Mesh-free shakedown analysis of cohesive-frictional pavement under moving traffic loads: deterministic and probabilistic frameworks
A mesh-free limit analysis approach has been modified and extended to comprise the problem of shakedown analysis of pavements. In this novel study, both deterministic and probabilistic frameworks are presented. Deterministic modelling is undertaken by the combination of Melan’s shakedown theorem, Shepard’s mesh-free technique and linear programming. A probabilistic framework is also introduced to incorporate soil’s shear strength inherent heterogeneity into the mesh-free shakedown analysis. In this context, the covariance matrix decomposition technique is used to generate the random fields of cohesion and friction angle. Thereafter, analyses have been conducted by employing Monte Carlo simulations which invoke mesh-free shakedown analysis several times. At the end of the paper, as an application of stochastic modelling, the probability of failure has been presented as a function of safety factor to quantify the geotechnical risks of pavement’s design from shakedown concept viewpoint.
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/14680629
-
Supplemental Notes:
- © 2018 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
-
Authors:
- Rahmani, R
- Binesh, S M
- Publication Date: 2020-5
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 1096-1134
-
Serial:
- Road Materials and Pavement Design
- Volume: 21
- Issue Number: 4
- Publisher: Taylor & Francis
- ISSN: 1468-0629
- EISSN: 2164-7402
- Serial URL: http://www.tandfonline.com/loi/trmp20
Subject/Index Terms
- TRT Terms: Cohesion; Failure; Friction; Linear programming; Live loads; Monte Carlo method; Pavement design; Probability; Shakedown tests; Stochastic programming
- Subject Areas: Design; Highways; Pavements;
Filing Info
- Accession Number: 01742141
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 9 2020 10:41AM