Dear bldg-sim?rs,

I?m interested in how people save time and improve accuracy when it comes to calibrated simulation.

Calibrated simulation attempts to model a vast amount of parameters. In comparison to regression methods it?s completely overspecified. We do it in the hope of creating a model (a ?digital twin?) that gives us many more what-if? scenarios than regression could on its own.

However, the process is often fraught with dead ends. Of course it is! There are too many details. We can waste a lot of time on getting one parameter right, only to find it has little effect. Even worse, we could overlook something major and compensate with our own erroneous assumptions. Or, we can work through a whole model and find something very late on, causing us to backtrack over previous work. The act of calibration seems beyond detailed management because of the sheer number of building types, servicing approaches, operational parameters, embedded issues (this is a longer list but I?ve ran out of words?).

The exam question is:

* Does anybody follow a simple high level framework (a bit like Maslow) for calibration?

Sorry. I could have asked that at the start of the email ?

All the best

Chris