Phase-space flow

A partial differential equation is then developed for the number density of particles in the phase space (analogous to the classical Liouville equation that expresses the conservation of probability in the phase space of a mechanical system) (32>. In other words, if the particle states (i.e. points in the particle phase space) are regarded at any moment as a continuum filling a suitable portion of the phase space, flowing with a velocity field specified by the function u , then one may ask for the density of this fluid streaming through the phase space, i.e. the number density function n(z,t) of particles in the phase space defined as the number of particles in the system at time t with phase coordinates in the range z (dz/2). 

Figure 4 shows a schematic portrait of the phase space flows (denoted by arrows) in the ( i(p, q),Pi(p, q)) plane and the caricature of the corresponding... 

Figure 4. A schematic portrait of the stable and unstable invariant manifolds and the phase-space flows on (4i(p,q),Pi(p,q)).

Another of Poincare s new methods was the reduction of the continuous phase-space flow of a classical dynamical system to a discrete mapping. This is certainly one of the most useful techniques ever introduced into the theory of dynamical systems. Modem journals on nonlinear dynamics abound with graphical representations of Poincare mappings. A quick glance into any one of these journals will attest to this fact. Because of the usefulness and the formal simplicity of mappings, this topic is introduced and discussed in Section 2.2. 

Since the phase space flow conserves the equilibrium distribution, we also have... 

The final equality results from the fact that the phase-space flow generated by time evolution conserves probability. Because the reversibility criterion is satisfied, the simple acceptance probabilities from Eqs. (1.27) and (1.29) can be used, provided a stationary distribution p exists. 

The form of eqn (7.33) is termed full normal form (full NF) here. Figure7.6(c) depiets the phase space flow in the case where the full NF theory is applicable. In addition to the reaction mode aetion I, all the vibrational mode... 

Figure 7.6(b) depicts the phase space flow in the case where the partial NF is applicable. The projection of trajectories on the bath mode coordinates can exhibit any complicated motions because we allow any coupling terms in eqn (7.41). The projection on the NF reaction coordinates q, p ), however, shows regular structure given by the constancy of /j, whereby the phase space objects are readily identifiable. 

The question of non-classical manifestations is particularly important in view of the chaos that we have seen is present in the classical dynamics of a multimode system, such as a polyatomic molecule, with more than one resonance coupling. Chaotic classical dynamics is expected to introduce its own peculiarities into quantum spectra [29, 77]. In Fl20, we noted that chaotic regions of phase space are readily seen in the classical dynamics corresponding to the spectroscopic Flamiltonian. Flow important are the effects of chaos in the observed spectrum, and in the wavefiinctions of tire molecule In FI2O, there were some states whose wavefiinctions appeared very disordered, in the region of the... 

It is convenient to analyse tliese rate equations from a dynamical systems point of view similar to tliat used in classical mechanics where one follows tire trajectories of particles in phase space. For tire chemical rate law (C3.6.2) tire phase space , conventionally denoted by F, is -dimensional and tire chemical concentrations, CpC2,- are taken as ortliogonal coordinates of F, ratlier tlian tire particle positions and velocities used as tire coordinates in mechanics. In analogy to classical mechanical systems, as tire concentrations evolve in time tliey will trace out a trajectory in F. Since tire velocity functions in tire system of ODEs (C3.6.2) do not depend explicitly on time, a given initial condition in F will always produce tire same trajectory. The vector R of velocity functions in (C3.6.2) defines a phase-space (or trajectory) flow and in it is often convenient to tliink of tliese ODEs as describing tire motion of a fluid in F with velocity field/ (c p). 

Chaotic attractors are complicated objects with intrinsically unpredictable dynamics. It is therefore useful to have some dynamical measure of the strength of the chaos associated with motion on the attractor and some geometrical measure of the stmctural complexity of the attractor. These two measures, the Lyapunov exponent or number [1] for the dynamics, and the fractal dimension [10] for the geometry, are related. To simplify the discussion we consider tliree-dimensional flows in phase space, but the ideas can be generalized to higher dimension. 

For autonomous Hamiltonians = 0 the solution in phase space depends only on t — to where the t-flow 4>t,n is defined as... 

A mapping is said to be symplectic or canonical if it preserves the differential form dp A dq which defines the symplectic structure in the phase space. Differential forms provide a geometric interpretation of symplectic-ness in terms of conservation of areas which follows from Liouville s theorem [14]. In one-degree-of-freedom example symplecticness is the preservation of oriented area. An example is the harmonic oscillator where the t-flow is just a rigid rotation and the area is preserved. The area-preserving character of the solution operator holds only for Hamiltonian systems. In more then one-degree-of-freedom examples the preservation of area is symplecticness rather than preservation of volume [5]. 

