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Addressing Model Inadequacy in Inverse Uncertainty Quantification for Fuel Performance Modeling by using a Hierarchical Statistical Formulation
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.ORCID iD: 0000-0001-5296-7430
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.ORCID iD: 0000-0002-7595-8024
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.ORCID iD: 0000-0001-7370-6539
2022 (English)In: SIAM 2022: Conference on Uncertainty Quantification, 2022, p. 6-6Conference paper, Oral presentation with published abstract (Other academic)
Place, publisher, year, edition, pages
2022. p. 6-6
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Engineering and Technology Physical Sciences
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URN: urn:nbn:se:uu:diva-484172OAI: oai:DiVA.org:uu-484172DiVA, id: diva2:1693870
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SIAM Conference on Uncertainty Quantification (UQ22), Atlanta, April 12-15, 2022
Note

Oral presentation by: Gustav Robertson

Title of presentation: CaNel - Calibration of Nuclear fuel performance codes: Addressing Model Inadequacy in Inverse Uncertainty Quantification for Fuel Performance Modeling by using a Hierarchical Statistical Formulation

Available from: 2022-09-08 Created: 2022-09-08 Last updated: 2022-09-08Bibliographically approved

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Robertson, GustavSjöstrand, HenrikAndersson, Peter

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