A holistic investigation of complexity sources in nuclear power plant control rooms

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, September 2011."July 2011." Cataloged from PDF version of thesis.Includes bibliographical references (p. 99-104).The nuclear power community in the United States is moving to modernize aging power plant control rooms as well as develop control rooms for new reactors. New generation control rooms, along with modernized control rooms, will rely more heavily on automation and computerized procedures. Of particular importance to the Nuclear Regulatory Commission (NRC) is the impact such modernizations or new technologies will have upon operator performance and reliability in these safety-critical control room environments. One specific area of interest is the effect that various complexities in the control room have on operator performance and reliability. This research identifies various definitions of complexity and characterizes complexity in the nuclear power plant (NPP) domain, focusing on the common complexity dimensions of number, variety, and interconnections. Based on this characterization of complexity, a comprehensive list of complexity sources within the NPP control room is presented, along with a novel approach to describe complexity source interconnections. Understanding the sources of complexity in advanced NPP control rooms and the associated effects on human reliability is critical for ensuring safe performance of both operators and the entire system. However, most of the previous approaches in investigating complexity typically focus on either objective or subjective views of complexity, and a systematic approach that considers both views is missing from previous approaches. This research provides a novel methodology to assess the sources of complexity in NPP control rooms both objectively and subjectively while understanding the difference between the two and introduces a systems theoretic descriptive model of these sources of complexity, leveraging network theory. Finally a method is introduced to investigate the differences between the complexity views of different groups of NPP stakeholders. Incident report databases and in particular, 22 nuclear incidents in the Human Event Repository and Analysis (HERA) database were parsed to find objective evidence for the identified sources. Using this evidence-based approach, some of the potential interactions between these sources could be captured. A network called "Complexity Source Network" (CSN) was created for each incident in HERA to present the sources (nodes) and potential interactions between them (links). An ensemble of networks was developed consisting of 22 CSNs, one for each of the incidents in HERA. A tool called CXViz was developed to visualize and analyze the CSNs. Using the aggregate network (22 CSNs combined) the most common sources and interactions were identified. The complexity views of three groups of stakeholders, namely Operators, Designers and NRC Reviewers, were collected using a survey tool called CXSurvey. Using this tool, the interviewees were asked to rate the identified sources of perceived complexity and to rank the top five in terms of contribution to perceived complexity. Data gathered from 16 operators, 8 designers and 3 NRC reviewers were collected and the top five sources identified by each group were compared to the top five most supported sources from the 22 incidents in HERA. The results show large variations between the subjective views of the operators and designers and the objective top five. In addition, the subjective source rating of the three groups of stakeholders were compared. The results show large variations between the complexity views between the stakeholders on some controversial sources such as boredom, and training.by Farzan Sasangohar.S.M

Improving Interruption Recovery in Human-Supervisory Control (HSC)

Interruptions have negative effects on the task performance in modern work environments. These negative effects are not affordable in tasks in which decisions are time-critical and have a life-critical nature. Human-supervisory control (HSC) tasks in time-critical settings such as mission command and control and emergency response are especially vulnerable to the negative effects of interruptions since supervisors in these settings are prone to frequent interruptions which are valuable source of information and hence cannot be ignored and consequences of a wrong decision in these settings is very costly because of their life-critical nature. To address this issue, this thesis investigates an activity-centric design approach that aims to help team supervisors in a complex mission control operation to remain aware of the activities that most likely would affect their decisions, while minimizing disruption. An interruption recovery assistant (IRA) tool was designed to promote activity and situation awareness of a team of UAV operators in a representative task. Initial pilot studies showed a positive trend in effectiveness of the IRA tool on recovery time and decision accuracy. This thesis explores alternative design approaches to validate the effectiveness of an interruption recovery tool that enable mission commanders rapidly and effectively regain the situational awareness after an interruption occurs in the mission environment. This thesis overview these design approaches and present results from a series of formative evaluations of our prototype designs. These evaluations were conducted in an experimental platform designed to emulate futuristic semi-autonomous UAV team mission operations

Conceptualizing Multiagency Emergency Management System as Joint Cognitive System

PresentationEmergency management system (EMS) provides a crucial barrier for the protection of socio-ecological infrastructure from man-made disasters and natural threats. To meet diverse demands from hazardous events, resilience engineering is considered as an effective approach to enhance the performance of EMS. While conceptual and qualitative descriptions of resilience are abundant, ideas of operationalizing resilience are scarce. In this regard, the present work redefines resilience in the EMS and proposes a framework of measuring resilience by abstracting the EMS as a joint cognitive system

Evaluating Mental Stress Among College Students Using Heart Rate and Hand Acceleration Data Collected from Wearable Sensors

