Simulating low pressure in your hydraulic model can identify/confirm the cause of the problem and point you to the right solution.

Real-world problems are ugly, and simplifications and assumptions need to be made to make the problem solvable. The researchers tend to gloss over these assumptions—if they mention them at all. I think many researchers may not even realize that they are making them. Most researchers are graduate students and their advisors, who have never worked on real-world problems. As a starting point for their work, they rely on prior research papers that contain assumptions that the prior authors did not mention. As a result, real-world complications are often lost in legacy papers.

Last fall, I did a hydraulics quiz and readers seemed to enjoy it. So, here’s another one. See how you do and feel free to share. Answers are at the end, but don’t peek.

In my work in water and wastewater hydraulics, the two that show up most of the time are the Reynolds number and Froude number. A small Reynolds number indicates that viscous forces dominate, while a large value says that inertial forces dominate. A large Froude number indicates rapid flow, while a small number points to tranquil flow.

There are several reasons. First, the pressure is so high and constant in water systems in most developed countries that the effects of pressure on flow is negligible.

They are nonlinear, partial differential equations which are about the worst kinds of equations to solve. About the only things that can make them worse are changes in state (e.g. steam condensing) or non-Newtonian fluids (e.g. mudflows). Numerous researchers have shown that it is impossible to arrive at a closed-form, analytical solution in the form v(r, φ, z) =… When people work with these equations these days, they almost always use numerical solutions. I heard a story once that Albert Einstein started his research in solving the Navier-Stokes equations but gave up because it was too difficult. He moved on to easy topics like quantum physics and relativity. I haven’t been able to verify this, but it makes for a good story.

The problem was that the people who developed the data underlying the GIS/CAD (I’ll call it GIS in this blog) used to build the model were not careful in how they laid out intersections. They would run the same pipe down several blocks without consideration of whether crossing pipes were interconnected. While we have tools in our model to clean up these issues (View > Network Navigator), it is best to avoid them from the start. Read Tom Walski’s blog and learn how to fix a model where the piping at intersections was poorly represented.