2016
DOI: 10.1504/ijvd.2016.074421
|View full text |Cite
|
Sign up to set email alerts
|

Modelling roughness of road profiles on parallel tracks using roughness indicators

Abstract: The vertical road input is the most important load for durability assessments of vehicles. We focus on stochastic modelling of the parallel road profiles with the aim to find a simple but still accurate model for such bivariate records. A model is proposed that is locally Gaussian with randomly gamma distributed variances leading to a generalized Laplace distribution of the road profile. This Laplace model is paired with the ISO spectrum and is specified by only three parameters. Two of them can be estimated d… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
22
0
1

Year Published

2016
2016
2024
2024

Publication Types

Select...
6

Relationship

2
4

Authors

Journals

citations
Cited by 30 publications
(24 citation statements)
references
References 29 publications
0
22
0
1
Order By: Relevance
“…In (Bogsjö et al, 2012) it was shown that replacing Gaussian noise by Laplace noise √ R k X k produces a more accurate model of roughness. In this paper we summarize principles of Laplace distribution modelling that arise from work in (Åberg et al, 2009;Bogsjö et al, 2012) and its extensions and applications presented in (Johannesson & Rychlik, 2013, 2014Kvanström et al, 2013;Johannesson et al, 2015a;Kozubowski et al, 2013).…”
Section: Roughnessmentioning
confidence: 99%
See 4 more Smart Citations
“…In (Bogsjö et al, 2012) it was shown that replacing Gaussian noise by Laplace noise √ R k X k produces a more accurate model of roughness. In this paper we summarize principles of Laplace distribution modelling that arise from work in (Åberg et al, 2009;Bogsjö et al, 2012) and its extensions and applications presented in (Johannesson & Rychlik, 2013, 2014Kvanström et al, 2013;Johannesson et al, 2015a;Kozubowski et al, 2013).…”
Section: Roughnessmentioning
confidence: 99%
“…Clearly, two-tracks data are strongly correlated, particularly in the regions of high roughness of the roads. Here we give extensions of the Laplace models to multiple correlated signals to cover the case of road profiles along parallel tracks, see (Kozubowski et al, 2013;Johannesson et al, 2015a).…”
Section: Multi-dimensional Loadsmentioning
confidence: 99%
See 3 more Smart Citations