Modeling of Asphalt Mixture Behaviour at High Temperature

In this thesis various analyses and modeling of asphalt mixtures are represented. It is\ud composed of four main parts. In the first part we build up the database of individual\ud measurements of bituminous binder, aggregate and asphalt mixtures. These data are\ud analyzed using statistical methods which determine whether the effects of factors and their\ud interactions are statistically significant. In addition we have used artificial neural networks\ud for modeling relationship between different parameters and air voids content in asphalt\ud mixtures and voids content in a mixture of aggregate. In the second part of the study cyclic\ud triaxial tests and wheel tracking tests were performed to determine the resistance of asphalt\ud mixtures to permanent deformation at high temperatures. Furthermore other conventional\ud analyses of asphalt mixtures were performed to use them in different models. Experiments\ud were done for all principal asphalt mixtures to obtain an extensive model of asphalt\ud behaviour for mixtures which contain the most and the least air voids. Various linear\ud models, their validation and extensions to other asphalt mixtures are featured. The third\ud part deals with the use of different artificial neural networks for modeling permanent\ud deformation from triaxial tests. The last part presents the use of ultrasonic shear wave\ud reflection (USWR) method on bituminous binder. For the evaluation of this method three\ud paving grade bitumens and two polymer modified bitumens were tested. Differences in the\ud evolution of shear wave reflection coefficient with temperature in the case of different\ud bitumen types indicate that the presented ultrasonic wave reflection method could\ud represent an advanced non-destructive technique for monitoring the hardening process of\ud different types of bitumen

Statistical deviations in the analysis of asphalt mix properties

Glavni je cilj ovog istraživanja pronaći metodu kojom se određuju statistička odstupanja u analizama svojstava asfaltnih mješavina AC 22, koja ne nastaju slučajno, već su uzrokovana vanjskim faktorima poput promjene normi, laboratorijske opreme ili osoblja. Proveden je proračun kako bi se odredila odstupanja koeficijenata korelacije u svojstvima asfaltnih mješavina raspoređenih u dvije skupine. Skupine se odnose na dva vremenska razmaka, a proračun je ponovljen nasumičnim odabirom podataka unutar dviju skupina, kako bi se odredila odstupanja unutar skupina.The main purpose of this research is to establish a method for identifying statistical deviations in the analysis of properties of the asphalt mix AC 22, which are not accidental, but are caused by external factors, such as the change of standards, laboratory equipment, or staff. The analysis was made to determine deviation of correlation coefficients for properties of asphalt mixes divided into two groups. The groups are related to two time intervals, and the computation was repeated by random selection of data within the two groups, so as to determine deviations within the groups

Vpliv Modeling the behavior of asphalt mixtures at higher temperatures

V doktorski disertaciji se ukvarjamo z različnimi analizami in modeliranjem asfaltnih zmesi. Naloga je vsebinsko sestavljena iz štirih delov. V prvem delu pripravimo bazo podatkov, ki predstavljajo posamezne meritve bitumenskega veziva, agregata in asfaltne zmesi. Te podatke analiziramo s statističnimi metodami, s katerimi ugotovimo, ali so vplivi faktorjev in njihovih interakcij statistično značilni. Poleg tega z umetnimi nevronskimi mrežami modeliramo zveze med različnimi parametri in deležem votlin v asfaltni zmesi in deležem votlin v zmesi kamnitega materiala. V drugem delu naloge so bili za ugotavljanje odpornosti asfaltnih vzorcev proti nastanku trajnih deformacij pri visokih temperaturah izvedeni ciklični triosni preizkusi in klasični preizkusi nastajanja kolesnic. Za uporabo pri različnih modelih so bile izvedene tudi klasične analize asfaltnih zmesi. Testi so narejeni za štiri glavne asfaltne zmesi z namenom, da bi dobili grobi model obnašanja asfaltnih zmesi, ki vsebujejo največ in najmanj zračnih votlin. Predstavljeni so različni linearni modeli, njihova validacija in preizkus razširitve na druge asfaltne zmesi. Tretji del obravnava modeliranje trajne deformacije, dobljene iz triosnega testa, z različnimi umetnimi nevronskimi mrežami. V zadnjem delu pa je prikazana možnost uporabe nedestruktivne metode odboja strižnih ultrazvočnih valov, ki na področju bitumnov še ni bila uporabljena. Za ovrednotenje te preiskave so bili testirani trije cestogradbeni bitumni in dva s polimeri modificirana bitumna. Razlike v razvoju strižnega odbojnega koeficienta s temperaturo za različne tipe bitumnov kažejo na občutljivost strižnega odbojnega koeficienta na sestavo bitumna in s tem primernost ultrazvočne metode za ugotavljane utrjevanja različnih tipov bitumnov.In this thesis various analyses and modeling of asphalt mixtures are represented. It is composed of four main parts. In the first part we build up the database of individual measurements of bituminous binder, aggregate and asphalt mixtures. These data are analyzed using statistical methods which determine whether the effects of factors and their interactions are statistically significant. In addition we have used artificial neural networks for modeling relationship between different parameters and air voids content in asphalt mixtures and voids content in a mixture of aggregate. In the second part of the study cyclic triaxial tests and wheel tracking tests were performed to determine the resistance of asphalt mixtures to permanent deformation at high temperatures. Furthermore other conventional analyses of asphalt mixtures were performed to use them in different models. Experiments were done for all principal asphalt mixtures to obtain an extensive model of asphalt behaviour for mixtures which contain the most and the least air voids. Various linear models, their validation and extensions to other asphalt mixtures are featured. The third part deals with the use of different artificial neural networks for modeling permanent deformation from triaxial tests. The last part presents the use of ultrasonic shear wave reflection (USWR) method on bituminous binder. For the evaluation of this method three paving grade bitumens and two polymer modified bitumens were tested. Differences in the evolution of shear wave reflection coefficient with temperature in the case of different bitumen types indicate that the presented ultrasonic wave reflection method could represent an advanced non-destructive technique for monitoring the hardening process of different types of bitumen