Abstract :

Chemical Reaction Networks Often Exhibit Highly Nonlinear Dynamic Behavior Due To Complex Interactions Among Reactants, Intermediates, And Catalysts. Among Various Nonlinear Phenomena, Homoclinic Bifurcations Play A Crucial Role In Determining Transitions Between Stable And Unstable System States, Oscillatory Behavior, And The Emergence Of Complex Temporal Dynamics. Understanding And Modeling These Bifurcations Are Essential For Predicting Reaction Mechanisms, Controlling Process Stability, And Optimizing Chemical Reactor Performance. Homoclinic Bifurcations Occur When A System Trajectory Departs From And Returns To The Same Saddle Equilibrium Point, Resulting In Significant Qualitative Changes In System Dynamics. Such Phenomena Are Frequently Observed In Autocatalytic Reactions, Combustion Systems, Biochemical Pathways, And Industrial Chemical Processes. This Study Presents A Comprehensive Investigation Into The Modeling And Inverse Analysis Of Homoclinic Bifurcations In Chemical Reaction Networks. Mathematical Models Based On Nonlinear Ordinary Differential Equations Are Employed To Describe Reaction Kinetics And Dynamic Interactions Among Chemical Species. Bifurcation Analysis Techniques Are Utilized To Identify Critical Parameter Values Associated With The Onset Of Homoclinic Behavior. Furthermore, Inverse Analysis Methods Are Applied To Estimate Unknown Reaction Parameters And Reconstruct System Dynamics From Observed Experimental Data. Numerical Simulations Are Conducted To Evaluate The Influence Of Kinetic Parameters On System Stability And Bifurcation Structures. The Results Demonstrate That Inverse Modeling Significantly Enhances The Identification Of Homoclinic Bifurcation Points And Improves The Understanding Of Complex Reaction Dynamics. The Study Contributes To The Development Of Reliable Analytical Frameworks For Nonlinear Chemical Systems And Supports Advanced Process Monitoring, Prediction, And Control In Chemical Engineering Applications.

Published:

16-12-2022

Issue:

Vol. 22 No. 12 (2022)

Page Nos:

44-53

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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