24. NATURAL TIME

2017 ◽  
pp. 89-94
Keyword(s):  
Natural Time

scholarly journals Statistical and Criticality Analysis of the Lower Ionosphere Prior to the 30 October 2020 Samos (Greece) Earthquake (M6.9), Based on VLF Electromagnetic Propagation Data as Recorded by a New VLF/LF Receiver Installed in Athens (Greece)

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 676
Author(s):  
Dimitrios Z. Politis ◽  
Stelios M. Potirakis ◽  
Yiannis F. Contoyiannis ◽  
Sagardweep Biswas ◽  
Sudipta Sasmal ◽  
...  
Keyword(s):  
Time Series ◽  
Fresnel Zone ◽  
Lower Ionosphere ◽  
Propagation Path ◽  
Northern Coast ◽  
Analysis Method ◽  
Ionospheric Propagation ◽  
Amplitude Data ◽  
Natural Time ◽  
Criticality Analysis

In this work we present the statistical and criticality analysis of the very low frequency (VLF) sub-ionospheric propagation data recorded by a VLF/LF radio receiver which has recently been established at the University of West Attica in Athens (Greece). We investigate a very recent, strong (M6.9), and shallow earthquake (EQ) that occurred on 30 October 2020, very close to the northern coast of the island of Samos (Greece). We focus on the reception data from two VLF transmitters, located in Turkey and Israel, on the basis that the EQ’s epicenter was located within or very close to the 5th Fresnel zone, respectively, of the corresponding sub-ionospheric propagation path. Firstly, we employed in our study the conventional analyses known as the nighttime fluctuation method (NFM) and the terminator time method (TTM), aiming to reveal any statistical anomalies prior to the EQ’s occurrence. These analyses revealed statistical anomalies in the studied sub-ionospheric propagation paths within ~2 weeks and a few days before the EQ’s occurrence. Secondly, we performed criticality analysis using two well-established complex systems’ time series analysis methods—the natural time (NT) analysis method, and the method of critical fluctuations (MCF). The NT analysis method was applied to the VLF propagation quantities of the NFM, revealing criticality indications over a period of ~2 weeks prior to the Samos EQ, whereas MCF was applied to the raw receiver amplitude data, uncovering the time excerpts of the analyzed time series that present criticality which were closest before the Samos EQ. Interestingly, power-law indications were also found shortly after the EQ’s occurrence. However, it is shown that these do not correspond to criticality related to EQ preparation processes. Finally, it is noted that no other complex space-sourced or geophysical phenomenon that could disturb the lower ionosphere did occur during the studied time period or close after, corroborating the view that our results prior to the Samos EQ are likely related to this mainshock.

Remote sensing natural time analysis of heartbeat data by means of a portable photoplethysmography device

2020 ◽  
Vol 42 (6) ◽  
pp. 2292-2302
Author(s):  
G. Baldoumas ◽  
D. Peschos ◽  
G. Tatsis ◽  
V. Christofilakis ◽  
S. K. Chronopoulos ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Analysis ◽  
Natural Time ◽  
Natural Time Analysis

Vehicle Stability Control Through Predictive and Optimal Tire Saturation Management

2012 ◽  
Author(s):  
Justin Sill ◽  
Beshah Ayalew
Keyword(s):  
Stability Control ◽  
Vehicle Stability ◽  
Distribution Problem ◽  
Scale Separation ◽  
Torque Distribution ◽  
Hydraulic Hybrid ◽  
Time Scale Separation ◽  
Vehicle Stability Control ◽  
Natural Time ◽  
Set Up

This paper presents a predictive vehicle stability control (VSC) strategy that distributes the drive/braking torques to each wheel of the vehicle based on the optimal exploitation of the available traction capability for each tire. To this end, tire saturation levels are defined as the deficiency of a tire to generate a force that linearly increases with the relevant slip quantities. These saturation levels are then used to set up an optimization objective for a torque distribution problem within a novel cascade control structure that exploits the natural time scale separation of the slower lateral handling dynamics of the vehicle from the relatively faster rotational dynamics of the wheel/tire. The envisaged application of the proposed vehicle stability strategy is for vehicles with advanced and emerging pure electric, hybrid electric or hydraulic hybrid power trains featuring independent wheel drives. The developed predictive control strategy is evaluated for, a two-axle truck featuring such an independent drive system and subjected to a transient handling maneuver.

