A comparison of uncertainty and sensitivity analysis results obtained with random and Latin hypercube sampling

2005 ◽  
Vol 89 (3) ◽  
pp. 305-330 ◽  
Author(s):  
J.C. Helton ◽  
F.J. Davis ◽  
J.D. Johnson
1996 ◽  
Vol 465 ◽  
Author(s):  
Christian Ekberg ◽  
Allan T. Emrén ◽  
Anders Samuelsson

ABSTRACTThe use of computer simulations in the performance assessment for a repository for spent nuclear fuel, are in many cases the only method to get information on how the rock-repository system will work. One important factor is the solubility of the elements released if the repository is breached. This solubility may be determined experimentally or simulated. Ifit is simulated, several factors such as thermodynamical uncertainties will affect the reliability of the results. If these uncertainties are assumed to be small, the composition of the water used in the calculations may play a major part in the uncertainties in solubility. The water composition, in tum, is either determined experimentally or calculated through water-rock interactions. Thus, if the mineral composition of the rock is known, it is possible to foresee the water composition. However, in most cases a determination of the rock composition is made from drilling cores and is thus quite uncertain. Therefore, if solubility calculations are to be based on water properties calculated from rock-water interactions another uncertainty is introduced. This paper is focused on uncertainty and sensitivity analysis of rock-water interaction simulations and the uncertainties thus obtained are propagated through a program making uncertainty and sensitivity analysis of the solubility calculations. In both cases the latin hypercube sampling technique have been used. The results show that the solubilities are in most cases log normal distributed while the different elements in the simulated groundwater in some cases diverge significantly from such a distribution. The numerical results are comforting in that the uncertainty intervals of the solubilities are rather small, i.e. up to 30%.


2006 ◽  
Vol 8 (3) ◽  
pp. 223-234 ◽  
Author(s):  
Husam Baalousha

Characterisation of groundwater modelling involves significant uncertainty because of estimation errors of these models and other different sources of uncertainty. Deterministic models do not account for uncertainties in model parameters, and thus lead to doubtful output. The main alternatives for deterministic models are the probabilistic models and perturbation methods such as Monte Carlo Simulation (MCS). Unfortunately, these methods have many drawbacks when applied in risk analysis of groundwater pollution. In this paper, a modified Latin Hypercube Sampling method is presented and used for risk, uncertainty, and sensitivity analysis of groundwater pollution. The obtained results were compared with other sampling methods. Results of the proposed method have shown that it can predict the groundwater contamination risk for all values of probability better than other methods, maintaining the accuracy of mean estimation. Sensitivity analysis results reveal that the contaminant concentration is more sensitive to longitudinal dispersivity than to velocity.


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