Model order reduction

Model order reduction is like taking a big cake and making it smaller, but still keeping the main flavors of the cake. But instead of cake, we're talking about math models (which are like recipes that describe how things work).

Imagine you have a super big math model (recipe) that describes how something works, like how airplanes fly or how heat moves in a house. This model is so big that it takes a lot of time and space to work with it.

Now, let's say you want to simplify this model and make it smaller, so it's easier and faster to work with. You don't want to lose the important parts of the model, but you want to get rid of the extra details that aren't as important.

So, you take the original recipe (model), look at it super carefully, and figure out which parts aren't that important. Then, you throw those parts away, keep the important parts, and make a smaller recipe that still tastes good (a smaller model that still works well).

Now, you have a simpler and faster model that won't take as much time and space to work with. It's like a smaller cake that still tastes good (and does what it's supposed to do). This is model order reduction!