Data & model conditioning for multivariate systematic uncertainty in model calibration, validation, and extrapolation

Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference

Volumn , Issue , 2010, Pages

  Romero, Vicente ^a  

^a SANDIA NATIONAL LABORATORIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EXPERIMENTAL CONDITIONS; EXPERIMENTAL SYSTEM; HIERARCHICAL MODELING; INDUSTRIAL-SCALE EXPERIMENT; INFERENCE ERRORS; MEASUREMENT BIAS; MODEL CALIBRATION; MODEL VALIDATION; MODELING AND SIMULATION; MODELING UNCERTAINTIES; OUTPUT DATA; POST PROCESSING; RANDOM UNCERTAINTIES; REAL-SPACE; SYSTEMATIC UNCERTAINTIES;

COMPUTER SIMULATION; DATA HANDLING; EXPERIMENTS; ISOMERS; STRUCTURAL DYNAMICS; SYSTEMATIC ERRORS;

UNCERTAINTY ANALYSIS;

EID: 84855623841     PISSN: 02734508     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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42. Romero, V.J., "A Practical and Versatile Framework for Characterizing and Propagating Uncertainty in Hierarchical Modeling: Data and Model Conditioning; Model Verification and Validation; Extrapolative Prediction with Uncertainty," Sandia National Laboratories report in preparation. Summary presentation available: "A New Interval-Based "Real Space" Approach to Model Validation Involving Aleatory and Epistemic Uncertainty," Sandia National Laboratories document SAND2009-3160P, April 30, 2009.
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