Civil Engineering / İnşaat Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/13
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Article Citation - WoS: 55Citation - Scopus: 64High-Early Ductile Cementitious Composites With Characteristics of Low Early-Age Shrinkage for Repair of Infrastructures(Springer Verlag, 2015) Şahmaran, Mustafa; Al-Emam, Muhannad; Yıldırım, Gürkan; Şimşek, Yunus Emre; Erdem, Tahir Kemal; Lachemi, MohamedReduced performance in concrete infrastructures is mainly caused by the formation of cracks, which may arise due to deteriorating mechanisms during service life. In most cases, reduced performance calls for urgent repairs to the degraded section. Therefore, it is highly desirable to develop dimensionally stable, ductile repair materials that can attain adequately high strength in a limited amount of time, compensate for significant deformation due to mechanical and environmental loadings, and prevent early-age shrinkage cracks. In this paper, the performance of such a material (high-early-strength engineered cementitious composites, HES-ECC, with very low early-age shrinkage capacity) was investigated by studying mechanical properties and dimensional stability. Composites were produced with different water to cementitious materials and slag to Portland cement ratios. In order to enhance composite properties in terms of ductility and early-age shrinkage characteristics, saturated lightweight aggregates replaced sand in the mixtures. The experimental results show that the majority of HES-ECC mixtures developed in this study attained compressive strength values of more than 20.0 MPa and minimum flexural strength of 6.0 MPa within 6 h. Moreover, the HES-ECC mixtures exhibited strain-hardening behavior with strain capacities comparable to normal strength ECC, as well as substantially reduced autogenous shrinkage strain, both of which are unlikely to trigger the formation of cracks in tension at early ages. The integration of these conflicting parameters suggests that HES-ECC can easily meet the need for fast and durable repairs.Article Citation - WoS: 135Citation - Scopus: 157The Use of Ga-Anns in the Modelling of Compressive Strength of Cement Mortar(Elsevier Ltd., 2003) Akkurt, Sedat; Özdemir, Serhan; Tayfur, Gökmen; Akyol, BurakIn this paper, results of a project aimed at modelling the compressive strength of cement mortar under standard curing conditions are reported. Plant data were collected for 6 months for the chemical and physical properties of the cement that were used in model construction and testing. The training and testing data were separated from the complete original data set by the use of genetic algorithms (GAs). A GA-artificial neural network (ANN) model based on the training data of the cement strength was created. Testing of the model was also done within low average error levels (2.24%). The model was subjected to sensitivity analysis to predict the response of the system to different values of the factors affecting the strength. The plots obtained after sensitivity analysis indicated that increasing the amount of C3S, SO3 and surface area led to increased strength within the limits of the model. C2S decreased the strength whereas C3A decreased or increased the strength depending on the SO3 level. Because of the limited data range used for training, the prediction results were good only within the same range. The utility of the model is in the potential ability to control processing parameters to yield the desired strength levels and in providing information regarding the most favourable experimental conditions to obtain maximum compressive strength.