Strength of Concrete with Different Aggregates Through ANN : A Review

Authors(3) :-Rahul Bhargava, Nadish Pandey, Rajesh Joshi

Concrete is a fusion of cement, coarse aggregate, fine aggregates and water. Its success lies in its adaptability as can be designed to resist cruel environments although taking on the most inspirational forms. Scientists and Engineers are further aiming to enhance its limits with the help of novel admixtures and various waste alternate materials (WAMs). Previously WAMs comprises of readily available materials, natural like diatomaceous earth or volcanic ash. The engineering marvels like Roman aqueducts, the Coliseum are examples of this practice used by Romans and Greeks. Currently, the majority concrete mixture consists ACMs which are mainly by-product or waste materials from other industrial processes. From the perspective of economy in cement requirement for given w/c ratio rounded aggregates are more preferred than angular aggregates. Flat particles in concrete are having unpleasant effect over the workability of concrete, cement requirement, strength and durability. In common high content of flaky aggregates formed low quality concrete. In th paper we are preenting review of literature related to our study on concrete utilizing ANN technique.

Authors and Affiliations

Rahul Bhargava
P. G. Scholar, Department of Civil Engineering, RGPM, Bhopal, Madhya Pradesh, India
Nadish Pandey
Assistant Professor, Technocrats Institute of Technology, Excellence, Madhya Pradesh, India
Rajesh Joshi
Head of Department, Rajiv Gandhi Proudyogiki Mahavidyalaya Bhopal, Madhya Pradesh, India

Concrete, ANN, network, strength, review, analysis.

  1. W. O, Ajagbe, M. A. Tijani and O. A. Agbede, [Compressive Strength of Concrete Made from Aggregates of Different Sources], USEP: Journal of Research Information in Civil Engineering, Vol.15, No.1, 2018.
  2. Rama Mohan Rao.P and H.Sudarsana Rao, [Prediction Of Compressive Strength Of Concrete With Different Aggregate Binder Ratio Using ANN Model], International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-0181, Vol. 1 Issue 10, December- 2012.
  3. Amirreza Kandiri, Farid Sartipi and Mahdi Kioumarsi, [Predicting Compressive Strength of Concrete Containing Recycled Aggregate Using Modified ANN with Different Optimization Algorithms], Appl. Sci. 2021, 11, 485.
  4. Neela Deshpande, Shreenivas Londhe and Sushma Kulkarni, [Modeling compressive strength of recycled aggregate concrete by Artificial Neural Network, Model Tree and Non-linear Regression], International Journal of Sustainable Built Environment (2014) 3, 187–198.
  5. Mohamad Ali Ridho B K A, Chayut Ngamkhanong, Yubin Wu and Sakdirat Kaewunruen, [Recycled Aggregates Concrete Compressive Strength Prediction Using Artificial Neural Networks (ANNs)], Infrastructures 2021, 6, 17.
  6. M. Deepak, A. Gopalan, R. Akshay Raj, S.Shanmugi and P.Usha, [Modeling of Concrete Slump and Compressive Strength using ANN], International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-5S March, 2019.
  7. Sagar Chhetri, Kiran Neupane, Nirmal Prasad Baral and Baburam Bhandari, [Effect of Coarse Aggregate Size Variation on Compressive Strength of Concrete along the Length of Seti River], International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-0181, Vol. 10 Issue 03, March-2021.
  8. Magudeaswaran.P, Vivek Kumar C and M S Britto Jeyakumar, [Forecasting of strength and durability properties of High Performance Composites by Artificial Neural Networks (ANN)], E3S Web of Conferences 184, 01103 (2020).
  9. Sakshi Gupta, [Using Artificial Neural Network to Predict the Compressive Strength of Concrete containing Nano-silica], Civil Engineering and Architecture 1(3): 96-102, 2013.
  10. Palika Chopra, Rajendra Kumar Sharma and Maneek Kumar, [Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming], Hindawi Publishing Corporation Advances in Materials Science and Engineering Volume 2016, Article ID 7648467, 10 pages.
  11. Hosein Naderpour, Amir Hossein Rafiean and Pouyan Fakharian, [Compressive strength prediction of environmentally friendly concrete using artificial neural networks], Journal of Building Engineering 16 (2018) 213–219.
  12. R. Pranamika, Dr. M. Senthil Pandian and K. Karthikeyan, [Predictive study on Mechanical strength of Lightweight concrete using MRA and ANN], Turkish Journal of Computer and Mathematics Education, Vol.12 No.10 (2021), 7774-7792.
  13. FAEZEHOSSADAT KHADEMI and SAYED MOHAMMADMEHDI JAMAL, [PREDICTING THE 28 DAYS COMPRESSIVE STRENGTH OF CONCRETE USING ARTIFICIAL NEURAL NETWORK], i-manager’s Journal on Civil Engineering, Vol. 6lNo. 2lMarch - May 2016.
  14. Faezehossadat Khademi, Sayed Mohammadmehdi Jamal, Neela Deshpande and Shreenivas Londhe, [Predicting strength of recycled aggregate concrete using Artificial Neural Network, Adaptive Neuro-Fuzzy Inference System and Multiple Linear Regression], International Journal of Sustainable Built Environment (2016) 5, 355–369.

Publication Details

Published in : Volume 6 | Issue 2 | March-April 2022
Date of Publication : 2022-03-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 01-08
Manuscript Number : IJSRCE22622
Publisher : Technoscience Academy

ISSN : 2456-6667

Cite This Article :

Rahul Bhargava, Nadish Pandey, Rajesh Joshi, "Strength of Concrete with Different Aggregates Through ANN : A Review", International Journal of Scientific Research in Civil Engineering (IJSRCE), ISSN : 2456-6667, Volume 6, Issue 2, pp.01-08, March-April.2022
URL : https://ijsrce.com/IJSRCE22622

Article Preview

Contact Us

  • Address : 3 & 4, Sterling Plaza, Indira Circle, 150 Feet Ring Road, Rajkot-360005, Gujarat, India