PHASER 2.10 methodology for dependence, importance, and sensitivity: The role of scale factors, confidence factors, and extremes
Abstract
PHASER (Probabilistic Hybrid Analytical System Evaluation Routine) is a software tool that has the capability of incorporating subjective expert judgment into probabilistic safety analysis (PSA) along with conventional data inputs. An earlier report described the PHASER methodology, but only gave a cursory explanation about how dependence was incorporated in Version 1.10 and about how ``Importance`` and ``Sensitivity`` measures were to be incorporated in Version 2.00. A more detailed description is given in this report. The basic concepts involve scale factors and confidence factors that are associated with the stochastic variability and subjective uncertainty (which are common adjuncts used in PSA), and the safety risk extremes that are crucial to safety assessment. These are all utilized to illustrate methodology for incorporating dependence among analysis variables in generating PSA results, and for Importance and Sensitivity measures associated with the results that help point out where any major sources of safety concern arise and where any major sources of uncertainty reside, respectively.
- Authors:
-
- Sandia National Labs., Albuquerque, NM (United States). System Studies Dept.
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE, Washington, DC (United States)
- OSTI Identifier:
- 392821
- Report Number(s):
- SAND-96-2304
ON: DE97000460; TRN: AHC29622%%57
- DOE Contract Number:
- AC04-94AL85000
- Resource Type:
- Technical Report
- Resource Relation:
- Other Information: PBD: Sep 1996
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; 42 ENGINEERING NOT INCLUDED IN OTHER CATEGORIES; SAFETY ANALYSIS; P CODES; EXPERT SYSTEMS; SCALING LAWS; STOCHASTIC PROCESSES; RISK ASSESSMENT; FAULT TREE ANALYSIS; FUZZY LOGIC
Citation Formats
Cooper, J A. PHASER 2.10 methodology for dependence, importance, and sensitivity: The role of scale factors, confidence factors, and extremes. United States: N. p., 1996.
Web. doi:10.2172/392821.
Cooper, J A. PHASER 2.10 methodology for dependence, importance, and sensitivity: The role of scale factors, confidence factors, and extremes. United States. https://doi.org/10.2172/392821
Cooper, J A. 1996.
"PHASER 2.10 methodology for dependence, importance, and sensitivity: The role of scale factors, confidence factors, and extremes". United States. https://doi.org/10.2172/392821. https://www.osti.gov/servlets/purl/392821.
@article{osti_392821,
title = {PHASER 2.10 methodology for dependence, importance, and sensitivity: The role of scale factors, confidence factors, and extremes},
author = {Cooper, J A},
abstractNote = {PHASER (Probabilistic Hybrid Analytical System Evaluation Routine) is a software tool that has the capability of incorporating subjective expert judgment into probabilistic safety analysis (PSA) along with conventional data inputs. An earlier report described the PHASER methodology, but only gave a cursory explanation about how dependence was incorporated in Version 1.10 and about how ``Importance`` and ``Sensitivity`` measures were to be incorporated in Version 2.00. A more detailed description is given in this report. The basic concepts involve scale factors and confidence factors that are associated with the stochastic variability and subjective uncertainty (which are common adjuncts used in PSA), and the safety risk extremes that are crucial to safety assessment. These are all utilized to illustrate methodology for incorporating dependence among analysis variables in generating PSA results, and for Importance and Sensitivity measures associated with the results that help point out where any major sources of safety concern arise and where any major sources of uncertainty reside, respectively.},
doi = {10.2172/392821},
url = {https://www.osti.gov/biblio/392821},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Sep 01 00:00:00 EDT 1996},
month = {Sun Sep 01 00:00:00 EDT 1996}
}