Selection of novel geopolymeric mortars for sustainable construction applications using fuzzy topsis approach

Construction is recognized as one of the most polluting and energy consuming industries worldwide, especially in developing countries. Therefore, Research and Development (R&D) of novel manufacturing technologies and green construction materials is becoming extremely compelling. This study aims at evaluating the reuse of various wastes, originated in the Kraft pulp-paper industry, as raw materials in the manufacture of novel geopolymeric (GP) mortars whose properties fundamentally depend on the target application (e.g., insulating panel, partition wall, structural element, furnishing, etc.). Five different wastes were reused as filler: Two typologies of Biomass Fly Ash, calcareous sludge, grits, and dregs. The produced samples were characterized and a multi criteria analysis, able to take into account not only the engineering properties, but also the environmental and economic aspects, has been implemented. The criteria weights were evaluated using the Delphi methodology. The fuzzy Topsis approach has been used to consider the intrinsic uncertainty related to unconventional materials, as the produced GP-mortars. The computational analysis showed that adding the considered industrial wastes as filler is strongly recommended to improve the performance of materials intended for structural applications in construction. The results revealed that the formulations containing 5 wt.% of calcareous sludge, grits, and dregs and the one containing 7.5 wt.% of calcareous sludge, grits, dregs, and Biomass Fly Ash-1 have emerged as the best alternatives. Furthermore, it resulted that the Biomass Fly Ash-2 negatively influences the structural performance and relative rank of the material. Finally, this case study clearly shows that the fuzzy Topsis multi-criteria analysis represents a valuable and easy tool to investigate construction materials (either traditional and unconventional) when an intrinsic uncertainty is related to the measurement of the quantitative and qualitative characteristics.