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Stacey Langfitt Hendrickson
Researcher at Sandia National Laboratories
Publications - 18
Citations - 150
Stacey Langfitt Hendrickson is an academic researcher from Sandia National Laboratories. The author has contributed to research in topics: Human reliability & Brainstorming. The author has an hindex of 5, co-authored 18 publications receiving 137 citations.
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Issues in Benchmarking Human Reliability Analysis Methods: A Literature Review
TL;DR: A literature review was conducted, reviewing past benchmarking studies in the areas of psychology and risk assessment, and a number of lessons learned is presented in order to aid in the design of future HRA benchmarking endeavors.
Journal Article
EPRI/NRC-RES Fire Human Reliability Analysis Guidelines
John A. Forester,Susan E. Cooper,Kendra Hill,Jeffrey A. Julius,Jan Grobbelaar,Kaydee Kohlhepp,G. William Hannaman,Bijan Najafi,Erin Collins,Stacey Langfitt Hendrickson +9 more
TL;DR: This document provides a methodology and guidance for conducting a fire HRA, which includes identification and definition of post-fire human failure events, qualitative analysis, quantification, recovery, dependency, and uncertainty, and three approaches to quantification: screening, scoping, and detailed HRA.
Journal ArticleDOI
Improving extreme-scale problem solving: assessing electronic brainstorming effectiveness in an industrial setting.
TL;DR: The data indicate that work-relevant challenges are better solved by aggregating electronic individual responses rather than by electronically convening a group, and large nominal groups may be more appropriate corporate problem-solving vehicles.
A Mid-Layer Model for Human Reliability Analysis: Understanding the Cognitive Causes of Human Failure Events
Song-Hua Shen,James Y. H. Chang,Ronald L. Boring,April M. Whaley,Erasmia Lois,Stacey Langfitt Hendrickson,Johanna Oxstrand,John A. Forester,Dana Kelly,Ali Mosleh +9 more
TL;DR: In this article, the authors present a draft of the method's middle layer, a part of the qualitative analysis phase that links failure mechanisms to performance shaping factors, and identify potential failure mechanisms using the mid-layer model.