·The probabilistic characteristics including the average value associated dispersion and distribution of the compressive strength generally play an essential role in the reliable design and safety evaluation of concrete structures as well as the quality assessment of concrete [1] [2] [3] In terms of interpreting the strength distribution the normal distribution is
·The process of concrete production involves mixing cement water and other materials The quantity of each of these materials results in a performance that is particularly estimated in terms of compressive or flexural strength It has been observed that the final performance of concrete has a high variance and that traditional formulation methods do not
·It is known that in the last few decades the cement and concrete industries have been witnessing advancements in terms of material properties production performance and even trend [27] Yet regardless of these developments the stochastic model for the characterisation of concrete compressive strength recommended in Probabilistic Model Code [28] a reference
·Compressive strength of cement mortar CASA Hardened concrete air void structure analyzer f cc Cubic compressive strength CT Computed Tomography f cu 28 Cubic compressive strength at 28 days ITZ Interface transition zone σ c The stress of concrete matrix under the peak load KRC Concrete with KH 570 pretreated rubber aggregate σ NC
·Several authors investigated the strength properties of 3D printed fiber reinforced concrete 3DP FRC as provided in Table et al [20] investigated the impact of 13 mm length and mm diameter short steel fibers on 3D printed concrete and stated that the specimen with % steel fibers provided the highest CS In another study Xiao et al [34]
·a prescribed range until failure occurs The compressive strength of the specimen is calculated by dividing the maxi mum load attained during the test by the cross sectional area of the specimen 4 Significance and Use Care must be exercised in the interpretation of the significance of compressive strength determinations by this test
·The compressive strength of the FRHSC is MPa % and % higher than that of the HSC and ESi HSC respectively The FRHSC boasts not only the highest compressive strength but also the highest lateral strain at the peak stress in the three concretes Table 4 To understand the effect of strain capacity of the mortar matrix we
·The compressive strength acquired from the concrete cores was adjusted by consulting both the Korean Standard KS F 2422 2022 "Method of obtaining and testing drilled cores and sawed beams of concrete" [23] and ACI 10 [24]
·This indicates that the relationship between compressive strength and these input parameters is not a simple multivariate linear relationship but a complex nonlinear mapping Moreover trying to establish an explicit equation seems to be difficult This is the reason why machine learning models are used in this paper to predict the compressive
·An artificial neural network ANN model for predicting the compressive strength of concrete is established in this study The Back Propagation BP network with one hidden layer is chosen as the structure of the ANN The database of real concrete mix proportioning listed in earlier research by another author is used for training and testing the ANN The proper number
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