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Periodica Polytechnica Civil Engineering
Article . 2015 . Peer-reviewed
Data sources: Crossref
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Modelling Marshall Design Test Results of Polypropylene Modified Asphalt by Genetic Programming Techniques

Authors: Tapkın, Serkan; Çevik, Abdükadir; Uşar, Ün; Kurtoğlu, Ahmet;

Modelling Marshall Design Test Results of Polypropylene Modified Asphalt by Genetic Programming Techniques

Abstract

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 and flow tests were carried out on specimens fabricated with dierent type of polypropylene fibers. It has been shown that addition of polypropylene fibers improved Marshall stabilities and Marshall quotient values in a considerable manner. Input variables in the developed genetic programming model use the physical properties of standard Marshall specimens such as polypropylene type, polypropylene percentage, bitumen percentage, specimen height, calculated unit weight, voids in mineral aggregate, voids filled with asphalt and air voids. Performance of the genetic programming model is quite satisfactory. Besides, to obtain main eects plot, a wide range of parametric studies have been performed. The presented closed form solution will also help further researchers willing to perform similar studies, without carrying out destructive tests.

Country
Turkey
Keywords

Polypropylene Fibers, Genetic Programming, Marshall Design, Asphalt, Closed Form Solutions

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Top 10%
Average
Green
gold