Haven't a Cue? Mapping the CUE Space as an Aid to HRA Modeling

Advances in automation present a new modeling environment for the human reliability analysis (HRA) practitioner. Many, if not most, current day HRA methods have their origin in characterizing and quantifying human performance in analog environments where mode awareness and system status indications are potentially less comprehensive, but simpler to comprehend at a glance when compared to advanced presentation systems. The introduction of highly complex automation has the potential to lead to: decreased levels of situation awareness caused by the need for increased monitoring; confusion regarding the often non-obvious causes of automation failures, and emergent system dependencies that formerly may have been uncharacterized. Understanding the relation of incoming cues available to operators during plant upset conditions, in conjunction with operating procedures, yields insight into understanding the nature of the expected operator response in this control room environment. Static systems methods such as fault trees do not contain the appropriate temporal information or necessarily specify the relationship among cues leading to operator response. In this paper, we do not attempt to replace standard performance shaping factors commonly used in HRA nor offer a new HRA method, existing methods may suffice. In this paper we strive to enhance current understanding of the basis for operator response through a technique that can be used during the qualitative portion of the HRA analysis process. The CUE map is a means to visualize the relationship among salient cues in the control room that help influence operator response, show how the cognitive map of the operator changes as information is gained or lost, and is applicable to existing as well as advanced hybrid plants and small modular reactor designs. A brief application involving loss of condensate is presented and advantages and limitations of the modeling approach and use of the CUE map are discussed.