We present a semi-supervised method for panoptic segmentation based on ConsInstancy regularisation, a novel strategy for semi-supervised learning. It leverages completely unlabelled data by enforcing consistency between predicted instance representations and semantic segmentations during training in order to improve the segmentation performance. To this end, we also propose new types of instance representations that can be predicted by one simple forward path through a fully convolutional network (FCN), delivering a convenient and simple-to-train framework for panoptic segmentation. More specifically, we propose the prediction of a three-dimensional instance orientation map as intermediate representation and two complementary distance transform maps as final representation, providing unique instance representations for a panoptic segmentation. We test our method on two challenging data sets of both, hardened and fresh concrete, the latter being proposed by the authors in this paper demonstrating the effectiveness of our approach, outperforming the results achieved by state-of-the-art methods for semi-supervised segmentation. In particular, we are able to show that by leveraging completely unlabelled data in our semi-supervised approach the achieved overall accuracy (OA) is increased by up to 5% compared to an entirely supervised training using only labelled data. Furthermore, we exceed the OA achieved by state-of-the-art semi-supervised methods by up to 1.5%.

Calcined clays (CCs) as supplementary cementitious materials (SCMs) can be a promising option to reduce clinker content and CO₂ emissions in eco-friendly concretes. Although CCs as components of composite cements in combination with Ordinary Portland Cement (OPC) and limestone powder (LSP) have attracted industry interest, their use as concrete additives is limited. This study investigates the effects of the addition of CCs on the fresh and hardened properties of industry-standard ready-mixed concretes. Four concrete mix designs, each with three superplasticizer dosages, were tested, resulting in 12 variations. The CCs used, which are typical of 2:1 bentonite clays with low metakaolin content, reflect the clays available in Germany. The results showed that CCs significantly influenced the workability, which could be controlled with a high superplasticizer dosage. Increased CC contents reduced bleeding tendencies, which was beneficial for certain structural applications. Early age strength decreased with CCs, but the 28-day strength exceeded that of pure OPC concretes up to 30 wt% CCs. Resistance to CO₂-induced carbonation decreased with higher levels of CCs but was comparable up to 15 wt%. Freeze–thaw damage decreased, and chloride migration resistance improved due to a denser microstructure. The global warming potential (GWP) of the concretes tested is in line with that reported in the literature for concretes made from highly blended cements, suggesting that CCs can improve the sustainability of concrete production.

In this study, the impact of binder granulometry as well as chemical additives on the early strength and early age stiffness development of eco-efficient mortars with low clinker content and ternary blended cements with high contents of slag and limestone powder was investigated. With regard to granulometry, the particle size distribution of the slag was varied in two steps. In addition, admixtures based on nano-granular C-S-H seeds were used for the acceleration of the hydration reaction. Both the compressive strength at 1d and the in-situ ultrasound pulse velocity for the first 36 h were determined. The granulometric optimization of the slag leads to an improvement in compressive strength of up to 162% in the early phase of the first 24 h. In addition, C-S-H seeding enhanced the hydration reaction mortars as early as 6 h after water addition (at 20 °C). An increase in the dosage level of the C-S-H seeding admixture further resulted in a corresponding increase in early strength, particularly when the clinker content exceeds 30 wt% up to 103%. The proposed combined granulometric and admixture-based approach significantly improves the reaction of the binder in the early phase, so that the clinker factor can be significantly reduced while maintaining a comparable binder intensity.