Parameter Sensitivity
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2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Juncheng Wang ◽  
Li Zhou ◽  
Wenzhi Song ◽  
Houle Zhang ◽  
Yongxin Wu

This study investigated the effect of different probabilistic distributions (Lognormal, Gamma, and Beta) to characterize the spatial variability of shear modulus on the soil liquefiable response. The parameter sensitivity analysis included the coefficient of variation and scale of fluctuation of soil shear modulus. The results revealed that the distribution type had no significant influence on the liquefication zone. In particular, the estimation with Beta distribution is the worst scenario. It illuminated that the estimation with Beta distribution can provide a conservative design if site investigation is absent.


2022 ◽  
Vol 248 ◽  
pp. 106197
Author(s):  
Marta Cousido-Rocha ◽  
Santiago Cerviño ◽  
Alexandre Alonso-Fernández ◽  
Juan Gil ◽  
Isabel González Herraiz ◽  
...  

2021 ◽  
Vol 11 (24) ◽  
pp. 11942
Author(s):  
Cong Chen ◽  
Dongji Xuan ◽  
Mingge Wu ◽  
Shengnan Liu ◽  
Yunde Shen

In this paper, a method to improve the performance of PEMFCs using porous material as a flow channel baffle is proposed. The results show that PEMFCs with four porous baffles flow channels have better performance at high current density compared with the traditional flow channel. The structural parameters of the flow channel explored in this study include porosity, the thickness of the baffle and the number of baffles, and their influence on the performance of PEMFCs. Sensitivity analysis results show that the performance of the PEMFCs with the porous baffle channel is the most sensitive to baffle thickness, and the thickness and baffle could be appropriately adjusted. The number of plates and porosity of the baffle are adjusted to improve the performance of the PEMFCs.


Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3464
Author(s):  
Jinhao Liu ◽  
Jianhua Wu ◽  
Yusheng Zhang ◽  
Xinhao Wu

The purpose of this study was to evaluate the sensitivity of input parameters to output results when using the method of characteristics (MOC) for hydraulic transient simulations. Based on a gravity flow water delivery project, we selected six main parameters that affect the hydraulic transient simulation and selected maximum pressure as the output parameter in order to perform a parameter sensitivity analysis. The Morris sensitivity analysis (Morris) and the partial rank correlation coefficient method based on Latin hypercube sampling (LHS-PRCC) were both adopted. The results show that the sensitivity of each parameter is the same except for the friction factor. The flow rate and Young’s modulus are positively correlated with the maximum pressure, whereas the pipe diameter, valve closing time, and wall thickness are negatively correlated. It is discussed that the variability of the friction factor comes from the function of the flow and pressure regulating valve. When other conditions of the gravity flow project remain unchanged, the maximum pressure increases with the increase in the friction factor. The flow rate, pipe diameter, and valve closing time are the key parameters that affect the model. Meanwhile, Morris and LHS-PRCC proved to be effective methods for evaluating parameter sensitivity in hydraulic transient simulations.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Helena A. Saunders ◽  
Jean-Marc Schwartz

AbstractSince the onset of the coronavirus disease 2019 (COVID-19) pandemic, different mitigation and management strategies limiting economic and social activities have been implemented across many countries. Despite these strategies, the virus continues to spread and mutate. As a result, vaccinations are now administered to suppress the pandemic. Current COVID-19 epidemic models need to be expanded to account for the change in behaviour of new strains, such as an increased virulence and higher transmission rate. Furthermore, models need to account for an increasingly vaccinated population. We present a network model of COVID-19 transmission accounting for different immunity and vaccination scenarios. We conduct a parameter sensitivity analysis and find the average immunity length after an infection to be one of the most critical parameters that define the spread of the disease. Furthermore, we simulate different vaccination strategies and show that vaccinating highly connected individuals first is the quickest strategy for controlling the disease.


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