Yazar "Goekalp, Islam" seçeneğine göre listele

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    Öğe
    Relationship Between Abrasion, Fragmentation and Thermal Weathering Resistance of Aggregates: Regression and Artificial Neural Network Analyses
    (Springernature, 2023) Goekalp, Islam; Kaya, Orhan; Uz, Volkan Emre
    For being used in pavement construction, properties of aggregates must satisfy the minimum requirements specified by highway agencies or institutions. The properties of the aggregates are determined by many tests lasting anywhere between a couple of hours to a few weeks depending on the type of the test. If good correlations can be established between the tests taking longer time and the ones taking comparably shorter time, there might be no need to conduct these longer time-taking tests for the sake of time. The aim of this study is to investigate the relationships between abrasion, fragmentation, and thermal weathering resistances of different aggregate types. To accomplish this aim, aggregates with different origins (natural and slags) were tested and correlative analyses utilizing regression analysis and artificial neural network (ANN) models were performed to establish relationships between the results of these test methods. It was found that good correlations can be established especially with ANN models and significant amount of time and effort can be saved with these developed models.
  • [ X ]
    Öğe
    Relationship Between Abrasion, Fragmentation and Thermal Weathering Resistance of Aggregates: Regression and Artificial Neural Network Analyses
    (Springernature, 2023) Goekalp, Islam; Kaya, Orhan; Uz, Volkan Emre
    For being used in pavement construction, properties of aggregates must satisfy the minimum requirements specified by highway agencies or institutions. The properties of the aggregates are determined by many tests lasting anywhere between a couple of hours to a few weeks depending on the type of the test. If good correlations can be established between the tests taking longer time and the ones taking comparably shorter time, there might be no need to conduct these longer time-taking tests for the sake of time. The aim of this study is to investigate the relationships between abrasion, fragmentation, and thermal weathering resistances of different aggregate types. To accomplish this aim, aggregates with different origins (natural and slags) were tested and correlative analyses utilizing regression analysis and artificial neural network (ANN) models were performed to establish relationships between the results of these test methods. It was found that good correlations can be established especially with ANN models and significant amount of time and effort can be saved with these developed models.