Thermal and mechanical properties of hardened cement paste reinforced with Posidonia-Oceanica natural fibers

Autor: Laurent Ibos, Atef Mazioud, Oualid Limam, Ons Hamdaoui
Přispěvatelé: Centre d'Etudes et Recherches en Thermique, Environnement et Systèmes [Créteil] (CERTES EA 3481), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), University of Tunis El Manar
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Construction and Building Materials
Construction and Building Materials, Elsevier, 2021, 269, pp.121339-. ⟨10.1016/j.conbuildmat.2020.121339⟩
ISSN: 0950-0618
Popis: This paper focuses on thermal and mechanical properties of a hardened cement paste reinforced with Posidonia-Oceanica fibers. Fibers volume fractions are varied from 0% to 20%. Thermophysical and mechanical properties are measured. Simplified models are developed to predict thermal conductivity, tensile and compressive stresses and fracture toughness variation as a function of fibers volume fraction and geometrical characteristics of samples. Results showed that the addition of Posidonia-Oceanica fibers improved the material insulating properties. In fact, a decrease of about 22% (from 0.0718 W.m-1.K-1 to 0.559 W.m-1.K-1) of thermal conductivity was found with adding 20% of fibers compared to control cement paste. Concerning mechanical properties, flexural and compressive strengths increased for fiber volume fractions in the range of 5 to 10% and then decreased for higher fiber volume fractions. It was shown through a simplified model and MEB observations that agglomeration of fibers for high volume fraction is behind this phenomenon. Moreover, a noticeable increase of toughness was observed with increasing fibers amount: for instance, an increase of about 65% (from 0.245 MPa.m1/2 to 0.404 MPa.m1/2) was observed with the introduction of 20% of fibers in the composite. Simplified analytical models are also developed to predict thermal conductivity, tensile and compressive strengths and fracture toughness. These models are validated with experimental data.
Databáze: OpenAIRE