ME 516: Macroscale Heat Transfer

Welcome to ME 516 Macroscale Heat Transfer!

Solutions to HT problems that are 1. Relevant, 2. Credible, 3. Efficient.

Why ‘Macroscale’ and not Conduction or Radiative (or Convective for that matter) heat transfer as the official course title suggests? How often do you find a problem that is purely heat transfer through just one mode? Seldom — and when you do, the solution is fairly easy to find. Yet probably 90% of all graduate level Mechanical Engineering programs in the US teach three independent courses for each of these modes, and have done so for over 70 years.

Things change. While the modes of heat transfer and the known solutions to heat transfer problems have not, the methods and tools we have for solving heat transfer problems have changed dramatically. Artificial Intelligence (AI) and Finite Element Analysis (FEA) software are powerful tools for solving heat transfer problems. These tools have already changed heat transfer so much that some are abandoning the classical approaches all together.

So why would I double down on classical Heat Transfer in the face of these game changing technologies? AI, FEA, and online libraries have made solving problems so easy that the traditional mathematics challenges are no longer the limiting step in Heat Transfer analyses. The limiting problem now very much could be knowing what problem to solve — i.e. knowing what physics to include in your problem. If you’re unable to do this task, the complex software tools are still able to provide solutions to the conditions you applied, however, you are more likely to obfuscate the issues that really matter, and will likely waste considerable computing time along the way.

My goal by the end of this class is for you to be able to:

1. Identify Relevant physical phenomena in heat transfer problems through quick back of the envelope calculations. By knowing what matters, and what is most sensitive to the problem, you can quickly decide what is needed in the simulation and what is not.
2. Quickly derive Credible differential equations with solutions/solvers available in textbooks and open source software. You should be able to quantify your confidence in the simulation before you are finished.
3. Follow a process for Efficient solving and reporting solutions. After completing only the calculations necessary, having an ability to plot/display the solutions to efficiently communicate what matters to key stakeholders.

In short, you’ll be able to look at a situation, quickly point out what matters, and efficiently provide a valuable result. Here’s the draft Syllabi for Fall 2019: ME 516 syllabus Fall 2019.