scholarly journals Flow* 1.2: More Effective to Play with Hybrid Systems

10.29007/1w4t ◽  
2018 ◽  
Author(s):  
Xin Chen ◽  
Sriram Sankaranarayanan ◽  
Erika Abraham
Keyword(s):  
Hybrid Systems ◽  
Non Linear ◽  
Efficient Scheme ◽  
Linear Odes

This paper gives a brief overview of the new features introduced in the latest version of the tool Flow*. We mainly describe the new efficient scheme for integrating linear ODEs. We show that it can efficiently handle the challenging benchmarks on which, to the best of our knowledge, only SpaceEx works. Moreover, it is also possible to extend the method to deal with unbounded initial sets. A comparison between Flow* 1.2 and SpaceEx on those benchmarks is given. Besides, we also investigate the scalability Flow* 1.2 based on our non-linear line circuit benchmarks.

Non-Linear ODEs Of First and Second Order

2007 ◽  
pp. 239-364
Author(s):  
Mircea V. Soare ◽  
Petre P. Teodorescu ◽  
Ileana Toma
Keyword(s):  
Second Order ◽  
Non Linear ◽  
Linear Odes

A computationally efficient scheme for the non-linear diffusion equation

2009 ◽  
Vol 373 (17) ◽  
pp. 1573-1577
Author(s):  
P. Termonia ◽  
H. Van de Vyver
Keyword(s):  
Diffusion Equation ◽  
Computationally Efficient ◽  
Linear Diffusion ◽  
Non Linear ◽  
Efficient Scheme

scholarly journals Passive control of magneto-nanomaterials transient flow subject to non-linear thermal radiation

2021 ◽  
pp. 169-169
Author(s):  
Ikram Ullah ◽  
Sayed Shah ◽  
Gul Zaman ◽  
Taseer Muhammad ◽  
Zakir Hussain
Keyword(s):  
Thermal Radiation ◽  
Passive Control ◽  
Stretching Sheet ◽  
Transient Flow ◽  
Brownian Diffusion ◽  
Convection Flow ◽  
Stretching Surface ◽  
Surface Drag ◽  
Non Linear ◽  
Linear Odes

Present investigation is concerned with mixed convection flow of Williamson nanoliquid over an unsteady slandering stretching sheet. Aspects of non-linear thermal radiation, Brownian diffusion and thermophoresis effects are addressed. Non-linear stretching surface of varying thickness induce the flow. Novel features of combined zero mass flux and convective conditions are accounted. Use of appropriate transformations results into the non-linear ODEs. Computations for the convergent solutions are provided. Graphs are designed for interpretations to quantities. Nusselt number and surface drag are computationally inspected. Our computed results indicate that attributes of nanoparticles and non-linear thermal radiation enhance the temperature distribution.

scholarly journals Flow*: An Analyzer for Non-linear Hybrid Systems

2013 ◽  
pp. 258-263 ◽  
Author(s):  
Xin Chen ◽  
Erika Ábrahám ◽  
Sriram Sankaranarayanan
Keyword(s):  
Hybrid Systems ◽  
Non Linear

Application of interacting multiple model-based fault detection method on a hydraulic two-tank system

2018 ◽  
Vol 8 (2) ◽  
pp. 42-51
Author(s):  
M Hajizadeh ◽  
M G Lipsett
Keyword(s):  
Fault Detection ◽  
Confusion Matrix ◽  
Detection Algorithm ◽  
Fault Detection And Diagnosis ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Non Linear ◽  
Tank System ◽  
Efficient Scheme ◽  
Estimation Scheme

This paper addresses the problem of designing a fault identification and detection algorithm for non-linear systems. Timely identification and detection of a fault in a system is crucial in condition monitoring systems. However, finding the source of the failure is not trivial in systems with large numbers of components and complex component relationships. In this paper, an efficient scheme to detect adverse changes in system reliability and find the failed component is proposed, based on the interacting multiple model (IMM) algorithm, with fault detection and diagnosis formulated as a hybrid multiple model estimation scheme. The proposed approach provides an integrated framework for fault detection, diagnosis and state estimation. Its performance is illustrated for fault detection of a non-linear two-tank system. The proposed method can be used with different kinds of filters, using the confusion matrix and classification accuracy as comparison metrics. A particle filter is used with the IMM algorithm and its performance is compared to the linear Kalman filter as a comparative case concerning the improvement that can be achieved when going beyond the consideration that the system is linear.

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