Classical dimensional analysis in its original form starts by expressing the units for derived quantities, such as force, in terms of power products of basic units etc. This suggests the use of toric ideal theory from algebraic geometry. Within this the Graver basis provides a unique primitive basis in a well-defined sense, which typically has more terms than the standard Buckingham approach. Some textbook examples are revisited and the full set of primitive invariants found. First, a worked example based on convection is introduced to recall the Buckingham method, but using computer algebra to obtain an integer matrix from the initial integer matrix holding the exponents for the derived quantities. The matrix defines the dimensionless variables. But, rather than this integer linear algebra approach it is shown how, by staying with the power product representation, the full set of invariants (dimensionless groups) is obtained directly from the toric ideal defined by . One candidate for the set of invariants is a simple basis of the toric ideal. This, although larger than the rank of , is typically not unique. However, the alternative Graver basis is unique and defines a maximal set of invariants, which are primitive in a simple sense. In addition to the running example four examples are taken from: a windmill, convection, electrodynamics and the hydrogen atom. The method reveals some named invariants. A selection of computer algebra packages is used to show the considerable ease with which both a simple basis and a Graver basis can be found.
Citation: Atherton MA, Bates RA, Wynn HP (2014) Dimensional Analysis Using Toric Ideals: Primitive Invariants. PLoS ONE 9(12): e112827. https://doi.org/10.1371/journal.pone.0112827
Editor: Enrico Scalas, Universita' del Piemonte Orientale, Italy
Received: January 29, 2014; Accepted: October 15, 2014; Published: December 1, 2014
Copyright: © 2014 Atherton et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The third author received funding from Leverhulme Trust Emeritus Fellowship (1-SST-U445) and United Kingdom EPSRC grant: MUCM EP/D049993/1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Dimensional analysis has a long history. It was discussed by Newton and provided useful intuition to Maxwell, see , chapter 3. A recent paper giving popular overview is . The first rigorous and most well-known treatment is by Buckingham –, whose name is attached to the main theorem. Dimensional analysis is still considered a fundamental part of physics and is usually taught at an early stage. It is sometimes studied under a heading of qualitative physics  . In engineering it gives a useful additional tool for the analysis of systems . It is used in engineering design and in experimental design for engineering experiments    and a recent paper with discussion  . It has also been used in economics . For an interesting recent application to turbulence and criticality see  .
We give an algebraic development of dimensional analysis based on the theory of toric ideals and toric varieties. Although this is essentially a reformulation, the algebraic theory itself is by no means elementary and the theory of toric ideals is a live branch of algebraic geometry. We have used  and the recent comprehensive volume . We shall see that the methods give all primitive invariants for a particular problem, in a well-defined sense, which are typically more than given by the Buckingham method.
Within mathematical physics dimensional analysis can also be seen as an elementary application of the theory of Lie groups and invariants, when the group is the scale group defined by multiplication. We shall draw on  in Section 5.
1.1 Basic dimensional analysis
The basic idea of dimensional analysis is that physical systems use fundamental quantities, or units, of mass (), length () and time (). To this list may be added various others such as temperature () and current (), depending on the domain. The extent to which derived quantities can be expressed in terms of goes to the heart of physics but we shall not delve deeply. Mathematical models for physical systems use so-called derived quantities such as: force, energy, momentum, capacity etc. Dimensional analysis tells us that each one of these quantities has units which have a power product representation. Below are a few examples from mechanics.
We note that the formulae for the expression of derived units have integer powers. This is critical for our development: it makes them algebraic in the sense of polynomial algebra.
In a physical system we may be interested in a special collection of derived quantities. The task of dimensional analysis is to derive dimensionless variables with a view to finding, by additional theory or experiment, or both, the relationship between these dimensionless variables. As mentioned, the key theorem in the area is due to Buckingham. In this section we explain it with an example.
Rather than use the notation we assume that there are some basic quantities of interest which we label . Each such quantity is assumed to have the scaling property, namely if the fundamental units, which we now call are scaled up or down this induces a transformation on the . Whether this means simply a change in units or actual physical scaling of the system is sometimes unclear in the literature, but we shall prefer the latter interpretation. Thus the area of a rectangle with sides of length and , and which would have units , would be transformed into . under a physical scaling, , of the length. Although the same scaling would occur with a change of units.
