[en] This paper introduces a novel augmentation to the current heuristic usability evaluation methodology. The SPAR-H human reliability analysis method was developed for categorizing human performance in nuclear power plants. Despite the specialized use of SPAR-H for safety critical scenarios, the method also holds promise for use in commercial off-the-shelf software usability evaluations. The SPAR-H method shares task analysis underpinnings with human-computer interaction, and it can be easily adapted to incorporate usability heuristics as performance shaping factors. By assigning probabilistic modifiers to heuristics, it is possible to arrive at the usability error probability (UEP). This UEP is not a literal probability of error but nonetheless provides a quantitative basis to heuristic evaluation. When combined with a consequence matrix for usability errors, this method affords ready prioritization of usability issues

[en] This paper describes a cognitively based human reliability analysis (HRA) quantification technique for estimating the human error probabilities (HEPs) associated with operator and crew actions at nuclear power plants. The method described here, Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method, was developed to aid in characterizing and quantifying human performance at nuclear power plants. The intent was to develop a defensible method that would consider all factors that may influence performance. In the SPAR-H approach, calculation of HEP rates is especially straightforward, starting with pre-defined nominal error rates for cognitive vs. action-oriented tasks, and incorporating performance shaping factor multipliers upon those nominal error rates

[en] An ongoing issue within human-computer interaction (HCI) is the need for simplified or ''discount'' methods. The current economic slowdown has necessitated innovative methods that are results driven and cost effective. The myriad methods of design and usability are currently being cost-justified, and new techniques are actively being explored that meet current budgets and needs. Recent efforts in human reliability analysis (HRA) are highlighted by the ten-year development of the Standardized Plant Analysis Risk HRA (SPAR-H) method. The SPAR-H method has been used primarily for determining human centered risk at nuclear power plants. The SPAR-H method, however, shares task analysis underpinnings with HCI. Despite this methodological overlap, there is currently no HRA approach deployed in heuristic usability evaluation. This paper presents an extension of the existing SPAR-H method to be used as part of heuristic usability evaluation in HCI

[en] This paper summarizes an emerging collaboration between Idaho National Laboratory and NASA Ames Research Center regarding the utilization of high-fidelity MIDAS simulations for modeling control room crew performance at nuclear power plants. The key envisioned uses for MIDAS-based control room simulations are: (1) the estimation of human error with novel control room equipment and configurations, (2) the investigative determination of risk significance in recreating past event scenarios involving control room operating crews, and (3) the certification of novel staffing levels in control rooms. It is proposed that MIDAS serves as a key component for the effective modeling of risk in next generation control rooms

[en] This paper summarizes an emerging project regarding the utilization of high-fidelity MIDAS simulations for visualizing and modeling control room crew performance at nuclear power plants. The key envisioned uses for MIDAS-based control room simulations are: (1) the estimation of human error associated with advanced control room equipment and configurations, (2) the investigative determination of contributory cognitive factors for risk significant scenarios involving control room operating crews, and (3) the certification of reduced staffing levels in advanced control rooms. It is proposed that MIDAS serves as a key component for the effective modeling of cognition, elements of situation awareness, and risk associated with human performance in next generation control rooms

[en] This report describes a simplified, tractable, and usable procedure within the US Nuclear Regulator Commission (NRC) for seeking expert opinion and judgment. The NRC has increased efforts to document the reliability and risk of nuclear power plants (NPPs) through Probabilistic Risk Assessment (PRA) and Human Reliability Analysis (HRA) models. The Significance Determination Process (SDP) and Accident Sequence Precursor (ASP) programs at the NRC utilize expert judgment on the probability of failure, human error, and the operability of equipment in cases where otherwise insufficient operational data exist to make meaningful estimates. In the past, the SDP and ASP programs informally sought the opinion of experts inside and outside the NRC. This document represents a formal, documented procedure to take the place of informal expert elicitation. The procedures outlined in this report follow existing formal expert elicitation methodologies, but are streamlined as appropriate to the degree of accuracy required and the schedule for producing SDP and ASP analyses

[en] 3D manikins are often used in visualizations to model human activity in complex settings. Manikins assist in developing understanding of human actions, movements and routines in a variety of different environments representing new conceptual designs. One such environment is a nuclear power plant control room, here they have the potential to be used to simulate more precise ergonomic assessments of human work stations. Next generation control rooms will pose numerous challenges for system designers. The manikin modeling approach by itself, however, may be insufficient for dealing with the desired technical advancements and challenges of next generation automated systems. Uncertainty regarding effective staffing levels; and the potential for negative human performance consequences in the presence of advanced automated systems (e.g., reduced vigilance, poor situation awareness, mistrust or blind faith in automation, higher information load and increased complexity) call for further research. Baseline assessment of novel control room equipment(s) and configurations needs to be conducted. These design uncertainties can be reduced through complementary analysis that merges ergonomic manikin models with models of higher cognitive functions, such as attention, memory, decision-making, and problem-solving. This paper will discuss recent advancements in merging a theoretical-driven cognitive modeling framework within a 3D visualization modeling tool to evaluate of next generation control room human factors and ergonomic assessment. Though this discussion primary focuses on control room design, the application for such a merger between 3D visualization and cognitive modeling can be extended to various areas of focus such as training and scenario planning