The
distributed activation energy model (DAEM) is widely used in
chemical kinetics to statistically describe the occurrence of numerous
independent parallel reactions. In this article, we suggest a rethink
in the context of a Monte Carlo integral formulation to compute the
conversion rate at any time without approximation. After the basics
of the DAEM are introduced, the considered equations (under isothermal
and dynamic conditions) are respectively expressed into expected values,
which in turn are transcribed into Monte Carlo algorithms. To describe
the temperature dependence of reactions under dynamic conditions,
a new concept of null reaction, inspired from null-event Monte Carlo
algorithms, has been introduced. However, only the first-order case
is addressed for the dynamic mode due to strong nonlinearities. This
strategy is then applied to both analytical and experimental density
distribution functions of the activation energy. We show that the
Monte Carlo integral formulation is efficient in solving the DAEM
without approximation and that it is well-adapted due to the possibility
of using any experimental distribution function and any temperature
profile. Furthermore, this work is motivated by the need for coupling
chemical kinetics and heat transfer in a single Monte Carlo algorithm.