neural Network (ANN) and Extreme Gradient Boosting (XG Boost). A thorough search of the literature was done to compile a variety of information on the CS and TS of BFRC. 153 CS findings and 127 TS outcomes were included in the review. The water-to-cement, BF, fiber length (FL), and coarse aggregates ratios were the influential characteristics found. The outcomes showed that GEP can accurately forecast the CS and TS of BFRC as compared to ANN and XG Boost. Efficiency of GEP was validated by comparing Regression (R2) value of all three models. It was shown that the CS and TS of BFRC increased initially up to a certain limit and then started decreasing as the BF % and FL increased. The ideal BF content for industrial-scale BF reinforcement of concrete was investigated in this study which could be an economical solution for production of BFRC on industrial scale.

Flexural Performance Study of Basalt-Fiber-Reinforced Polymer Bar Basalt-Fiber-Reinforced Concrete Beams

The utilization of Fiber-Reinforced Polymer (FRP) rods to strengthen concrete beam structures can enhance their ultimate load-carrying capacity and mitigate steel reinforcement corrosion damage. However, a prominent issue with BFRP (Basalt FRP) rod reinforcement in flexural members is its lack of yielding behavior, which can lead to catastrophic brittle failure without any preventive measures. Therefore, this study aims to enhance the ductility of concrete by introducing a specific quantity of basalt fiber, thereby reducing the hazards associated with the brittle failure of this composite structure. This experiment focuses on two main variables: the inclusion rate of basalt fiber and the type of longitudinal reinforcement and conducts four-point static bending tests on four BFRP bar BFRC (Basalt-Fiber-Reinforced Concrete) beams. Results showed that the inclusion of fibers resulted in a delayed initiation of vertical cracks and a reduction in the severity of beam failure, thereby enhancing structural safety and reliability. When the basalt fiber inclusion rate was 0.2%, the cracking load and ultimate load of the beam increased by 18.42% and 8.27%, respectively. Furthermore, compared to traditional RC beams, BFRP bar BFRC beams showed a 58.27% increase in ultimate load capacity. A cracking moment calculation model for BFRP beams is proposed and subsequently validated through the utilization of existing experimental data.

Nonlinear Ultrasonic Characterization of Performance Variation of Basalt Fiber-Reinforced Concrete Subjected to Thermal Treatment and Water Curing

Nonlinear Ultrasonic Characterization of Performance Variation of Basalt Fiber-Reinforced Concrete Subjected to Thermal Treatment and Water Curing

Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface

This study investigated the importance of applying explainable artificial intelligence (XAI) on different machine learning (ML) models developed to predict the strength characteristics of basalt-fiber reinforced concrete (BFRC). Even though ML is widely adopted in strength prediction in concrete, the black-box nature of predictions hinders the interpretation of results. Among several attempts to overcome this limitation by using explainable AI, researchers have employed only a single explanation method. In this study, we used three tree-based ML models (Decision tree, Gradient Boosting tree, and Light Gradient Boosting Machine) to predict the mechanical strength characteristics (compressive strength, flexural strength, and tensile strength) of basal fiber reinforced concrete (BFRC). For the first time, we employed two explanation methods (Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME)) to provide explanations for all models. These explainable methods reveal the underlying decision-making criteria of complex machine learning models, improving the end user's trust. The comparison highlights that tree-based models obtained good accuracy in predicting strength characteristics yet, their explanations were different either by the magnitude of feature importance or the order of importance. This disagreement pushes towards complicated decision-making based on ML predictions which further stresses (1) extending XAI-based research in concrete strength predictions, and (2) involving domain experts to evaluate XAI results. The study concludes with the development of a “user-friendly computer application” which enables quick strength prediction of basalt fiber reinforced concrete (BFRC).

