Advanced Graphite Creep Uncertainty Analysis Article Swipe
Jason Brookman
,
William E Windes
,
Jorge Giner Navarro
,
Vishal R. Patel
,
Thomas Holschuh
·
YOU?
·
· 2022
· Open Access
·
YOU?
·
· 2022
· Open Access
·
Radiation damage estimation is an important component of the post irradiation analysis of the Advanced Graphite Creep (AGC) experiment. It depends primarily on the fast fluence, which is determined using well established methods of spectral adjustment. These are based on best estimates from models such as Monte Carlo N-Particle (MCNP), input cross-sections, and measured activities from flux wires in the experiment. Each of these parameters can propagate uncertainties which will affect the uncertainty in the calculated dose levels for AGC, or any experiment irradiated within a reactor. While the methods of propagating uncertainty are well-established, the final uncertainty estimates they provide are only as good as the estimates of uncertainty in the inputs on which they are based. The purpose of this work is to outline some deficiencies in the ways these input uncertainties are presently estimated, and to outline a methodology by which they can be improved. The fast fluence and radiation damage received by graphite specimens irradiated in the Advanced Graphite Creep (AGC) experiments is presently estimated using spectral adjustment methods that are based on both flux wire activity measurements, and MCNP model predictions. This work describes an ongoing effort to quantify and propagate uncertainties in inputs to the spectral adjustment process, and thereby quantify the resultant error in radiation damage (dpa) estimates. The effort is multi-faceted, and we consider the impacts of both the set of flux wires selected, and the counting process. An expanded set of flux wires is identified that provides a more comprehensive data set on the fast spectrum. To address the counting process itself, a series of round-robin measurements in several reactor metrology laboratories across the Department of Energy (DOE) complex and nuclear industry are being undertaken to refine the American Society for Testing and Materials (ASTM) standards for flux wire measurements. To address the contribution of uncertainty in the MCNP model predictions, an uncertainty quantification (UQ) tool has been developed that statistically samples the model input parameters, runs a series of cases, and assimilates the results to provide an overall uncertainty. The impact of the MCNP UQ tool results is demonstrated by re-analyzing previous AGC flux wire and irradiation data. While the expanded flux wire set obviously cannot be added to these experiments retroactively, plans for future graphite irradiations are outlined.
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Metadata
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- Landing Page
- https://www.osti.gov/biblio/1906510
- https://www.osti.gov/biblio/1906510
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- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4312207504
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4312207504Canonical identifier for this work in OpenAlex
- Title
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Advanced Graphite Creep Uncertainty AnalysisWork title
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otherOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-12-26Full publication date if available
- Authors
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Jason Brookman, William E Windes, Jorge Giner Navarro, Vishal R. Patel, Thomas HolschuhList of authors in order
- Landing page
-
https://www.osti.gov/biblio/1906510Publisher landing page
- PDF URL
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https://www.osti.gov/biblio/1906510Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.osti.gov/biblio/1906510Direct OA link when available
- Concepts
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Creep, Graphite, Materials science, Composite materialTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.fluence, | 25 |
| abstract_inverted_index.graphite | 156, 375 |
| abstract_inverted_index.industry | 280 |
| abstract_inverted_index.measured | 53 |
| abstract_inverted_index.previous | 351 |
| abstract_inverted_index.process, | 203 |
| abstract_inverted_index.process. | 235 |
| abstract_inverted_index.provides | 245 |
| abstract_inverted_index.quantify | 193, 206 |
| abstract_inverted_index.reactor. | 86 |
| abstract_inverted_index.received | 154 |
| abstract_inverted_index.spectral | 34, 170, 201 |
| abstract_inverted_index.Materials | 292 |
| abstract_inverted_index.Radiation | 0 |
| abstract_inverted_index.component | 6 |
| abstract_inverted_index.describes | 188 |
| abstract_inverted_index.developed | 317 |
| abstract_inverted_index.estimated | 168 |
| abstract_inverted_index.estimates | 41, 98, 107 |
| abstract_inverted_index.important | 5 |
| abstract_inverted_index.improved. | 147 |
| abstract_inverted_index.metrology | 269 |
| abstract_inverted_index.obviously | 364 |
| abstract_inverted_index.outlined. | 378 |
| abstract_inverted_index.presently | 135, 167 |
| abstract_inverted_index.primarily | 21 |
| abstract_inverted_index.propagate | 66, 195 |
| abstract_inverted_index.radiation | 152, 211 |
| abstract_inverted_index.resultant | 208 |
| abstract_inverted_index.selected, | 231 |
| abstract_inverted_index.specimens | 157 |
| abstract_inverted_index.spectrum. | 254 |
| abstract_inverted_index.standards | 294 |
| abstract_inverted_index.Department | 273 |
| abstract_inverted_index.N-Particle | 48 |
| abstract_inverted_index.activities | 54 |
| abstract_inverted_index.adjustment | 171, 202 |
| abstract_inverted_index.calculated | 75 |
| abstract_inverted_index.determined | 28 |
| abstract_inverted_index.estimated, | 136 |
| abstract_inverted_index.estimates. | 214 |
| abstract_inverted_index.estimation | 2 |
| abstract_inverted_index.experiment | 82 |
| abstract_inverted_index.identified | 243 |
| abstract_inverted_index.irradiated | 83, 158 |
| abstract_inverted_index.parameters | 64 |
| abstract_inverted_index.undertaken | 283 |
| abstract_inverted_index.adjustment. | 35 |
| abstract_inverted_index.assimilates | 331 |
| abstract_inverted_index.established | 31 |
| abstract_inverted_index.experiment. | 18, 60 |
| abstract_inverted_index.experiments | 165, 370 |
| abstract_inverted_index.irradiation | 10, 356 |
| abstract_inverted_index.methodology | 141 |
| abstract_inverted_index.parameters, | 324 |
| abstract_inverted_index.propagating | 91 |
| abstract_inverted_index.round-robin | 264 |
| abstract_inverted_index.uncertainty | 72, 92, 97, 109, 304, 311 |
| abstract_inverted_index.contribution | 302 |
| abstract_inverted_index.deficiencies | 127 |
| abstract_inverted_index.demonstrated | 348 |
| abstract_inverted_index.irradiations | 376 |
| abstract_inverted_index.laboratories | 270 |
| abstract_inverted_index.measurements | 265 |
| abstract_inverted_index.predictions, | 309 |
| abstract_inverted_index.predictions. | 185 |
| abstract_inverted_index.re-analyzing | 350 |
| abstract_inverted_index.uncertainty. | 338 |
| abstract_inverted_index.comprehensive | 248 |
| abstract_inverted_index.measurements, | 181 |
| abstract_inverted_index.measurements. | 298 |
| abstract_inverted_index.statistically | 319 |
| abstract_inverted_index.uncertainties | 67, 133, 196 |
| abstract_inverted_index.multi-faceted, | 218 |
| abstract_inverted_index.quantification | 312 |
| abstract_inverted_index.retroactively, | 371 |
| abstract_inverted_index.cross-sections, | 51 |
| abstract_inverted_index.well-established, | 94 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/13 |
| sustainable_development_goals[0].score | 0.550000011920929 |
| sustainable_development_goals[0].display_name | Climate action |
| citation_normalized_percentile |