Abstract

Obtaining a representative loading spectrum that corresponds well to the reality is still one of the greatest challenges for fatigue life calculations and optimal design of the trailer body. A good qualitative and quantitative knowledge of the spectrum leads to more efficient usage of material, a better design of connection points and an overall decrease of the weight of the trailer, which finally results in a significant decrease in the price of a ton of cargo per km. Despite that, the approach is nowadays mostly based on the experience and rules of thumb. It typically results in over-dimensioning of some parts while other parts remain vulnerable to failure due to unknown loading patterns. This paper describes a generic approach to solve the problems mentioned above applied in a research project named FORWARD (Fuel Optimized trailer Referring to Well Assessed Realistic Design loads). The project lasted two years and was carried out in cooperation with several different trailer manufacturers and 1st tier suppliers. The loading history of more than 1000 hours for five trailer types were captured in the shape of strains, accelerations and velocities of various elements of the trailers, enabling reconstruction of the loading in terms of forces and moments acting on the wheels and kingpin. Parallel to this extensive test-campaign, a novel generic physics-based computational approach was developed to predict selected loads encountered during common manoeuvres to all trailer types. The computational approach was validated against test-data and resulted in creating a generic multibody library applicable for all trailer types, and an automated post-processing routine for the large amount of test-data. First Published Online: 16 Dec 2014

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The different versions of the original document can be found in:

http://dx.doi.org/10.3846/16484142.2014.982174
https://doaj.org/toc/1648-4142,
https://doaj.org/toc/1648-3480
https://trid.trb.org/view/1335751,
https://www.narcis.nl/publication/RecordID/oai%3Apure.tue.nl%3Apublications%2Fd1aa71bf-ff8c-473f-8781-467f32840865,
https://research.tue.nl/en/publications/determination-of-representative-loading-conditions-for-effective-,
https://www.tandfonline.com/doi/abs/10.3846/16484142.2014.982174,
https://core.ac.uk/display/158724497,
https://academic.microsoft.com/#/detail/2155366018
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Published on 01/01/2014

Volume 2014, 2014
DOI: 10.3846/16484142.2014.982174
Licence: Other

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