Search Results (2)

Construction and Demolition Waste (CDW) is among the largest waste streams in the world. Therefore, within the Circular Economy concept, there is a growing interest in its reuse. The purpose of this work was to study the use of recycled aggregates (RAs) obtained by a specific separation method from CDW, replacing natural aggregates (NAs) in the manufacture of precast concrete elements, such as kerbstones and paver blocks. The physical and technological properties of precast products formulated with RAs were analysed in accordance with current regulations, comparing them with those of commercial products manufactured with NAs. The results indicated that partial or total substitution of NAs by RAs increased the water absorption and apparent porosity values of the precast elements while reducing the bulk density and compressive strength. However, all units manufactured with RAs showed breaking load values higher than the minimum required by EN 1338 and, in some cases, slightly higher average tensile strength values than the reference material. In addition, some of the compositions including RAs gave rise to pieces that, according to their flexural strength, were classified as class 1 and marked S in accordance with EN 1340. According to abrasion resistance, in most cases, the precast elements are classified as Class 4 and I (≤20 mm). Finally, precast concrete produced from RAs satisfies the tolerance requirements for classification as class 3 (≤1.5 kg m⁻²). Therefore, it could be suitable for use in high pedestrian or traffic areas. Full article

Automated processing of the data provided by a laser-based mobile mapping system will be a necessity due to the huge amount of data produced. In the future, vehiclebased laser scanning, here called mobile mapping, should see considerable use for road environment modelling. Since the geometry of the scanning and point density is different from airborne laser scanning, new algorithms are needed for information extraction. In this paper, we propose automatic methods for classifying the road marking and kerbstone points and modelling the road surface as a triangulated irregular network. On the basis of experimental tests, the mean classification accuracies obtained using automatic method for lines, zebra crossings and kerbstones were 80.6%, 92.3% and 79.7%, respectively. Full article