Combining meta-modeling and categorical indicators for global sensitivity analysis of long-running flow simulators with spatially dependent inputs

DOI10.1007/s10596-013-9391-xzbMath1393.86006OpenAlexW1995948782MaRDI QIDQ1663651

Jeremy Rohmer

Publication date: 22 August 2018

Published in: Computational Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10596-013-9391-x

zbMATH Keywords

surrogate modelSobol' indicescomputationally intensive flow modeladaptive component selection and shrinkage operatorpointer variablesspatially dependent inputs

Mathematics Subject Classification ID

Stochastic analysis applied to problems in fluid mechanics (76M35) Computational methods for problems pertaining to geophysics (86-08)

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Post-injection trapping of mobile \(\text{CO}_{2}\) in deep aquifers: assessing the importance of model and parameter uncertainties

Uses Software

• R
• gss
• ElemStatLearn
• TOUGH
• sensitivity

Cites Work

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