We use the arrow to indicate that scaling of the fundamental quantities implies a scaling of the derived quantity. With a collection of derived quantities we have one such transformation for each . Dimensionless quantities are rational functions of derived quantities for which there is no scaling: is the identity.
Here is a well known example which we shall use as our running example. It concerns a body in an incompressible fluid and the derived quantities of interest are fluid density (), fluid velocity (), object diameter (), fluid dynamic viscosity () and fluid resistance () (drag force). Taking the units into account the transformation is:(1)
After a little algebra, or formal use of Buckingham's theorem, we can derive dimensionaless quantitiesand it is straightforward to check that in each case the cancel so there is no scaling. The first quantity is Reynolds number and the second is sometimes referred to as the dimensional drag.
To repeat, the term dimensionless is interpreted by saying that replacing each by the in the transformation in (1), leaves the unchanged: they are rational invariants of the transformation.
The dimensionless principal, for our example, embodied in the Buckingham theorem is that any function of which is invariant under is a function of and which we write: .
This matrix has rank 3 and we can find a full rank integer kernel matrix, namely an integer matrix which has rank 2 and such that . This is readily computed using existing functions in computer algebra, as oppose to a numerical package which may, for example, give a non-integer orthonormal kernel basis. The nullspace or kernal commands in Maple can be used. For the above we obtained using these commandsand with a sign change in the first row we obtain
The key point is that the rows of give the exponents of in and , above.
This gives an alternative to , above, namely . The approach of this paper clarifies, among other issues, the problem of the choice of which this example exposes.
Power Products and Toric Ideals
Algebraic geometry is concerned with ideals and their counterpart algebraic varieties. We give a very short description here. (Note that we shall use for variables in an abstract algebraic setting reserving for “real” problems.)
A standard reference is  and in this and the next paragraph we present a very short summary of the first two chapters. We start with the ring of all polynomials in variables over a field k: . A set of polynomials in , is an ideal if (i) zero is in , (ii) is preserved under addition and (iii) implies is in for any in . By a theorem of Hilbert all ideals are finitely generated. That is we can find a set of basis polynomials such that any can be written for some in . An ideal gives a variety as the set of such that for all . It will also be enough to work within the field of rationals.
Modern computational algebra has benefitted hugely from the theory of Gröbner bases and the algorithms that grew out of the theory, notably the Buchburger algorithm. We will need one more concept, that of a monomial term ordering, or term ordering for short. Monomials , where ie , drive the theory. A monomial term ordering, written is (i) a total (linear) ordering with as the unique minimal element and the additional condition (ii) implies , for all . Since such an ordering is linear every polynomial has a leading term with respect to the ordering: . If we fix the monomial ordering, , the Gröbner basis of an ideal with respect to is a basis such that the ideal generated by all leading terms in the ideal is the same as that generated by the set of leading terms of the basis . Given and the Buchburger algorithm delivers . We will be concerned with the set of all Gröbner bases as ranges over all monomial term orderings. This is called the fan and is finite, although it can be very large.
One of the main definitions of a toric ideal fits perfectly with the power product transformations of dimensional analysis. It is this observation which motivates this paper. We shall emphasize the connection by using the same notation: , with or according to emphasis, in both the algebraic and physical theories.
The following development can be taken from a number of books, but  is our main source. The main steps in the definition are.
1. The polynomial ring over variables .
2. A matrix with columns labeled .
By formal elimination we mean in the algebraic sense as explained in , Chapter 3, that is obtaining the so-called elimination ideal: the intersection of the original ideal with the subring of polynomial excluding the .
The last equation can be written , which is equivalent to being in the kernel of .
The connection with dimensional analysis now becomes clear. Let us put dimensional analysis on a similar notational footing, only using instead of . Start with a matrix with columns . The general form of the mapping in (1), in the introduction, becomes(2)
Now, suppose we have a possible invariant . We first express in terms of the . We use to denote integer vectors with non-negative entries to distinguish the positive from the negative exponents. Thus, we write
We are now in a position to test invariance. The necessary and sufficient condition for to be an invariant is that substituting each by in the right hand side of (3) for leaves unchanged. But the condition for this is, replacing “”, by “”
Theorem 2.1 A variable , for non-negative integer vectors is a dimensional invariant in a system defined by a matrix , with derived variable , if and only if . Moreover the set of all corresponding quantitiesform the toric ideal with generator matrix .
A brief summary is that the set of all dimensionless variables associated with a set of quantities defined by an integer matrix are exactly those given by the toric ideal .
