An Experimental Study on Partial Replacement of Fine Aggregate using Steel Slag
Journal: GRD Journal for Engineering (Vol.3, No. 07)Publication Date: 2018-04-04
Authors : R. Mahalingam; G. Sri Durga; N. Varshini; M. Sharmila; R. Vishnu Priya;
Page : 12-16
Keywords : Fine Aggregates; Steel Slag; Compressive Strength; Split Tensile Strength;
Abstract
Modification of concrete properties by the addition of appropriate materials is a popular field of concrete research. In this study we are focusing on the use of selected waste of steel industry (steel slag) as a partial replacement for fine aggregate in the production of concrete. In this research study, concretes were made with steel slag as substitution for raw fine aggregate. Fine aggregate was replaced by these wastes in different proportions (20%, 40%, & 60 %,) by weight of fine aggregate. The aim of this study is to investigate the compressive strength, split tensile strength and Material properties of concrete with steel chips as a partial replacement for fine aggregate. The experimental results indicates that, the concrete mixed with steel chips have better strength than conventional concrete, while in the case of concrete mixed with the scale of 40%, it attains the maximum strength.
Citation: R. Mahalingam, Sri Vidya College Engineering &Technology, India; G. Sri Durga ,Sri Vidya College Engineering &Technology, India; N. Varshini ,Sri Vidya College Engineering &Technology, India; M. Sharmila ,Sri Vidya College Engineering &Technology, India; R. Vishnu Priya ,Sri Vidya College Engineering &Technology, India. "An Experimental Study on Partial Replacement of Fine Aggregate using Steel Slag." Global Research and Development Journal For Engineering : 12 - 16.
Other Latest Articles
- Mining Human Activity Patterns from Smarthome Big Data by using MapReduce Algorithm
- Optimization of Bandwidth using Load Balancing Algorithm in Data Centers
- Tracing the Way of Data in a TCP Connection through the Linux Kernel
- Performance of Micro Strip Patch Antenna for Dual Band Application
- Data Mining Systems to Determine Sales Trends and Quantity Forecast Using Association Rule and CRISP-DM Method
Last modified: 2018-05-22 03:05:06