Interest in the sensitivity methods that were developed and widely used in the 1970s (the FORSS methodology at ORNL among others) has increased recently as a result of potential use in the area of criticality safety data validation procedures to define computational bias, uncertainties and area(s) of applicability. Functional forms of the resulting sensitivity coefficients can be used as formal parameters in the determination of applicability of benchmark experiments to their corresponding industrial application areas. In order for these techniques to be generally useful to the criticality safety practitioner, the procedures governing their use had to be updated and simplified. This paper will describe the resulting sensitivity analysis too...
Sensitivity and uncertainty methods have been developed to aid in the establishment of areas of appl...
The Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP) funded the development of a...
The solution of several operations research problems requires the creation of a quantitative model. ...
This paper presents the application of sensitivity and uncertainty (S/U) analysis methodologies to t...
Abstract – The theoretical basis for the application of sensitivity and uncertainty (S/U) analysis m...
The use of cross-section covariance data has long been a key part of traditional sensitivity and unc...
A system of statistically treating validation calculations for the purpose of determining computer c...
As computing power increases and data relating to elementary chemical and physical processes improve...
International audienceIn the framework of uncertainty treatment in numerical simulation, Global sens...
AbstractIn metrology, Monte-Carlo Methods are used to evaluate the measurement uncertainty whereas m...
A systematic approach has been developed to determine benchmark biases and apply those biases to cod...
This paper reviews the state of the art in five related types of analysis, namely (i) sensitivity or...
At the Oak Ridge National Laboratory (ORNL), sensitivity and uncertainty (S/U) analysis methods and ...
The objectives of this study on the application of statistical techniques to the analysis of reactor...
This report documents establishment of bias, bias trends and uncertainty for validation of the CSAS2...
Sensitivity and uncertainty methods have been developed to aid in the establishment of areas of appl...
The Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP) funded the development of a...
The solution of several operations research problems requires the creation of a quantitative model. ...
This paper presents the application of sensitivity and uncertainty (S/U) analysis methodologies to t...
Abstract – The theoretical basis for the application of sensitivity and uncertainty (S/U) analysis m...
The use of cross-section covariance data has long been a key part of traditional sensitivity and unc...
A system of statistically treating validation calculations for the purpose of determining computer c...
As computing power increases and data relating to elementary chemical and physical processes improve...
International audienceIn the framework of uncertainty treatment in numerical simulation, Global sens...
AbstractIn metrology, Monte-Carlo Methods are used to evaluate the measurement uncertainty whereas m...
A systematic approach has been developed to determine benchmark biases and apply those biases to cod...
This paper reviews the state of the art in five related types of analysis, namely (i) sensitivity or...
At the Oak Ridge National Laboratory (ORNL), sensitivity and uncertainty (S/U) analysis methods and ...
The objectives of this study on the application of statistical techniques to the analysis of reactor...
This report documents establishment of bias, bias trends and uncertainty for validation of the CSAS2...
Sensitivity and uncertainty methods have been developed to aid in the establishment of areas of appl...
The Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP) funded the development of a...
The solution of several operations research problems requires the creation of a quantitative model. ...