Open AccessApplication of the Bayesian statistical approach to develop a Stone Mastic Asphalt (SMA) pavement performance model
Author(s) -
Alireza Joshaghani
Publication year - 2020
Publication title -
journal of architectural environment and structural engineering research
Language(s) - English
Resource type - Journals
ISSN - 2630-5232
DOI - 10.30564/jaeser.v2i4.1671
Subject(s) - sma* , asphalt , computer science , set (abstract data type) , service life , bayesian probability , performance prediction , field (mathematics) , engineering , reliability engineering , artificial intelligence , simulation , mathematics , algorithm , materials science , programming language , pure mathematics , composite material
Article history Received: 9 January 2020 Accepted: 21 March 2020 Published Online: 31 March 2020 Stone mastic asphalt (SMA) has not been widely used in the pavement industry, and there are no detailed design specifications for this type of asphalt. Therefore, long-term behavior properties of this pavement type are not accessible widely, and no model has been established for SMA regarding its performance. The main purpose of this study was to incorporate expert experience (using the Markov-chain process) and data from field experiments to propose a model for SMA performance using the Bayesian approach. The implementation of these sources resulted in a well-organized method to develop a performance model for SMA pavements, which did not have a long-term data. Finally, a linear performance model was established to calculate the SMA service life. The service life of SMA can be predicted explicitly according to the developed performance model which has been validated using a new set of data.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom