Functionals of the distribution functions

Similar generalizations came more slowly in equilibrium statistical medtanks, but have proved equaUy fruitful. In this section we introduce functionals of arbitrary distribution functions which have the two properties, first, that they are at extrema when the distribution functions are those of the equOibrium state, and secondly, that these extremal values 

Let us therefore consider in the canonical ensemble a dfetribution function which is normalized (cf. 4.2) 

The import of this functional is seen by considering two simple special cases. The first is Un = 0, when p - can be factorized into the product of singlet densities  

when we write F[p], and later n[p], we are implying a restriction on p that means we can equally take F and O to be functionals of the singlet density, Ftp(r)] and n[p(r)], and we shall exploit this property later, e.g. in (4.130) below. A fortiori, F[p = p] or F(p] is a functional of the singlet density p(r). 

The second special case of (4.119) is that when has its equilibrium value p - , cf. (4.61), 

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Hiroike K 1972 Long-range correlations of the distribution functions in the canonical ensemble J. Phys. Soc. Japan 32 904... 

The most probable value of the speed v p can be obtained by differentiation of the distribution function and setting dG(v)/dv = 0 (Kauzmann, 1966 Atkins 1990) to obtain... 

In chemical kinetics, it is often important to know the proportion of particles with a velocity that exceeds a selected velocity v. According to collision theories of chemical kinetics, particles with a speed in excess of v are energetic enough to react and those with a speed less than v are not. The probability of finding a particle with a speed from 0 to v is the integral of the distribution function over that interval... 

View the contour map in several planes to see the general form of the distribution. As long as you don t alter the molecular coordinates, you don t need to repeat the wave function calculation. Use the left mouse button and the HyperChem Rotation or Translation tools (or Tool icons) to change the view of a molecule without changing its atomic coordinates. 

A plot of the last entry versus M gives the integrated form of the distribution function. The more familiar distribution function in terms of weight fraction versus M is given by the derivative of this cumulative curve. It can be obtained from the digitized data by some additional manipulations, as discussed in Ref. 6. 

The complete characterization of a particulate material requires development of a functional relationship between crystal size and population or mass. The functional relationship may assume an analytical form (7), but more frequentiy it is necessary to work with data that do not fit such expressions. As such detail may be cumbersome or unavailable for a crystalline product, the material may be more simply (and less completely) described in terms of a single crystal size and a spread of the distribution about that specified dimension. 

Figure 15 shows how the population density function changes with the addition of classified-fines removal. It is apparent from the figure that fines removal increases the dominant crystal size, but it also increases the spread of the distribution. 

Parameters As a way of characterizing probabihty functions and densities, certain types of quantities called parameters can be defined. For example, the center or gravity of the distribution is defined to be the population mean, which is designated as [L. For the coin toss [L =. 5, which corresponds to the average value of x i.e., for half of the time X will take on a value 0 and for the other half a value 1. The average would be. 5. For the spinning wheel, the average value would also be. 5. 

Errors in advection may completely overshadow diffusion. The amplification of random errors with each succeeding step causes numerical instability (or distortion). Higher-order differencing techniques are used to avoid this instability, but they may result in sharp gradients, which may cause negative concentrations to appear in the computations. Many of the numerical instability (distortion) problems can be overcome with a second-moment scheme (9) which advects the moments of the distributions instead of the pollutants alone. Six numerical techniques were investigated (10), including the second-moment scheme three were found that limited numerical distortion the second-moment, the cubic spline, and the chapeau function. 

It follows that although the thermodynamic functions can be measured for a given distribution system, they can not be predicted before the fact. Nevertheless, the thermodynamic properties of the distribution system can help explain the characteristics of the distribution and to predict, quite accurately, the effect of temperature on the separation. 

The definition of the distribution function given above is valid in the canonical ensemble. This means that N is finite. Of course, N will, in general, be very large. Hence, g(ri,..., r/,) approaches 1 when aU the molecules are far apart but there is a term of order X/N that sometimes must be considered. This problem can be avoided by using the grand canonical ensemble. We will not pursue this point here but do wish to point it out. 

The primary difference between transmission and distribution systems is one of pressure. Transmission systems operate at high pressures (>7bar) while distribution systems operate at low (<75 mbar) and medium (75 mbar to7 bar) pressures. The functions are also different in that the transmission system is used to convey gas over distances and store it, while the distribution system is used to convey gas to the user over a local network. The pipe that conveys gas from the main of the distribution system to the meter control valve of the user is the service. 

