A Multi-Methods Approach to HRA and Human Performance Modeling: A Field Assessment

The Advanced Test Reactor (ATR) is a research reactor at the Idaho National Laboratory is primarily designed and used to test materials to be used in other, larger-scale and prototype reactors. The reactor offers various specialized systems and allows certain experiments to be run at their own temperature and pressure. The ATR Canal temporarily stores completed experiments and used fuel. It also has facilities to conduct underwater operations such as experiment examination or removal. In reviewing the ATR safety basis, a number of concerns were identified involving the ATR canal. A brief study identified ergonomic issues involving the manual handling of fuel elements in the canal that may increase the probability of human error and possible unwanted acute physical outcomes to the operator. In response to this concern, that refined the previous HRA scoping analysis by determining the probability of the inadvertent exposure of a fuel element to the air during fuel movement and inspection was conducted. The HRA analysis employed the SPAR-H method and was supplemented by information gained from a detailed analysis of the fuel inspection and transfer tasks. This latter analysis included ergonomics, work cycles, task duration, and workload imposed by tool and workplace characteristics, personal protective clothing, and operational practices that have the potential to increase physical and mental workload. Part of this analysis consisted of NASA-TLX analyses, combined with operational sequence analysis, computational human performance analysis (CHPA), and 3D graphical modeling to determine task failures and precursors to such failures that have safety implications. Experience in applying multiple analysis techniques in support of HRA methods is discussed

FRamework Assessing Notorious Contributing Influences for Error (FRANCIE): Perspective on Taxonomy Development to Support Error Reporting and Analysis

Beginning in the 1980s a primary focus of human reliability analysis was estimation of human error probabilities. However, detailed qualitative modeling with comprehensive representation of contextual variables often was lacking. This was likely due to the lack of comprehensive error and performance shaping factor taxonomies, and the limited data available on observed error rates and their relationship to specific contextual variables. In the mid 90s Boeing, America West Airlines, NASA Ames Research Center and INEEL partnered in a NASA sponsored Advanced Concepts grant to: assess the state of the art in human error analysis, identify future needs for human error analysis, and develop an approach addressing these needs. Identified needs included the need for a method to identify and prioritize task and contextual characteristics affecting human reliability. Other needs identified included developing comprehensive taxonomies to support detailed qualitative modeling and to structure meaningful data collection efforts across domains. A result was the development of the FRamework Assessing Notorious Contributing Influences for Error (FRANCIE) with a taxonomy for airline maintenance tasks. The assignment of performance shaping factors to generic errors by experts proved to be valuable to qualitative modeling. Performance shaping factors and error types from such detailed approaches can be used to structure error reporting schemes. In a recent NASA Advanced Human Support Technology grant FRANCIE was refined, and two new taxonomies for use on space missions were developed. The development, sharing, and use of error taxonomies, and the refinement of approaches for increased fidelity of qualitative modeling is offered as a means to help direct useful data collection strategies

Advancing Usability Evaluation through Human Reliability Analysis

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

Human reliability analysis for computerized procedures, part two: Applicability of current methods

Computerized procedures (CPs) are an emerging technology within nuclear power plant control rooms. While CPs have been implemented internationally in advanced control rooms, to date no U.S. nuclear power plant has implemented CPs in its main control room. Yet, CPs are a reality of new plant builds and are an area of considerable interest to existing plants, which see advantages in terms of easier records management by omitting the need for updating hardcopy procedures. The overall intent of this paper is to provide a characterization of human reliability analysis (HRA) issues for computerized procedures. It is beyond the scope of this document to propose a new HRA approach or to recommend specific methods or refinements to those methods. Rather, this paper serves as a review of current HRA as it may be used for the analysis and review of computerized procedures

