scholarly journals ERROR AND UNCERTAINTY QUANTIFICATION AND SENSITIVITY ANALYSIS IN MECHANICS COMPUTATIONAL MODELS

2011 ◽  
Vol 1 (2) ◽  
pp. 147-161 ◽  
Author(s):  
Sankaran Mahadevan ◽  
Bin Liang
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification ◽  
Computational Models

scholarly journals Uncertainty quantification and sensitivity analysis of COVID-19 exit strategies in an individual-based transmission model

2021 ◽  
Author(s):  
Federica Gugole ◽  
Luc E. Coffeng ◽  
Wouter Edeling ◽  
Benjamin Sanderse ◽  
Sake J. de Vlas ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification ◽  
Computational Models ◽  
Small Region ◽  
Contact Tracing ◽  
Transmission Model ◽  
Policy Makers ◽  
Distribution Of Values ◽  
Exit Strategies ◽  
Key Indicators

Many countries are currently dealing with the COVID-19 epidemic and are searching for an exit strategy such that life in society can return to normal. To support this search, computational models are used to predict the spread of the virus and to assess the efficacy of policy measures before actual implementation. The model output has to be interpreted carefully though, as computational models are subject to uncertainties. These can stem from, e.g., limited knowledge about input parameters values or from the intrinsic stochastic nature of some computational models. They lead to uncertainties in the model predictions, raising the question what distribution of values the model produces for key indicators of the severity of the epidemic. Here we show how to tackle this question using techniques for uncertainty quantification and sensitivity analysis. We assess the uncertainties and sensitivities of four exit strategies implemented in an agent-based transmission model with geographical stratification. The exit strategies are termed Flattening the Curve, Contact Tracing, Intermittent Lockdown and Phased Opening. We consider two key indicators of the ability of exit strategies to avoid catastrophic health care overload: the maximum number of prevalent cases in intensive care (IC), and the total number of IC patient-days in excess of IC bed capacity. Our results show that uncertainties not directly related to the exit strategies are secondary, although they should still be considered in comprehensive analysis intended to inform policy makers. The sensitivity analysis discloses the crucial role of the intervention uptake by the population and of the capability to trace infected individuals. Finally, we explore the existence of a safe operating space. For Intermittent Lockdown we find only a small region in the model parameter space where the key indicators of the model stay within safe bounds, whereas this region is larger for the other exit strategies.

scholarly journals Uncertainty quantification and sensitivity analysis of COVID-19 exit strategies in an individual-based transmission model

2021 ◽  
Vol 17 (9) ◽  
pp. e1009355
Author(s):  
Federica Gugole ◽  
Luc E. Coffeng ◽  
Wouter Edeling ◽  
Benjamin Sanderse ◽  
Sake J. de Vlas ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification ◽  
Computational Models ◽  
Small Region ◽  
Contact Tracing ◽  
Transmission Model ◽  
Policy Makers ◽  
Distribution Of Values ◽  
Exit Strategies ◽  
Key Indicators

Many countries are currently dealing with the COVID-19 epidemic and are searching for an exit strategy such that life in society can return to normal. To support this search, computational models are used to predict the spread of the virus and to assess the efficacy of policy measures before actual implementation. The model output has to be interpreted carefully though, as computational models are subject to uncertainties. These can stem from, e.g., limited knowledge about input parameters values or from the intrinsic stochastic nature of some computational models. They lead to uncertainties in the model predictions, raising the question what distribution of values the model produces for key indicators of the severity of the epidemic. Here we show how to tackle this question using techniques for uncertainty quantification and sensitivity analysis. We assess the uncertainties and sensitivities of four exit strategies implemented in an agent-based transmission model with geographical stratification. The exit strategies are termed Flattening the Curve, Contact Tracing, Intermittent Lockdown and Phased Opening. We consider two key indicators of the ability of exit strategies to avoid catastrophic health care overload: the maximum number of prevalent cases in intensive care (IC), and the total number of IC patient-days in excess of IC bed capacity. Our results show that uncertainties not directly related to the exit strategies are secondary, although they should still be considered in comprehensive analysis intended to inform policy makers. The sensitivity analysis discloses the crucial role of the intervention uptake by the population and of the capability to trace infected individuals. Finally, we explore the existence of a safe operating space. For Intermittent Lockdown we find only a small region in the model parameter space where the key indicators of the model stay within safe bounds, whereas this region is larger for the other exit strategies.

scholarly journals Fast Probabilistic Uncertainty Quantification and Sensitivity Analysis of a Mars Life Support System Model

2020 ◽  
Vol 53 (2) ◽  
pp. 7268-7273
Author(s):  
Georgios Makrygiorgos ◽  
Soumyajit Sen Gupta ◽  
Amor A. Menezes ◽  
Ali Mesbah
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification ◽  
Support System ◽  
Life Support ◽  
System Model ◽  
Life Support System ◽  
Probabilistic Uncertainty

06-02 Methods for Uncertainty Quantification, Sensitivity Analysis, and Prediction Sessions

2021 ◽  
Author(s):  
Michael Prime ◽  
Gavin Jones ◽  
Vicente Romero ◽  
Justin Winokur ◽  
Benjamin Schroeder
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification

scholarly journals Status Report on Uncertainty Quantification and Sensitivity Analysis Tools in the Geologic Disposal Safety Assessment (GDSA) Framework.

2019 ◽  
Author(s):  
Laura Painton Swiler ◽  
Jon C. Helton ◽  
Eduardo Basurto ◽  
Dusty Marie Brooks ◽  
Paul Mariner ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification ◽  
Safety Assessment ◽  
Status Report ◽  
Analysis Tools ◽  
Geologic Disposal
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