Deformation Damage and Energy Evolution of Basalt Fiber Reinforced Concrete under the Triaxial Compression

To explore the law of energy evolution and the change of damage before and after specimen failure, the conventional triaxial compression tests (5, 10, 15, 20, and 30 MPa) of basalt fiber reinforced concrete (BFRC) with different fiber volume fractions (0, 0.2% and 0.4%) were carried out by MTS816 rock testing system, and the cyclic loading and unloading tests of BFRC with a fiber content of 0.2% were carried out. The experimental results show that the peak strength and strain of BFRC increase with the increase of confining pressure. Tensile failure occurs under low confining pressure, and shear failure occurs under high confining pressure. The best volume fraction of fiber is 0.2%. Under different confining pressures, the input energy, elastic energy, plastic properties, and dissipated energy of the samples first increase and then decrease to a stable level. The elastic energy and dissipated energy reach the maximum near the peak stress, while the input energy and plastic properties reach the maximum at the peak. At the same time, the damage increases continuously with the input of load under different confining pressures, indicating that the failure of the specimen is a process of energy accumulation.

Compressive Strength Prediction of BFRC Based on a Novel Hybrid Machine Learning Model

Basalt fiber-reinforced concrete (BFRC) represents a form of high-performance concrete. In structural design, a 28-day resting period is required to achieve compressive strength. This study extended an extreme gradient boosting tree (XGBoost) hybrid model by incorporating genetic algorithm (GA) optimization, named GA-XGBoost, for the projection of compressive strength (CS) on BFRC. GA optimization may reduce many debugging efforts and provide optimal parameter combinations for machine learning (ML) algorithms. The XGBoost is a powerful integrated learning algorithm with efficient, accurate, and scalable features. First, we created and provided a common dataset using test data on BFRC strength from the literature. We segmented and scaled this dataset to enhance the robustness of the ML model. Second, to better predict and evaluate the CS of BFRC, we simultaneously used five other regression models: XGBoost, random forest (RF), gradient-boosted decision tree (GBDT) regressor, AdaBoost, and support vector regression (SVR). The analysis results of test sets indicated that the correlation coefficient and mean absolute error were 0.9483 and 2.0564, respectively, when using the GA-XGBoost model. The GA-XGBoost model demonstrated superior performance, while the AdaBoost model exhibited the poorest performance. In addition, we verified the accuracy and feasibility of the GA-XGBoost model through SHAP analysis. The findings indicated that the water–binder ratio (W/B), fine aggregate (FA), and water–cement ratio (W/C) in BFRC were the variables that had the greatest effect on CS, while silica fume (SF) had the least effect on CS. The results demonstrated that GA-XGBoost exhibits exceptional accuracy in predicting the CS of BFRC, which offers a valuable reference for the engineering domain.

Research on impact toughness and crack propagation of basalt fiber reinforced concrete under SHPB splitting test

To cope with accidents such as explosion and high-speed impact, it is necessary to study the dynamic mechanical response of basalt fiber reinforced concrete (BFRC) under impact load. The dynamic splitting test of BFRC was conducted under different impact air pressures by Φ50 mm split Hopkinson pressure bar (SHPB) experimental platform and dynamic DIC acquisition system. The dynamic mechanical characteristics of BFRC under impact load were studied, focusing on analyzing the effects of different basalt fiber (BF) volume rates and average strain rates on its impact toughness. Meanwhile, the process of crack initiation, propagation, and penetration in BFRC during damage and failure was analyzed by DIC technique, the propagation speed and width of tensile crack were calculated by strain nephogram and pixel information. The results show that BFRC with 0.3% fiber content has the highest dynamic splitting tensile strength, dissipated energy and ultimate toughness. The strain rate effect of post-peak toughness is more obvious than that of pre-peak toughness. BF increases the impact toughness of concrete mainly by affecting the post-peak toughness. The crack propagation speed of BFRC is the slowest and the tensile crack width is the smallest with 0.3% fiber content, that is, the appropriate BF content (0.3%) can effectively reduce the damage degree of the matrix under the impact load and has the most obvious effect on the crack resistance and toughening of the matrix.

Fracture properties of graded basalt fiber reinforced concrete: Experimental study and Mori-Tanaka method application

Fiber additions can improve the flexural strength of concrete, which is brittle. In this study, the improvement effect of graded basalt fibers on the mechanical properties of a matrix was studied at the macroscale using the elastic modulus, and compressive and flexural strengths. At the mesoscale, fiber concrete is regarded as a multiphase composite material composed of aggregate, cement mortar, fiber, and aggregate-mortar and fiber-mortar interface transition zones (ITZ). The Mori-Tanaka (M−T) homogenization theory was used to calculate the elastic modulus of basalt fiber-reinforced concrete (BFRC), and the accuracy of the test parameters was verified by comparing the test results with the homogenization results. Moreover, a finite element model (FEM) was established to reveal the crack evolution process and crack resistance mechanism of the graded fibers. The FEM results revealed that the addition of fibers reduces the stress intensity factor at the crack tip and inhibits the generation and development of cracks. Moreover, because of the side wall effect, short fibers were evenly distributed in the mortar and long fibers, which absorb and consume more energy during crack development and improve the mechanical strength and deformation capacity of the concrete, were more distributed near the aggregate.

Experimental Study of the Mechanical Properties and Microstructure of Basalt Fiber-Reinforced Concrete

Experimental Study of the Mechanical Properties and Microstructure of Basalt Fiber-Reinforced Concrete

Bond durability performance of sand-coated BFRP bars in high-strength fiber reinforced concrete

The ever-increasing utilization of fiber-reinforced polymer (FRP) bars has led to a surge in research regarding their bonding properties with concrete. In this study, the bond durability behavior between high-strength fiber-reinforced concrete (FRC) and sand-coated basalt FRP (BFRP) bars was examined under three different environmental conditions including immersion in seawater solution at 50 °C for 3, 6, and 9 months, immersion in the sulfuric acid solution for 3, 6, and 9 months with an ambient temperature range of 20 to 30 °C, and exposure to 270 freeze–thaw cycles. A total of 60 pull-out samples were prepared using either basalt (B) fibers or polypropylene (PP) fibers. Plain concrete pull-out samples were served as controls. Test results revealed that all exposures have degraded the bond, leading to pull-out failure in all of the specimens. Exposure to 50 °C seawater was found to cause the most significant degradation. However, the use of basalt fibers helped to mitigate the loss of bond strength in the specimens when compared to plain concrete specimens. For example, after 3, 6, and 9 months of exposure to 50 °C seawater, bond strength retentions of 73.58%, 56.04%, and 34.47% were observed for basalt FRC (BFRC) specimens, compared to 39.64%, 49.37%, and 29.61% for plain concrete specimens. On the other hand, a lower retention in bond strength of 16.28% was recorded for polypropylene FRC (PPFRC) specimens at 9 months of exposure to 50 °C seawater. The bond stress-slip relationship of the tested bars was accurately predicted using two calibrated analytical models: the Eligehausen, Popov, and Bertero (BPE) model and the Cosenza, Manfredi, and Realfonzo (CMR) model. Notably, both models showed a strong correlation with the observed bond stress-slip relationships in the experiments.

Effect of different fiber sizing on basalt fiber-reinforced cement-based materials at low temperature: From macro mechanical properties to microscopic mechanism

The interfacial bonding performance between basalt fiber bundles with three type of sizing agent and cement-based materials at different curing environment was studied through analyses on pull-out tests and scanning electron microscope (SEM) results. The mechanical development law of three type of basalt fiber reinforced concrete (BFRC) was studied through analyses on mechanical property tests and computed tomography (CT) results and theoretical analysis of molecular structure. It is concluded that: (1) The low-temperature environment significantly deteriorates the bonding properties of the basalt fiber and the cement mortar. The effect of bonding strength of basalt fiber cement mortar (BFCM) specimens with different fiber sizing agents differs significantly: dispersed type > flexible type > cluster type; (2) The SEM micro-morphology and CT scanning analysis show that the type of sizing agent affects the optimal volume dose of basalt fiber in concrete. Besides, the type of sizing agent affects the formation and development of the interface transition zone between the fiber and the cement matrix. (3) The differences in the molecular structure of the sizing agents have a significant effect on the interfacial properties of the basalt fiber-cement matrix, in which sizing agent containing KH560 component is better for the interface improvement between fiber and cement matrix. Large molecular weight epoxy resins may reduce the surface roughness of the basalt fiber sizing agents.

