Fracture Toughness Of Concrete Research Articles

Influence of Specimen Width on Crack Propagation Process in Lightly Reinforced Concrete Beams

Models used to study the fracture process of concrete are often considered 2D, ignoring the influence of specimen width. However, during the fracture process in pre-cracked concrete beams, the crack length varies along the thickness direction, especially in reinforced concrete. To study the influence of specimen width on reinforced concrete fracture behavior, a 3D numerical method was used to simulate the crack propagation processes of lightly reinforced concrete beams based on Fracture Mechanics. Nonlinear spring elements with different stress-displacement constitutive laws were employed to characterize the softening behavior of concrete and the bond-slip behavior between the steel bars and concrete, respectively. It is assumed that the crack begins to propagate when the maximum stress intensity factor at the crack tip along the beam width reaches the initial fracture toughness of concrete. To verify the validity of the proposed method, the completed crack propagation processes of lightly reinforced concrete three-point bending notched beams were simulated, and the calculated load-crack mouth opening displacement curves showed a reasonable agreement with the experimental data. Moreover, the impact of the 2D reinforced concrete beam model on the crack propagation process was analyzed. The results indicate that at the initial loading stage, the external load P obtained from the 2D model is significantly larger than the result from the presented 3D model.

Fracture Toughness of Ordinary Plain Concrete Under Three-Point Bending Based on Double-K and Boundary Effect Fracture Models.

Fracture tests are a necessary means to obtain the fracture properties of concrete, which are crucial material parameters for the fracture analysis of concrete structures. This study aims to fill the gap of insufficient test results on the fracture toughness of widely used ordinary C40~C60 concrete. A three-point bending fracture test was conducted on 28 plain concrete and 6 reinforced concrete single-edge notched beam specimens with various depths of prefabricated notches. The results are reported, including the failure pattern, crack initiation load, peak load, and complete load versus crack mouth opening displacement curves. The cracking load showed significant variation due to differences in notch prefabrication and aggregate distribution, while the peak load decreased nonlinearly with an increase in the notch-to-height ratio. The reinforced concrete beams showed a significantly higher peak load than the plain concrete beams, attributed to the restraint of steel reinforcement, but the measured cracking load was comparable. A compliance versus notch-to-height ratio curve was derived for future applications, such as estimating crack length in crack growth rate tests. Finally, fracture toughness was determined based on the double-K fracture model and the boundary effect model. The average fracture toughness value for C50 concrete from this study was 2.0 MPa·m, slightly smaller than that of lower-strength concrete, indicating the strength and ductility dependency of concrete fracture toughness. The fracture toughness calculated from the two models is consistent, and both methods employ a closed-form solution and are practical to use. The derived fracture toughness was insensitive to the discrete parameters in the boundary effect model. The insights gained from this study significantly contribute to our understanding of the fracture toughness properties of ordinary structural concrete, highlighting its potential to shape future studies and applications in the field.

Prediction of fracture toughness of concrete using the machine learning approach

In the process of structural design, it is useful to estimate the fracture toughness of concrete samples. This research showcases the effectiveness of utilizing machine learning methods to determine the fracture toughness of concrete. Taking into account variables such as mix design, machine learning techniques can accurately predict the mode I fracture toughness of concrete. Dimensionless stress intensity factor of concrete prediction using twelve different machine learning techniques namely, Linear regression (LR), Extreme Gradient-Boosting (XGboost), K-Nearest Neighbors (KNN), Random Forest (RF), Category Boosting (CB), Decision Tree (DT), Extra Trees (ET), Light Gradient-Boosting (LightGB), Adaptive boosting (AdaBoost), Bagging (BA), Gaussian Process (GP), Artificial Neural Network (ANN) and Support Vector Machine (SVM). The result of utilizing the training adaptive moment estimation algorithm has been developed to create an outstanding machine learning-based system. After carefully analyzing comparisons between the predictions produced by different models and experimental findings, it has been discovered that the models demonstrate an impressive accuracy rate of about 90 percent when it comes to forecasting concrete fracture toughness. The research findings emphasize that the ANN model exhibited superior accuracy in its predictions (R2 value of 0.90, RMSE of 0.1517, and MAE of 0.1238). Upon conducting a thorough examination of the ANN method’s sensitivity, the cement parameter holds utmost significance in accurately estimating concrete’s fracture toughness using the available dataset. So, the ANN model can be used as a valuable method to provide practical assistance in predicting the fracture toughness of concrete. When evaluating the effective parameters, the cement and metakaolin dosage and the notch height to specimen height ratio have the greatest effect on the fracture resistance, while the coarse aggregate content is minimal. This result is consistent with the experimental data.

