A simple probabilistic numerical model was used to construct synthetic D_e distributions by combining the simulated OSL from grains of different sensitivities and with various simulated D_e values. This is useful for exploring the complex patterns generated by summing the signals from many grains in real, multiple grain OSL dating scenarios, and demonstrates that the form of the sensitivity distribution has a significant effect on the identification of mixed dose populations in multiple grain single aliquot methods. I describe the simple numerical model and its implementation. I present measured quartz single grain OSL sensitivity distributions for an aeolian dune sample from the Simpson Desert, Northern Territory, Australia, and from a suite of 9 fluvial sediments from Namadgi National Park, Australian Capital Territory, Australia, to illustrate effects that result from natural differences. Minimum age model determinations of synthetic D_e values are used to assess the validity of dose values estimated from multiple grain single aliquot measurements.