In this study the development of a metakaolin based geopolymeric mortar to be used as bonding matrix for external strengthening of reinforced concrete beams is reported. Four geopolymer formulations have been obtained by varying the composition of the activating solution in terms of SiO₂/Na₂O ratio. The obtained samples have been characterized from a structural, microstructural and mechanical point of view. The differences in structure and microstructure have been correlated to the mechanical properties. A major issue of drying shrinkage has been encountered in the high Si/Al ratio samples. In the light of the characterization results, the optimal geopolymer composition was then applied to fasten steel fibers to reinforced concrete beams. The mechanical behavior of the strengthened reinforced beams was evaluated by four-points bending tests, which were performed also on reinforced concrete beams as they are for comparison. The preliminary results of the bending tests point out an excellent behavior of the geopolymeric mixture tested, with the failure load of the reinforced beams roughly twice that of the control beam.

Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC) structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN) that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM) approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions.

Most European buildings built before 1980s were constructed without any design concern for energy efficiency and environmental sustainability. In addition to this issue, over the last decades, the essential need of safer buildings has progressively attracted the interest of scientific community and government institutions. However, the strong interaction between energy and structural aspects in building retrofit design has never been handled via robust and reliable approaches. The present study explores this knowledge gap by introducing a novel multi-step approach that addresses the retrofit of existing buildings by integrating energy, structural and economic aspects. To this end, a multi-stage energy optimization is carried out by implementing a genetic algorithm and a smart research strategy. Thus, the cost-optimal energy retrofit solution is identified and the impact of the expected economic losses due to seismic damage is assessed throughout the building lifecycle. The methodology is applied to a multi-story residential building, considering the effects of two different building locations, namely Milan and Norcia. These latter are characterized by similar climatic conditions but by a different level of seismic risk, which is higher for Norcia. The outcomes show that the estimated seismic economic losses associated with the energy retrofit solutions are strongly affected by the building location. Thus, the selection of the optimal energy retrofit measures should be related to the building structural behavior in order to achieve reliable economic and sustainability benefits.

The preparation and characterization of innovative organic-inorganic hybrid geopolymers, obtained by valorizing coal fly ash generated from thermoelectric power plants, is reported for the first time. These hybrid materials are prepared by simultaneously reacting fly ash and dimethylsiloxane oligomers at 25 °C in a strongly alkaline environment. Despite their lower density, the obtained materials are characterized by highly improved mechanical properties when compared to the unmodified geopolymer obtained without the use of polysiloxanes, hence confirming the effectiveness of the applied synthetic strategy which specifically aims at obtaining hybrid materials with better mechanical properties in respect to conventional ones. This study is an example of the production of new materials by reusing and valorizing waste raw resources and by-products, thus representing a possible contribution towards the circular economy.

This research investigates the preparation and characterization of new organic–inorganic geopolymeric foams obtained by simultaneously reacting coal fly ash and an alkali silicate solution with polysiloxane oligomers. Foaming was realized in situ using Si⁰ as a blowing agent. Samples with density ranging from 0.3 to 0.7 g/cm³ that show good mechanical properties (with compressive strength up to ≈5 MPa for a density of 0.7 g/cm³) along with thermal performances (λ = 0.145 ± 0.001 W/m·K for the foamed sample with density 0.330 g/cm³) comparable to commercial lightweight materials used in the field of thermal insulation were prepared. Since these foams were obtained by valorizing waste byproducts, they could be considered as low environmental impact materials and, hence, with promising perspectives towards the circular economy.