scholarly journals Subsurface stormflow modeling with sensitivity analysis using a Latin-hypercube sampling technique

1994 ◽  
Author(s):  
J. P. Gwo ◽  
L. E. Toran ◽  
M. D. Morris ◽  
G. V. Wilson
Keyword(s):  
Sensitivity Analysis ◽  
Sampling Technique ◽  
Latin Hypercube Sampling ◽  
Latin Hypercube

scholarly journals Subsurface Stormflow Modeling with Sensitivity Analysis Using a Latin-Hypercube Sampling Technique

Ground Water ◽  
1996 ◽  
Vol 34 (5) ◽  
pp. 811-818 ◽  
Author(s):  
J. P. Gwo ◽  
L. E. Toran ◽  
M. D. Morris ◽  
G. V. Wilson
Keyword(s):  
Sensitivity Analysis ◽  
Sampling Technique ◽  
Latin Hypercube Sampling ◽  
Latin Hypercube

scholarly journals Sensitivity analysis on the pollutant trapping efficiencies of a novel sewerage overflow screening device

2016 ◽  
Vol 18 (6) ◽  
pp. 1007-1018
Author(s):  
M. A. Aziz ◽  
M. A. Imteaz ◽  
H. M. Rasel ◽  
M. Samsuzzoha
Keyword(s):  
Sensitivity Analysis ◽  
Sampling Technique ◽  
Latin Hypercube Sampling ◽  
Capture Efficiency ◽  
Industry Standard ◽  
Informed Decisions ◽  
Input Parameters ◽  
Perform Sensitivity Analysis ◽  
Hydro Jet ◽  
Screening Device

A novel ‘Comb Separator’ was developed and tested with the aim of improving sewer solids capture efficiency and reducing blockages on the screen. Experimental results were compared against the industry standard ‘Hydro-Jet™’ screen. Analysing the parameter sensitivity of a hydraulic screen is a standard practice to get better understanding of the device performance. In order to understand the uncertainties of the Comb Separator's input parameters, it is necessary to undertake sensitivity analysis; this will assist in making informed decisions regarding the use of this device. Such analysis will validate the device's performance in urban sewerage overflow scenarios. The methodology includes multiple linear regression and sampling using the standard Latin hypercube sampling technique to perform sensitivity analysis on different experimental parameters, such as flowrate, effective comb spacing, device runtime, weir opening and comb layers. The input parameters ‘weir opening’ and ‘comb layers’ have an insignificant influence on capture efficiency; hence, they were omitted from further analysis. Among the input parameters, ‘effective spacing’ was the most influential, followed by ‘inflow’ and ‘runtime’. These analyses provide better insights about the sensitivities of the parameters for practical application. This will assist device managers and operators to make informed decisions.

The Effect of Mineral Variability on the Solubility of Some Actinides: an Uncertainty Analysis

1996 ◽  
Vol 465 ◽  
Author(s):  
Christian Ekberg ◽  
Allan T. Emrén ◽  
Anders Samuelsson
Keyword(s):  
Sensitivity Analysis ◽  
Spent Nuclear Fuel ◽  
Sampling Technique ◽  
Latin Hypercube Sampling ◽  
Rock Composition ◽  
Water Composition ◽  
Uncertainty And Sensitivity Analysis ◽  
Rock Water Interaction ◽  
Simulated Groundwater ◽  
Log Normal

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%.

scholarly journals Groundwater pollution risk using a modified Latin hypercube sampling

2006 ◽  
Vol 8 (3) ◽  
pp. 223-234 ◽  
Author(s):  
Husam Baalousha
Keyword(s):  
Sensitivity Analysis ◽  
Groundwater Pollution ◽  
Probabilistic Models ◽  
Latin Hypercube Sampling ◽  
Model Parameters ◽  
Latin Hypercube ◽  
Deterministic Models ◽  
Estimation Errors ◽  
Mean Estimation ◽  
Longitudinal Dispersivity

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.

Sign in / Sign up

Export Citation Format

Share Document