Yazar "Çevik, Abdükadir" için listeleme
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Accumulated strain prediction of polypropylene modified marshall specimens in repeated creep test using artificial neural networks
Tapkın, Serkan; Çevik, Abdükadir; Uşar, Ün (Pergamon-Elsevier Science LTD, 2009)This study presents an application of artificial neural networks (ANN) for the prediction of repeated creep test results for polypropylene (PP) modified asphalt mixtures. Polypropylene fibers are used to modify the bituminous ... -
Modelling Marshall Design Test Results of Polypropylene Modified Asphalt by Genetic Programming Techniques
Tapkın, Serkan; Çevik, Abdükadir; Uşar, Ün; Kurtoğlu, Ahmet (Budapest University Technology Economics, 2015)Determining Marshall design test results is time consuming. If the researchers can obtain stability and flow values by mechanical testing, rest of the calculations will just be mathematical manipulations. Marshall stability ... -
Prediction of Marshall test results for polypropylene modified dense bituminous mixtures using neural networks
Tapkın, Serkan; Çevik, Abdükadir; Uşar, Ün (Pergamon-Elsevier Science LTD, 2010)This study presents an application of neural networks (NN) for the prediction of Marshall test results for polypropylene (PP) modified asphalt mixtures. PP fibers are used to modify the bituminous binder in order to improve ... -
Prediction of rutting potential of dense bituminous mixtures with polypropylene fibers via repeated creep testing by using neuro-fuzzy approach
Tapkın, Serkan; Çevik, Abdükadir; Uşar, Ün (Budapest University Technology Economics, 2012)This study investigates the potential use of the neuro-fuzzy (NF) approach to model the rutting prediction by the aid of repeated creep testing results for polypropylene modified asphalt mixtures. Marshall specimens, ... -
Rutting Prediction of Asphalt Mixtures Modified by Polypropylene Fibers via Repeated Creep Testing by Utilising Genetic Programming
Tapkın, Serkan; Çevik, Abdükadir; Uşar, Ün; gülsan, Eren (University Fed Sao Carlos, Dept Engenharia Materials, 2013)A novel application of genetic programming (GP) for modelling and presenting closed form solutions to the rutting prediction for polypropylene (PP) modified asphalt mixtures is investigated. Various PP fibers have been ... -
Utilising Neural Networks and Closed Form Solutions to Determine Static Creep Behaviour and Optimal Polypropylene Amount in Bituminous Mixtures
Tapkın, Serkan; Çevik, Abdükadir; Özcan, Şenol (University Fed Sao Carlos, Dept Engenharia Materials, 2012)The testing procedure in order to determine the precise mechanical testing results in Marshall design is very time consuming. Also, the physical properties of the asphalt samples are obtained by further calculations. ...
