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LIDIA LA MENDOLA

STATE OF THE ART ON BOND BETWEEN FRCM SYSTEMS AND MASONRY/CONCRETE SUBSTRATE: DATABASE ANALYSIS AND IMPROVED MODELS

  • Autori: Bramato G.; Leone M.; Ceroni F.; Oddo M.C.; Minafo' G.; Aiello M.A.; La Mendola L.
  • Anno di pubblicazione: 2023
  • Tipologia: Contributo in atti di convegno pubblicato in rivista
  • OA Link: http://hdl.handle.net/10447/591042

Abstract

The use of the Fabric Reinforced Cementitious Mortars (FRCMs) is nowadays a promising solution for the strengthening of both reinforced concrete and masonry structural elements. The application consists of a bond-dependent face-to-face plastering of an open grid or mesh by means of an inorganic-based matrix, i.e. a cement-based mortar. The main advantage of such a strengthening technique is the good compatibility with different types of substrates since the most suitable matrix can be selected focusing on the most similar breathability and stiffness. On the other side, the strengthening efficiency could be over-estimated if the potential bond failure is neglected. The FRCM-bond behaviour depends on many parameters, e.g., mechanical properties of substrate and reinforcement, environmental conditions, etc. Due to the wide range of variability of these parameters, nowadays, formulations for a reliable prediction of the maximum strain which the FRCM is able to develop for avoiding bond failure are not available. At this scope, the present paper collects a large database of experimental results of bond tests available in literature in order to investigate the main parameters influencing the performance of this strengthening technique, to identify the aspects that have to be further studied, and to calibrate an empirically-based analytical model proposed by the authors to predict the maximum design strain in the FRCM reinforcement. The parameters assumed in the model are the following: type of substrate (i.e. masonry or concrete), type of fabric (i.e. carbon, glass, steel, basalt), type of matrix (i.e. cement, lime, alkali-activated based) and failure mode (detachment, slippage, rupture, etc.). The database was clustered depending on the failure mode in order to calibrate targeted and more accurate equations.