Identifying the critical parameters of a cyanobacterial growth and movement model by using generalised sensitivity analysis

2007 ◽  
Vol 207 (1) ◽  
pp. 11-21 ◽  
Author(s):  
Basak Guven ◽  
Alan Howard
Keyword(s):  
Sensitivity Analysis ◽  
Critical Parameters ◽  
Movement Model ◽  
Generalised Sensitivity Analysis

Modelling of Nitrification at the Mogden Treatment Works

1989 ◽  
Vol 21 (4-5) ◽  
pp. 305-314
Author(s):  
J. P. Lumbers ◽  
S. C. Cook ◽  
G. A. Thomas
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo Simulation ◽  
River Basin Management ◽  
Independent Data ◽  
Activated Sludge Process ◽  
Basin Management ◽  
Alternative Control ◽  
Control Actions ◽  
Parameter Values ◽  
Generalised Sensitivity Analysis

An application of a dynamic model of the activated sludge process is described within the context of real-time river basin management. The model has been calibrated and validated on independent data and then applied to investigate losses of nitrification at the Mogden Works. Monte Carlo simulation and generalised sensitivity analysis were found to be effective ways of identifying appropriate parameter values and their importance. The prediction of unmeasured states such as the autotroph population enabled the effects of alternative control actions to be better understood and the most suitable measures found.

Awarding Health: Contracts at the National Institutes of a Sensitivity Analysis of the Critical Parameters

1994 ◽  
Vol 1 (2) ◽  
pp. 117-124
Author(s):  
R. Craig Stotts ◽  
Larry G. Kessler ◽  
John C. Hershey ◽  
Nicholas G. Hall ◽  
Jessie G. Gruman
Keyword(s):  
Sensitivity Analysis ◽  
Critical Parameters

scholarly journals Sensitivity analysis of critical parameters in board test

1996 ◽  
Vol 13 (1) ◽  
pp. 58-63 ◽  
Author(s):  
M.M.V. Tegethoff ◽  
T.W. Chen
Keyword(s):  
Sensitivity Analysis ◽  
Critical Parameters ◽  
Board Test

Systematic Parameter Estimation and Sensitivity Analysis Using a Multidimensional PEMFC Model Coupled With DAKOTA

2010 ◽  
Author(s):  
Brian Carnes ◽  
Ken S. Chen ◽  
Fangming Jiang ◽  
Gang Luo ◽  
Chao-Yang Wang
Keyword(s):  
Sensitivity Analysis ◽  
Parameter Estimation ◽  
Proton Exchange Membrane ◽  
Computational Models ◽  
Proton Exchange ◽  
Operating Conditions ◽  
Critical Parameters ◽  
Model Parameters ◽  
Two Phase ◽  
Manual Adjustment

Current computational models for proton exchange membrane fuel cells (PEMFCs) include a large number of parameters such as boundary conditions, material properties, and numerous parameters used in sub-models for membrane transport, two-phase flow and electrochemistry. In order to successfully use a computational PEMFC model in design and optimization, it is important to identify critical parameters under a wide variety of operating conditions, such as relative humidity, current load, temperature, etc. Moreover, when experimental data is available in the form of polarization curves or local distribution of current and reactant/product species (e.g., O2, H2O concentrations), critical parameters can be estimated in order to enable the model to better fit the data. Sensitivity analysis and parameter estimation are typically performed using manual adjustment of parameters, which is also common in parameter studies. We present work to demonstrate a systematic approach based on using a widely available toolkit developed at Sandia called DAKOTA that supports many kinds of design studies, such as sensitivity analysis as well as optimization and uncertainty quantification. In the present work, we couple a multidimensional PEMFC model (which is being developed, tested and later validated in a joint effort by a team from Penn State Univ. and Sandia National Laboratories) with DAKOTA through the mapping of model parameters to system responses. Using this interface, we demonstrate the efficiency of performing simple parameter studies as well as identifying critical parameters using sensitivity analysis. Finally, we show examples of optimization and parameter estimation using the automated capability in DAKOTA.

scholarly journals An EOQ model for deteriorating items under supplier credits when demand is stock dependent

2010 ◽  
Vol 20 (1) ◽  
pp. 145-156
Author(s):  
Nita Shah ◽  
Poonam Mishra
Keyword(s):  
Sensitivity Analysis ◽  
Optimal Solution ◽  
Deteriorating Items ◽  
Critical Parameters ◽  
Eoq Model ◽  
Constant Rate ◽  
Cash Discount

In many circumstances retailer is not able to settle the account as soon as items are received. In that scenario supplier can offer two promotional schemes namely cash discount and /or a permissible delay to the customer. In this study, an EOQ model is developed when units in inventory deteriorate at a constant rate and demand is stock dependent. The salvage value is associated to deteriorated units. An algorithm is given to find the optimal solution. The sensitivity analysis is carried out to analyze the effect of critical parameters on optimal solution.

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