Rancor-HUNTER - data collection and virtual operator modeling tool

Historically, human reliability analysis (HRA) methods require analysts to develop static models of human error within a predetermined human failure event through expert estimation. Objective quantitative models of human performance in the form of a virtual operator offer an avenue to perform dynamic HRA through Monte Carlo simulation. Idaho National Laboratory developed the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) as a dynamic HRA framework and has demonstrated success in modeling existing scenarios. More data is needed to create generalizable virtual human models to explore undefined human failure event space. The Rancor Microworld Simulator is a simplified nuclear process control simulator that students can easily train to use and that can be modified to support the development of concepts of operation for advanced reactors. Rancor-HUNTER fills the data collection niche by integrating the Rancor Microworld Simulator with the HUNTER software. Rancor automates human performance data collection with a digital procedure system compatible with HUNTER’s procedure database through their integration. This digital procedure system provides implicit task level goals associated with each step that affords automatic HRA coded data collection. Therefore, high-resolution sequences of operator behaviors can now be automatically recorded with error rates and time distributions, which collectively represent a virtual human. A thermal power dispatch concept of operations development use case highlights benefits of Rancor-HUNTER to augment human factors evaluation through automated human performance data collection, which can then be used to also inform HRA models.

Authors

Publication Details

Journal
AHFE international
Published
2025-01-01
DOI
https://doi.org/10.54941/ahfe1006287
Primary Topic
Advanced Data Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Rancor-HUNTER - data collection and virtual operator modeling tool

Olugbenga Gideon, Ji-Suk Kim, Thomas Ulrich, Kelly Dickerson et al.
AHFE international
Advanced Data Processing Techniques
article

Rancor-HUNTER - data collection and virtual operator modeling tool

Olugbenga Gideon, Ji-Suk Kim, Thomas Ulrich, Kelly Dickerson, Ronald L. Boring, Roger Lew, Dylan Jurski
article en

Abstract

Historically, human reliability analysis (HRA) methods require analysts to develop static models of human error within a predetermined human failure event through expert estimation. Objective quantitative models of human performance in the form of a virtual operator offer an avenue to perform dynamic HRA through Monte Carlo simulation. Idaho National Laboratory developed the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) as a dynamic HRA framework and has demonstrated success in modeling existing scenarios. More data is needed to create generalizable virtual human models to explore undefined human failure event space. The Rancor Microworld Simulator is a simplified nuclear process control simulator that students can easily train to use and that can be modified to support the development of concepts of operation for advanced reactors. Rancor-HUNTER fills the data collection niche by integrating the Rancor Microworld Simulator with the HUNTER software. Rancor automates human performance data collection with a digital procedure system compatible with HUNTER’s procedure database through their integration. This digital procedure system provides implicit task level goals associated with each step that affords automatic HRA coded data collection. Therefore, high-resolution sequences of operator behaviors can now be automatically recorded with error rates and time distributions, which collectively represent a virtual human. A thermal power dispatch concept of operations development use case highlights benefits of Rancor-HUNTER to augment human factors evaluation through automated human performance data collection, which can then be used to also inform HRA models.

AHFE internationalVol. 173
Openalex Percentile: Top 83%
Advanced Data Processing Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.