We can give a minimal set of generators for the toric ideal of our running example. We use the Toric function on the computer algebra package CoCoA, , which takes the matrix as input. Simply to ease the notation in the use of computer algebra we use , for . The script with output is.
Toric([[1,0,0,1,1], [−3,1,1,−1,1], [0,−1,0,−1,−2]]);
The second two terms give the dimensional variables from the alternative kernel matrix , above. A key point is that the toric ideal may have more generators than the rank of the kernel in Buckingham's theorem. The next section amplifies this point.
2.1 Saturation and Gröbner bases
To summarise, the toric version of dimensional analysis says that we can generate dimensionless quantities from the toric ideal which is the elimination ideal of the original power product representation, being careful to use elimination in the proper algebraic sense.
A lattice ideal associated with an integer defining matrix is the ideal based on a full rank kernel matrix. That is if is with rank then we find an integer matrix , with rank with rows with .
But, as we have seen, this is one fewer generators than the toric ideal. However, given any such lattice ideal we can obtain the toric ideal using a process called saturation. The process has two steps. Fix the defining matrix compute a kernel and let be a lattice ideal associated with .
2. Eliminate from to give the toric ideal for . That is, the toric ideal is obtained as the elimination ideal for .
The process of elimination in this saturation process is a formal procedure and leads to a reduced Gröbner basis of the toric ideal which depends in general on the monomial ordering used in the elimination algorithm. Reduced means all coefficients of the leading terms are 1 and removing basis terms gives a ring which cannot contained the remove term; essentially there is no redundancy.
Saturation gives an explanation for the fact that the toric ideal contains, but is not necessarily equal to the lattice ideal: the addition condition giving the variety defined by forces all the to be nonzero. Translated into the original the toric ideal description of the dimensionless quantities has the physical interpretation that it gives the full set of rational polynomial invariants when none of the defining variables is allowed to be zero. This removal of zeros is intimately connected with the more abstract definitions of toric varieties but we do not develop this here, see .
The Gröbner Fan, Primitive Invariants and the Graver Basis
A natural question, given the ease of computing invariants using toric methods, is whether the invariants obtained in this way are in some sense minimal. This turns out to be the case. We can illustrate this with our example. A little inspection of the basis shows that we cannot get simpler invariants from this basis by multiplication (or division): ifthen which, although a new invariant, is not obtained by reducing the numerator or denominator of any of the original invariants.
Definition 1 A basis element of is called is called primitive if there is no other (different) basis element invariant such that such that divides and divides . We call an invariant primitive if and only if is primitive as a basis element of .
The following is straightforward alternative definition.
Definition 2 A dimensionless invariant is primitive if and only if it cannot be written as the product of two other such invariants which do not have common variables.
In the above example and have in common. In linear programming notation the condition is that there are no such that and , recalling that “” means entrywise.
Lemma 4.6 of  is
Lemma 3.1 Every invariant obtained from a reduced Gröbner basis of is primitive.
Note that in what follows we are a little lazy in not to distinguish an invariant from its inverse.
As mentioned, as we range over all monomial term orderings defining the individual Gröbner basis we obtain the complete Gröbner fan and by the Lemma 3.1 and our definition all resulting invariants are primitive. This union of bases is called the universal Gröbner basis and the computer programme Gfan is recommended to compute the fan .
Definition 3 The set of all primitive basis elements (which may be larger than the universal Gröbner basis), is called the Graver basis.
Algorithm 7.2 of  can be used to compute the Graver basis. The method starts by constructing from an extended matrix called the Lawrence lifting:where the zero is a zero matrix and is a identity matrix. Then introducing more derived variables to make a set a toric ideal is constructed using . Finally, set .
In this case the set is the same as given by the fan. That is, the universal Gröbner basis and the Graver basis are the same.
For each of the examples below we give the derived quantities using the classical notation, (i) the matrix (ii) a single toric ideal basis given by the default function on CoCoA and (iii) a full set of primitive basis elements, that is the Graver basis, given by the maple ToricIdealBasis command and the Lawrence lifting. From this a full set of primitive invariants is immediate. It turns out that for all except one of our examples (windmill) the Graver basis is also the universal Gröbner basis. We mention when we find well-known invariants.
This standard problem is taken from , Section 9.3. (We have changed there to ).
