Mechanical Engineering / Makina Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/4129
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Article Doe and Ann Models for Powder Mixture Packing(American Ceramic Society, 2007) Akkurt, Sedat; Romagnoli, Marcello; Sütçü, MücahitDesign of experiments (DOE) and artificial neural network (ANN) techniques were used to study packing of fused alumina powders composed of three different sizes of particles. The first is the mixture design technique that produces a polynomial model of the powder-packing system. While, the ANN technique is extensively used to model complex systems in many fields. The methodological approach used is mixture design, which can be used to study the influences of two or more additives. It is a structured and organized method for determining the relationship between the components and the output of that process. The mixture design approach permits optimization of size distribution to obtain a target value of porosity. Sensitivity analysis involves the use of the developed ANN model to predict outputs (porosity) at varying levels of the input factor effects.Conference Object Citation - WoS: 4Citation - Scopus: 4Prediction of the Slag Corrosion of Mgo-C Ladle Refractories by the Use of Artificial Neural Networks(Trans Tech Publications, 2004) Akkurt, SedatA multilayer feed-forward back-propagation learning algorithm was employed as an artificial neural network (ANN) tool to create a model to predict the corrosion of MgO-C ladle refractory bricks based on laboratory slag corrosion test data. The corrosion process occurred by immersion of the rectangular refractory specimens in molten slag-steel bath. An ANN model to predict the amount of corrosion was created by using the training data. The model was also tested with experimentally measured data and relatively low error levels were achieved. This model was then used to predict the response of the slag-corrosion system to different values of the factors affecting the corrosion of bricks at high temperatures. Exposure time, exposure temperature of slag-brick contact and CaO/SiO2 ratio of the slag were the factors used for modelling. Model results provided the potential for selection of the best conditions for avoiding the factor combinations that may accelerate corrosion.