Culture Representation in Human Reliability Analysis

Understanding human-system response is critical to being able to plan and predict mission success in the modern battlespace. Commonly, human reliability analysis has been used to predict failures of human performance in complex, critical systems. However, most human reliability methods fail to take culture into account. This paper takes an easily understood state of the art human reliability analysis method and extends that method to account for the influence of culture, including acceptance of new technology, upon performance. The cultural parameters used to modify the human reliability analysis were determined from two standard industry approaches to cultural assessment: Hofstede’s (1991) cultural factors and Davis’ (1989) technology acceptance model (TAM). The result is called the Culture Adjustment Method (CAM). An example is presented that (1) reviews human reliability assessment with and without cultural attributes for a Supervisory Control and Data Acquisition (SCADA) system attack, (2) demonstrates how country specific information can be used to increase the realism of HRA modeling, and (3) discusses the differences in human error probability estimates arising from cultural differences

The Development of A Human Systems Simulation Laboratory: Strategic Direction

The Human System Simulation Laboratory (HSSL) at the Idaho National Laboratory is one of few facilities of its kind that allows human factors researchers to evaluate various aspects of human performance and human system interaction for proposed reactor designs and upgrades. A basic system architecture, physical configuration and simulation capability were established to enable human factors researchers to support multiple, simultaneous simulations and also different power plant technologies. Although still evolving in terms of its technical and functional architecture, the HSSL is already proving its worth in supporting current and future nuclear industry needs for light water reactor sustainability and small modular reactors. The evolution of the HSSL is focused on continual physical and functional refinement to make it a fully equipped, reconfigurable facility where advanced research, testing and validation studies can be conducted on a wider range of reactor technologies. This requires the implementation of additional plant models to produce empirical research data on human performance with emerging human-system interaction technologies. Additional beneficiaries of this information include system designers and HRA practitioners. To ensure that results of control room crew studies will be generalizable to the existing and evolving fleet of US reactors, future expansion of the HSSL may also include other SMR plant models, plant-specific simulators and a generic plant model aligned to the current generation of pressurized water reactors (PWRs) and future advanced reactor designs. Collaboration with industry partners is also proving to be a vital component of the facility as this helps to establish a formal basis for current and future human performance experiments to support nuclear industry objectives. A long-range Program Plan has been developed for the HSSL to ensure that the facility will support not only the Department of Energy’s Light Water Reactor Sustainability Program, but also to provide human factors guidance for all future developments of the nuclear industry

Draft Function Allocation Framework and Preliminary Technical Basis for Advanced SMR Concepts of Operations

This report presents preliminary research results from the investigation in to the development of new models and guidance for concepts of operations (ConOps) in advanced small modular reactor (aSMR) designs. In support of this objective, three important research areas were included: operating principles of multi-modular plants, functional allocation models and strategies that would affect the development of new, non-traditional concept of operations, and the requiremetns for human performance, based upon work domain analysis and current regulatory requirements. As part of the approach for this report, we outline potential functions, including the theoretical and operational foundations for the development of a new functional allocation model and the identification of specific regulatory requirements that will influence the development of future concept of operations. The report also highlights changes in research strategy prompted by confirmationof the importance of applying the work domain analysis methodology to a reference aSMR design. It is described how this methodology will enrich the findings from this phase of the project in the subsequent phases and help in identification of metrics and focused studies for the determination of human performance criteria that can be used to support the design process

How training and experience affect the benefits of autonomy in a dirty-bomb experiment

A dirty-bomb experiment conducted at the INL is used to evaluate the effectiveness and suitability of three different modes of robot control. The experiment uses three distinct user groups to understand how participants’ background and training affect the way in which they use and benefit from autonomy. The results show that the target mode, which involves automated mapping and plume tracing together with a point and click tasking tool, provides the best performance for each group. This is true for objective performance such as source detection and localization accuracy as well as subjective measures such as perceived workload, frustration and preference. The best overall performance is achieved by the Explosive Ordinance Disposal group which has experience in both robot teleoperation and dirty bomb response. The user group that benefits least from autonomy is the Nuclear Engineers that have no experience with either robot operation or dirty bomb response. The group that benefits most from autonomy is the Weapons of Mass Destruction Civil Response Team that has extensive experience related to the task, but no robot training

Development of Human Factors Guidance for Human-Sy

This report characterizes a range of advanced HS