Featured Application: This work can be utilized to predict the flexural strength and the compressive strength of ultra-high performance concrete (UHPC), determine the volume fraction of steel fibers in ultra-high performance steel fiber reinforced concrete (UHPFRC), and optimize the UHPFRC mixtures.Abstract: Steel fibers enhance the flexural strength, the compressive strength and the ductility of untra-high performance concrete, predicting the flexural strength and the compressive strength of ultra-high performance steel fiber reinforced concrete (UHPFRC) accurately has significant influence on controlling steel fiber volume fraction and optimizing UHPFRC mix proportion. In this study, to evaluate the effects of steel fibers on the mechanical properties of UHPFRC, two artificial neural networks were developed in order to predict the flexural strength and the compressive strength of UHPFRC, respectively. 102 test data sets and 162 test data sets from literature were trained and tested to establish the flexural strength model and the compressive strength model, respectively. In these two models, the influential parameters, including the water to binder ratio, the diameter, the length, the aspect ratio, and the volume fraction of steel fibers, as well as the compressive strength and the flexural strength of concrete without fibers were investigated as the inputs, while the compressive strength and the flexural strength of UHPFRC were the outputs. The results show that the artificial neural network models predicted the compressive strength and flexural strength of UHPFRC accurately. Then, by comparing with existing analytical models, it was determined that the proposed models had high applicability and reliability with respect to predicting the compressive strength and the flexural strength of UHPFRC.the strength and the ductility of UHPFRC [3]. Unfortunately, too many steel fibers lead to fibers inter-wrap and interlock with each other, affecting the workability of UHPFRC, to reduce the strength of UHPFRC [4]. Furthermore, steel fibers are expensive and numerous steel fibers added to the UHPFRC cost too much. Thus, predicting the compressive strength and the flexural strength of UHPFRC accurately can optimize mix proportion, control the volume fraction of steel fibers, and decrease the costs of UHPFRC. However, evaluating the flexural strength and the compressive strength of the UHPFRC is a huge challenge due to the complex composite behavior caused by the properties steel fibers (diameter (D), length (L), aspect ratio (AR), and volume fraction (VF)) and concrete matrix (water to binder ratio (W/B) and concrete strength without fibers).Nowadays, the contribution of cement-based materials to sustainability is a topic of study [5-8] and the performance of several additions in cement-based materials, such as silica fume, fly ash, the water to cement ratio, and so on, has been analyzed, which could be also suitable for being used in high performance concrete. This fact also makes it necessary to consider their influence...
The objective of this study was to examine the shrinkage and creep of reactive power concrete (RPC) with different steel fibre contents (0%, 1% and 2% by volume). A total of 37 RPC specimens were prepared and tested for compression strength, elastic modulus, shrinkage, and creep. In addition, different axial stress ratios (0.2, 0.3 and 0.4) were used in the creep tests. Furthermore, the accuracy of the ACI 209-82 model, CEB-FIP 90 model, B3 model, and GL 2000 model for predicting the shrinkage and creep of RPC was evaluated and new numerical shrinkage and creep models were developed. The experimental results revealed that the compressive strength and elastic modulus increase with increasing steel fibre content. The shrinkage and creep decreased with increasing addition of steel fibre from 0% to 2%. A good linear relationship was found between the axial stress ratios and creep strain. All four existing models were unable to accurately predict the shrinkage and creep of RPC. A good agreement between the experimental results and proposed shrinkage and creep numerical models was observed. Therefore, it is suggested that the proposed shrinkage and creep models can be used to calculate the shrinkage and creep of RPC.
The compositions and curing regimes have significant effects on the compressive strength and the fluidity of ultra-high performance concrete (UHPC). Fifty-eight mixtures were examined to determine the effects of key factors on the fluidity and the compressive strength of UHPC. These parameters include water-binder ratio, cement strength, steel fiber content, fly ash content, nanoparticles content, silica fume grade, and curing regimes. The fluidity of UHPC was in the ranges 122-237 mm, while the 28d compressive strength on 70.7 mm cube specimens of UHPC were in the ranges 77-211 MPa. The results showed that fly ash and nanoparticles had significant effects on the fluidity and slight effects on the compressive strength; silica fume grade had slight effects on both the compressive strength and the fluidity; the water to binder ratio, curing regimes, and steel fiber had noticeable effects on the compressive strength. Based on results, the influence coefficients of the investigated key parameters were obtained by regression analysis. Furthermore, the prediction models of the fluidity and the compressive strength of UHPC were proposed by combining the influence coefficients of the investigated key parameters. Therefore, the prediction models can be utilized to optimize the proportions of UHPC mixtures within the ranges of the investigated parameters. K E Y W O R D Scompressive strength, fluidity, key parameters, prediction model, ultra-high performance concrete
This paper tested the behaviour of 32 high-strength concrete columns confined by high-strength spirals under concentric compression. The test parameters included unconfined concrete compressive strength, spiral yield strength, volumetric ratio, and spiral spacing. The results showed that bulging and shear sliding were the two characteristic types of failure patterns of the thirty-two confined columns, depending on spiral spacing and concrete strength. Moreover, the spiral in most specimens did not yield at the confined concrete compressive strength. An analytical confinement model for high-strength concrete columns confined by high-strength spirals was proposed. In this proposed model, the calculated value of the spiral stress at the confined concrete compressive strength was used to calculate the feature points of the stressstrain curve. The proposed model showed good correlations with available experimental results of 64 columns.
In concrete structures design, the compressive strength of circular concrete columns confined by spiral stirrups is an important mechanical property in evaluating the performance of concrete structures. However, evaluating the compressive strength of confined concrete columns is rich in challenge due to the complex mechanics between the concrete and the transverse reinforcements. The objective of this paper is to establish an artificial neural network (ANN) model to evaluate the compressive strength of concrete columns confined by transverse reinforcements. The model proposed in this study is suitable for both normal-strength and high-strength concrete columns, covering concrete strengths were in the range of 19.1-151 MPa. Three main influential parameters, including the tensile yield strength and the volumetric ratio of the transverse reinforcements, as well as the concrete strength, were applied as input variables to the model. The ANN model was trained and tested by a reliable database consisting of 240 data sets obtained from authors and published literature. The proposed ANN model used to predict the compressive strength of circular concrete columns confined by spiral stirrup had high applicability and reliability compared with existing analytical models.
The lateral confinement of stirrups can effectively restrain the unstable lateral expansion of confined concrete and improve the load capacity and the ductility of concrete. The lateral response of stirrups affects the effective confinements on confined concrete and the dilation of core concrete. However, the lateral response of confined concrete has not received enough attention. In this paper, the lateral responses of 24 ultra‐high performance concrete (UHPC) and ultra‐high fiber‐reinforced performance concrete (UHPFRC) columns confined with high strength stirrups were obtained by experiments. The investigated parameters included concrete strength, stirrups volumetric ratio, and steel fibers contents. The axial stress‐lateral strain curves and lateral strain‐axial strain responses of specimens were presented to understand the dilation of concrete. The results showed that high strength concrete and high steel fibers contents decreased the dilation of concrete, when stirrups volumetric ratio increased from 1.0 to 2.0%, the dilation of concrete increased by 1.45~2.09 times. Furthermore, the lateral strain‐axial strain response prediction models were developed by introducing the effects of steel fibers, which were suitable for predicting the lateral strain‐axial strain of confined concrete.
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