Cause, Stability Analysis, and Monitoring of Cracks in the Gate Storehouse of a Flood Diversion Sluice

The cracks in a gate storehouse for a flood-diversion sluice of the Wangfuzhou Water Conservancy Project were studied to diagnose the structural safety. The study was based on an integrated method that involved the analysis of the cause of cracks, an assessment of the crack stability, online safety monitoring and diagnosis, and real-time monitoring and control. The results demonstrated that two dominant factors leading to cracks were the non-uniform settlement of the foundation of this gate storehouse structure combined with temperature drops in winter. By comparing crack-tip stress intensity factors at different cracking depths with concrete fracture toughness, the results showed that cracks at the gate storehouse would not continue to propagate, although some time-dependent components separated from the measuring point did not converge but tended to be closed. Therefore, the diagnosis suggests that the cracks at the gate storehouse are currently in a stable state. Additionally, the crack opening index estimated using the small probability method can be used for future real-time monitoring of crack behavior.

Prediction model and measurement of fracture parameters in eco-friendly coarse copper slag-SFRSCC based on semi-circular bending test

This research has used 16 concrete mix designs containing 0.1, 0.3, and 0.5% steel fiber (SF), and 20, 30, 40, 50, and 60% copper slag (CS) to examine their fresh and hardened characteristics, and study their microstructural features with the help of scanning electron microscope (SEM) images. In addition, it has tried to evaluate the fracture characteristics of semi-circular bending (SCB) samples under loading modes I, I/II, II/I, and II. According to the results, increasing CS will improve the fresh concrete properties and reduce the negative SF effects on its performance. At 60% (fixed) CS, using 0.1% SF reduces the compressive strength by 10.08%, and applying 0.5% SF increases it by 17.24%, compared to the control sample. Increasing SF and CS improves the tensile strength of all concretes in the 14.02–86.02% range, compared to the control design. SEM images show that up to 30% replacement, the WCS-steel fiber reinforced self-compacting concrete (SFRSCC) microstructure is homogeneous, integrated and dense, and the fracture toughness and energy are higher under, respectively, pure loading modes II and I than other modes. Fracture toughness of concretes with the highest SF and CS volumes, compared to plain concrete, has increased 1.45, 1.61, 1.67, and 1.36 times under loading modes I, I/II, II/I, and II, respectively. Compared to ANN, using ALK to estimate the fracture features reduces the need for training data by 36.53%, and R2 (correlation coefficient) reduces by 0.91 and 1.52% for estimating the fracture energy and fracture toughness, respectively. Using ANN and ALK can provide a robust prediction model to estimate the fracture energy parameters of the CS-FRSCCs (R2 ≥ 0.970).

Effect of Coarse Aggregate Grading on Mechanical Parameters and Fracture Toughness of Limestone Concrete

