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Mahdi Nematzadeh

Mahdi Nematzadeh

Academic rank: Professor
ORCID: 0000-0002-8065-0542
Education: PhD.
ScopusId: 36198613700
HIndex:
Faculty: Faculty of Technology and Engineering
Address:
Phone: 011-35302903

Research

Title
Hardened density of freshly compressed concrete and its effect on mechanical properties
Type
JournalPaper
Keywords
freshly compressed concrete، density، pressure، mechanical properties، codes، prediction model
Year
2014
Journal European Journal of Environmental and Civil Engineering
DOI
Researchers Morteza Naghipour ، Mahdi Nematzadeh ، Javad Jalali ، Abolghasem Salari ، Seyed Tohid Nemati

Abstract

This paper presents the results of an experimental investigation into the hardened density of freshly compressed concrete and its effect on the mechanical properties including compressive strength and modulus of elasticity. The concrete specimens were compressed in a fabricated pressure apparatus under different values of pressure and reference concrete strength. Two types of pressure, long-term pressure and short-term pressure were also applied to the fresh concrete to evaluate the effect of pressure duration on the concrete density. The results indicated that the increase in the compressed concrete density increases with the increase in primary pressure and decrease in reference concrete strength. Moreover, the pressure duration poorly affects the concrete density. By considering the density, this study also provides a model for predicting the modulus of elasticity of the compressed and the uncompressed concretes, which covers the wide range of the compressive strength between 18 and 81 MPa. Finally, a comparison between the measured values of the modulus of elasticity and those calculated by the prediction models, given in ACI 318, ACI 363 and EC2, was performed, and then correction factors were proposed for the model codes to estimate the modulus of elasticity of the compressed concrete. The results showed that ACI 318 and ACI 363 models involving the concrete density yield correction factors close to one, while EC2 model involving a coefficient reflecting the effect of aggregate type gives a very higher value