Optimization of Cement Mortar Mix using Digital Image Analysis: State of Art

Journal Title: GRD Journal for Engineering - Year 2019, Vol 4, Issue 0

Abstract

Cement mortar comprises 50-90% of fine aggregates which has a significant effect on the fresh properties of the mix such as workability, adhesiveness, cohesiveness, and density. The mix characteristics depend on the aggregate properties such as the shape, size, and surface texture. The most common method used on the construction site to check the quality of the aggregate is sieve analysis. Flakiness and elongation tests are used to measure the shape characteristics of coarse aggregates only. Currently, workability for mortar is adjusted to the need either by adding water or introducing superplasticizer. It is difficult to decide cement fine aggregate proportion and dosage of admixture for the desired workability of the mix. It is possible to design mix using the surface area of fine aggregates and many researchers are working in that area. Digital Image Processing (DIP) method gives accurate information about the shape morphology of fine aggregate. One can assess the behaviour of shape characteristics of aggregates on workability. The mix design of mortar can be optimized by calculating the surface area of fine aggregates. This research paper summarizes measurement techniques to evaluate the morphology of fine aggregates, wet packing density to obtain the desired mix, and rheological aspects of cement mortar.

Authors and Affiliations

Chintan Vohra, P Thaker

Keywords

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  • EP ID EP552415
  • DOI -
  • Views 125
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How To Cite

Chintan Vohra, P Thaker (2019). Optimization of Cement Mortar Mix using Digital Image Analysis: State of Art. GRD Journal for Engineering, 4(0), 198-203. https://europub.co.uk/articles/-A-552415