This work presents a discussion of the basic properties of broken mineral limestone aggregates with the specification of the properties affecting the fracture toughness of concretes made with these aggregates. To determine the influence of the grain-size distribution of coarse aggregates for each concrete series, two types of aggregate grain were used, with maximum grain sizes of 8 mm (series of concrete L1) and 16 mm (series of concrete L2). Fracture-toughness tests were carried out using mode I fractures in accordance with the RILEM Draft recommendations, TC-89 FMT. During the experiments the critical stress-intensity factor (KIcS) and crack-tip-opening displacements (CTODc) were determined. The main mechanical parameters, i.e., the compressive strength (fcm) and splitting tensile strength (fctm), were also assessed. Based on the obtained results, it was found that the grain-size distribution of the limestone aggregate influenced the concrete’s mechanical and fracture-mechanics parameters. The obtained results showed that the series-L2 concrete had higher strength and fracture-mechanics parameters, i.e.,: fcm—45.06 MPa, fctm—3.03 MPa, KIcS—1.22 MN/m3/2, and CTODc —12.87 m10−6. However, the concrete with a maximum grain size of 8 mm (series of concrete L1) presented lower values for all the analyzed parameters, i.e.,: fcm—39.17 MPa, fctm—2.57 MPa, KIcS—0.99 MN/m3/2, and CTODc —10.02 m10−6. The main reason for the lower fracture toughness of the concretes with smaller grain sizes was the weakness of the ITZ in this composite compared to the ITZ in the concrete with a maximum grain size of 16 mm. The obtained test results can help designers, concrete producers, and contractors working with concrete structures to ensure the more conscious composition of concrete mixes with limestone aggregates, as well as to produce precise forecasts for the operational properties of concrete composites containing fillers obtained from carbonate rocks.

Several machine learning models to estimate the effect of an acid environment on the effective fracture toughness of normal and reinforced concrete

Crack extension and subsequent concrete fracture are regulated by the concrete's fracture toughness, making it an essential feature. Concrete, made from the most common and inexpensive building components, is the material of choice in civil engineering. Therefore, fractures and cracks may cause significant damage that may be impossible to repair. Furthermore, concrete constructions lose mechanical strength when encountering an acidic environment. This has led to the development of fiber-reinforced concrete, which addresses the issues. Therefore, studying the mechanical properties of concrete under different environmental conditions is of particular importance and should be considered in designs. For this purpose, in this study, the effect of an acid environment (PH = 5) on the effective fracture toughness (Keff) of three types of concrete, including conventional concrete (CC), glass fiber-reinforced concrete (GFC), and glass fiber/microsilica-reinforced concrete (GFMSC), was investigated using the central straight notched Brazilian disc (CSNBD) test. Also, since conducting laboratory tests to obtain the Keff of concrete samples is time-consuming and costly, it is necessary to provide tools to estimate this concrete property with high accuracy in a short period and without the need for such a high cost. Using machine learning (ML)-based models was a suitable option to address such problems. For this purpose, twelve ML-based models were presented using 420 datasets generated from the CSNBD test to estimate the Keff of different concrete samples. The behavior of the ML models compared to the CSNBD test was investigated, and the correct and acceptable performance of each of them in estimating the Keff of concrete was confirmed. The CSNBD and ML results showed that an acid environment (PH = 5) has a more destructive effect on the concrete’s Keff than a neutral environment (PH = 7). Also, reinforced concrete (GFC and GFMSC) is always more resistant to acid environments than normal concrete (CC). To further aid in the estimation of the concrete's Keff for engineering challenges, a graphical user interface (GUI) for the ML-based models was developed.

Experimental Study on the Influence of Humidity on Double-K Fracture Toughness and Fracture Energy of Concrete under Water Environment

Saturated concrete is significantly different from dry concrete in fracture mechanical properties. Using the wedge-splitting tensile method to research the rule of change in moisture content, double-K fracture toughness and fracture energy of three strength grades (C20, C30, and C40) of concrete immersed in a free water environment for 0 h, 2 h, 5 h, 24 h, and 120 h were studied in order to provide support for the safety evaluation of concrete structures in a water environment. The initial cracking fracture toughness of C20, C30, and C40 concrete in saturated state were, respectively, 29.6%, 23.2%, and 33.4% lower than that in dry state. The unstable fracture toughness of C20, C30, and C40 concrete in saturated state were, respectively, 22.7%, 23.9% and 33.8% lower than that in dry state. The fracture energy of C20, C30, and C40 concrete in saturated state are only 71.99%, 70.29%, and 66.11% of that in dry state, respectively. The initial cracking fracture toughness and unstable fracture toughness of concrete all show a linear, decreasing trend with an increase in moisture content. Before the crack initiation, the measured P–CMOD curve had an obvious linear elastic stage, stable expansion stage, and unstable expansion stage. The critical crack opening displacement gradually decreases with an increase in moisture content; the deformation capacity and toughness of concrete are shown to decrease. The humidity state should be fully considered when evaluating the fracture mechanical properties of concrete.

