(588d) Alarm and Safety System Design Using Forward Flux Sampling

Safety and reliability events are of primary concern in the process and manufacturing industries, where safety issues can cause detrimental impacts on human health and environment due to extreme operating conditions, such as high temperatures and pressures and the presence of hazardous chemicals and materials. In the vicinities of unsafe operation, automated Safety Instrumented Systems (SIS) can shutdown plants, thereby avoiding related consequences. However, such measures can increase unreliability with production-time losses due to shutdowns, maintenance, and start-up delays. Moreover, they may disrupt routine procedures, adversely impacting human health and the environment. Hence, there is a strong motivation to develop strategies to avert unsafe operations more effectively.

Alarm management schemes are key to ensure the safety and reliability of manufacturing plants and processes. They aid in mitigating losses by ensuring that the concerned process variables remain within bounds of safe operation by triggering actionable alarms when these variables individually approach unsafe regions, following which, adequate steps are taken, either by safety systems, or operator interventions (Mehta and Reddy, 2015). Such alarm schemes effectively tackle commonly occurring ‘postulated’ events that lead to interlock activation, but often fail to predict the rare ‘un-postulated’ abnormal-event trajectories. Hence, the design of alarms to alert the occurrence of such rare trajectories can improve plant safety and reliability (Moskowitz et al., 2018).

In this research, novel, multivariable alarms and safety systems are introduced using process modeling and path-sampling for un-postulated abnormal events resulting from perturbations in one or more process variables. Forward-flux sampling (FFS), developed to discover rare molecular dynamics pathways, is applied (Allen et al., 2009). For a proportional P-controlled exothermic CSTR approximate process model with perturbed feed concentration, the FFS algorithm is applied to identify rare trajectories between high- and low-conversion steady states, with key process variables saved at various ‘crossing points’ (Sudarshan et al., 2021). Then, committer probabilities, p_B, are computed at each crossing point (Borrero and Escobedo, 2007), yielding a mathematical model that expresses p_B as a function of the key process variables; i.e., the reactor temperature, T, cooling-water flow-rate, F_C, and cooling-water temperature, T_C, identifying them as suitable choices for the primary alarm variables. Alarm thresholds, i.e., L-low, LL-low low, and ESD (emergency shutdown), are suggested by computing the critical ranges of the process variables, given the p_B ranges for every alarm threshold. Next, using alarm rationalization strategies, the acceptability of every alarm threshold is evaluated, with the alarm thresholds modified accordingly. Lastly, safety actions are suggested for each alarm threshold, assigning more aggressive safety actions for higher alarm priorities.

Keywords: Forward-flux Sampling, Committer Probabilities, Alarm Thresholds

References:

Allen, R.J., Valeriani, C., Rein Ten Wolde, P., 2009. Forward flux sampling for rare event simulations. Journal of Physics Condensed Matter 21

Borrero, E.E., Escobedo, F.A., 2007. Reaction coordinates and transition pathways of rare events via forward flux sampling. Journal of Chemical Physics 127

Mehta, B.R., Reddy, Y.J., 2015. Alarm management systems, in: Industrial Process Automation Systems

Moskowitz, I.H., Seider, W.D., Patel, A.J., Arbogast, J.E., Oktem, U.G., 2018. Understanding rare safety and reliability events using transition path sampling. Computers and Chemical Engineering

Sudarshan, V., Seider, W.D., Patel, A.J., Arbogast, J.E., 2021. Understanding rare safety and reliability events using forward-flux sampling. Computers and Chemical Engineering 153