Damage induced by repetitive freezing and thawing processes is one of the critical factors that affect concrete durability in cold climates. This deterioration process manifests as surface scaling and internal damage. The damage processes are governed by physicochemical mechanisms that are active across multiple scales. In this contribution, we present a novel multiscale theoretical framework for estimating the critical pressure required for microcrack initiation during freezing and thawing of cementitious mortar. Continuum micromechanics and fracture mechanics is used to model the phenomena of microcrack initiation and growth. Damage at the microscale is upscaled to the level of the specimen using multilevel homogenization. The critical pressure is estimated using poromechanics at the microscopic scale. A theoretical analysis shows that in the frozen state, the material can resist higher pressures. As a consequence, the material is more susceptible to damage during thawing. The micromechanical predictions are within the range of the predictions obtained by electrokinetic theory.

Surface deterioration of concrete subjected to freezing and thawing in combination with deicing salts is one of the most important factors determining the durability of concrete infrastructure in cold climates. The freeze–thaw deicing salt (FTDS) resistance of cementitious materials can be determined by the capillary suction of de‐icing chemicals and freeze–thaw (CDF) test. Specimens are subjected to repeated freeze–thaw cycles with simultaneous addition of deicing salt and the amount of material scaled off near the surface is determined. For concretes with adequate FTDS resistance, this test method works very well. However, specimens with unknown performance often experience increased edge scaling. This leads to a falsification of results and consequently to an underestimation of the actual freeze–thaw resistance. In materials research, however, concretes with high levels of surface deterioration are studied in order to investigate various factors of influence on the freeze–thaw resistance of concretes in a targeted manner. This article presents a novel methodology that delivers new information regarding surface deterioration of CDF samples using high‐resolution 3D scan data. Change of volume is used to support deterioration results of the standard CDF methodology. Increase of surface area is used to estimate change in roughness of samples.

Deterioration of concrete subjected to freezing and thawing climatic conditions is one of most important factors affecting the durability of concrete infrastructure in cold climates. The freeze-thaw resistance of cementitious materials like concrete and mortar can be determined by the CDF test (Capillary Suction of De-icing chemicals and Freeze-Thaw Test). Here, concrete specimens are subjected to repeated freeze-thaw cycles with simultaneous addition of de-icing salt and the amount of material weathered near the surface is determined. For concretes with adequate freeze-thaw resistance, this test method works very well. However, specimens with inadequate or unknown performance often experience increased edge weathering, which is caused by the detachment of the lateral isolation tape. The increasing edge influence thus leads to a falsification of the results and consequently to an underestimation of the actual freeze-thaw resistance of the material. In materials research in particular, however, concretes with high levels of weathering are studied in order to be able to investigate various factors of influence on the freeze-thaw resistance of concretes in a targeted manner. This paper presents a novel methodology that delivers new information regarding the weathering of CDF test samples and the associated distribution function of the height decrease using high resolution 3D scan data. The results indicate a correlation between the progression of the distribution function and the sample's maximum aggregate size. The change of the sample volume can be used to support the weathering results of the standard CDF methodology. The increase of the surface area is used to estimate the tortuosity of the sample surface. It indicates an asymptotic curve approaching a specific maximum value, which is dependent on the the weathering depth of the sample.

This study presents a distribution-optimized mesostructure estimation method for statistically modeling near-surface aggregate size distributions in concrete by optimizing the spatial arrangement of polydisperse spherical aggregates with respect to formwork boundaries. The approach is based on minimizing the deviation between a generated cumulative aggregate volume function and an idealized linear target function corresponding to a constant area fraction along the specimen depth. To enable efficient computation for systems containing a large number of aggregates, grain size groups derived from the grading curve are represented using symmetric Beta distributions, allowing each group to be described by a single shape parameter. The resulting optimization problem is solved using a derivative-free Powell algorithm. The method inherently captures wall effects, leading to a migration of smaller aggregates toward the specimen boundaries to compensate for the geometric constraints of bigger aggregates. Experimental validation was performed for a single concrete mixture and specimen geometry by determining the depth-dependent mean bulk density of a concrete cube using incremental surface grinding combined with high-resolution 3D laser scanning. The optimized mesostructure shows strong agreement with measured density profiles for the investigated specimen. While the validation is limited to a single mixture and geometry, the results indicate that the proposed method is a computationally efficient approach for incorporating wall effects into mesoscale concrete models. Furthermore, increasing aggregate volume fractions intensify the near-surface accumulation of fine particles.