Yapay Zeka Hızlı Bakış & Çıkarımlar
AI InsightThe results obtained in both, the training and testing phases strongly show the potential use of ANN to pre- dict 28 days tensile strength of concretes containing partly pozzolanic materials and manufactured sand.
📌 3 Maddede Bu Makale
Özet
The overuse level of cement and natural sand for civil industry has several undesira- ble social and ecological consequences. As an answer for this, industrial wastes or by- products (pozzolanic materials) such as fly ash, GGBFS, silica fume and metakaolin can be used to interchange partially cement and natural sand by manufacturing sand (M-sand). In this study, Artificial Neural Networks (ANNs) models were developed for predicting the tensile strength, at the age of 28 days, of concretes containing partly pozzolanic materials and partly replacing natural sand by manufactured sand. Tensile strength test were performed and test results were used to construct ANN model. A total of 131 values was used for modeling ANN, 80% in the training phase, and 20% in the testing phase. To construct the model, 25 input parameters were used to achieve one output parameter, referred to as the tensile strength of concrete con- taining partly pozzolanic materials and manufactured sand. The results obtained in both, the training and testing phases strongly show the potential use of ANN to pre- dict 28 days tensile strength of concretes containing partly pozzolanic materials and manufactured sand.