scispace - formally typeset
M

Mucteba Uysal

Researcher at Istanbul University

Publications -  64
Citations -  2075

Mucteba Uysal is an academic researcher from Istanbul University. The author has contributed to research in topics: Geopolymer & Compressive strength. The author has an hindex of 16, co-authored 47 publications receiving 1256 citations. Previous affiliations of Mucteba Uysal include Sakarya University & Yıldız Technical University.

Papers
More filters
Journal ArticleDOI

Effect of mineral admixtures on properties of self-compacting concrete

TL;DR: In this article, the benefits of limestone powder (LP, basalt powder (BP) and marble powder (MP) as partial replacement of Portland cement are established, without attempting any additional processing in the production of self-compacting concrete (SCC).
Journal ArticleDOI

Performance of self-compacting concrete containing different mineral admixtures

TL;DR: In this paper, the influence of fly ash (FA), granulated blast furnace slag (GBFS), limestone powder (LP), basalt powder (BP), and marble powder (MP) on the properties of self-compacting concrete (SCC) was investigated.
Journal ArticleDOI

Mechanical and microstructural characterization of fiber reinforced fly ash based geopolymer composites

TL;DR: In this paper, an experimental investigation was carried out to study some mechanical and microstructural characteristics of fly ash based geopolymer mortars reinforced with three different fiber types: steel, polypropylene, and polyvinyl alcohol fibers.
Journal ArticleDOI

The effect of mineral admixtures on mechanical properties, chloride ion permeability and impermeability of self-compacting concrete

TL;DR: In this paper, the effectiveness of various mineral admixtures in producing self-compacting concrete (SCC) was evaluated using slump flow, T 50 time, L-box and V-funnel tests.
Journal ArticleDOI

Estimation of compressive strength of self compacting concrete containing polypropylene fiber and mineral additives exposed to high temperature using artificial neural network

TL;DR: In this article, an artificial neural network model for compressive strength of self-compacting concretes (SCCs) containing mineral additives and polypropylene (PP) fiber exposed to elevated temperature were devised.