Donald D. Dudenhoeffer
Idaho National Laboratory
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Featured researches published by Donald D. Dudenhoeffer.
winter simulation conference | 2006
Donald D. Dudenhoeffer; May R. Permann; Milos Manic
Todays society relies greatly upon an array of complex national and international infrastructure networks, such as transportation, utilities, telecommunication, and even financial networks. While modeling and simulation tools have provided insight into the behavior of individual infrastructure networks, a far less understood area is that of the interrelationships among multiple infrastructure networks including the potential cascading effects that may result due to these interdependencies. This paper first describes infrastructure interdependencies, as well as presenting a formalization of interdependency types. Next the paper describes a modeling and simulation framework called CIMScopy and the work that is being conducted at the Idaho National Laboratory (INL) to model and simulate infrastructure interdependencies and the complex behaviors that can result
2007 IEEE 8th Human Factors and Power Plants and HPRCT 13th Annual Meeting | 2007
Tuan Q. Tran; Ronald L. Boring; Donald D. Dudenhoeffer; Bruce P. Hallbert; M.David Keller; Tessa M. Anderson
We propose using non-obtrusive physiological assessment (e.g., eye tracking,) to assess human information processing errors (e.g., loss of vigilance) and limitations (e.g., workload) for advanced energy systems early in the design process. This physiological approach for assessing risk will circumvent many limitations of current risk methodologies such as subjective rating (e.g., rater’s biases) and performance modeling (e.g., risk assessment is scripted and is based upon the individual modeler’s judgment). Key uses will be to evaluate (early in the design process) novel control room equipment and configurations as well as newly developed automated systems that will inevitably place a high information load on operators. The physiological risk assessment tool will allow better precision in pinpointing problematic design issues and will provide a “real-time” assessment of risk. Furthermore, this physiological approach would extend the state-of-the-art of human reliability methods from a “static” measure to more “dynamic.” This paper will discuss a broad range of the current popular online performance gauges as well as its advantages and disadvantages for use in next generation control room.
human factors in computing systems | 2005
Ronald L. Boring; Jacques Hugo; Christian Richard; Donald D. Dudenhoeffer
The purpose of this CHI Special Interest Group (SIG) is to facilitate the convergence between human-computer interaction (HCI) and control room design. HCI researchers and practitioners actively need to infuse state-of-the-art interface technology into control rooms to meet usability, safety, and regulatory requirements. This SIG outlines potential HCI contributions to instrumentation and control (I&C) and automation in control rooms as well as to general control room design.
2007 IEEE 8th Human Factors and Power Plants and HPRCT 13th Annual Meeting | 2007
Tuan Q. Tran; David I. Gertman; Donald D. Dudenhoeffer; Ronald L. Boring; alan mecham
3D manikins are often used in visualizations to model human activity in complex settings. Manikins assist in developing understanding of the range, scope and timing of various human activities. They are applicable to a wide range of environments.. One such environment,, the nuclear power plant control room, is a setting where manikins can 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, is insufficient for dealing with the technical advancements and performance demands associated with proposed next generation control rooms. 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. One approach to managing design uncertainty is 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 conduct next generation control room human factors and ergonomic assessments. Though this discussion primary focuses on control room design, merging 3D visualization and cognitive modeling can be extended to various areas of focus such as training and scenario planning.
Volume 3: Thermal Hydraulics; Instrumentation and Controls | 2008
Don W. Miller; Steven A. Arndt; Leonard J. Bond; Donald D. Dudenhoeffer; Bruce P. Hallbert; David Eugene Holcomb; Richard Thomas Wood; Joseph A. Naser; John O’Hara; Edward L. Quinn
Instrumentation, controls, and human-machine interfaces are essential enabling technologies that strongly influence nuclear power plant performance and operational costs. The nuclear power industry is currently engaged in a transition from traditional analog-based instrumentation, controls, and human-machine interface (ICHMI) systems to implementations employing digital technologies. This transition has primarily occurred in an ad hoc fashion through individual system upgrades at existing plants and has been constrained by a number of concerns. Although international implementation of evolutionary nuclear power plants and the progression toward new plants in the United States have spurred design of more fully digital plantwide ICHMI systems, the experience base in the nuclear power application domain is limited. Additionally, design and development programs by the U.S. Department of Energy (DOE) for advanced reactor concepts, such as the Generation IV Program and Next Generation Nuclear Plant (NGNP), introduce different plant conditions and unique plant configurations that increase the need for enhanced ICHMI capabilities to fully achieve programmatic goals related to economic competitiveness, safety and reliability, sustainability, and proliferation resistance and physical protection. As a result, there are challenges that need to be addressed to enable the nuclear power industry to effectively and efficiently complete the transition to safe and comprehensive use of digital technology.Copyright
summer computer simulation conference | 2007
Donald D. Dudenhoeffer; May R. Permann; Steven Woolsey; Robert Timpany; Chuck Miller; Anthony McDermott; Milos Manic
International Workshop on Future Control Station Designs and Human Performance Issues in Nuclear Pow,to be completed later,05/12/2006,05/13/2006 | 2006
Ronald L. Boring; Donald D. Dudenhoeffer; Bruce P. Hallbert; Brian F. Gore
Archive | 2008
Don W. Miller; Steven A. Arndt; Donald D. Dudenhoeffer; Bruce P. Hallbert; Leonard J. Bond; David Eugene Holcomb; Richard Wood; Joseph A. Naser; John M. O'Hara; Edward L. Quinn
Archive | 2015
Charles Q. Miller; Allen D. Bierbaum; Donald D. Dudenhoeffer; Anthony McDermott; David M. Miller-Klugman
Workshop Meeting on Advanced Control-System Designs,Genova, Italy,08/31/2006,09/01/2006 | 2006
Donald D. Dudenhoeffer; Tuan Q. Tran; Ronald L. Boring; Bruce P. Hallbert