Traditional Global Sensitivity Analysis（GSA） focuses on ranking inputs according to their contributions to the output uncertainty.However,information about how the specific regions inside an input affect the output ...Traditional Global Sensitivity Analysis（GSA） focuses on ranking inputs according to their contributions to the output uncertainty.However,information about how the specific regions inside an input affect the output is beyond the traditional GSA techniques.To fully address this issue,in this work,two regional moment-independent importance measures,Regional Importance Measure based on Probability Density Function（RIMPDF） and Regional Importance Measure based on Cumulative Distribution Function（RIMCDF）,are introduced to find out the contributions of specific regions of an input to the whole output distribution.The two regional importance measures prove to be reasonable supplements of the traditional GSA techniques.The ideas of RIMPDF and RIMCDF are applied in two engineering examples to demonstrate that the regional moment-independent importance analysis can add more information concerning the contributions of model inputs.展开更多
Identifying source information after river chemical spill occurrences is critical for emergency responses.However,the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet...Identifying source information after river chemical spill occurrences is critical for emergency responses.However,the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated.To fill this gap,stochastic analysis approaches,including a regional sensitivity analysis method,identifiability plot and perturbation methods,were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework.Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules.For example,the release load can be most easily inverted,and the source location is responsible for the largest uncertainty among the source parameters.The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty.The differences among the different objective functions are smaller for instantaneous release than for continuous release cases.Small monitoring errors affect the inversion results only slightly,which can be ignored in practice.Interestingly,the estimated values of the release location and time negatively deviate from the real values,and the extent is positively correlated with the relative size of the mixing zone to the objective river reach.These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.展开更多
基金supported by the National Natural Science Foundation of China(No.NSFC51608446)the Fundamental Research Fund for Central Universities of China(No.3102016ZY015)
文摘Traditional Global Sensitivity Analysis（GSA） focuses on ranking inputs according to their contributions to the output uncertainty.However,information about how the specific regions inside an input affect the output is beyond the traditional GSA techniques.To fully address this issue,in this work,two regional moment-independent importance measures,Regional Importance Measure based on Probability Density Function（RIMPDF） and Regional Importance Measure based on Cumulative Distribution Function（RIMCDF）,are introduced to find out the contributions of specific regions of an input to the whole output distribution.The two regional importance measures prove to be reasonable supplements of the traditional GSA techniques.The ideas of RIMPDF and RIMCDF are applied in two engineering examples to demonstrate that the regional moment-independent importance analysis can add more information concerning the contributions of model inputs.
基金funded by the China Postdoctoral Science Foundation(Grant No.2014M551249)the National Natural Science Foundation of China(Grant No.51509061)support was provided by the Southern University of Science and Technology(Grant No.G01296001).
文摘Identifying source information after river chemical spill occurrences is critical for emergency responses.However,the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated.To fill this gap,stochastic analysis approaches,including a regional sensitivity analysis method,identifiability plot and perturbation methods,were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework.Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules.For example,the release load can be most easily inverted,and the source location is responsible for the largest uncertainty among the source parameters.The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty.The differences among the different objective functions are smaller for instantaneous release than for continuous release cases.Small monitoring errors affect the inversion results only slightly,which can be ignored in practice.Interestingly,the estimated values of the release location and time negatively deviate from the real values,and the extent is positively correlated with the relative size of the mixing zone to the objective river reach.These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.
