1. Introduction
In this post I outline the Buckingham
Theorem which shows how to use dimensional analysis to compute answers to seemingly intractable physical problems. For instance, in
Geoffrey Taylor used the theorem to work out the energy payload released by the 1945 Trinity test atomic explosion in New Mexico simply by looking at slow motion video records. My main source for this post is Bluman and Kumei (1989).
Frame from slow motion footage of the Trinity nuclear test with a distance measurement showing the blast radius as well as a time measure showing seconds elapsed since denotation.
2. Basic Framework
The Buckingham
Theorem concerns physical problems with the following form: There is a variable of interest,
, which is some unknown function of
different physical quantities
.
(1) ![]()
Each of these physical quantities is composed of measurements in only
fundamental dimensions labeled
. Thus, I can define a dimension operator which gives the dimensions of an arbitrary variable
and write its output as:
(2) ![Rendered by QuickLaTeX.com \begin{align*} \mathtt{dim}[z] &= \prod_{m=1}^{M} c_m^{a_m} \end{align*}](http://www.alexchinco.com/wp-content/ql-cache/quicklatex.com-301820102a65da59da5b9b73b24019eb_l3.png)
So, for example, if
is measuring pressure on the surface of a table, I could write
where
,
,
and
.
Definition (Dimensionless Quantity):
An arbitrary variableis dimensionless if:
(3)
3. Main Result
Now, I show how to reformulate this problem and apply linear algebra to the dimensional exponents to derive a characterization of the solution to
as a function of dimensionless quantities. First, I define
as an
matrix of dimensional exponents for
and
as the
vector of dimensional exponents for
:
(4) 
Next, we know that if
has full rank, then there will
solutions to the system of equations
. Define
as this
matrix of solutions.
(5) 
Finally, define
as the solution to system of equations
:
(6) ![]()
With these objects in hand, I can now state the Buckingham
Theorem.
Proposition (Buckingham
):
A physical systemwith
fundamental dimensions can be restated as:
(7)
where
,
is an unknown function and
are dimensionless parameters constructed from the physical parameters
using equations of the form below:
(8)
4. An Example
I now give an example of how to employ this theorem by working out the nuclear payload example from the introduction. For more information on this example, take a look at this blog post. Suppose that an atomic blast has a shock wave radius of
with variables:
: Energery released by the explosion,
: Time elapsed since the explosion took place,
: Initial density, and
: Initial pressure.
For this problem
and
with fundamental dimensions of length
, mass
, and time
yielding the dimensional matrix
written below:
(9) 
The energy (force) released by the bomb is the amount of mass accelerating through a unit square on the surface of the blast wave. Since
, we have only
dimensionless constant which can be computed as the solution to the system of equations
:
(10) 
Setting the scalar free parameter
, I can write
as:
(11) ![]()
The dimension of the shock wave radius
is in units of distance yielding the
dimension matrix below:
(12) ![]()
The system of
equations
has
unknowns:
(13) 
Thus, the vector
will thus be defined up to a single free parameter
:
(14) 
Using the formula
and tuning
, I can compute
as:
(15) ![Rendered by QuickLaTeX.com \begin{align*} \pi &= \delta \cdot \left[ \frac{\epsilon \cdot \tau^2}{\rho} \right]^{-1/5} \end{align*}](http://www.alexchinco.com/wp-content/ql-cache/quicklatex.com-9a8f5f9350b1d0849063950119a56b2d_l3.png)
Combining all of these results yields a formulation for
in terms of a constant
and an unknown function of the dimensionless quantity
:
(16) ![Rendered by QuickLaTeX.com \begin{align*} \delta &= \left[ \frac{\epsilon \cdot \tau^2}{\rho} \right]^{1/5} \cdot g \left( \pi_1 \right) \end{align*}](http://www.alexchinco.com/wp-content/ql-cache/quicklatex.com-fb291bc669a7adf9f8d8af5934fd5601_l3.png)
Taylor expanding around
where
yields a formulation where
with scaling constant
given by:
(17) ![]()
Setting
, the
plot of
vs
yielded an accurate fit where the predicted values fall on the solid line and the (declassified) empirically observed values are denoted by
‘s in the plot below:
