Bifurcations discussion

One may also observe a transition to a type of defect-mediated turbulence in this Turing system (see figure C3.6.12 (b). Here the defects divide the system into domains of spots and stripes. The defects move erratically and lead to a turbulent state characterized by exponential decay of correlations [59]. Turing bifurcations can interact with the Hopf bifurcations discussed above to give rise to very complicated spatio-temporal patterns [63, 64]. 

The saddle-node bifurcations discussed in Section 111. A play a crucial role in the dynamics of the molecules investigated, because the stable PO bom at the bifurcation follows the reaction pathway over a large energy range. Consequently, the quantum states that are scarred by this PO stretch further and further along the reaction pathway and can be considered as the precursors of the... 

As usual in bifurcation theory, there are several other names for the bifurcations discussed here. The supercritical pitchfork is sometimes called a forward bifurcation, and is closely related to a continuous or second-order phase transition in sta-... 

To date, no chemical reaction has produced chiral asymmetry in this simple manner. However, symmetry breaking does occur in the crystallization of NaC103 [9, 10] in far from equilibrium conditions. The simple model however leads to interesting conclusions regarding the sensitivity of bifurcation discussed below. 

This Is a didactic Introduction to some of the techniques of bifurcation theory discussed In this article. 

This route should already be familiar to us from our discussion of the logistic map in chapter 4, Prom that chapter, we recall that the Feigenbaum route calls for a sequence of period-doubling bifurcations pitchfork bifurcations versus the Hopf bifurcations of the Landau-Hopf route) such that if subharmonic bifurcations are observed at Reynolds numbers TZi and 7 2, another can be expected at TZ determined by... 

The bifurcation of the second kind was established by Poincar6, but the bifurcation of the first kind was established more recently (1937) by A. Andronov.4 For further discussion, see this reference, or reference 6. The direct analytical approach to the theory of bifurcation is very difficult, and the only known case in which it could be carried through is that of Andronov. 

This equation has been derived as a model amplitude equation in several contexts, from the flow of thin fluid films down an inclined plane to the development of instabilities on flame fronts and pattern formation in reaction-diffusion systems we will not discuss here the validity of the K-S as a model of the above physicochemical processes (see (5) and references therein). Extensive theoretical and numerical work on several versions of the K-S has been performed by many researchers (2). One of the main reasons is the rich patterns of dynamic behavior and transitions that this model exhibits even in one spatial dimension. This makes it a testing ground for methods and algorithms for the study and analysis of complex dynamics. Another reason is the recent theory of Inertial Manifolds, through which it can be shown that the K-S is strictly equivalent to a low dimensional dynamical system (a set of Ordinary Differentia Equations) (6). The dimension of this set of course varies as the parameter a varies. This implies that the various bifurcations of the solutions of the K-S as well as the chaotic dynamics associated with them can be predicted by low-dimensional sets of ODEs. It is interesting that the Inertial Manifold Theory provides an algorithmic approach for the construction of this set of ODEs. 

We discuss some characteristics of the bifurcation diagram of the K-S for low values of the parameter a (for details see (7)). We will work in one dimension and with periodic boundary conditions. In what follows, we always subtract the mean drift... 

The mechanism of these transitions is nontrivial and has been discussed in detail elsewhere Q, 12) it involves the development of a homoclinic tangencv and subsequently of a homoclinic tangle between the stable and unstable manifolds of the saddle-type periodic solution S. This tangle is accompanied by nontrivial dynamics (chaotic transients, large multiplicity of solutions etc.). It is impossible to locate and analyze these phenomena without computing the unstable, saddle-tvpe periodic frequency locked solution as well as its stable and unstable manifolds. It is precisely the interactions of such manifolds that are termed global bifurcations and cause in this case the loss of the quasiperiodic solution. 

However, because of the strong nonllnearltles In the reactor fiow problem, continuation procedures must be used to obtain a good Initial guess for the Newton Iteration. A simple first order continuation scheme falls at fiow transition points (bifurcations) where the Jacobian, G, becomes singular. To circumvent this problem an arclength continuation scheme discussed by Keller (26.27) and Chan (2S.) Is used which leads to the Infiated system ... 

Procedures enabling the calculation of bifurcation and limit points for systems of nonlinear equations have been discussed, for example, by Keller (13) Heinemann et al. (14-15) and Chan (16). In particular, in the work of Heineman et al., a version of Keller s pseudo-arclength continuation method was used to calculate the multiple steady-states of a model one-step, nonadiabatic, premixed laminar flame (Heinemann et al., (14)) a premixed, nonadiabatic, hydrogen-air system (Heinemann et al., (15)). 

Besides the two most well-known cases, the local bifurcations of the saddle-node and Hopf type, biochemical systems may show a variety of transitions between qualitatively different dynamic behavior [13, 17, 293, 294, 297 301]. Transitions between different regimes, induced by variation of kinetic parameters, are usually depicted in a bifurcation diagram. Within the chemical literature, a substantial number of articles seek to identify the possible bifurcation of a chemical system. Two prominent frameworks are Chemical Reaction Network Theory (CRNT), developed mainly by M. Feinberg [79, 80], and Stoichiometric Network Analysis (SNA), developed by B. L. Clarke [81 83]. An analysis of the (local) bifurcations of metabolic networks, as determinants of the dynamic behavior of metabolic states, constitutes the main topic of Section VIII. In addition to the scenarios discussed above, more complicated quasiperiodic or chaotic dynamics is sometimes reported for models of metabolic pathways [302 304]. However, apart from few special cases, the possible relevance of such complicated dynamics is, at best, unclear. Quite on the contrary, at least for central metabolism, we observe a striking absence of complicated dynamic phenomena. To what extent this might be an inherent feature of (bio)chemical systems, or brought about by evolutionary adaption, will be briefly discussed in Section IX. 

Once the parametric representation of the Jacobian is obtained, the possible dynamics of the system can be evaluated. As detailed in Sections VILA and VII.B, the Jacobian matrix and its associated eigenvalues define the response of the system to (small) perturbations, possible transitions to instability, as well as the existence of (at least transient) oscillatory dynamics. Moreover, by taking bifurcations of higher codimension into account, the existence of complex dynamics can be predicted. See Refs. [293, 299] for a more detailed discussion. 

From a mathematical point of view, the onset of sustained oscillations generally corresponds to the passage through a Hopf bifurcation point [19] For a critical value of a control parameter, the steady state becomes unstable as a focus. Before the bifurcation point, the system displays damped oscillations and eventually reaches the steady state, which is a stable focus. Beyond the bifurcation point, a stable solution arises in the form of a small-amplitude limit cycle surrounding the unstable steady state [15, 17]. By reason of their stability or regularity, most biological rhythms correspond to oscillations of the limit cycle type rather than to Lotka-Volterra oscillations. Such is the case for the periodic phenomena in biochemical and cellular systems discussed in this chapter. The phase plane analysis of two-variable models indicates that the oscillatory dynamics of neurons also corresponds to the evolution toward a limit cycle [20]. A similar evolution is predicted [21] by models for predator-prey interactions in ecology. 

After the bifurcation behavior is examined, the role of flame-wall thermal interactions in NOj is studied. First, adiabatic operation is considered. Next, the roles of wall quenching and heat exchange in emissions are discussed. Two parameters are studied the inlet fuel composition and the hydrod3mamic strain rate. Results for the stagnation microreactor are contrasted with the PSR to understand the difference between laminar and turbulent flows. 

Figure 26.56 is the corresponding plot for 12% inlet H2 in air. In this case, there is an extinction at about 1000 K for both reactors. The qualitative features are similar to that of the PSR discussed above for 28% H2 in air. For such fuel-lean mixtures, the flame is attached to the surface. As a result, the thermal coupling between the surface and the gas phase is strong, and reduction in surface temperature affects the entire thermal boundary layer resulting in significant reduction of NOj,. These results indicate that the bifurcation behavior, in terms of extinction, determines the role of flame-wall thermal interactions in emissions. 

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