Estimation of the Spacing Factor Based on Air Pore Distribution Parameters in Air-Entrained Concrete

Air-void characteristics are defined in the EN-480-11 test method. The primary criticism of Powers' model comes from the fact that the spacing factor is calculated with the average chord length, without taking into account the chord length distribution. The aim of this study is to determine whether an analysis of the chord length distribution can provide a more accurate estimate of the spacing factor. A data set containing 110 air-entrained concretes with various characteristics was analyzed. The artificial neural network method was applied to develop a model that determines the relationship between the spacing factor, L2, and the parameters of the air-void structure. The input parameters for the ANN-L2 model included the following: A, d, and W-characteristics of the chord size distribution, P-cement paste content, and N5-number of large pores. The ANN model allows for a sufficiently accurate estimation of the spacing factor, L2. The most significant factors that influenced L were the peak amplitude, A; peak width, W; and cement paste content, P. There was a strong correlation between the results of the ANN model and the standard spacing factor L2, indicating that both calculation methods produced comparable results. Finally, a simple method for using the ANN model to calculate the spacing factor in Excel is demonstrated.