On modeling of the structures of statistical dependence of the extreme type

2020 ◽  
Vol 1 ◽  
pp. 70-79
Author(s):  
Евгений Щетинин
Keyword(s):  
Statistical Dependence ◽  
Extreme Type

scholarly journals Measuring compound flood potential from river discharge and storm surge extremes at the global scale

2020 ◽  
Vol 20 (2) ◽  
pp. 489-504 ◽  
Author(s):  
Anaïs Couasnon ◽  
Dirk Eilander ◽  
Sanne Muis ◽  
Ted I. E. Veldkamp ◽  
Ivan D. Haigh ◽  
...  
Keyword(s):  
Storm Surge ◽  
River Discharge ◽  
Flood Hazard ◽  
Joint Probability ◽  
Global Scale ◽  
Statistical Dependence ◽  
Dependence Structure ◽  
Meteorological Forcing ◽  
Continental Scale ◽  
Bivariate Dependence

Abstract. The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding potential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical independence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions.

scholarly journals Analysis of the System of Controlling Paid Parking Zones

2021 ◽  
Vol 13 (8) ◽  
pp. 4211
Author(s):  
Maciej Kozłowski ◽  
Andrzej Czerepicki ◽  
Piotr Jaskowski ◽  
Kamil Aniszewski
Keyword(s):  
Control System ◽  
Smart City ◽  
Measurement Errors ◽  
Fundamental Problem ◽  
Urban Traffic ◽  
Statistical Dependence ◽  
Actual State ◽  
Event Time ◽  
Operational Data

Urban traffic can be curbed in various ways, for instance, by introducing paid unguarded parking zones (PUPZ). The operational functionality of this system depends on whether or not the various system features used to document parking cases function properly, including those which enable positioning of vehicles parked in the PUPZ, recognition of plate numbers, event time recording, and the correct anonymisation of persons and other vehicles. The most fundamental problem of this system is its reliability, understood as the conformity of control results with the actual state of matters. This characteristic can be studied empirically, and this article addresses the methodology proposed for such an examination, discussed against a case study. The authors have analysed the statistical dependence of the e-control system’s measurement errors based on operational data. The results of this analysis confirm the rationale behind the deployment of the e-control system under the implementation of the smart city concept in Warsaw.

Value of information of in situ inspections of mooring lines

2021 ◽  
pp. 1748006X2098740
Author(s):  
Jorge Mendoza ◽  
Jacopo Paglia ◽  
Jo Eidsvik ◽  
Jochen Köhler
Keyword(s):  
Pitting Corrosion ◽  
Value Of Information ◽  
Structural Reliability ◽  
Structural Safety ◽  
Statistical Dependence ◽  
Mooring System ◽  
Mooring Lines ◽  
Corrosion Condition ◽  
Chain Links

Mooring systems that are used to secure position keeping of floating offshore oil and gas facilities are subject to deterioration processes, such as pitting corrosion and fatigue crack growth. Past investigations show that pitting corrosion has a significant effect on reducing the fatigue resistance of mooring chain links. In situ inspections are essential to monitor the development of the corrosion condition of the components of mooring systems and ensure sufficient structural safety. Unfortunately, offshore inspection campaigns require large financial commitments. As a consequence, inspecting all structural components is unfeasible. This article proposes to use value of information analysis to rank identified inspection alternatives. A Bayesian Network is proposed to model the statistical dependence of the corrosion deterioration among chain links at different locations of the mooring system. This is used to efficiently update the estimation of the corrosion condition of the complete mooring system given evidence from local observations and to reassess the structural reliability of the system. A case study is presented to illustrate the application of the framework.

Magnetooscillations in quasi-two-dimensional extreme type II superconductors

1988 ◽  
Vol 153-155 ◽  
pp. 1179-1180 ◽  
Author(s):  
T. Maniv ◽  
R.S. Markiewicz ◽  
I.D. Vagner ◽  
P. Wyder
Keyword(s):  
Type Ii ◽  
Two Dimensional ◽  
Type Ii Superconductors ◽  
Extreme Type

Statistical Dependence of Input Variables in Doproc Method / Statistická Závislost Vstupních Veličin V Metodě Popv

2012 ◽  
Vol 12 (2) ◽  
pp. 48-58 ◽  
Author(s):  
Petr Janas ◽  
Krejsa Martin
Keyword(s):  
Reliability Assessment ◽  
Random Variables ◽  
Statistical Dependence ◽  
Software System ◽  
Dependent Variables ◽  
Computational Procedures ◽  
Input Variables

Abstract In probabilistic tasks, input random variables are often statistically dependent. This fact should be considered in correct computational procedures. In case of the newly developed Direct Optimized Probabilistic Calculation (DOProC), the statistically dependent variables can be expressed by the socalled multidimensional histograms, which can be used e.g. for probabilistic calculations and reliability assessment in the software system ProbCalc.

Structural analysis of the trajectories of random processes formed in non-linear vibration isolation systems

2021 ◽  
Author(s):  
A.S. Gusev ◽  
L.V. Zinchenko ◽  
S.A. Starodubtseva
Keyword(s):  
Structural Analysis ◽  
Vibration Isolation ◽  
Fundamental Principle ◽  
Statistical Dependence ◽  
Absolute Maximum ◽  
Time Interval ◽  
Apparent Lack ◽  
The Road ◽  
Isolation Systems ◽  
Non Gaussian

When designing technical structures, the safety of their elements is a fundamental principle. This highlights the significance of the proposed solution to the structural analysis of the trajectories of non-Gaussian stationary processes. The solution aims to acquire source data for calculating the stress-strength reliability of structural elements operating under random loads. We analyze an approach that makes it possible to account for the statistical dependence between processes and their derivatives, despite the apparent lack of correlation between them. The considered approach can be utilized in the design of vibration protection of transport vehicles to calculate the probability of a shock absorber breakdown, the probability of loss of the road-wheel contact, etc. The operation reliability of such systems is defined as the probability that the absolute maximum of the process does not exceed the specified standard level during a certain time interval. The article presents the reliability calculation using structural analysis on the example of a one-dimensional stochastic system.

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