Natural-time analysis of critical phenomena: The case of seismicity

2010 ◽  
Vol 92 (2) ◽  
pp. 29002 ◽  
Author(s):  
P. A. Varotsos ◽  
N. V. Sarlis ◽  
E. S. Skordas ◽  
S. Uyeda ◽  
M. Kamogawa
Keyword(s):  
Critical Phenomena ◽  
Time Analysis ◽  
Natural Time ◽  
Natural Time Analysis

scholarly journals Multivariate fractional phase–type distributions

2020 ◽  
Vol 23 (5) ◽  
pp. 1431-1451 ◽  
Author(s):  
Hansjörg Albrecher ◽  
Martin Bladt ◽  
Mogens Bladt
Keyword(s):  
Tail Dependence ◽  
Jump Process ◽  
Multivariate Distributions ◽  
New Class ◽  
Natural Time ◽  
Special Cases ◽  
Phase Type ◽  
Phase Type Distributions ◽  
Markovian Jump Process ◽  
Heavy Tailed

Abstract We extend the Kulkarni class of multivariate phase–type distributions in a natural time–fractional way to construct a new class of multivariate distributions with heavy-tailed Mittag-Leffler(ML)-distributed marginals. The approach relies on assigning rewards to a non–Markovian jump process with ML sojourn times. This new class complements an earlier multivariate ML construction [2] and in contrast to the former also allows for tail dependence. We derive properties and characterizations of this class, and work out some special cases that lead to explicit density representations.

scholarly journals Statistical physics models for aftershocks and induced seismicity

2018 ◽  
Vol 377 (2136) ◽  
pp. 20170397 ◽  
Author(s):  
Molly Luginbuhl ◽  
John B. Rundle ◽  
Donald L. Turcotte
Keyword(s):  
Induced Seismicity ◽  
Statistical Physics ◽  
Aftershock Sequence ◽  
Induced Earthquakes ◽  
Aftershock Activity ◽  
Gas Field ◽  
Natural Time ◽  
Parkfield Earthquake ◽  
Groningen Gas Field

A standard approach to quantifying the seismic hazard is the relative intensity (RI) method. It is assumed that the rate of seismicity is constant in time and the rate of occurrence of small earthquakes is extrapolated to large earthquakes using Gutenberg–Richter scaling. We introduce nowcasting to extend RI forecasting to time-dependent seismicity, for example, during an aftershock sequence. Nowcasting uses ‘natural time’; in seismicity natural time is the event count of small earthquakes. The event count for small earthquakes is extrapolated to larger earthquakes using Gutenberg–Richter scaling. We first review the concepts of natural time and nowcasting and then illustrate seismic nowcasting with three examples. We first consider the aftershock sequence of the 2004 Parkfield earthquake on the San Andreas fault in California. Some earthquakes have higher rates of aftershock activity than other earthquakes of the same magnitude. Our approach allows the determination of the rate in real time during the aftershock sequence. We also consider two examples of induced earthquakes. Large injections of waste water from petroleum extraction have generated high rates of induced seismicity in Oklahoma. The extraction of natural gas from the Groningen gas field in The Netherlands has also generated very damaging earthquakes. In order to reduce the seismic activity, rates of injection and withdrawal have been reduced in these two cases. We show how nowcasting can be used to assess the success of these efforts. This article is part of the theme issue ‘Statistical physics of fracture and earthquakes’.

scholarly journals Nonparametric factor of variability of hydroecological time series

2021 ◽  
pp. 103-108
Author(s):  
Vladislav Artemenko ◽  
◽  
Volodymyr Petrovych ◽  
Keyword(s):  
Time Series ◽  
Nonparametric Method ◽  
Natural Time

Nonparametric factor of variability is offered for improvement of the estimation of variability of time series. By means of this nonparametric factor in this article is considered change of variability of hydroecological time series depending on season of the year. Considered nonparametric method is allows to find factor of variability practically for any natural time series.

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