Prediction of calcium leaching resistance of fly ash blended cement composites using artificial neural network

  • Lee, Yujin; 
  • Seo, Seunghoon; 
  • You, Ilhwan; 
  • Yun, TaeSup; 
  • Zi, Goangseup
Citations

WEB OF SCIENCE

3
Citations

SCOPUS

3

초록

Calcium leaching is one of the main deterioration factors in concrete structures contact with water, such as dams, water treatment structures, and radioactive waste structures. It causes a porous microstructure and may be coupled with various harmful factors resulting in mechanical degradation of concrete. Several numerical modeling studies focused on the calcium leaching depth prediction. However, these required a lot of cost and time for many experiments and analyses. This study presents an artificial neural network (ANN) approach to predict the leaching depth quickly and accurately. Totally 132 experimental data are collected for model training and validation. An optimal ANN model was proposed by ANN topology. Results indicate that the model can be applied to estimate the calcium leaching depth, showing the determination coefficient of 0.91. It might be used as a simulation tool for engineering problems focused on durability.

키워드

artificial intelligence; artificial neural networks; calcium leach; concrete durability; fly ash concrete; modeling; EXTERNAL SULFATE ATTACK; MECHANICAL-PROPERTIES; TRANSPORT-PROPERTIES; PORE STRUCTURE; PASTES; BEHAVIOR; CONCRETE; MICROSTRUCTURE; DETERIORATION; DEGRADATION
제목
Prediction of calcium leaching resistance of fly ash blended cement composites using artificial neural network
저자
Lee, Yujin; Seo, Seunghoon; You, Ilhwan; Yun, TaeSup; Zi, Goangseup
DOI
10.12989/cac.2023.31.4.315
발행일
2023-04
유형
Article
저널명
Computers and Concrete, An International Journal
권
31
호
4
페이지
315 ~ 325