# Advancing Inverse Sensitivity/Uncertainty Methods for Nuclear Fuel Cycle Applications

## Abstract

The inverse sensitivity/uncertainty quantification (IS/UQ) method has recently been implemented in the Inverse Sensitivity/UnceRtainty Estimator (INSURE) module of the AMPX cross section processing system [M.E. Dunn and N.M. Greene, “AMPX-2000: A Cross-Section Processing System for Generating Nuclear Data for Criticality Safety Applications,” Trans. Am. Nucl. Soc. 86, 118–119 (2002)]. The IS/UQ method aims to quantify and prioritize the cross section measurements along with uncertainties needed to yield a given nuclear application(s) target response uncertainty, and doing this at a minimum cost. Since in some cases the extant uncertainties of the differential cross section data are already near the limits of the present-day state-of-the-art measurements, requiring significantly smaller uncertainties may be unrealistic. Therefore, we have incorporated integral benchmark experiments (IBEs) data into the IS/UQ method using the generalized linear least-squares method, and have implemented it in the INSURE module. We show how the IS/UQ method could be applied to systematic and statistical uncertainties in a self-consistent way and how it could be used to optimize uncertainties of IBEs and differential cross section data simultaneously. We itemize contributions to the cost of differential data measurements needed to define a realistic cost function.

- Authors:

- Reactor and Nuclear Systems Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6171 (United States)
- Department of Nuclear Engineering, North Carolina State University, Raleigh, NC 27695-7909 (United States)

- Publication Date:

- OSTI Identifier:
- 22436757

- Resource Type:
- Journal Article

- Resource Relation:
- Journal Name: Nuclear Data Sheets; Journal Volume: 123; Conference: International workshop on nuclear data covariances, Santa Fe, NM (United States), 28 Apr - 1 May 2014; Other Information: Copyright (c) 2014 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA)

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 73 NUCLEAR PHYSICS AND RADIATION PHYSICS; BENCHMARKS; DIFFERENTIAL CROSS SECTIONS; FUEL CYCLE; LEAST SQUARE FIT; NUCLEAR FUELS; REACTOR SAFETY; STATISTICAL MODELS

### Citation Formats

```
Arbanas, G., E-mail: arbanasg@ornl.gov, Williams, M.L., Leal, L.C., Dunn, M.E., Khuwaileh, B.A., Wang, C., and Abdel-Khalik, H.
```*Advancing Inverse Sensitivity/Uncertainty Methods for Nuclear Fuel Cycle Applications*. United States: N. p., 2015.
Web. doi:10.1016/J.NDS.2014.12.009.

```
Arbanas, G., E-mail: arbanasg@ornl.gov, Williams, M.L., Leal, L.C., Dunn, M.E., Khuwaileh, B.A., Wang, C., & Abdel-Khalik, H.
```*Advancing Inverse Sensitivity/Uncertainty Methods for Nuclear Fuel Cycle Applications*. United States. doi:10.1016/J.NDS.2014.12.009.

```
Arbanas, G., E-mail: arbanasg@ornl.gov, Williams, M.L., Leal, L.C., Dunn, M.E., Khuwaileh, B.A., Wang, C., and Abdel-Khalik, H. Thu .
"Advancing Inverse Sensitivity/Uncertainty Methods for Nuclear Fuel Cycle Applications". United States.
doi:10.1016/J.NDS.2014.12.009.
```

```
@article{osti_22436757,
```

title = {Advancing Inverse Sensitivity/Uncertainty Methods for Nuclear Fuel Cycle Applications},

author = {Arbanas, G., E-mail: arbanasg@ornl.gov and Williams, M.L. and Leal, L.C. and Dunn, M.E. and Khuwaileh, B.A. and Wang, C. and Abdel-Khalik, H.},

abstractNote = {The inverse sensitivity/uncertainty quantification (IS/UQ) method has recently been implemented in the Inverse Sensitivity/UnceRtainty Estimator (INSURE) module of the AMPX cross section processing system [M.E. Dunn and N.M. Greene, “AMPX-2000: A Cross-Section Processing System for Generating Nuclear Data for Criticality Safety Applications,” Trans. Am. Nucl. Soc. 86, 118–119 (2002)]. The IS/UQ method aims to quantify and prioritize the cross section measurements along with uncertainties needed to yield a given nuclear application(s) target response uncertainty, and doing this at a minimum cost. Since in some cases the extant uncertainties of the differential cross section data are already near the limits of the present-day state-of-the-art measurements, requiring significantly smaller uncertainties may be unrealistic. Therefore, we have incorporated integral benchmark experiments (IBEs) data into the IS/UQ method using the generalized linear least-squares method, and have implemented it in the INSURE module. We show how the IS/UQ method could be applied to systematic and statistical uncertainties in a self-consistent way and how it could be used to optimize uncertainties of IBEs and differential cross section data simultaneously. We itemize contributions to the cost of differential data measurements needed to define a realistic cost function.},

doi = {10.1016/J.NDS.2014.12.009},

journal = {Nuclear Data Sheets},

number = ,

volume = 123,

place = {United States},

year = {Thu Jan 15 00:00:00 EST 2015},

month = {Thu Jan 15 00:00:00 EST 2015}

}