Monte Carlo simulations of the fracture resistance degradation of asphalt concrete subjected to environmental factors
 
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1
Gdansk University of Technology, Faculty of Civil and Environmental Engineering, Department of Highway and Transportation Engineering, 11/12 Gabriela Narutowicza Street, 80-233 Gdansk, Poland
 
2
Gdansk University of Technology, Faculty of Civil and Environmental Engineering, Department of Structural Mechanics, 11/12 Gabriela Narutowicza Street, 80-233 Gdansk, Poland
 
 
Submission date: 2022-07-04
 
 
Acceptance date: 2022-08-05
 
 
Publication date: 2023-04-03
 
 
Archives of Civil Engineering 2023;1(1):245-257
 
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ABSTRACT
The paper presents the results of laboratory tests of SCB (semi-circular beam) samples of asphalt concrete, subjected to the destructive effect of water and frost as well as the aging processes. The determined values of material parameters show significant dispersions, which makes the design of mixtures difficult. Statistical analysis of the test results supplemented by computer simulations made with the use of the proprietary FEM model was carried out. The main distinguishing feature of the model is the assignment of material parameters of coarse aggregate and bituminous mortar to randomly selected finite elements. The parameters of the mortar are selected by trial and error to match the numerical results to the experimental ones. The stiffness modulus of the bituminous mortar is, therefore, a substitute parameter, taking into account the influence of many factors, including material degradation resulting from the aging and changing environmental conditions, the influence of voids, and contact between the aggregate and the bituminous mortar. The use of the Monte Carlo method allows to reflect the scattering of the results obtained based on laboratory tests. The computational algorithm created in the ABAQUS was limited only to the analysis of the global mechanical bending response of the SCB sample, without mapping the failure process in detail. The combination of the results of laboratory tests usually carried out on a limited number of samples and numerical simulations provide a sufficiently large population of data to carry out a reliable statistical analysis, and to estimate the reliability of the material designed.
eISSN:2300-3103
ISSN:1230-2945
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