Acoustic Emission Wavelet Analysis and Damage Stage Identification of Basalt Fiber-Reinforced Concrete under Dynamic Splitting Tensile Loads

Acoustic Emission Wavelet Analysis and Damage Stage Identification of Basalt Fiber-Reinforced Concrete under Dynamic Splitting Tensile Loads

Experimental study on uniaxial compressive properties and damage evolution of basalt fiber reinforced concrete after being subjected to high temperature

The study investigated basalt fiber reinforced concrete (BFRC) for failure characteristics after being subjected to high temperatures under uniaxial compression. Twenty-five sets of cylindrical BFRC specimens were carried out under different basalt fiber (BF) content and temperature. Based on 3D digital image correlation (3D-DIC) and acoustic emission (AE), the effects of temperature and volume content of BF on the compressive mechanical properties, damage evolution and failure mode of BFRC are analyzed. The results indicate that the proper volume content (0.26%) of BF can improve the compressive strength of concrete. Generally, the uniaxial compressive strength of BFRC decreases with increasing temperature. The internal and external damage evolution trend of BFRC is basically the same, which can be divided into pore compaction stage, stable crack growth stage and unstable crack growth stage. The proper volume content (0.26%) of BF reduces the degree of BFRC damage. The increase in the volume content of BF leads to an increase shear cracks proportion in BFRC, and the failure mode of the main crack gradually changes from tension-shear failure to shear failure. Conversely, the increase in temperature increased the degree of BFRC damage. The internal and external failure modes of BFRC are basically the same. At 20 °C, the failure of concrete without basalt fiber is mainly tensile crack. With the increase of temperature, the main failure mode is tension-shear failure.

Study of Mechanical Properties of Pre-Stressed Basalt Fibre Reinforced Concrete – A Review

Study of Mechanical Properties of Pre-Stressed Basalt Fibre Reinforced Concrete – A Review

Investigating stress–strain relationship and damage constitutive model of basalt fiber reinforced concrete under uniaxial compression

Basalt fiber is a useful reinforcing and toughening material for concrete. The stress–strain relationship and damage evolution of concrete under compression can provide an experimental and theoretical basis for the design of structures. This research conducts uniaxial compression tests on basalt fiber reinforced concrete (BFRC) specimens with five different strength grades, namely BFRC25, BFRC30, BFRC40, BFRC50, and BFRC60, to investigate their stress–strain relationship. Digital image correlation (DIC) technology was adopted to analyze the damage evolution during the compressive loading process. Results revealed that with increasing the strength grade of BFRC, the peak stress and elastic modulus increased, the peak strain varied insignificantly, and the ratio of the ultimate strain to peak strain decreased. Considering the effects of the strength grade and fiber, a segmental constitutive model for predicting the stress–strain relationship of the BFRC was developed. In addition, the analysis of the transverse strain cloud diagrams collected by DIC revealed the local strain concentration phenomena during compressive damage to BFRC. The damage constitutive model considering the factors of strength grade and fiber was established, which can predict the compressive damage process of the BFRC specimens.

Mechanical and permeability properties of basalt fibre Reinforced concrete

Concrete, the most consumed construction material, is capable to resist under compressive force but not in tension. To improve this inherent defect in concrete, several methods have been adopted. One of these methods is the addition of fibres in concrete. The addition of Basalt Fibres (BF) improves the tensile strength of concrete and considerably reduces the development and propagation of cracks. By hindering the propagation of cracks, the permeability of the concrete is also reduced considerably. BF, a fibre produced from naturally occurring basalt rock, has improved chemical and thermal stability and higher elastic modulus, with improved compressive, tensile and flexural strength. This study primarily emphases on the effect of the addition of BF in concrete. First, the optimum dosage of BF is found through multiple strength test on hardened concrete. From the BF dosages of 0.2%, 0.3%, 0.4%, 0.5% and 0.6% of volume of concrete, 0.3% is obtained as optimum. The permeability properties, water and chloride ion penetrability of Basalt Fibre Reinforced Concrete (BFRC) are also tested and concluded that optimum addition reduces the permeability. The behaviour of BFRC beams on the flexural loading is studied experimentally and determined that BFRC has significant increase in the cracking load, ultimate load carrying capacity and reduced propagation of cracks.

