Since depletion of natural resources and the amount of construction and demolition waste have overcome the socially and environmentally acceptable level, the construction industry must address this issue and reduce its impact on the environment. A step towards sustainability in the construction industry is the application of recycled aggregates and supplementary cementitious materials as integral components of concretes, which provides conserving natural aggregates and waste reduction. This study adopts a holistic approach to producing green self-compacting concrete with the highest portion of recycled aggregate as a replacement for natural aggregate and fly ash as filler. Based on the particle packing density method, four series of self-compacting concrete were prepared: the first series was made with natural fine and coarse aggregate, the second series was made with fine natural aggregate and recycled coarse aggregate, the third with 50 % (by mass) of fine natural aggregate replaced by recycled fine aggregate and recycled coarse aggregate, and the fourth series completely with recycled fine and coarse aggregate. The content of fly ash remained constant. Regardless of the expected decrease of workability in a fresh state with the increase of the recycled aggregate content, all series exceeded the requirements set for the hardened structural concrete.

Thermal shock stability plays a great role in the selection of optimal refractory material. Different methods of characterization were developed for this purpose, including the implementation of nondestructive testing. Image analysis is a very well method for characterization of different materials structures, as well as changes and occurred defects in structure caused by different influences. In this paper, possible application of image analysis will be presented related to the monitoring thermal shock behavior of selected refractory materials. Different parameters such are R parameter, level of destruction, as well as determination of morphological descriptors (area, perimeter, diameter, roundness) using Image analysis, will be presented.