It concerns a simple windmill widely used to pump water. The units are: is
Since there are only two algebraically independent invariants. The standard argument may suggest testing the relationship between any two independent invariants, for example in a wind tunnel. An important question, which should be the subject of further research, is say which two or, more generally, whether the dimensional analysis is sufficiently trusted to test only one pair and infer other relationships from the algebra.
4.2 Forced convection
The interest is in the following derived quantities: the forced convection coefficient , the velocity, , the characteristic length of the heat transfer surface , the conductivity of the fluid , the dynamic viscosity, , the fluid specific heat capacity, and the fluid density, . The fundamental dimensions are and two new ones temperature () and energy (). The table of units is
forced convection coefficient,
heat transfer surface length,
thermal conductivity of the fluid,
fluid dynamic viscosity,
fluid specific heat capacity,
As an exercise we take six basic quantities for electro-dynamics and use the literature to give some expression in terms of mass , length , time and current (). We do not have any particular electromagnetic device in mind, but simply try to find some dimensionless quantities. The following is one version:
Note that only has rank 3. It turns out that this is a complete list of primitive basis elements.
4.4 Hydrogen atom
Toric ideals are embedded in advanced models in physics but one can get some way with simple dimensional analysis. This example is given in some form by a number of authors. We found , section 1.3.1, useful. The hydrogen atom consists of a proton and a neutron and the Bohr radius is the distance between them. We have used slightly non-standard notation. In a somewhat cavalier manner we have introduced the speed of light as a derived quantity.
mass of electron,
( is elementary charge);
speed of light,
It is not known whether this list has been given explicitly before.
The Wider Picture: Group Invariance
Dimensional analysis should be considered as a special case of the theory of group invariance and in an attempt to suggest a natural generalisation we very briefly sketch the theory of invariants.
We start with the action of a Lie group acting on a manifold in . The manifold will be our model and the group something to do with our physical understanding. The orbit of for a point in be the set of all for all in . If is invariant under then . This sets up an equivalence relation with members of in which the same orbit are equivalent. The collection of equivalence classes is denoted by the quotient and the projection maps every member of of into its correct equivalence class. Under suitable conditions is a manifold in its own right and we say that acts regularly on . Also, the mapping can be used to set up a coordinate system on and note that itself is an invariant. This discussion leads naturally to the following.
Proposition 5.1 Let a group act regularly on a manifold M. A manifold defined by a smooth function is a set . It is -invariant if and only if there is a function defining a smooth sub-manifold on such thatwhere is the projection from to .
An interpretation of the toric variety is as characterising the orbits of the scale group of transformation, as discussed above. We have not formally proved the Buckingham theorem, but drawing on the above discussion it is given as Theorem 2.22 in .
Limitations of the Study, Open Questions and Future Work
We have seen that the toric ideal method, via the Graver basis, is a fast way to compute all primitive invariants in dimensional analysis. There are some areas of further study which this suggests.
The first area arises from the possibility that different physical systems may yield different types of toric ideal or variety. The most important general class is normal toric varieties. Briefly, such varieties are related to polyhedral cones and polyhedra with integer or rational generators. The standard approach is to take the a suitable cone and compute its Hilbert basis, which is a set of integer generators of the dual cone giving all integer grid points in that cone. From this there is a natural toric ideal. But an open problem, it seems to the authors, is whether this rich theory of normal varieties and polyhedra has a role in classical physics and engineering.
A second area is a natural development from the previous section. A discussion missing from this paper is the way in which differentials are converted to derived quantities. For example velocity, which is , for some length variable and time is allocated the units . One way to keep the advantages of awarding derived quantities to differential terms, but retain differentials is to use combinations of differential and polynomial operators. The algebraic environment which allows this is differential algebra and in particular Weyl algebras. Much of the existing work uses the methods to study identifiability (see ) but the challenge, here, is to find differential-algebraic invariants in the same spirit as the invariants in this paper. A noteworthy development is –, especially in the context of dynamical systems.
Finally, the authors are aware of the value of standard dimensional analysis when the exponents are rational but not necessarily integer. This arises in the work on turbulence mentioned , . This can be studied by changing the base lattice to have fractional levels and the authors are considering research in this area.
