Stochastic Characterization of Voltage Sag Occurrence Based on Field Data

2019 ◽  
Vol 34 (2) ◽  
pp. 496-504 ◽  
Author(s):  
Andre dos Santos ◽  
Tiago Rosa ◽  
Maria Teresa Correia de Barros
Metrika ◽  
2001 ◽  
Vol 53 (3) ◽  
pp. 207-222 ◽  
Author(s):  
Erkki P. Liski ◽  
Alexander Zaigraev

1984 ◽  
Vol 16 (8-9) ◽  
pp. 147-153 ◽  
Author(s):  
Van-Thanh-Van Nguyen

The present study, a continuation of a previous work by the author, suggests a new theoretical approach to the characterization of the temporal pattern of storms. A storm is defined as a continuous run of non-zero one-hour rainfall depths. A general stochastic model is developed to determine the probability distributions of cumulative storm rainfall amounts at successive time intervals after the storm began. The previous model for characterizing storm temporal patterns was based on the assumption that hourly rainfall depths were independent and identically exponentially distributed random variables, while sequences of wet hours were modeled by a first-order stationary Markov chain. Hence, the model did only introduce dependence of wet hour occurences into the rainfall process through the first-order Markov chain. The present paper proposes a more general model that can take into account both the persistence in hourly rainfall occurrences and the dependence between successive hourly rainfall depths. Results of an illustrative example show that by accounting for the correlation structure of consecutive rainfall depths the present model gives a better fit to the observations than the previous one.


1994 ◽  
Vol 17 (1-2) ◽  
pp. 47-59 ◽  
Author(s):  
Juan B. Valdés ◽  
Eunho Ha ◽  
Chulsang Yoo ◽  
Gerald R. North

Author(s):  
S. Radhakrishnan ◽  
G. Subbarayan ◽  
L. Nguyen ◽  
W. Mazotti

There is considerable uncertainty in the prediction of performance of a system mainly due to idealizations in geometry, material behavior, and loading history. Uncertainties in geometry can be predicted and controlled using tighter tolerances. However, the models currently used to describe material behavior are mostly deterministic. To predict the coupling efficiency of a photonic system to greater degree of confidence, stochastic analysis procedures are necessary. As part of this analysis, the behavior of materials must be stochastically characterized. In this paper, we present extensive experimental data on thermally and UV-cured epoxies typically used in photonic packages to enable stochastic analysis. The test data includes the viscoelastic behavior. We present analytical model to obtain the variation in the displacement of the epoxies resulting from its stochastic viscoelastic behavior. We utilize the analytical model to predict the uncertainty in the coupling efficiency of a generic photonic package.


Games ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 54
Author(s):  
Simone Battistini

Pursuit-evasion games are used to define guidance strategies for multi-agent planning problems. Although optimal strategies exist for deterministic scenarios, in the case when information about the opponent players is imperfect, it is important to evaluate the effect of uncertainties on the estimated variables. This paper proposes a method to characterize the game space of a pursuit-evasion game under a stochastic perspective. The Mahalanobis distance is used as a metric to determine the levels of confidence in the estimation of the Zero Effort Miss across the capture zone. This information can be used to gain an insight into the guidance strategy. A simulation is carried out to provide numerical results.


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