Influence of basalt fiber on the behavior of beam - column joint under cyclic loading

Beam-column joints are immensely complicated areas of reinforced concrete constructions. The strengthening of such components can have a significant impact on the earthquake resistant constructions because the rapid collapse of a building could occur if these beam-column joints fail. Recently, designing of reinforced concrete beam-column joints to resist earthquake load becomes more important using ductile design and high strength material. The fibers addition in a concrete directs to an improvement in cracking resistant, ductility, deformation and energy absorption capacity. However, there are currently many distinct types of fibres with various materials and geometric features are used in fiber reinforced concrete to improve the above said properties. The use of basalt fibre, an alternative material made from natural sources that comes from volcanic rock, is the main topic of this essay. The beam-column junction was used to assess the structural behaviour parameters for basalt fibre reinforced concrete, including load–deflection behaviour, ductility, stiffness value, energy absorption capacity, and energy index. From this work, it shows that the natural based basalt fiber shows excellent structural behavior when compared to control concrete. Basalt Fiber Reinforced Concrete (BFRC) has the potential for widespread application in the construction of concrete structures as well as in earthquake-prone regions.

Dynamic Mechanical Strength Prediction of BFRC Based on Stacking Ensemble Learning and Genetic Algorithm Optimization

Split Hopkinson pressure bar (SHPB) tests are usually used to determine the dynamic mechanical strength of basalt-fiber-reinforced concrete (BFRC), but this test method is time-consuming and expensive. This paper makes predictions about the dynamic mechanical strength of BFRC by employing machine learning (ML) algorithms and feature sets drawn from experimental data from prior works. However, there is still the problem of improving the accuracy of the dynamic mechanical strength prediction by the BFRC, which remains a challenge. Using stacking ensemble learning and genetic algorithms (GA) to optimize parameters, this study proposes a prediction method that combines these two techniques for obtaining accurate predictions. This method is composed of three parts: (1) the training uses multiple base learners, and the algorithms employed by the learners include extreme gradient boosting (XGBoost), gradient boosting (GB), random forest (RF), and support vector regression (SVR); (2) multi-base learners are combined using a stacking strategy to obtain the final prediction; and (3) using GA, the parameters are optimized in the prediction model. An experiment was conducted to compare the proposed approach with popular techniques for machine learning. In the study, the stacking ensemble algorithm integrated the base learner prediction results to improve the model’s performance and the GA further improved prediction accuracy. As a result of the application of the method, the dynamic mechanical strength of BFRC can be predicted with high accuracy. A SHAP analysis was also conducted using the stacking model to determine how important the contributing properties are and the sensitivity of the stacking model. Based on the results of this study, it was found that in the SHPB test, the strain rate had the most significant influence on the DIF, followed by the specimen diameter and the compressive strength.

Fresh, mechanical, and durability properties of basalt fiber-reinforced concrete (BFRC): A review

Basalt fiber-reinforced concrete (BFRC) is relatively a new type of fiber-reinforced concrete, which has demonstrated good mechanical performance. Several types of fibers such as steel, glass, and carbon fibers, are used to improve the performance of plain concrete. However, basalt fibers (BF) are being considered superior to these because of their comparable mechanical strength, higher durability than glass fibers, lesser cost than carbon fibers, sustainability due to abundant raw material, and environment-friendly production process. Hence, the number of studies on BFRC are increasing over the years. This review paper covers the properties of BF and BFRC. The effects of BF length and dosage are discussed in detail in term of fresh, hardened, and durability properties of BFRC, followed by highlighting some areas for future research. It is concluded that BF can potentially replace the other conventional fibers which are being used in the industry.

Using Random Forest and Random Tree model to Predict the splitting tensile strength for the concrete with basalt fiber reinforced concrete

The best model for predicting concrete splitting tensile strength using Basalt Fiber Reinforced Concrete (BFRC) was found utilising Random Forest (RF) and Random Tree (RT) implemented in this study. A total of 74 datasets were collected for this investigation from various academic papers. The entire data set is split into 51 training data sets and 23 testing data sets. The software which used for analysis in WEKA software. Cement, fine aggregate/crushed sand, coarse aggregate, water, superplasticizer, fly ash, Basalt Fiber Reinforced Concrete BFRC, diameter, length, and curing time are the input factors, while the compressive strength of the concrete containing BFRC is the output variable. Three performance assessment indices are used to assess the performance of the created models: Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Correlation Coefficient (CC). Containing CC (0.9889, 0.9579) and lower MAE (0.0886, 0.1842), RMSE (0.1430, 0.2406) for the training and testing data sets, the Random Forest was shown to be the best model for predicting the splitting tensile strength of concrete with BFRC. And by analysing the sensitivity it shows that the curing time is the most sensitive input among all the inputs.