A convenient and constructive approach to attain symplectic maps is given by the composition of symplectic maps, which yields again a symplectic map. For appropriate Hk, the splittings (6) and (7) are exactly of this form If the Hk are Hamiltonians with respect to the whole system, then the exp rLnk) define the phase flow generated by these Hk- Thus, the exp TL-Hk) are symplectic maps on the whole phase space and the compositions in (6) and (7) are symplectic maps, too. Moreover, in order to allow for a direct numerical realization, we have to find some Hk for which either exp(rL-Kfc) has an analytic solution or a given symplectic integrator. 

Regarding two pliase flow, pressurized liquid above its noniial boiling point will start to flash when released to aUiiospheric pressure, and two pliase flow will result. Two-pliase flow is also likely to occur from depressurization of tlie vapor space above a volatile liquid, especially if the liquid is viscous (e.g., greater tlian 500 cP) or has a tendency to foam. Fauske and Epstein liave provided tlie following practical calculation guidelines for two-phase flashing flows. The discharge of subcooled or saturated liquids is described by... 

Dissipative systems whether described as continuous flows or Poincare maps are characterized by the presence of some sort of internal friction that tends to contract phase space volume elements. They are roughly analogous to irreversible CA systems. Contraction in phase space allows such systems to approach a subset of the phase space, C P, called an attractor, as t — oo. Although there is no universally accepted definition of an attractor, it is intuitively reasonable to demand that it satisfy the following three properties ([ruelle71], [eckmanSl]) ... 

The cissertion that Hamiltonian flows preserve phase-space volumes is known as Louiville s Theorem, and is easily verified from equation 4.3 by using the Hamiltonian equations 4.5 ... 

Figure 2.40 shows the unsteady flow upstream of the ONE in one of the parallel micro-channels of d = 130 pm at = 228kW/m, m = 0.044 g/s (Hetsroni et al. 2001b). In this part of the micro-channel single-phase water flow was mainly observed. Clusters of water appeared as a jet, penetrating the bulk of the water (Fig. 2.40a). The vapor jet moved in the upstream direction, and the space that it occupied increased (Fig. 2.40b). In Fig. 2.40a,b the flow moved from bottom to top. These pictures were obtained at the same part of the micro-channel but not simultaneously. The time interval between events shown in Fig. 2.40a and Fig. 2.40b is 0.055 s. As a result, the vapor accumulated in the inlet plenum and led to increased inlet temperature and to increased temperature and pressure fluctuations.

On the continuum level of gas flow, the Navier-Stokes equation forms the basic mathematical model, in which dependent variables are macroscopic properties such as the velocity, density, pressure, and temperature in spatial and time spaces instead of nf in the multi-dimensional phase space formed by the combination of physical space and velocity space in the microscopic model. As long as there are a sufficient number of gas molecules within the smallest significant volume of a flow, the macroscopic properties are equivalent to the average values of the appropriate molecular quantities at any location in a flow, and the Navier-Stokes equation is valid. However, when gradients of the macroscopic properties become so steep that their scale length is of the same order as the mean free path of gas molecules,, the Navier-Stokes model fails because conservation equations do not form a closed set in such situations. 

Similar convection-diffusion equations to the Navier-Stokes equation can be formulated for enthalpy or species concentration. In all of these formulations there is always a superposition of diffusive and convective transport of a field quantity, supplemented by source terms describing creation or destruction of the transported quantity. There are two fundamental assumptions on which the Navier-Stokes and other convection-diffusion equations are based. The first and most fundamental is the continuum hypothesis it is assumed that the fluid can be described by a scalar or vector field, such as density or velocity. In fact, the field quantities have to be regarded as local averages over a large number of particles contained in a volume element embracing the point of interest. The second hypothesis relates to the local statistical distribution of the particles in phase space the standard convection-diffusion equations rely on the assumption of local thermal equilibrium. For gas flow, this means that a Maxwell-Boltzmann distribution is assumed for the velocity of the particles in the frame-of-reference co-moving with the fluid. Especially the second assumption may break dovm when gas flow at high temperature or low pressure in micro channels is considered, as will be discussed below. 

In Sections IVA, VA, and VI the nonequilibrium probability distribution is given in phase space for steady-state thermodynamic flows, mechanical work, and quantum systems, respectively. (The second entropy derived in Section II gives the probability of fluctuations in macrostates, and as such it represents the nonequilibrium analogue of thermodynamic fluctuation theory.) The present phase space distribution differs from the Yamada-Kawasaki distribution in that... 

The availability of a phase space probability distribution for the steady state means that it is possible to develop a Monte Carlo algorithm for the computer simulation of nonequilibrium systems. The Monte Carlo algorithm that has been developed and applied to heat flow [5] is outlined in this section, following a brief description of the system geometry and atomic potential. 

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