If estimated of distribution parameters are desired from data plotted on a hazard paper, then the straight line drawn through the data should be based primarily on a fit to the data points near the center of the distribution the sample is from and not be influenced overly by data points in the tails of the distribution. This is suggested because the smallest and largest times to failure in a sample tend to vary considerably from the true cumulative hazard function, and the middle times tend to lie close to it. Similar comments apply to the probability plotting. 

The analysis of the distribution curves of the fiber filler length after compression permits one to conclude that a variation of the fiber average length at compression may be approximately considered as a function of the value of applied pressure irrespective of the composition of the mixture and the state of the polymer [47]. In this case, it should be taken into consideration that longer fibers are destroyed more easily. This is bound up with destruction due to bending at the fiber contact points, the number of which depends directly on the fiber length. 

Figure 14 shows the displacement of the distribution function towards high / , i.e. the uncoiling of molecules under the influence of stretching for polyethylene (A = 3 x 10-9 m, N = 100 and T = 420 K). This displacement will be characterized by the position of the maximum of the distribution curve, the most probable value of / , i.e. j3m, as a function of x (Fig. 15). Figure 15 also shows the values of stresses a that should be applied to the melt to attain the corresponding values of x (o = xkT/SL, where S is the transverse cross-section of the molecule). 

In its more advanced aspects, kinetic theory is based upon a description of the gas in terms of the probability of a particle having certain values of coordinates and velocity, at a given time. Particle interactions are developed by the ordinary laws of mechanics, and the results of these are averaged over the probability distribution. The probability distribution function that is used for a given macroscopic physical situation is determined by means of an equation, the Boltzmann transport equation, which describes the space, velocity, and time changes of the distribution function in terms of collisions between particles. This equation is usually solved to give the distribution function in terms of certain macroscopic functions thus, the macroscopic conditions imposed upon the gas are taken into account in the probability function description of the microscopic situation. 

Discussion of the Equation.—The Boltzmann equation describes the manner in which the distribution function for a system of particles, /x = /(r,vx,f), varies in terms of its independent variables r, the position of observation vx, the velocity of the particles considered and the time, t. The variation of the distribution function due to the external forces acting on the particles and the action of collisions are both considered. In the integral expression on the right of Eq. (1-39), the Eqs. (1-21) are used to express the velocities after collision in terms of the velocities before collision the dynamics of the collision process are taken into account in the expression for x(6,e), from Eqs. (1-11) and (1-12), which enters into the k of Eqs. (1-21). Alternatively, as will be shown to be useful later, the velocities before and after collision may be expressed, by Eq. (1-20), in terms of G,g, and g the dynamics of the collision comes into the relation between g and g of Eq. (1-19). 

Boltzmann s H-Theorem. —One of the most striking features of transport theory is seen from the result that, although collisions are completely reversible phenomena (since they are based upon the reversible laws of mechanics), the solutions of the Boltzmann equation depict irreversible phenomena. This effect is most clearly seen from a consideration of Boltzmann s IZ-function, which will be discussed here for a gas in a uniform state (no dependence of the distribution function on position and no external forces) for simplicity. 

The quantities n, V, and (3 /m) T are thus the first five (velocity) moments of the distribution function. In the above equation, k is the Boltzmann constant the definition of temperature relates the kinetic energy associated with the random motion of the particles to kT for each degree of freedom. If an equation of state is derived using this equilibrium distribution function, by determining the pressure in the gas (see Section 1.11), then this kinetic theory definition of the temperature is seen to be the absolute temperature that appears in the ideal gas law. 

The hydrodynamic equations are a set of five equations involving the five simple moments of the distribution function, n (or />), v ... 

Bather than using the Chapman-Enskog procedure directly, we shall employ the technique of Burnett,12 which involves an expansion of the distribution function in a set of orthogonal polynomials in particle-velocity space. 

Expansion Polynomials.—The techniques to be discussed here for solving the Boltzmann equation involve the use of an expansion of the distribution function in a set of orthogonal polynomials in particle velocity space. The polynomials to be used are products of Sonine polynomials and spherical harmonics some of their properties will be discussed in this section, while the reason for their use will be left to Section 1.13. 

The moments of the distribution function can be amply related to the expansion coefficients. Using the fact that ( ) andF (0,9>) are unity, we have for the number density ... 

If the interval r is large compared with the time for a collision to be completed (but small compared with macroscopic times), then the arguments of the distribution functions are those appropriate to the positions and velocities before and after a binary collision. The integration over r2 may be replaced by one over the relative distance variable r2 — rx as noted in Section 1.7, collisions taking place during the time r occur in the volume g rbdbde, where g is the relative velocity, and (6,e) are the relative collision coordinates. Incomplete collisions, or motions involving periodic orbits take place in a volume independent of r when Avx(r) and Av2(r) refer to motion for which a collision does not take place (or to the force-field free portion of the... 

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