RECURRENCE QUANTIFICATION ANALYSIS OF ELECTROCHEMICAL NOISE DATA DURING PIT DEVELOPMENT

2007 ◽  
Vol 17 (10) ◽  
pp. 3725-3728 ◽  
Author(s):  
LUIS SANTOS MONTALBÁN ◽  
PÄIVI HENTTU ◽  
ROBERT PICHÉ
Keyword(s):  
Time Series ◽  
Pitting Corrosion ◽  
Electrochemical Noise ◽  
Recurrence Quantification Analysis ◽  
Corrosion Process ◽  
Current Time ◽  
Recurrence Quantification ◽  
Noise Data ◽  
Quantification Analysis ◽  
Aisi 316

Electrochemical noise (EN) data is commonly used to monitor corrosion of metals in various environments. In this work we use recurrence quantification analysis (RQA) to study EN time series of stainless steel AISI 316 samples immersed in a mildly corrosive electrolyte. It is found that RQA of current and potential time series reveal different information: current time series provides detailed information on the kinetics of the pitting corrosion process, while the potential time series identifies the transitions from one thermodynamic state to another in the pitting corrosion process.

Recurrence Quantification Analysis of Financial Markets

2013 ◽  
pp. 50-62
Author(s):  
João A. Bastos
Keyword(s):  
Time Series ◽  
Financial Time Series ◽  
Recurrence Quantification Analysis ◽  
Government Bonds ◽  
Financial Time ◽  
Analysis Technique ◽  
Recurrence Quantification ◽  
Us Government ◽  
Minimum Number ◽  
Quantification Analysis

Recurrence quantification analysis is a nonlinear time series analysis technique that detects deterministic dependencies in time series. This technique is particularly appropriate for modeling financial time series since it requires no assumptions on stationarity, statistical distribution, and minimum number of observations. This chapter illustrates two applications of recurrence quantification analysis to financial data: a set of international stock indices, and zero-coupon yields of US government bonds.

RECURRENCE QUANTIFICATION ANALYSIS OF TEMPERATURE FLUCTUATIONS IN A HORIZONTAL ROUND HEATED TURBULENT JET

2009 ◽  
Vol 19 (08) ◽  
pp. 2487-2498 ◽  
Author(s):  
T. E. KARAKASIDIS ◽  
A. LIAKOPOULOS ◽  
A. FRAGKOU ◽  
P. PAPANICOLAOU
Keyword(s):  
Time Series ◽  
Temperature Fluctuations ◽  
Recurrence Quantification Analysis ◽  
Turbulent Jet ◽  
Transitional Flow ◽  
Horizontal Line ◽  
Recurrence Quantification ◽  
Quantification Analysis ◽  
Instantaneous Temperature ◽  
Temperature Time

We present an analysis of temperature fluctuations in a horizontal round heated turbulent jet. Instantaneous temperature time series were recorded at several points along a horizontal line in the plane of symmetry of the jet. The time series are analyzed using Recurrence Quantification Analysis (RQA). The variation of characteristic RQA measures is associated with and interpreted via the transitions of the physical state of the fluid from the fully-turbulent flow near the jet centerline to the transitional flow near the boundary of the jet.

scholarly journals Detection of Two-Phase Flow Patterns in a Vertical Minichannel Using the Recurrence Quantification Analysis

2015 ◽  
Vol 9 (2) ◽  
pp. 99-104
Author(s):  
Romuald Mosdorf ◽  
Grzegorz Górski
Keyword(s):  
Time Series ◽  
Two Phase Flow ◽  
Bubbly Flow ◽  
Flow Patterns ◽  
Recurrence Quantification Analysis ◽  
Phase Flow ◽  
Two Phase ◽  
Signal Characteristics ◽  
Recurrence Quantification ◽  
Quantification Analysis

Abstract The two-phase flow (water-air) occurring in square minichannel (3x3 mm) has been analysed. In the minichannel it has been observed: bubbly flow, flow of confined bubbles, flow of elongated bubbles, slug flow and semi-annular flow. The time series recorded by laser-phototransistor sensor was analysed using the recurrence quantification analysis. The two coefficients:Recurrence rate (RR) and Determinism (DET) have been used for identification of differences between the dynamics of two-phase flow patterns. The algorithm which has been used normalizes the analysed time series before calculating the recurrence plots.Therefore in analysis the quantitative signal characteristicswas neglected. Despite of the neglect of quantitative signal characteristics the analysis of its dynamics (chart of DET vs. RR) allows to identify the two-phase flow patterns. This confirms that this type of analysis can be used to identify the two-phase flow patterns in minichannels.

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