Experimental evaluation of the effect of mix design ratios on compressive strength of cement mortars containing cement strength class 42.5 and 52.5 MPa-Reference-Cited by-同舟云学术

Experimental evaluation of the effect of mix design ratios on compressive strength of cement mortars containing cement strength class 42.5 and 52.5 MPa

Published:2018 Issue: Volume:22 Page:392-398
ISSN:2351-9789
Container-title:Procedia Manufacturing
language:en
Short-container-title:Procedia Manufacturing

Author:

Eskandari-Naddaf Hamid,Kazemi Ramin

Publisher

Elsevier BV

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering

Reference32 articles.

1. An Improved Ant Colony Model for Cost Optimization of Composite Beams.;Korouzhdeh;Applied Artificial Intelligence.,2017

2. Cost optimization and sensitivity analysis of composite beams.;Eskandari;Civil Engineering Journal.,2016

3. Designing;Eskandari;Proposing and Comparing the Methods Predicting the Compressive Strength of the Ferro cement Mortar. Concrete Research Letters.,2015

4. Lightweight Ferrocement Matrix Compressive Behavior: Experiments Versus Finite Element Analysis.;Madadi;Arabian Journal for Science and Engineering,2017

5. Edgell, G. and B.A. Haseltine. Building Mortar for Low Rise Housing: Recommendations, Problems and Solutions. (Year) of Conference.: British Masonry Society.

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