Buckingham π theorem


In engineering, applied mathematics, and physics, the dimensional groups theorem is a key theorem in dimensional analysis, often called pi theorem and/or Buckingham theorem. It is a formalization of Rayleigh's method of dimensional analysis. Loosely, the theorem states that if there is a physically meaningful equation involving a certain number n of physical variables, then the original equation can be rewritten in terms of a set of p = n − k dimensionless parameters 1, 2,..., p constructed from the original variables.
The theorem provides a method for computing sets of dimensionless parameters from the given variables, or nondimensionalization, even if the form of the equation is still unknown.
The Buckingham theorem indicates that validity of the laws of physics does not depend on a specific unit system. A statement of this theorem is that any physical law can be expressed as an identity involving only dimensionless combinations of the variables linked by the law. If the dimensionless combinations' values changed with the systems of units, then the equation would not be an identity, and Buckingham's theorem would not hold.

History

Although named for Edgar Buckingham, the theorem was first proved by French mathematician Joseph Bertrand in 1878. Bertrand considered only special cases of problems from electrodynamics and heat conduction, but his article contains, in distinct terms, all the basic ideas of the modern proof of the theorem and clearly indicates the theorem's utility for modelling physical phenomena. The technique of using the theorem became widely known due to the works of Rayleigh. The first application of the theorem in the general case to the dependence of pressure drop in a pipe upon governing parameters probably dates back to 1892, a heuristic proof with the use of series expansions, to 1894.
Formal generalization of the theorem for the case of arbitrarily many quantities was given first by A. Vaschy in 1892, then in 1911—apparently independently—by both A. Federman and D. Riabouchinsky, and again in 1914 by Buckingham. It was Buckingham's article that introduced the use of the symbol "i" for the dimensionless variables, and this is the source of the theorem's name.

Statement

More formally, the number of dimensionless terms that can be formed, p, is equal to the nullity of the dimensional matrix, and k is the rank. For experimental purposes, different systems that share the same description in terms of these dimensionless numbers are equivalent.
In mathematical terms, if we have a physically meaningful equation such as
where the qi are the n independent physical variables, and they are expressed in terms of k independent physical units, then the above equation can be restated as
where the i are dimensionless parameters constructed from the qi by p = n − k dimensionless equations — the so-called Pi groups — of the form
where the exponents ai are rational numbers.

Significance

The Buckingham theorem provides a method for computing sets of dimensionless parameters from given variables, even if the form of the equation remains unknown. However, the choice of dimensionless parameters is not unique; Buckingham's theorem only provides a way of generating sets of dimensionless parameters and does not indicate the most "physically meaningful".
Two systems for which these parameters coincide are called similar ; they are equivalent for the purposes of the equation, and the experimentalist who wants to determine the form of the equation can choose the most convenient one. Most importantly, Buckingham's theorem describes the relation between the number of variables and fundamental dimensions.

Proof

Outline

It will be assumed that the space of fundamental and derived physical units forms a vector space over the rational numbers, with the fundamental units as basis vectors, and with multiplication of physical units as the "vector addition" operation, and raising to powers as the "scalar multiplication" operation:
represent a dimensional variable as the set of exponents needed for the fundamental units. For instance, the standard gravity g has units of , so it is represented as the vector with respect to the basis of fundamental units.
Making the physical units match across sets of physical equations can then be regarded as imposing linear constraints in the physical-units vector space.

Formal proof

Given a system of n dimensional variables in k fundamental dimensions, write the dimensional matrix M, whose rows are the fundamental dimensions and whose columns are the dimensions of the variables: the th entry is the power of the ith fundamental dimension in the jth variable. The matrix can be interpreted as taking in a combination of the dimensions of the variable quantities and giving out the dimensions of this product in fundamental dimensions. So
is the units of
A dimensionless variable is a quantity with fundamental dimensions raised to the zeroth power, which is equivalent to the kernel of this matrix.
By the rank–nullity theorem, a system of n vectors in k linearly independent dimensions leaves a nullity, p, satisfying, where the nullity is the number of extraneous dimensions which may be chosen to be dimensionless.
The dimensionless variables can always be taken to be integer combinations of the dimensional variables. There is mathematically no natural choice of dimensionless variables; some choices of dimensionless variables are more physically meaningful, and these are what are ideally used.
The International System of Units defines k=7 base units, which are the ampere, kelvin, second, metre, kilogram, candela and mole. It is sometimes advantageous to introduce additional base units and techniques to refine the technique of dimensional analysis