Fracture characteristics of various concrete composites containing polypropylene fibers through five fracture mechanics methods

Abstract This paper investigates and compares the experimental results of fracture characteristics in various polypropylene fiber-reinforced concretes (high strength concrete, lightweight concrete, and engineered cementitious composite) on 90 three-point bend (notched and un-notched) beams. Five widely used fracture mechanics testing methods, such as work of fracture method, stress-displacement curve method, size effect method, J integral method, and ASTM E399, were used to investigate the fracture behavior. Results have demonstrated that fracture energy and fracture toughness improved as the dosage of polypropylene fibers increased in concretes. However, this improvement was different in concretes owing to various results of fracture mechanics testing methods and different properties of each concrete. Aggregates played significant role in the performance of polypropylene fibers on the fracture behavior of concretes. Among testing methods, the ASTM E399 showed the lowest values for the fracture toughness of concretes. Both work of fracture and stress-displacement curve methods exhibited appropriate results for the fracture energy of polypropylene fiber-reinforced concrete composites. The accuracy of size effect method was acceptable for determining size-independent fracture parameters of plain high strength and lightweight concretes. Furthermore, the J integral method showed more relevant results for the fracture toughness of polypropylene fiber-reinforced engineered cementitious composite.

Method for Determining the Fracture Parameters of Fully Graded Dam Concrete

This paper describes a method for determining the initiation and unstable toughness of fully graded concrete of arbitrary specimen size. The method first predicts the initiation and peak loads of concrete specimens of any size, as well as crack length-to-height ratios based on the fracture test results of concrete specimens with limited sizes or crack length-to-height ratios. Then, combined with the fracture extreme theory, the fracture toughness of concrete with varying size or crack length-to-height ratios is determined. Finally, in order to verify the applicability of the method, it is used to calculate the fracture toughness of small aggregate concrete and fully graded concrete with different sizes or crack length-to-height ratios, and its prediction accuracy is evaluated through indices such as mean absolute percentage error, root mean square error and reliability index a15. The results show that the proposed method can meet the needs of practical engineering applications and can provide theoretical basis for the optimization of the fracture test method of fully graded concrete and the determination of fracture parameters in crack stability or propagation analysis.

Optimization of Composition of Nanofiber Concrete in Terms of Fracture Toughness by Matrix Modifiсation

Concrete is a quasi-brittle building material that has low tensile strength. The process of its destruction under loading is inhomogeneous, due to the nature of the concrete structure mass, consisting of components with different physical and mechanical properties. Gradual deformation and destruction can be characterized as a process of formation and development of microcracks. The presence of different-sized components in concrete makes it possible to consider its structure as a multi-level system. In this system, each level is a matrix with its own structural inclusions, which play both a structure-forming role and the role of stress concentrators under the action of mechanical loads. The critical stress intensity factor is a good indicator of the crack resistance (fracture toughness) of a material. Nanoconcrete, from the point of view of a multilevel system, is a concrete composite with crack propagation inhibitors at the level of the cementing substance (carbon nanotubes are consi-dered as inhibitors). The presence of fiber fibers at subsequent scale levels allows us to consider concrete as a composite with multi-level dispersed reinforcement (nanofiber concrete). The paper discusses the change of concrete fracture toughness indicator (crack resistance) with dispersed reinforcement of the matrix at different structural levels. The presented for normal separation of notched cubes under eccentric compression with the determination of the stress intensity factor for concrete modified with carbon nanotubes acting as crack propagation inhibitors at the level of cementing substance (nanoconcrete), as well as for nanofiber concrete with dispersed reinforcement at the level of fine-grained concrete. Based on experimental studies by non-equilibrium methods of fracture mechanics, compositions of nanofiber-reinforced concrete of maximum crack resistance (fracture toughness) with different fiber concentrations and several types of matrices modified with nanocarbon additives are proposed in the paper.

