Open Access Open Access  Restricted Access Subscription Access

Study on Concrete

Varun Sharma

Abstract


The current review targets exploring the presentation of high volume fly debris (HVFA) concrete at raised temperature uncovered upto 100 oC to 200oC for three hours term is examined. The study focuses on the mechanical and physical characteristics of high volume fly ash concrete. The test program's variable calls for replacing cement with fly ash at temperatures ranging from 27 degrees Celsius to 200 degrees Celsius for three hours. Residual compressive strength is one of the studied mechanical and physical properties. The results of the test showed that concrete that was used as replacements lost more strength than normal concrete.

 


Full Text:

PDF

References


Nil and Tang (2012) Prediction of compressive strength of concrete by neural networks. Cement and Concrete Research, 30(8), 1245-1250.

Aldalton, F., Kişi, Ö., & Aydin, K. (2012). Predicting the compressive strength of steel fiber added lightweight concrete using neural network. Computational Materials Science, 42(2), 259-265.

Öztaş, A., Pala, M., Özbay, E., Kanca, E., Çagˇlar, N., & Bhatti, M. A. (2006). Predicting the compressive strength and slump of high strength concrete using neural network. Construction and Building Materials, 20(9), 769-775.

Bilim, C., Atiş, C. D., Tanyildizi, H., & Karahan, O. (2009). Predicting the compressive strength of ground granulated blast furnace slag concrete using artificial neural network. Advances in Engineering Software, 40(5), 334-340.

Zarandi, M. F., Türksen, I. B., Sobhani, J., & Ramezanianpour, A. A. (2008). Fuzzy polynomial neural networks for approximation of the compressive strength of concrete.

Applied Soft Computing, 8(1), 488-


Refbacks

  • There are currently no refbacks.