Examples

Speed

This example is elementary but serves to demonstrate the procedure.
Suppose a car is driving at 100 km/h; how long does it take to go 200 km?
This question considers three dimensioned variables: distance d, time t, and velocity v, and we are seeking some law of the form . These variables admit a basis of two dimensions: time dimension T and distance dimension D. Thus there is 3 − 2 = 1 dimensionless quantity.
The dimensional matrix is
in which the rows correspond to the basis dimensions D and T, and the columns to the considered dimensions D, T, and V, where the latter stands for the velocity dimension. The elements of the matrix correspond to the powers to which the respective dimensions are to be raised. For instance, the third column, states that, represented by the column vector, is expressible in terms of the basis dimensions as, since.
For a dimensionless constant, we are looking for vectors such that the matrix-vector product Ma equals the zero vector . In linear algebra, the set of vectors with this property is known as the kernel of the dimensional matrix. In this particular case its kernel is one-dimensional. The dimensional matrix as written above is in reduced row echelon form, so one can read off a non-zero kernel vector to within a multiplicative constant:
If the dimensional matrix were not already reduced, one could perform Gauss–Jordan elimination on the dimensional matrix to more easily determine the kernel. It follows that the dimensionless constant, replacing the dimensions by the corresponding dimensioned variables, may be written:
Since the kernel is only defined to within a multiplicative constant, the above dimensionless constant raised to any arbitrary power yields another dimensionless constant.
Dimensional analysis has thus provided a general equation relating the three physical variables:
or, letting denote a zero of function,
which can be written as
The actual relationship between the three variables is simply. In other words, in this case has one physically relevant root, and it is unity. The fact that only a single value of C will do and that it is equal to 1 is not revealed by the technique of dimensional analysis.

The simple pendulum

We wish to determine the period T of small oscillations in a simple pendulum. It will be assumed that it is a function of the length L, the mass M, and the acceleration due to gravity on the surface of the Earth g, which has dimensions of length divided by time squared. The model is of the form
There are 3 fundamental physical dimensions in this equation: time, mass, and length, and 4 dimensional variables, T, M, L, and g. Thus we need only 4 − 3 = 1 dimensionless parameter, denoted π, and the model can be re-expressed as
where π is given by
for some values of a1,..., a4.
The dimensions of the dimensional quantities are:
The dimensional matrix is:
We are looking for a kernel vector a = such that the matrix product of M on a yields the zero vector . The dimensional matrix as written above is in reduced row echelon form, so one can read off a kernel vector within a multiplicative constant:
Were it not already reduced, one could perform Gauss–Jordan elimination on the dimensional matrix to more easily determine the kernel. It follows that the dimensionless constant may be written:
In fundamental terms:
which is dimensionless. Since the kernel is only defined to within a multiplicative constant, if the above dimensionless constant is raised to any arbitrary power, it will yield another equivalent dimensionless constant.
This example is easy because three of the dimensional quantities are fundamental units, so the last is a combination of the previous. Note that if a2 were non-zero, there would be no way to cancel the M value; therefore a2 must be zero. Dimensional analysis has allowed us to conclude that the period of the pendulum is not a function of its mass.
The model can now be expressed as:
Assuming the zeroes of f are discrete, we can say gT2/L = Cn, where Cn is the nth zero of the function f. If there is only one zero, then gT2/L = C. It requires more physical insight or an experiment to show that there is indeed only one zero and that the constant is in fact given by C = 4π2.
For large oscillations of a pendulum, the analysis is complicated by an additional dimensionless parameter, the maximum swing angle. The above analysis is a good approximation as the angle approaches zero.

Cooling a drink with ice cubes

Drinks cooled with small ice cubes cool faster than drinks cooled with the same mass of larger ice cubes. The common explanation for this phenomenon is that smaller cubes have greater surface area, and this greater area causes greater heat conduction and therefore faster cooling. If this explanation were correct, then it would imply that the rate of cooling should be proportional to, where is the length of the cube edges, and thus the time for the drink to cool should be proportional to. In fact, dimensional analysis shows this common explanation to be incorrect, and gives the surprising result that the time to cool the drink is proportional to.
The important dimensional quantities are the length scale of the cubes , the time , the temperature , the thermal conductivity , and the volumetric heat capacity . The dimensional matrix is:The nullspace of M is 1-dimensional, and the kernel is spanned by the vector and therefore. Therefore, the cooling time of the drink is solved by an implicit functionthat is, when the argument of the function is some constant c. Therefore, the drink cooling time is, so that the cooling time is proportional to the length scale of the ice cube squared, not just the length scale.
Why is the cooling time proportional to and not ? While it's true that the total ice cube surface area is proportional to, that accounts for only one factor in the increased cooling rate. Because the cubes are smaller, the thermal gradients are larger, again by a factor of, which increases the cooling rate by a factor of. So there are two effects that increase the cooling rate, each by a factor of, and the conventional explanation accounts for only one of these.

Other examples

A simple example of dimensional analysis can be found for the case of the mechanics of a thin, solid and parallel-sided rotating disc. There are five variables involved which reduce to two non-dimensional groups. The relationship between these can be determined by numerical experiment using, for example, the finite element method.

Exposition

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