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Experimental & computational study on fly ash and kaolin based synthetic lightweight aggregate
Süleyman İpek,Kasım Mermerdaş 사단법인 한국계산역학회 2020 Computers and Concrete, An International Journal Vol.26 No.4
The objective of this study is to manufacture environmentally-friendly synthetic lightweight aggregates that may be used in the structural lightweight concrete production. The cold-bonding pelletization process has been used in the agglomeration of the pozzolanic materials to achieve these synthetic lightweight aggregates. In this context, it was aimed to recycle the waste fly ash by employing it in the manufacturing process as the major cementitious component. According to the well-known facts reported in the literature, it is stated that the main disadvantage of the synthetic lightweight aggregate produced by applying the cold-bonding pelletization technique to the pozzolanic materials is that it has a lower strength in comparison with the natural aggregate. Therefore, in this study, the metakaolin made of high purity kaolin and calcined kaolin obtained from impure kaolin have been employed at particular contents in the synthetic lightweight aggregate manufacturing as a cementitious material to enhance the particle crushing strength. Additionally, to propose a curing condition for practical attempts, different curing conditions were designated and their influences on the characteristics of the synthetic lightweight aggregates were investigated. Three substantial features of the aggregates, specific gravity, water absorption capacity, and particle crushing strength, were measured at the end of 28-day adopted curing conditions. Observed that the incorporation of thermally treated kaolin significantly influenced the crushing strength and water absorption of the aggregates. The statistical evaluation indicated that the investigated properties of the synthetic lightweight aggregate were affected by the thermally treated kaolin content more than the kaoline type and curing regime. Utilizing the thermally treated kaolin in the synthetic aggregate manufacturing lead to a more than 40% increase in the crushing strength of the pellets in all curing regimes. Moreover, two numerical formulations having high estimation capacity have been developed to predict the crushing strength of such types of aggregates by using softcomputing techniques: gene expression programming and artificial neural networks. The R-squared values, indicating the estimation performance of the models, of approximately 0.97 and 0.98 were achieved for the numerical formulations generated by using gene expression programming and artificial neural networks techniques, respectively.
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Ultimate Capacity Prediction of Axially Loaded CFST Short Columns
Esra Mete Güneyisi,Ayşegül Gültekin,Kasım Mermerdaş 한국강구조학회 2016 International Journal of Steel Structures Vol.16 No.1
Composite columns have superior strength and ductility performance, and they have become more widely accepted in the engineering applications. However, the filled tubular columns require more attention. This study aims to present a new formulation for the axial load carrying capacity ( Nu ) of circular concrete filled steel tubular (CFST) short columns having various geometrical and material properties. Although there have been some empirical relations for predicting Nu in the literature, genetic algorithm based explicit formulation is not available. In the current study, 314 comprehensive experimental data samples presented in the previous studies were examined to prepare a data set for training and testing of the prediction model. The prediction parameters were selected as outer diameter of column (D), wall thickness ( t ), length of column ( L ), compressive strength of concrete ( fc ), and yield strength of steel ( fy ). The prediction model was obtained by means of gene expression programming (GEP). The proposed model was compared with available ones presented in the current design codes (ACI, Australian Standards, AISC, AIJ, Eurocode 4, DL/T, and CISC) and some existing empirical models proposed by researchers. The prediction performance of all models were also evaluated by the statistical parameters. The results indicated that the GEP model was much better than the available formulae, yielding higher correlation coefficient and lower error
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Prediction of the flexural overstrength factor for steel beams using artificial neural network
Esra Mete Güneyisi,Mario D’Aniello,Raffaele Landolfo,Kasım Mermerdaş 국제구조공학회 2014 Steel and Composite Structures, An International J Vol.17 No.3
The flexural behaviour of steel beams significantly affects the structural performance of the steel frame structures. In particular, the flexural overstrength (namely the ratio between the maximum bending moment and the plastic bending strength) that steel beams may experience is the key parameter affecting the seismic design of non-dissipative members in moment resisting frames. The aim of this study is to present a new formulation of flexural overstrength factor for steel beams by means of artificial neural network (NN). To achieve this purpose, a total of 141 experimental data samples from available literature have been collected in order to cover different cross-sectional typologies, namely I-H sections, rectangular and square hollow sections (RHS-SHS). Thus, two different data sets for I-H and RHS-SHS steel beams were formed. Nine critical prediction parameters were selected for the former while eight parameters were considered for the latter. These input variables used for the development of the prediction models are representative of the geometric properties of the sections, the mechanical properties of the material and the shear length of the steel beams. The prediction performance of the proposed NN model was also compared with the results obtained using an existing formulation derived from the gene expression modeling. The analysis of the results indicated that the proposed formulation provided a more reliable and accurate prediction capability of beam overstrength.
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Experimental investigation on durability performance of rubberized concrete
Guneyisi, Erhan,Gesoglu, Mehmet,Mermerdas, Kasim,Ipek, Suleyman Techno-Press 2014 Advances in concrete construction Vol.2 No.3
The study presented herein aims to investigate the durability related properties of rubberized concrete. Two types of waste scrap tire rubber were used as fine and coarse aggregate, respectively. The rubber was replaced with aggregate by three crumb rubber and tire chips levels of 5, 15, and 25% for the rubberized concrete productions. In order to improve the transport properties and corrosion resistance of rubberized concretes, SF was replaced with cement at 10% replacement level by weight of total binder content. The transport properties of the rubberized concretes were investigated through water absorption, gas permeability, and water permeability tests. The corrosion behavior of reinforcing bars embedded in plain and silica fume based rubberized concretes was investigated by linear polarization resistance (LPR) test. The results indicated that the utilization of SF in the rubberized concrete production enhanced the corrosion behavior and decreased corrosion current density values. Moreover, the reduction in the water and gas permeability coefficients was observed by the incorporation of SF in plain and especially rubberized concretes.
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