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PostprintThis is the accepted version of a paper published in Vehicle System Dynamics. This paper has been peer-reviewed but does not include the final publisher proof-corrections or journal pagination.Citation for the original published paper (version of record):Casanueva, C., Doulgerakis, E., Jönsson, P., Stichel, S. (2014) Influence of switches and crossings on wheel profile evolution in freight vehicles. Vehicle System Dynamics AbstractWheel reprofiling costs for freight vehicles are a major issue in Sweden, reducing the profitability of freight traffic operations and therefore hindering the modal shift needed for achieving reduced emissions. In order to understand the damage modes in freight vehicles, uniform wear prediction with Archard's wear law has been studied in a two axle timber transport wagon, and simulation results have been compared to measurements. Challenges of wheel wear prediction in freight wagons are discussed, including the influence of block brakes and switches and crossings. The latter have a major influence on the profile evolution of this case study, so specific simulations are performed and a thorough discussion is carried out.

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The main idea behind lattice sieving algorithms is to reduce a sufficiently large number of lattice vectors with each other so that a set of short enough vectors is obtained. It is therefore natural to study vectors which cannot be reduced. In this work we give a concrete definition of an irreducible vector and study the properties of the set of all such vectors. We show that the set of irreducible vectors is a subset of the set of Voronoi relevant vectors and study its properties. For extremal lattices this set may contain as many as $$2^n$$ 2 n vectors, which leads us to define the notion of a complete system of irreducible vectors, whose size can be upper-bounded by the kissing number. One of our main results shows that modified heuristic sieving algorithms heuristically approximate such a set (modulo sign). We provide experiments in low dimensions which support this theory. Finally we give some applications of this set in the study of lattice problems such as SVP, SIVP and CVPP. The introduced notions, as well as various results derived along the way, may provide further insights into lattice algorithms and motivate new research into understanding these algorithms better.