  We describe an adaptive Markov chain Monte Carlo method suitable for the
estimation of rare failure probabilities in complex probabilistic models. This
method, the Accelerated Weight Histogram (AWH) method, has its origin in
statistical physics (Lidmar, 2012) and has successfully been applied to
molecular dynamics simulations in biophysics. Here we introduce it in the
context of structural reliability and demonstrate its usefulness for
calculation of failure probabilities in some selected problems of varying
degrees of complexity and compare with other established techniques, e.g.,
subset simulations.
