A Methodology for Global Sensitivity Analysis of Activated Sludge Models: Case Study with Activated Sludge Model No. 3 ( ASM 3)

2019 ◽  
Vol 91 (9) ◽  
pp. 865-876
Author(s):  
Dhan Lord B. Fortela ◽  
Kyle Farmer ◽  
Alex Zappi ◽  
Wayne W. Sharp ◽  
Emmanuel Revellame ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Activated Sludge ◽  
Global Sensitivity Analysis ◽  
Activated Sludge Model ◽  
Global Sensitivity ◽  
Activated Sludge Models

Global sensitivity analysis of an urban microclimate system under uncertainty: Design and case study

2017 ◽  
Vol 124 ◽  
pp. 153-170 ◽  
Author(s):  
Jiachen Mao ◽  
Joseph H. Yang ◽  
Afshin Afshari ◽  
Leslie K. Norford
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Urban Microclimate ◽  
Global Sensitivity

scholarly journals Variable Selection in Regression Models Using Global Sensitivity Analysis

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
William Becker ◽  
Paolo Paruolo ◽  
Andrea Saltelli
Keyword(s):  
Sensitivity Analysis ◽  
Variable Selection ◽  
Regression Models ◽  
Global Sensitivity Analysis ◽  
Physical Models ◽  
Model Fit ◽  
Global Sensitivity ◽  
Testing Sequence ◽  
Input Variables

Abstract Global sensitivity analysis is primarily used to investigate the effects of uncertainties in the input variables of physical models on the model output. This work investigates the use of global sensitivity analysis tools in the context of variable selection in regression models. Specifically, a global sensitivity measure is applied to a criterion of model fit, hence defining a ranking of regressors by importance; a testing sequence based on the ‘Pantula-principle’ is then applied to the corresponding nested submodels, obtaining a novel model-selection method. The approach is demonstrated on a growth regression case study, and on a number of simulation experiments, and it is found competitive with existing approaches to variable selection.

scholarly journals Global sensitivity analysis to optimize basin-scale conductive model calibration – A case study from the Upper Rhine Graben

Geothermics ◽  
2021 ◽  
Vol 95 ◽  
pp. 102143
Author(s):  
Denise Degen ◽  
Karen Veroy ◽  
Jessica Freymark ◽  
Magdalena Scheck-Wenderoth ◽  
Thomas Poulet ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Model Calibration ◽  
Global Sensitivity Analysis ◽  
Upper Rhine Graben ◽  
Global Sensitivity ◽  
Rhine Graben ◽  
Basin Scale ◽  
Upper Rhine

scholarly journals Inter-compound and Intra-compound Global Sensitivity Analysis of a Physiological Model for Pulmonary Absorption of Inhaled Compounds

2020 ◽  
Vol 22 (5) ◽  
Author(s):  
Nicola Melillo ◽  
Silvia Grandoni ◽  
Nicola Cesari ◽  
Giandomenico Brogin ◽  
Paola Puccini ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Pbpk Model ◽  
Global Sensitivity Analysis ◽  
Model Development ◽  
Physiological Model ◽  
Pbpk Modelling ◽  
Global Sensitivity ◽  
Fraction Absorbed ◽  
Whole Space

Abstract In recent years, global sensitivity analysis (GSA) has gained interest in physiologically based pharmacokinetics (PBPK) modelling and simulation from pharmaceutical industry, regulatory authorities, and academia. With the case study of an in-house PBPK model for inhaled compounds in rats, the aim of this work is to show how GSA can contribute in PBPK model development and daily use. We identified two types of GSA that differ in the aims and, thus, in the parameter variability: inter-compound and intra-compound GSA. The inter-compound GSA aims to understand which are the parameters that mostly influence the variability of the metrics of interest in the whole space of the drugs’ properties, and thus, it is useful during the model development. On the other hand, the intra-compound GSA aims to highlight how much the uncertainty associated with the parameters of a given drug impacts the uncertainty in the model prediction and so, it is useful during routine PBPK use. In this work, inter-compound GSA highlighted that dissolution- and formulation-related parameters were mostly important for the prediction of the fraction absorbed, while the permeability is the most important parameter for lung AUC and MRT. Intra-compound GSA highlighted that, for all the considered compounds, the permeability was one of the most important parameters for lung AUC, MRT and plasma MRT, while the extraction ratio and the dose for the plasma AUC. GSA is a crucial instrument for the quality assessment of model-based inference; for this reason, we suggest its use during both PBPK model development and use.

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