Dynamic event tree analysis with the SAS4A/SASSYS-1 safety analysis code

A Dynamic Bayesian Network Structure for Joint Diagnostics and Prognostics of Complex Engineering Systems

“…In order to show how such a DBN structure can be used to provide joint prognostics and diagnostic capabilities aimed at assessing CES health and their potential failures following an accident event, the remainder of this paper will present a sample DBN for modeling and monitoring an SFR reactor in a transient overpower event. This case study is a simplified exercise conducted by Groth et al [1] with the data modifications made by Jankovsky et al [24]. This section will begin with a description of both the SFR and the TOP scenario that the model is designed to monitor.…”

“…Such an event can be caused by external factors, e.g., an earthquake, that result in a sudden surge of power generation in the reactor. When such an event occurs, the reactor's automatic scram mechanism is expected to respond by inserting control rods into the reactor to greatly reduce power generation; common indicators for the automatic scram mechanism include large power-to-flow readings, as well as high values of reactor pressure, inlet, and outlet temperature [24]. Depending on the cause of the accident, however, scram functions may be impacted, limiting their ability to prevent core reactions from further escalating.…”

“…The accident data used in this case study is from the study by Jankovsky et al [24]. In their report, a series of accident event scenarios were constructed using a dynamic event tree that addressed potential failure points in response to the TOP.…”

“…The following abbreviations are used in this manuscript: CES The data used in this case study are the result of simulations run by Jankovsky et al [24] using the SAS4A/SASSYS-1 and PRIMAR4 models as part of a project to develop methodologies for merging dynamic event trees (DETs) with operator actions. The dynamic event tree was designed to "investigate the effects of various mitigating actions and uncertain plant parameters in an SFR following an inadvertent insertion of reactivity".…”

“…Overview Figure A1 is the illustration of the DBN model nodes and directed relationships within their respective information regions. This network structure was determined by a general understanding of the nature of the scramming mechanism and the two described failure modes in the study by Jankovsky, et al [24]. Table A1 lists the nodes constructed in the model, the information region they are located in, and the number and the value of node states.…”