Real-time modelling of wavepackets in turbulent jets

2017 ◽  
Vol 821 ◽  
pp. 458-481 ◽  
Author(s):  
Kenzo Sasaki ◽  
Selene Piantanida ◽  
André V. G. Cavalieri ◽  
Peter Jordan
Keyword(s):  
Transfer Function ◽  
Moving Average ◽  
Equations Of Motion ◽  
Turbulent Jets ◽  
Autoregressive Moving Average ◽  
Mean Flow ◽  
Full Field ◽  
Input Multiple Output ◽  
Flow Variables ◽  
Empirical Approaches

Three methods are considered for estimating the downstream evolution of wavepackets in turbulent jets based on upstream measurements. The parabolised stability equations are used to compute a transfer function between axially and radially separated points in the flow, and the performance of this theoretical model is compared with that of two empirical approaches, direct transfer function calculation and autoregressive moving-average exogenous system identification, both of which require unsteady experimental data. The three approaches, which perform equally well, prove suitable for estimation of the downstream evolution of wavepackets using pressure data measured in the near-nozzle region. Over distances of the order of a couple of jet diameters, correlations of up to 80 % are observed between estimation and measurement. The performance deteriorates as axial separation between input and output is increased. While the two empirical approaches are limited in terms of both the number of input–output pairs and the number of flow variables that can be reasonably considered, the parabolised stability equations-based approach has no such limitation and can be used to perform full-field estimates comprising all of the dependent variables; in this it constitutes a potentially formidable means by which to perform single-input–multiple-output estimation. It has the further advantage of not requiring unsteady data for its construction, the only necessary ingredients being the mean flow and the linearised equations of motion.

scholarly journals Predicting Lower Band Chorus With Autoregressive‐Moving Average Transfer Function (ARMAX) Models

2019 ◽  
Vol 124 (7) ◽  
pp. 5692-5708
Author(s):  
Laura E. Simms ◽  
Mark J. Engebretson ◽  
Craig J. Rodger ◽  
Jesper W. Gjerloev ◽  
Geoffrey D. Reeves
Keyword(s):  
Transfer Function ◽  
Moving Average ◽  
Autoregressive Moving Average ◽  
Lower Band

Multivariate Transfer Function-Noise Model of River Flow for Hydropower Operation

1986 ◽  
Vol 17 (3) ◽  
pp. 185-202 ◽  
Author(s):  
Tryggvi Olason ◽  
W. Edgar Watt
Keyword(s):  
Time Series ◽  
Transfer Function ◽  
River Flow ◽  
Moving Average ◽  
Noise Model ◽  
Lead Times ◽  
Autoregressive Moving Average ◽  
Northern Ontario ◽  
Daily Data ◽  
Univariate Time Series

The formulation of multivariate autoregressive moving average (ARMA) time series models and their transfer function noise (TFN) form is described. Development of a multivariate TFN model is difficult if the multiple inputs are correlated. Various methods for developing a multivariate TFN models with correlated multiple inputs are critically reviewed. A simple approach to developing multiple input TFN models with correlated inputs is described. This approach is successfully applied to developing a forecasting model for average daily flow of the Mattagami River at Little Long Generation Station in Northern Ontario, Canada. System inputs are upstream and tributary flows. Only three years of daily data for the period April 1st to October 31st were required to calibrate the model. Two further years were used to verify the model. Forecasts at lead times of one and two days were good for both calibration and verification periods. The average standard errors were 8% of average inflows (1-day lead) and 18% (2-day lead). The system produces significantly better forecasts than a univariate time series model.

Using The Fully Modified M Method In Estimating The Effect Of Cultivated Area On Barley Production In Iraq For The Period 1970-2018

2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Estimation Method ◽  
Estimation Methods ◽  
Autoregressive Moving Average ◽  
Moving Average Models ◽  
Error Terms ◽  
Relationship Of ◽  
The Relationship ◽  
Barley Crop

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.

Model of vortex flow of charge in a vessel with turbine impeller

1987 ◽  
Vol 52 (8) ◽  
pp. 1888-1904
Author(s):  
Miloslav Hošťálek ◽  
Ivan Fořt
Keyword(s):  
Boundary Conditions ◽  
Equations Of Motion ◽  
Theoretical Data ◽  
Eddy Diffusion ◽  
Quantitative Agreement ◽  
Creeping Flow ◽  
Model Parameters ◽  
Mean Flow ◽  
Two Dimensional Flow ◽  
Vorticity Transport

A theoretical model is described of the mean two-dimensional flow of homogeneous charge in a flat-bottomed cylindrical tank with radial baffles and six-blade turbine disc impeller. The model starts from the concept of vorticity transport in the bulk of vortex liquid flow through the mechanism of eddy diffusion characterized by a constant value of turbulent (eddy) viscosity. The result of solution of the equation which is analogous to the Stokes simplification of equations of motion for creeping flow is the description of field of the stream function and of the axial and radial velocity components of mean flow in the whole charge. The results of modelling are compared with the experimental and theoretical data published by different authors, a good qualitative and quantitative agreement being stated. Advantage of the model proposed is a very simple schematization of the system volume necessary to introduce the boundary conditions (only the parts above the impeller plane of symmetry and below it are distinguished), the explicit character of the model with respect to the model parameters (model lucidity, low demands on the capacity of computer), and, in the end, the possibility to modify the given model by changing boundary conditions even for another agitating set-up with radially-axial character of flow.

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