This invited presentation summarizes new methodologies developed by the author for performing high-order sensitivity analysis, uncertainty quantification and predictive modeling. The presentation commences by summarizing the newly developed 3rd-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for linear systems, which overcomes the “curse of dimensionality” for sensitivity analysis and uncertainty quantification of a large variety of model responses of interest in reactor physics systems. The use of the exact expressions of the 2nd-, and 3rd-order sensitivities computed using the 3rd-ASAM is subsequently illustrated by presenting 3rd-order formulas for the first three cumulants of the response distribution, for quantifying response...
A novel procedure for the estimating the response sensitivity to input parameters of a complex FE mo...
The topic of this paper is the development of sensitivity and uncertainty analysis capability to the...
This work presents a perspective on deterministic predictive modeling methodologies, which aim at ex...
This invited presentation summarizes new methodologies developed by the author for performing high-o...
This work presents the Third-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for response-...
This work presents the Third-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for response-...
This work aims at underscoring the need for the accurate quantification of the sensitivities (i.e., ...
In this paper, the sensitivity analysis of a single scale model is employed in order to reduce the i...
This paper illustrates the relative importance of the largest first- and second-order sensitivities ...
This work illustrates the application of the nth-order comprehensive adjoint sensitivity analysis me...
In this paper, a new non-intrusive method for the propagation of uncertainty and sensitivity analysi...
Uncertainties associated with estimates of model parameters are inevitable when simulating and model...
An adaptive high dimensional model representation (HDMR) is used to decompose the response parameter...
Verification and validation (V&V) are playing more important roles to quantify uncertainties and...
Code Scaling, Applicability, and Uncertainty (CSAU) methodology was developed in late 1980s by US NR...
A novel procedure for the estimating the response sensitivity to input parameters of a complex FE mo...
The topic of this paper is the development of sensitivity and uncertainty analysis capability to the...
This work presents a perspective on deterministic predictive modeling methodologies, which aim at ex...
This invited presentation summarizes new methodologies developed by the author for performing high-o...
This work presents the Third-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for response-...
This work presents the Third-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for response-...
This work aims at underscoring the need for the accurate quantification of the sensitivities (i.e., ...
In this paper, the sensitivity analysis of a single scale model is employed in order to reduce the i...
This paper illustrates the relative importance of the largest first- and second-order sensitivities ...
This work illustrates the application of the nth-order comprehensive adjoint sensitivity analysis me...
In this paper, a new non-intrusive method for the propagation of uncertainty and sensitivity analysi...
Uncertainties associated with estimates of model parameters are inevitable when simulating and model...
An adaptive high dimensional model representation (HDMR) is used to decompose the response parameter...
Verification and validation (V&V) are playing more important roles to quantify uncertainties and...
Code Scaling, Applicability, and Uncertainty (CSAU) methodology was developed in late 1980s by US NR...
A novel procedure for the estimating the response sensitivity to input parameters of a complex FE mo...
The topic of this paper is the development of sensitivity and uncertainty analysis capability to the...
This work presents a perspective on deterministic predictive modeling methodologies, which aim at ex...