#### Dimensional Analysis, Pi Terms, and Dimensionless Numbers: Screencasts

Describes the importance of plotting dimensionless parameters as a function of other dimensionless variables to develop correlations. Uses the coefficient of drag and the Reynolds number as an example.

We suggest that after watching this screencast, you list the important points as a way to increase retention.

Describes how the coefficient of drag is correlated to the Reynolds number and how these dimensionless parameters were found.

We suggest that after watching this screencast, you list the important points as a way to increase retention.

##### Important Equations:

Buckingham Pi Theorem says that you can form \(k\,-\,r\) dimensionless groups (Π-terms).

\(k\) = number of variables in the problem

\(r\) = number of dimensions needed.

Oftentimes \(r\) = 3 because mass, length, and time are used in the problem.