Prediction of Mixed-mode I and II effective fracture toughness of several types of concrete using the extreme gradient boosting method and metaheuristic optimization algorithms

Complex sample preparation procedures, the necessity for highly accurate and sensitive instruments, early sample failure, and brittle samples all contribute to the difficulty of measurement of concrete fracture toughness (CFT) in the laboratory. With such limitations on the measuring CFT, it is necessary to develop new and more effective tools. Machine learning (ML) methods are promising tools for non-linear time series prediction. In this study, six extreme gradient boosting (XGBoost)-based meta-heuristic algorithms, including standard XGBoost, XGBoost-particle swarm optimization (PSO), XGBoost-imperialist competitive algorithm (ICA), XGBoost-grey wolf optimization (GWO), XGBoost-shuffled frog leaping algorithm (SFLA), and XGBoost-genetic algorithm (GA) were developed to predict the effective fracture toughness (K_eff) of concrete, utilizing 560 datasets obtained from the central straight notched Brazilian disc (CSNBD) test. Additives of micro silica and powdered stone, which are the most widely used building materials were used in the concrete samples to investigate their effect on the physical and mechanical properties. Therefore, 10 different materials made from a combination of concrete and different percentages of additives, were used in the experiment. The datasets included six input parameters effective on the K_eff, including concrete type (ST), diameter (D), thickness (t), length (L), force (F), and crack angle (α). The XGBoost-based models' performances were compared with those of each other and with four other ML methods of Gaussian process regression (GPR), decision trees (DT), support vector regression (SVR), and K-nearest neighbors (KNN). The ML models’ performance in the prediction of K_eff for both holdout and 5-fold methods from high to low is XGBoost-PSO, XGBoost-ICA, XGBoost-GWO, XGBoost-SFLA, XGBoost-GA, XGBoost, GPR, SVR, DT, and KNN. Considering the datasets utilized in this research, the feature selection method's sensitivity analysis revealed that, except for the parameter D, all other parameters considered in this study, significantly affect the K_eff. By developing the meta-heuristic methods, the ability of the XGBoost-based methods was significantly improved. Finally, this article recommends using the XGBoost-PSO hybrid model to predict the K_eff. This work’s significance is that it allows geotechnical engineers to accurately estimate the K_eff of different types of concrete. In this way, the high time and cost required for the CSNBD test can be eliminated.

Nanofiber Concrete: Multi-Level Reinforcement

Concrete is the most commonly used building material worldwide. One of its main disadvantages is the fragility of fracture and low crack resistance. The use of dispersed reinforcement of concrete composites is a promising direction in solving this type of problem. Dispersed fibers, evenly distributed over the entire volume of the material, create a spatial frame and contribute to the inhibition of developing cracks under the action of destructive forces. In order to increase the fracture toughness of concrete, dispersed fiber reinforcement is increasingly used in practice. The beginning of crack nucleation occurs at the nanoscale in the cement matrix. Thus, the use of nano-reinforcement with dispersed nanofibers can have a positive effect on the crack resistance of the cement composite. It is proposed to consider carbon nanotubes as such nanofibers. The presence of carbon nanofibers changes the microstructure and nanostructure of cement modified with carbon nanotubes. The result of the processes occurring in capillaries and cracks are deformations in the intergranular matrix, the free flow of which is prevented by rigid clinker grains and nanocarbon tubes, which creates a certain stress intensity at the tips of the separation cracks. The working hypothesis is confirmed that the required fracture toughness of structural concrete is provided by multi-level reinforcement: at the level of the crystalline aggregate of cement stone – carbon nanotubes, and at the level of fine-grained concrete – various macro-sized fibers (steel, polymer). Reinforcement of a crystalline joint with carbon nanotubes leads to an increase in the fracture toughness of the matrix (cement stone) by 20 %, compressive strength by 12 %, and tensile strength in bending by 20 %. When reinforcing at the level of fine-grained concrete, we obtain a composite – nanofibre-reinforced concrete with fracture toughness.

