The purpose of the present study was to determine the impact of image quality on the results of air void system parameters determination in air-entrained concretes. The focus was on technical aspects related to the preparation of the scanned image of the concrete surface, which was then subjected to 2D surface analysis. Image processing aimed at separating joined voids and removing various types of defects in aggregate and cement mortar. The specific surface of the voids was determined with the air void equivalent diameter or perimeter as the calculation basis. Applying the Schwartz–Saltykov method, the 3D distribution of the air voids was reconstructed based on 2D measurements. On this basis, the micro-air content A300 was determined. The results of the 2D method were compared with the results of determinations carried out using the linear traverse (1D) method according to EN 480-11. The tests confirm the need to correct the image prior to measurements. Comparative tests showed good agreement between the air void system parameters determined using the 2D analysis and the EN 480-11 chord length counting method.

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.

It is well known that the most important parameters for predicting the frost resistance of pavement concrete are the air pore spacing factor, L, and the micropore content, A₃₀₀. The A₃₀₀ parameter requires complex calculations with the estimation of the air-void size in a 3D space. The procedure is based only on one-dimensional chord lengths. The air-void distribution is used only to determine the content of micropores and has no other practical application. Based on the results of the analysis, it was found that there is a simpler way to estimate the A₃₀₀ parameter without the tedious calculations described in the EN 480-11 Standard. The presented approach is based on the existing linear correlation between the A₃₀₀ parameter and the number of chords in 28 length classes. The developed function includes only a few coefficients (eight classes) because only chord lengths of 10–350 µm are statistically significant. This fact is important not only for the simplification of calculations but may also have consequences for the methodology of testing parameters characterizing the structure of air-entrained concrete using the 2D method. The presented function allows the estimation of A₃₀₀ with a standard error not exceeding 0.02%, so it is useful for practical use.

Frost resistance of pavement concrete is closely related to air void structure. Traditionally, such a structure is assessed by measuring chord lengths according to the guidelines provided in the PN-EN 480-11 standard. In recent years, increased attention has been given to analyzing pore diameters (2D) on the surface of concrete samples. The measurement procedure employed in the surface method should enable accurate identification of small pores formed by modern air-entraining admixtures. Researchers suggest only pores under 300 µm significantly impact frost resistance, raising the question of whether pores over 1000 µm should be considered in measurements. This study attempts to define the measurement frame parameters required to obtain satisfactory results. Additionally, a comparative analysis of air void structure parameters from 2D and 1D methods was conducted. Geometrical models of air voids distributed within cement paste using the Monte Carlo method based on air void structure data derived from real concrete were created. Analysis of these models demonstrated good agreement between the 2D and 1D results. It was concluded that satisfactory results require the analysis of either three measurement frames of 50 × 50 mm or four frames of 40 × 40 mm, with a resolution of at least 3 µm/px.