Simulations of large-scale physical systems are often affected by the uncertainties in data, in model parameters, and by incomplete knowledge of the underlying physics. The traditional deterministic simulations do not account for such uncertainties. It is of interest to extend simulation results with “error bars” that quantify the degree of uncertainty. This added information provides a confide...

We analyze the ignition delay in hydrogen-oxygen combustion, and the important chain branching reaction H + O2 → OH + O that occurs behind the shock waves in shock-tube experiments. We apply a stochastic Bayesian approach (Beck et al., 1998 and Cheung et al., 2009) to quantify uncertainties in the theoretical model and experimental data. The approach involves a statistical inverse problem which...

Activity networks model the time to project completion based on the times to complete various subtasks, some of which can proceed concurrently and others of which are prerequisite to others. Uncertainty in the times to complete subtasks implies uncertainty in the overall time to complete the project. When the information about the times to complete subtasks is insufficient to fully specify a pr...

Simulation is nowadays a major tool in R&D and engineering studies. In industrial practice, in both design and operating stages, the behavior of a complex system is described and forecast by a computer model, which is, most of time, deterministic. Yet, engineers coping with quantitative predictions using deterministic models deal actually with several sources of uncertainties affecting the inpu...