Fuzzy inference systems based prediction of engineering properties of two-stage concrete
- 25 February 2017
- journal article
- research article
- Published by Techno-Press in Computers & concrete
- Vol. 19 (2), 133-142
- https://doi.org/10.12989/cac.2017.19.2.133
Abstract
Fuzzy inference systems based prediction of engineering properties of two-stage concrete two-stage concrete;fuzzy logic;efflux time;spread flow;compressive strength;tensile strength; Two-stage concrete (TSC), also known as pre-placed aggregate concrete, is characterized by its unique placement technique, whereby the coarse aggregate is first placed in the formwork, then injected with a special grout. Despite its superior sustainability and technical features, TSC has remained a basic concrete technology without much use of modern chemical admixtures, new binders, fiber reinforcement or other emerging additions. In the present study, an experimental database for TSC was built. Different types of cementitious binders (single, binary, and ternary) comprising ordinary portland cement, fly ash, silica fume, and metakaolin were used to produce the various TSC mixtures. Different dosages of steel fibres having different lengths were also incorporated to enhance the mechanical properties of TSC. The database thus created was used to develop fuzzy logic models as predictive tools for the grout flowability and mechanical properties of TSC mixtures. The performance of the developed models was evaluated using statistical parameters and error analyses. The results indicate that the fuzzy logic models thus developed can be powerful tools for predicting the TSC grout flowability and mechanical properties and a useful aid for the design of TSC mixtures.Keywords
This publication has 13 references indexed in Scilit:
- Two-stage concrete made with single, binary and ternary bindersMaterials and Structures, 2014
- Critical overview of two-stage concrete: Properties and applicationsConstruction and Building Materials, 2014
- OPTIMIZED FUZZY LOGIC MODEL FOR PREDICTING SELF-COMPACTING CONCRETE SHRINKAGEMechanika, 2013
- Rule-based Mamdani type fuzzy logic model for the prediction of compressive strength of silica fume included concrete using non-destructive test resultsNeural Computing & Applications, 2012
- Investigation into viability of using two-stage (pre-placed aggregate) concrete in Irish settingFrontiers of Architecture and Civil Engineering in China, 2010
- Neuro-fuzzy application for concrete strength prediction using combined non-destructive testsMagazine of Concrete Research, 2009
- Flow analysis of water–powder mixtures: Application to specific surface area and shape factorCement and Concrete Composites, 2009
- Neuro-fuzzy based prediction of the durability of self-consolidating concrete to various sodium sulfate exposure regimesComputers & concrete, 2008
- Prediction of compressive strength of concrete containing fly ash using artificial neural networks and fuzzy logicComputational Materials Science, 2008
- A new way of prediction elastic modulus of normal and high strength concrete—fuzzy logicCement and Concrete Research, 2005