Experimental investigation and modified calculation model of critical crack propagation length of concrete

The critical crack propagation length is essential to calculate the fracture toughness of concrete and the further safety evaluation of the cracked concrete structures. In this study, the critical crack propagation lengths of the notched three-point bending (TPB) beams with various geometric dimensions and concrete strength grades are measured with two experimental methods. One way is to paste strain gauges on the sides of the crack propagation path, and another way is to arrange clip gauges along the depth direction. The results indicate that the effective crack propagation lengths derived based on the existing fracture model are smaller than the experimentally measured critical crack propagation lengths with the maximum relative error of 45%. To obtain the critical crack propagation length with the simple theoretical model accurately, a modified analytical method is proposed, where the elastic equivalent crack propagation length corresponding to 95% of the peak load in the post-peak section is treated as a good approximation of the critical crack propagation length. With the modified method for determining the critical crack propagation length, the fracture toughness of concrete can be derived reasonably. It is expected that the modified method would provide a valuable reference for determining the fracture property of concrete using the small size TPB beams in practical engineering.

Size-effect independence of hybrid fiber-reinforced roller-compacted concrete fracture toughness

The present paper aims to prove the size-effect independence of Hybrid Fiber-Reinforced RCC (HyFR-RCC) fracture toughness determined through the Modified Two-Parameter Model (MTPM). A micromechanical numerical model is applied to simulate the fracture behavior of seven series of single edge-notched specimens, made of both plain-RCCs and FR-RCCs (single and hybrid reinforcements), subjected to three-point bending. The MTPM is applied to the numerical load vs CMOD curves to compute the fracture toughness. A comparison with experimental values, available in the literature, is performed. Therefore, RCC specimens with different sizes are numerically simulated and the fracture toughness is analytically determined through the MTPM, proving the size-effect independence.

Post-cracking regimes in the flexural behaviour of fibre-reinforced concrete beams

The flexural behaviour of steel fibre-reinforced concrete beams is discussed in the framework of Fracture Mechanics. The Bridged Crack Model is updated by means of a cohesive softening constitutive law of the reinforcement layers, taking into account the fibre slippage within the cementitious matrix. In this way, the model is able to describe the global response of the composite, including the local instability phenomena characterizing the different post-cracking regimes. The structural response is found to be governed by two dimensionless numbers: the reinforcement brittleness number, NP, which defines the minimum reinforcement condition of the composite beam, and the pull-out brittleness number, Nw, which describes its plastic rotation capacity. The former, NP = (Vfσ¯sh1/2)/KIC, depends on the fibre volume fraction, Vf, on the fibre slippage strength, σ¯s, on the concrete fracture toughness, KIC, and on the beam depth, h. The latter, Nw = (wcE)/(KICh1/2), depends on the fibre embedment length, wc, on the concrete Young’s Modulus, E, on the concrete fracture toughness, KIC, and on the beam depth, h. These two parameters make it possible to identify a softening post-cracking response of the fibre-reinforced concrete element that is scale-dependent. Finally, the numerical analyses are compared to several experimental results reported in the scientific literature, proving the effectiveness of the described model.

Study on flexural properties of 3D printed lattice-reinforced concrete structures using acoustic emission and digital image correlation

Lattice-reinforced concrete is considered to be a new method to improve the quasi-brittleness, ductility and fracture toughness of concrete. 3D printing technology provides the possibility for lattice molding with complex structures. Therefore, 3D printed lattice-reinforced concrete structures have aroused great interest. However, there are relatively few studies on the mechanical properties of 3D printed lattice-reinforced concrete, and the effects of lattices with different structures are not considered. In this paper, the three-point bending properties of 3D printed lattice-reinforced concrete with different reinforced structures are tested. Five different structures of lattices with identical volume reinforced ratio are designed and printed by selective laser sintering (SLS). The 3D printed lattice-reinforced concrete structures are prepared, and the plain concrete without lattice is set as the control groups. Acoustic emission (AE) and digital image correlation (DIC) technologies are combined to monitor the specimens from the surface to inside, and the differences in mechanical properties between the control specimen and lattice reinforcement specimens with different structures were compared. The test results show that the lattice can significantly improve the mechanical properties of concrete, and the rhombicuboctahedron (RO) lattice can significantly improve the maximal bearing capacity of concrete specimens under three-point bending. This test further demonstrates the feasibility of 3D printed lattice-reinforced concrete structures, provides a new method to improve the quasi-brittleness and ductility of concrete.

