Pär Johannesson: Rainflow cycles for random loads with
                 Markov regime.


Rainflow cycles are often used in fatigue of materials
for describing the variability of applied loads. Therefore,
an important characteristic of a load process is the
intensity of rainflow cycles, the expected rainflow matrix.
In this work methods are developed for computation of the
expected rainflow matrix for random loads, especially loads
where the stochastic properties change over time, due to
changes of the system dynamics. For a vehicle the change of
properties could reflect different driving conditions. A
switching process with Markov regime, also called a hidden
Markov model, is used to describe the random load. This means
that the properties of the random load change according to a
hidden (not observed) Markov chain.

An algorithm for computation of the expected rainflow matrix
is developed for a switching load process where each
subprocess is modelled by a Markov chain. Since, only the
local extremes, also called turning points, are of importance
for rainflow analysis, another useful approach is to model the
sequence of turning points by a Markov chain. The main result
of this work is an algorithm for computation of the expected
rainflow matrix for a switching load process where each
subprocess is described by a Markov chain of turning points.
The algorithms are illustrated by several numerical examples,
including analysis of measurements of truck loads.