Uncertainty analysis
An evaluation is made of the suitability of analytical and statistical sampling methods for making uncertainty analyses. The adjoint method is found to be well-suited for obtaining sensitivity coefficients for computer programs involving large numbers of equations and input parameters. For this purpose the Latin Hypercube Sampling method is found to be inferior to conventional experimental designs. The Latin hypercube method can be used to estimate output probability density functions, but requires supplementary rank transformations followed by stepwise regression to obtain uncertainty information on individual input parameters. A simple Cork and Bottle problem is used to illustrate the efficiency of the adjoint method relative to certain statistical sampling methods. For linear models of the form Ax=b it is shown that a complete adjoint sensitivity analysis can be made without formulating and solving the adjoint problem. This can be done either by using a special type of statistical sampling or by reformulating the primal problem and using suitable linear programming software.
- Research Organization:
- Battelle Memorial Inst., Columbus, OH (United States). Office of Nuclear Waste Isolation
- DOE Contract Number:
- AC06-76RL01830
- OSTI ID:
- 5196673
- Report Number(s):
- ONWI-380; ON: DE82020058; TRN: 82-018398
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
RADIOACTIVE WASTE DISPOSAL
PERFORMANCE
STATISTICAL MODELS
SENSITIVITY ANALYSIS
DATA COVARIANCES
PROBABILITY
MANAGEMENT
MATHEMATICAL MODELS
WASTE DISPOSAL
WASTE MANAGEMENT
052002* - Nuclear Fuels- Waste Disposal & Storage
990200 - Mathematics & Computers