List of Articles Seyed Azim Hosseini

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  1 - Presenting a novel approach for estimation the compressive strength of high strength concrete using ANN & GEP
  Seyed Azim Hosseini
  10.1007/ijase.2022.1965020.1054
  In this article, the application of artificial neural networks in predicting the degree of concrete compressive strength of High Strength Concrete (HSC) was investigated. For this purpose, use was made of the pattern recognition neural network and the obtained data from More

  In this article, the application of artificial neural networks in predicting the degree of concrete compressive strength of High Strength Concrete (HSC) was investigated. For this purpose, use was made of the pattern recognition neural network and the obtained data from the experimental tests for predicting the compressive strength degree of HSC. Five inputs from the HSC mix design were utilized for predicting the degree of compressive strength, by application of the scaled conjugate gradient backpropagation algorithm in neural network. The outputs were classified into 5 strength groups of M1, M2, M3, M4 and M5. The simulation results shows 97.9% accuracy in classifying the different predefined degrees of HSC using the confusion matrix diagram. Moreover, the cross-entropy error obtained from testing the neural network (NN) model and correlation coefficient (R2) of GEP for predicting compressive strength of the HSC were evaluated at 0.042096 and 0.9795, respectively, indicating high accuracy of the model. Application of this model could greatly help the persons, companies and research centers in terms of preparation and making of HSC with desired compressive strength, that are in need of this type of concrete. Manuscript profile
• Open Access Article
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  2 - Assessing the effects of self-consolidating concrete components on workability to compensate the negative impacts resulted by temperature and time
  Seyed Azim Hosseini
  10.1007/ijase.2022.702604
  Compared to other concrete types, the self-compacting concrete (SCC) offers a higher workability. Accordingly, the SCC performance is highly affected by the ambient temperature and extended transportation time. In previous studies, the effect of constituents on SCC at v More

  Compared to other concrete types, the self-compacting concrete (SCC) offers a higher workability. Accordingly, the SCC performance is highly affected by the ambient temperature and extended transportation time. In previous studies, the effect of constituents on SCC at various time and temperature was only studied after the concrete temperature reached the normal range. Nonetheless, in the present research, it is tried to reduce the negative impacts of changing temperature and time by using cement, limestone powder, and chemical admixtures without considering temperature constraints for concrete. In this research, SCC samples temperature were selected for different seasonal conditions. Therefore, once the concrete temperature reached the ambient temperature, slump flow, T50, VSI, J-ring, and rheology tests were conducted on a total of 21 different concrete mixtures with water to cement ratio of 0.4. According to the results, application of retarding admixture and increased cement dosage contributed to improved workability and rheological behavior. On the other hand, an increase in the limestone powder dosage, rather than cement, was seen to impose a larger contribution to increased passing ability of SCC through rebars, but since the concrete containing limestone powder exhibited larger slump losses, one should increase the dosage of cement or retarding admixture to retain the concrete workability. Generally, it was found that the temperature and concrete mixture composition effectively control performance characteristics of the SCC. Therefore, it is recommended to keep the concrete from being overheated as it can otherwise lead to the acceleration of cement hydration and hence decreased workability. Manuscript profile