Toric ideals are the appropriate framework for dimensional analysis with describe the rational invariants under the multivariate scale group. The key contribution is that the Graver basis, which can be the thought of as a unique “envelope” of bases for the toric ideal and consists of all primitive elements then gives rise to a notion of primitive invariants. These comprise the invariants which cannot be split into the product of two other invariants using disjoint sets of units. The suggestion is that this solves a classical but sometimes unspoken conundrum in dimensional analysis: namely that invariants produced by the celebrated Buckingham method are not unique. In addition the Graver basis is easily computed using computer algebra. In some examples we are able to find some named invariants, all, satisfyingly, primitive. But also, because the Graver basis is larger than a minimal basis for the toric ideal the methods throws up new primitive invariants which may attract scientific interest.
Many computations in this paper were performed by using Maple a trademark of Waterloo Maple Inc.
Wrote the paper: HPW. Supplied most of the engineering/physics input including ellucidation and interpretation of example: MA. Computational work on Grobner base, Engineering design motivation: RB.
- 1. Albrecht MC, Nachtsheim CJ, Albrecht TA, Cook RD (2013) Experimental design for engineering dimensional analysis. Techometrics 55:257–270.
- 2. Barnett W (2007) Dimensions and economics: some problems. Quarterly J. Austrian Economics 1:95–104.
- 3. Bhaskar R, Nigan A (1990) Qualitative physics using dimensional analysis. Artificial Intelligence 45:73–111.
- 4. Buckingham E (1919) On physically similar systems: illustration of the use of dimensional analysis. Physics Review 4:345–376.
- 5. Buckingham E (1915) The principle of similitude. Nature 96:396–397.
- 6. Buckingham E (1915) Model experiments and the forms of empirical equations. Trans. Amer. Soc. Mech. Eng. 37:263–296.
- 7. Chapman SC, Watkins NW (2009) Avalanching systems under intermediate driving rate. Plasma Phys. Control Fusion 51 : (124006).
- 8. Chapman SC, Rowlands G, Watkins NW (2009) Macroscopic control parameter for avalanche models of bursty transport. Physics of Plasmas 16 : (012303)
- 9. CoCoA: a system for doing Computations in Commutative Algebra. Available: http://cocoa.dima.unige.it
- 10. Cox DA, Little JB, O'Shea D (2007) Ideals, varieties, and algorithms: an introduction to computational algebraic geometry and commutative algebra. Third Edition. Springer, New York. 553 p.
- 11. Cox DA, Little JB, Schenck HK (2011) Toric varieties. Graduate Studies in Mathematics: 124. American Mathematical Society, Providence, Rhode Island. 841 p.
- 12. D'Agostino S (2002) A history of the ideas of theoretical physics. Kluwer, Dordrecht. 381 p.
- 13. Davis T (2013) Comment: dimensional analysis in statistical engineering. Technometrics 55:271–274.
- 14. Gibbings JC (1986) The systematic experiment. Cambridge University Press, Cambridge. 352 p.
- 15. Gibbings JC (2011) Dimensional analysis. Springer, London. 312 p.
- 16. Grove DM, Davis TP (1992) Engineering, quality and experimental design. Longmans, London. 361 p.
- 17. Hubert E, Labahn G (2013) Scaling Invariants and Symmetry Reduction of Dynamical Systems. Foundations Computational Mathematics 13:479–516.
- 18. Hubert E, Kogan I (2007) Rational Invariants of a Group Action. Construction and Rewriting. Journal of Symbolic Computation 42:203–217.
- 19. Hubert E (2013) Rational Invariants of a Group Action. Journees Nationales de Calcul Formel 3: (hal.inria.fr/hal-00839283)
- 20. Jensen AN (2011) Gfan, a software system for Gröbner fans and tropical varieties. http://home.imf.au.dk/jensen/software/gfan/gfan.html.
- 21. Bolster D, Hershberger RE, Donelly RJ (2011) Dynamic similarity, the dimensionless science. Physices today. 64:(9): 42–47.
- 22. Margaria G, Riccomagno E, Chappell MJ, Wynn HP (2001) Differential algebra methods for the study of the structural identifiability of rational function state-space models in the biosciences. Mathematical Biosciences 174:1–26.
- 23. Olver PJ (1986) Application of Lie groups to differential equations. Springer, New York. 513 p.
- 24. Smith H (1991) An introduction to quantum mechanics. World Scientific, New York. 285 p.
- 25. Sturmfels B (1996) Gröbner Bases and convex polytopes. University Lecture Note Series: 8 Amer. Math. Soc, Providence, Rhode Island. 162 p.
- 26. Szirtes T (2007) Applied Dimensional Analysis and Modeling. Butterworth-Heinemann, Burlington. 820 p.