Preliminaries for probabilistic railway sleeper design
Licentiatavhandling, 2006
Two investigations are presented, which can be seen as
contributions to the aim of introducing a probabilistic design
strategy of railway sleepers in the future. When using
probabilistic design the statistics of all relevant parameters
considered as stochastic must be known. One such is the loading
environment of the railway sleeper that can best be seen as
stochastic. For example there is a variation of the sleeper
embedding both from site to site and in its distribution under
each sleeper. We plan to perform tests in order to collect
statistics of the latter. A pretest investigation including a
numerical method for obtaining the maximum allowed sensor spacing
for accurate sampling of this distribution is one of the
investigations presented in this work. The numerical method is
based on a hypothesis of equality between this sensor distance and
a critical correlation length of the embedding stiffness. Before
applying reliability analysis on the sleeper dynamics several
aspects must be considered. One such is efficiency of the analysis
method. The complexity, and thus efficiency, of the probabilistic
design method that is required is basically determined by the
properties of the performance function used for probability of
failure estimation. An investigation, including both factorial
design and one-factor-at-a time analyses, of the appearances of
performance functions related to sleeper bending moments as
functions of varying loading parameters is the second
investigation presented in this work.
sensor placement
factorial design
Railway sleeper
ballast
load variation
stochastic parameters
correlation length