# Additive Manufacturing as an Alternative to Core Sampling in Concrete Strength Assessment
## 2 Materials and Methods
### Physical and Mechanical Testing of Concrete Cube Specimens  
To determine the average density and compressive strength of the concrete, standard testing procedures were followed in accordance with previous results [38; 39; 40], using cube-shaped specimens with an edge length of 70 mm. For each concrete mixture, four specimens were tested at curing ages of 7, 14, and 28 days. Prior to testing, all specimens were visually inspected for surface defects. None of the samples exhibited significant deviations or cracks. Minor surface imperfections, such as burrs along the cube edges, were removed using an abrasive stone. Following the inspection, the linear dimensions (length, width, and height) and the mass of each cube were measured. The statistical spread of dimensional values (a, b, h) for all five mix compositions is shown in Figure 6, which illustrates the variation and consistency in the shape of the specimens prepared under the same printing and compaction conditions. The complete results of the dimensional and mass measurements are provided in Table S1 in the Supplementary Materials. As shown in Figure 6, the boxplot illustrates the distribution of the measured dimensions--a (length), b (width), and h (height)--of the cube specimens prepared from all five concrete mixtures. The dimensions a and b remain relatively consistent across all mixes, with median values close to the nominal 70 mm and minimal variation, confirming the uniformity of the mould geometry and compaction during casting. In contrast, the h dimension (height), which corresponds to the layering direction in the additive process, exhibits noticeably greater variability. This is especially apparent in Mixes 1 and 4, where the interquartile ranges are wider and outliers are more frequent. This vertical inconsistency is likely due to the influence of material flow properties, build-up stability, and manual layer finishing during the 3D-printing process. Figure 6: Boxplot showing dimensional variation of cube specimens for each concrete mix. a (length), b (width), and h (height). The values were measured prior to compressive strength testing. Data correspond to Table S1 in the Supplementary Materials. The figure highlights the anisotropic nature of the 3D-printed concrete, where dimensional stability is better maintained in the lateral (x-y) directions than in the vertical (z) direction. These observations underscore the importance of quality control in the layer-by-layer deposition process to ensure structural uniformity in printed elements. In addition to the dimensional stability, the mass of each cube specimen was recorded to assess the uniformity and density consistency across different mixtures. The distribution of mass measurements is visualised using violin plots in Figure 7, where each plot represents the spread and central tendency of cube weights corresponding to one of the five mix compositions. As illustrated in Figure 7, Mix 2 exhibits the highest median mass (717.9 g), followed by Mixes 5 (710.3 g) and 3 (704.3 g). Mix 1 has the lowest median value (695.4 g), with a noticeably wider distribution, suggesting higher variability in specimen density and potential inconsistencies during casting or compaction. Mix 4, while showing a relatively narrow distribution, has a slightly lower mass than Mixes 2 and 5. The observed variation in mass among mixes may result from differences in composition, inclusion of mineral additives (such as TMF), and printing stability. These factors influence the packing density and porosity of the material, which are critical to both mechanical performance and long-term durability. To evaluate the consistency of specimen geometry and material characteristics, the coefficient of variation (CV, %) was calculated for each mix composition based on five key parameters: dimensions a, b, and h; specimen mass; and calculated density. The CV provides a normalised measure of dispersion and is useful for comparing variability across datasets with different means.