A comprehensive probabilistic approach for integrating and separating natural variability and parametric uncertainty in the prediction of distribution coefficient of radionuclides in rivers

2020 ◽  
Vol 225 ◽  
pp. 106371
Author(s):  
Ciffroy P
Author(s):  
Akshit Samadhiya ◽  
Kumari Namrata

AbstractThe paper presents a hierarchical polynomial chaos expansion-based probabilistic approach to analyze the single diode solar cell model under Gaussian parametric uncertainty. It is important to analyze single diode solar cell model response under random events or factors due to uncertainty propagation. The optimal values of five electrical parameters associated with the single diode model are estimated using six deterministic optimization techniques through the root-mean-square minimization approach. Values corresponding to the best objective function response are further utilized to describe the probabilistic design space of each random electrical parameter under uncertainty. Adequate samples of each parameter corresponding Gaussian uncertain distribution are generated using Latin hypercube sampling. Furthermore, a multistage probabilistic approach is adopted to evaluate the model response using low-cost polynomial chaos series expansion and perform global sensitivity analysis under specified Gaussian distribution. Coefficients of polynomial basis functions are calculated using least square and least angle regression techniques. Unlike the highly non-linear and complex single diode representation of solar cells, the polynomial chaos expansion model provides a low computational burden and reduced complexity. To ensure reproducibility, probabilistic output response computed using proposed polynomial chaos expansion model is compared with the true model response. Finally, a multidimensional sensitivity analysis is performed through Sobol decomposition of polynomial chaos series representation to quantify the contribution of each parameter to the variance of the probabilistic response. The validation and assessment result shows that the output probabilistic response of the solar cell under Gaussian parametric uncertainty correlates to a Rayleigh probability distribution function. Output response is characterized by a mean value of 0.0060 and 0.0760 for RTC France and Solarex MSX83 solar cells, respectively. The standard deviation of $$ \pm $$ ± 0.0034 and $$ \pm $$ ± 0.0052 was observed in the probabilistic response for RTC France and Solarex MSX83 solar cells, respectively.


2018 ◽  
Vol 4 (1) ◽  
pp. 165
Author(s):  
Herry Prabowo ◽  
Mochamad Hilmy

The assessment of the service life of concrete structures using the durability design approach is widely accepted nowadays. It is really encouraged that a simulation model can resemble the real performance of concrete during the service life. This paper investigates the concrete carbonation through probabilistic analysis. Data regarding Indonesian construction practice were taken from Indonesian National Standard (SNI). Meanwhile, data related to Indonesian weather condition for instance humidity and temperature are taken from local Meteorological, Climatological, and Geophysical Agency from 2004 until 2016. Hopefully the results can be a starting point for durability of concrete research in Indonesia.


2020 ◽  
Vol 22 (4) ◽  
pp. 983-990
Author(s):  
Konrad Mnich

AbstractIn this work we analyze the behavior of a nonlinear dynamical system using a probabilistic approach. We focus on the coexistence of solutions and we check how the changes in the parameters of excitation influence the dynamics of the system. For the demonstration we use the Duffing oscillator with the tuned mass absorber. We mention the numerous attractors present in such a system and describe how they were found with the method based on the basin stability concept.


2017 ◽  
Vol 12 (30) ◽  
pp. 90-97
Author(s):  
Yu.G. Klykov ◽  
◽  
R.N. Maksimov ◽  
A.I. Rakaev ◽  
L.V. Soroker ◽  
...  

2015 ◽  
Vol 105 (49) ◽  
pp. 1-8
Author(s):  
Katharina Fischer ◽  
Matthias Schubert ◽  
Mark Schaer ◽  
Stefan Margreth ◽  
Kristian Schellenberg

Sign in / Sign up

Export Citation Format

Share Document