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Title: FOQUS: A framework for organizational and quantification of uncertainty

Publication Date:
Research Org.:
National Energy Technology Lab. (NETL), Pittsburgh, PA, and Morgantown, WV (United States). In-house Research; National Energy Technology Lab. (NETL), Pittsburgh, PA, and Morgantown, WV (United States)
Sponsoring Org.:
USDOE Office of Fossil Energy (FE)
OSTI Identifier:
Report Number(s):
Resource Type:
Resource Relation:
Conference: AspenTech OPTIMIZE 2015 Conference, Westin Waterfront Hotel, Boston, MA, May 4-6, 2015
Country of Publication:
United States

Citation Formats

Miller, David C. FOQUS: A framework for organizational and quantification of uncertainty. United States: N. p., 2015. Web.
Miller, David C. FOQUS: A framework for organizational and quantification of uncertainty. United States.
Miller, David C. 2015. "FOQUS: A framework for organizational and quantification of uncertainty". United States. doi:.
title = {FOQUS: A framework for organizational and quantification of uncertainty},
author = {Miller, David C.},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2015,
month = 1

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  • Methods for developing Phenomenological Identification and Ranking Tables (PIRT) for nuclear power plants have been a useful tool in providing insight into modelling aspects that are important to safety. These methods have involved expert knowledge with regards to reactor plant transients and thermal-hydraulic codes to identify are of highest importance. Quantified PIRT provides for rigorous method for quantifying the phenomena that can have the greatest impact. The transients that are evaluated and the timing of those events are typically developed in collaboration with the Probabilistic Risk Analysis. Though quite effective in evaluating risk, traditional PRA methods lack the capability tomore » evaluate complex dynamic systems where end states may vary as a function of transition time from physical state to physical state . Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. A limitation of DPRA is its potential for state or combinatorial explosion that grows as a function of the number of components; as well as, the sampling of transition times from state-to-state of the entire system. This paper presents a method for performing QPIRT within a dynamic event tree framework such that timing events which result in the highest probabilities of failure are captured and a QPIRT is performed simultaneously while performing a discrete dynamic event tree evaluation. The resulting simulation results in a formal QPIRT for each end state. The use of dynamic event trees results in state explosion as the number of possible component states increases. This paper utilizes a branch and bound algorithm to optimize the solution of the dynamic event trees. The paper summarizes the methods used to implement the branch-and-bound algorithm in solving the discrete dynamic event trees.« less
  • Abstract not provided.
  • Post hoc analyses have demonstrated clearly that macro-system, organizational processes have played important roles in such major catastrophes as Three Mile Island, Bhopal, Exxon Valdez, Chernobyl, and Piper Alpha. How can managers of such high-consequence organizations as nuclear power plants and nuclear explosives handling facilities be sure that similar macro-system processes are not operating in their plants? To date, macro-system effects have not been integrated into risk assessments. Part of the reason for not using macro-system analyses to assess risk may be the impression that standard organizational measurement tools do not provide hard data that can be managed effectively. Inmore » this paper, I argue that organizational dimensions, like those in ISO 9000, can be quantified and integrated into standard risk assessments.« less
  • Tools, methods, and theories for assessing and quantifying uncertainties vary by application. Uncertainty quantification tasks have unique desiderata and circumstances. To realistically assess uncertainty requires the engineer/scientist to specify mathematical models, the physical phenomena of interest, and the theory or framework for assessments. For example, Probabilistic Risk Assessment (PRA) specifically identifies uncertainties using probability theory, and therefore, PRA's lack formal procedures for quantifying uncertainties that are not probabilistic. The Phenomena Identification and Ranking Technique (PIRT) proceeds by ranking phenomena using scoring criteria that results in linguistic descriptors, such as importance ranked with words, 'High/Medium/Low.' The use of words allows PIRTmore » to be flexible, but the analysis may then be difficult to combine with other uncertainty theories. We propose that a necessary step for the development of a procedure or protocol for uncertainty quantification (UQ) is the application of an Uncertainty Inventory. An Uncertainty Inventory should be considered and performed in the earliest stages of UQ.« less
  • Abstract not provided.