Effects of dolomite powder on the properties of C30 and C50 concretes

This study focused on the effects of dolomite powder on the properties of C30 and C50 concretes. The microstructure, splitting tensile strength, compressive strength and fracture toughness property of concretes incorporating dolomite powder were measured by mercury intrusion porosimetry (MIP), pressure testing machine and universal testing machine. Higher splitting tensile strength, compressive strength and fracture toughness of concretes could be seen with the increase of dolomite powder dosage within 90 days. After 1 day of curing, splitting tensile strength, compressive strength and fracture toughness of C30 and C50 concretes could be improved considerably. The positive effects of dolomite powder on the splitting tensile strength, compressive strength and fracture toughness decreased with the increase of curing age. Because the nucleation effect, micro-filler effect and mix proportions design of dolomite powder were beneficial to the refinement of pore structure of concretes, and dolomite powder had less influence on the later stage of cement hydration. The splitting tensile strength equations expressed in terms of the compressive strength was proposed. The analysis of regression equation proved that the equation of relationship between compressive strength and splitting tensile strength of concretes containing dolomite powder in this study had high prediction accuracy.

Brittleness of Concrete under Different Curing Conditions.

In order to shorten construction periods, concrete is often cured using steam and is loaded at an early age. This changes the performance and even the durability of the concrete compared to concrete that has been cured under normal conditions. Thus, the pattern and the mechanism of concrete performance change under different curing conditions, and loading ages are of great significance. The development of brittleness under different curing conditions and loading ages was studied. The evaluation methods that were used to determine concrete brittleness were expounded. Steam, standard, and natural curing conditions were carried out on single-side notched concrete beams as well as on a concrete prism and cubic blocks. The compressive strength and splitting tensile strength of the concrete blocks along with the fracture performance of the concrete beams were tested after 3, 7, 28, and 90 days. The steam curing condition significantly improved the strength of concrete before 28 days had passed, and the standard curing condition improved the strength of concrete after 28 days. Based on the experimental fracture parameters, a two-parameter fracture model was applied to study the development of fracture toughness , critical crack tip opening displacement , and critical strain energy release rate with hydration age under different curing conditions. With respect to long-term performance, the standard curing condition was better at resisting concrete crack propagations than the steam curing condition was. The characteristic length and the material length under the three curing conditions and the long-term development of brittleness in the concrete indicated that steam curing increased the concrete brittleness. Considering the effects of the curing condition and the loading age, a time-dependent concrete fracture toughness model was established, and the predicted value of the model was verified against the measured value. The results indicated that the model was able to accurately predict the fracture toughness with an error rate of less than 16%.

The Effect of Loading Rate on Fracture Toughness of Concrete using Type I Fracture Toughness Test Flattened Brazilian Disc (FBD) Mode

Mining activities in open pit and underground mines will always be associated with rock breaking or stripping activities (both mechanical and blasting), so that this can affect the structure and strength of rocks. The strength of the rock is strongly influenced by the presence of initial cracks (pre-existing cracks) and rock anisotropy conditions associated with discontinuous plane conditions. Fracture mechanics is a science that illustrates how a fracture can occur and propagate during applied stress on material. The main parameter in fracture mechanics is called fracture toughness which shows the resistance of the material to propagate the crack. There are several mode in determining type I fracture toughness, one of which is type I fracture toughness Flattened Brazilian Disc (FBD) mode. Type I fracture toughness test is carried out using a compression machine in a laboratory and is conducted on concrete samples consisting of 3 (three) various samples, with a ratio of cement and sand composition of 1:1, 1:2, and 2:1. This test also uses different loading rate values, namely 2.50 mm/min, 2.70 mm/min, and 2.83 mm/min. The results of the type I fracture toughness value from each loading rate will be compared to determine the effect of the loading rate on the value of type I fracture toughness. The obtained fracture toughness value is also related to the physical and mechanical properties of the samples. Based on the results of tests, it can be seen that the loading rate affects the value of fracture toughness, the increase in fracture toughness value is followed by the higher loading rate. In addition, it can be seen that the fracture toughness value is directly proportional to the uniaxial compressive strength value and the indirect tensile strength value. The average correlation value obtained is R2 = 0.9884 (indicating a strong relationship).