The assumptions, scope and achievements of a probabilistic dynamics th
eory based on a Chapman-Kolmogorov formulation of mixed probabilistic
and deterministic dynamics are reviewed. The formulation of the theory
involves both physical (or process) variables and (semi-) Markovian s
tates of the system under study allowing the inclusion of human error
modelling. The problem of crossing a safety threshold is used to empha
size the role of timing in concurrent sequences. We show how the adjoi
nt formulation can be used to obtain information on the outcomes of tr
ansients as a function of its starting characteristics. These outcomes
may, for instance, be damage resulting from safety boundary crossing,
or reliability functions. A comparison is made between a Monte-Carlo
solution and a DYLAM analysis of a simple multicomponent benchmark pro
blem which shows that for the same accuracy a Monte-Carlo method is mu
ch less sensitive to the size of the problem. (C) 1996 Elsevier Scienc
e Limited.