Process reliability and safety under uncertainties

Uncertainties in the initial conditions and parameters of process systems can lead to large variations in the predicted system performance, sometimes with catastrophic consequences. For systems with non-linear dynamics, often the only generally applicable approach to assess the impact of these uncertainties on system performance is a search through the operation and parameter range of interest by direct integration of the system equations. A methodology is presented that can be used to assess process reliability and safety under such uncertainties much faster than direct integration. The methodology extends the capabilities of a previously developed discrete state transition modeling approach to include capability for the determination of initial conditions that lead to desirable system operation. Implementation of the methodology on an example system taken from nuclear reactor dynamics shows that: a) the methodology can handle both small and large uncertainties in system parameters and initial conditions, and b) fast conventional approaches such as perturbation analysis may lead to the choice of more restrictive or narrower operational ranges for the system than that required by reliability/safety considerations.