Stress is various mental health disorders including depression and anxiety among college students. Early stress diagnosis and intervention may lower the risk of developing mental illnesses. We examined a machine learning-based method for identification of stress using data collected in a naturalistic study utilizing self-reported stress as ground truth as well as physiological data such as heart rate and hand acceleration. The study involved 54 college students from a large campus who used wearable wrist-worn sensors and a mobile health (mHealth) application continuously for 40 days. The app gathered physiological data including heart rate and hand acceleration at one hertz frequency. The application also enabled users to self-report stress by tapping on the watch face, resulting in a time-stamped record of the self-reported stress. We created, evaluated, and analyzed machine learning algorithms for identifying stress episodes among college students using heart rate and accelerometer data. The XGBoost method was the most reliable model with an AUC of 0.64 and an accuracy of 84.5%. The standard deviation of hand acceleration, standard deviation of heart rate, and the minimum heart rate were the most important features for stress detection. This evidence may support the efficacy of identifying patterns in physiological reaction to stress using smartwatch sensors and may inform the design of future tools for real-time detection of stress

Analyzing Procedure Performance using Abstraction Hierarchy: Implications of Designing Procedures for High-risk Process Operations

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Mapping complexity sources in nuclear power plant domains

Understanding the sources of complexity in advanced Nuclear Power Plant (NPP) control rooms and their effects on human reliability is critical for ensuring safe performance of both operators and the entire system. New generation control rooms will rely more heavily on automation and computerized Human-System Interfaces (HSI). Without proper management, information representation and required operator-system interaction could challenge operator information processing capabilities. This paper provides an initial step in assessing the sources of complexity in the NPP control rooms and introduces a systems-theoretic descriptive model of these sources of complexity leveraging network theory.U.S. Nuclear Regulatory Commissio

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Remote patient monitoring (RPM) technologies have been identified as a viable alternative to improve access to care in underserved communities. Successful RPM platforms are designed and implemented for seamless integration into healthcare providers work to increase adoption and availability for offering remote care. A quantitative survey was designed and administered to elicit perspectives from a wide range of stakeholders, including healthcare providers and healthcare administrators, about barriers and facilitators in the adoption and integration of RPM into clinical workflows in underserved areas. Ease of adoption, workflow disruption, changes in the patient-physician relationship, and costs and financial benefits are identified as relevant factors that influence the widespread use of RPM by healthcare providers; significant communication and other implementation preferences also emerged. Further research is needed to identify methods to address such concerns and use information collected in this study to develop protocols for RPM integration into clinical workflow

Team Cognition for Coordinated Decision-Making during Hurricane Harvey: A Case Study from Interviews with Responding Commanders

PresentationTo protect and assist threatened populations and infrastructures in response to natural and man- made disasters, emergency responders from diverse backgrounds collectively work as ad hoc teams. However, responders’ coordinated decision-making in real-time has not been adequately addressed in terms of team cognition. Here team cognition is a binding mechanism that produces coordinated behaviors among responders (adapted from Fiore & Salas, 2004). We are particularly interested in cognition of an incident management team (IMT), an ad hoc strategic decision-making team of command-level responders co-located at the incident command post of major incidents such as Hurricane Harvey. To develop and provide an incident action plan to subordinate branch directors in the field, an IMT continuously manages information based on incoming cues from outside, following a cyclical planning process. Interestingly, an IMT is a team of functional sub-teams, and each sub-team is also a team of functional units. The purpose of this on-going case study is to investigate the role of team cognition for coordinated real-time decision-making in emergency response, through a case study of a recent disaster, Hurricane Harvey. During the interviews with subject matter experts (SMEs, i.e., responding commanders worked during Hurricane Harvey), we asked how responding commanders as a cognitive system-of-systems (or a team-of-teams) continuously made coordinated decisions, especially in terms of communication and information management. In a prior work, a P∙D∙A (Perceive∙Diagnose∙Adapt) model, a theoretical interactionist model of team cognition in emergency response, was proposed as a proof-of-concept that depicts nonlinear, interdependent, and dynamic interactions observed within and among three functional sub-teams of a planning team of an IMT at a simulated incident command post (Moon, Son, Sasangohar, Peres, & Neville, 2018). Through interviews with SMEs, this case study is expected to validate the P∙D∙A model

Spectral Analysis of Hand Tremors induced during a Fatigue Test

In this paper, we analyze various kinds of hand tremors in the time and frequency domain, that are induced by performing a set of hand actions. We collected the tremor data using a simple, wearable accelerometer from 15 healthy individuals that had varying levels of athleticism. The overall results presented here show that the physiologic tremors in range of 8-14 Hz are most noticeable under fatigue

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Severe hypoglycemia leverages complication in diabetes patients: e.g., it increases death rate by a six-fold. Therefore, early detection and prediction of hypoglycemic events are of utmost importance. This publication presents a prototype of a wearable hand-tremor system that detects the onset of hypoglycemic events. The results show the prototype is capable of simulating anticipated frequency and amplitude of the tremor relevant for hypoglycemic events. The initial functional performance-tests demonstrate a maximum error of 4.75% in the detecting the tremor frequency