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
Mucteba Uysal,Kemalettin Yilmaz +1 more
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
Mucteba Uysal,Mansur Sümer +1 more
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
Mucteba Uysal,Harun Tanyildizi +1 more
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.