Title:
An Experimental Investigation on Workability and Bleeding Features
Author(s):
Fatih Çelik, Andaç Batur Çolak, Og˘uzhan Yıldız, and Samet Müfit Bozkır
Publication:
Materials Journal
Volume:
119
Issue:
5
Appears on pages(s):
63-76
Keywords:
artificial neural network (ANN); bleeding; fly ash (FA); nano alumina; stability of grouts; workability of grouts
DOI:
10.14359/51735949
Date:
9/1/2022
Abstract:
In this experimental study, the workability and bleeding properties of cement-based grout mixtures combined with fly ash (FA) and colloidal nanopowder (n-Al2O3) were investigated, and some prediction models were developed with an artificial neural network (ANN). Marsh cone flow time, mini-slump spreading diameter, and Lombardi plate cohesion of the grout samples were measured based on the workability test. Test results showed that the use of FA as mineral additive in the grout samples positively contributed to an increase of the fluidity of the grout samples as expected. Considerable effects were observed on workability features of grout mixtures with the addition of nano alumina because of having a large specific
surface area. In addition, the use of nano alumina together with FA in grout mixtures contributes to the stability of these mixtures by looking at changes in bleeding values. Using the experimental data obtained, an ANN model was developed to predict the values of Marsh cone flow time, mini-slump spreading diameter, and plate cohesion. The developed ANN model can predict mini-slump spreading diameter with an error rate of –0.04%, Marsh cone flow time value with an error rate of –0.23%, and plate cohesion value with an error rate of –1.07%.