System identification of lumped parameter models for weakly nonlinear systems

2019 ◽  
Vol 450 ◽  
pp. 78-95 ◽  
Author(s):  
P.S. Heaney ◽  
O. Bilgen
Keyword(s):  
System Identification ◽  
Nonlinear Systems ◽  
Weakly Nonlinear ◽  
Lumped Parameter ◽  
Lumped Parameter Models

Lumped parameter models for two-ventricle and healthy and failing extracardiac Fontan circulations

2021 ◽  
Author(s):  
Matthew G Doyle ◽  
Marina Chugunova ◽  
S Lucy Roche ◽  
James P Keener
Keyword(s):  
Single Ventricle ◽  
Left Ventricular ◽  
Sensitivity Analyses ◽  
Surgical Strategies ◽  
Lumped Parameter ◽  
Lumped Parameter Models ◽  
Fontan Failure ◽  
Existence Of Periodic Solutions ◽  
Mathematical Definitions ◽  
Extracardiac Fontan

Abstract Fontan circulations are surgical strategies to treat infants born with single ventricle physiology. Clinical and mathematical definitions of Fontan failure are lacking, and understanding is needed of parameters indicative of declining physiologies. Our objective is to develop lumped parameter models of two-ventricle and single-ventricle circulations. These models, their mathematical formulations and a proof of existence of periodic solutions are presented. Sensitivity analyses are performed to identify key parameters. Systemic venous and systolic left ventricular compliances and systemic capillary and pulmonary venous resistances are identified as key parameters. Our models serve as a framework to study the differences between two-ventricle and single-ventricle physiologies and healthy and failing Fontan circulations.

Lumped-parameter models for low-temperature geothermal fields and their application

Geothermics ◽  
2005 ◽  
Vol 34 (6) ◽  
pp. 728-755 ◽  
Author(s):  
Hulya Sarak ◽  
Mustafa Onur ◽  
Abdurrahman Satman
Keyword(s):  
Low Temperature ◽  
Lumped Parameter ◽  
Geothermal Fields ◽  
Lumped Parameter Models

scholarly journals Spectral analysis of vibration in weakly non-linear systems

2000 ◽  
Vol 22 (3) ◽  
pp. 181-192
Author(s):  
Nguyen Tien Khiem
Keyword(s):  
Nonlinear Systems ◽  
Spectral Density ◽  
Density Function ◽  
Asymptotic Methods ◽  
Random Excitation ◽  
Spectral Density Function ◽  
Kolmogorov Equation ◽  
Spectral Structure ◽  
Random Load ◽  
Weakly Nonlinear

The weakly nonlinear systems subjected to deterministic excitations have been fully and deeply studied by use of the well developed asymptotic methods [1-4]. The systems excited by a random load have been investigated mostly using the Fokker-Plank-Kolmogorov equation technique combined with the asymptotic methods [5-8]. However, the last approach in most successful cases allows to obtain only a stationary single point probability density function, that contains no information about the correlation nor' consequently, the spectral structure of the response. The linearization technique [9, 10] in general permits the spectral density of the response to be determined, but the spectral function obtained by this method because of the linearization eliminates the effect of the nonlinearity. Thus, spectral structure of response of weakly nonlinear systems to random excitation, to the author's knowledge, has not been studied enough. This paper deals with the above mentioned problem. The main idea of this work is the use of an analytical simulation of random excitation given by its spectral density function and afterward application of the well known procedure of the asymptotic method to obtain an asymptotic expression of the response spectral density function. The obtained spectral relationship covers the linear system case and especially emphasizes the nonlinear effect on the spectral density of response. The theory will be illustrated by an example and at the end of this paper there will be a discussion about the obtained results.  

scholarly journals Data derived NARMAX Dst model

2011 ◽  
Vol 29 (6) ◽  
pp. 965-971 ◽  
Author(s):  
R. J. Boynton ◽  
M. A. Balikhin ◽  
S. A. Billings ◽  
A. S. Sharma ◽  
O. A. Amariutei
Keyword(s):  
Mathematical Model ◽  
Solar Wind ◽  
System Identification ◽  
Nonlinear Systems ◽  
Wide Class ◽  
Geomagnetic Storms ◽  
Output Data ◽  
Dst Index ◽  
Geomagnetic Indices ◽  
Input And Output

Abstract. The NARMAX OLS-ERR methodology is applied to identify a mathematical model for the dynamics of the Dst index. The NARMAX OLS-ERR algorithm, which is widely used in the field of system identification, is able to identify a mathematical model for a wide class of nonlinear systems using input and output data. Solar wind-magnetosphere coupling functions, derived from analytical or data based methods, are employed as the inputs to such models and the outputs are geomagnetic indices. The newly deduced coupling function, p1/2V4/3BTsin6(θ/2), has been implemented as an input to model the Dst dynamics. It was shown that the identified model has a very good forecasting ability, especially with the geomagnetic storms.

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