How to deal with large models in BPS

[DaJansenGit]

When we deal with large models in BPS, we are confronted with numerous problems that do not occur (or do not occur as intensively) in small models. I'm talking about models with a large amount of stories and spaces and a file size > 100 MB usually. Even if the file size is not always an indicator for model size and complexity. Following, you can find a list of problems and potential solutions to cover them.

Problems and potential Solutions

• Loading and processing the model takes a lot of time. This could be improved by increasing the general performance of the code. See #242
• When dealing with models with a large amount of elements and spaces we are confronted with a lot of decisions, e.g. due to unclear space usages (required for enrichment of usage conditions).
  • If we have around 300 decisions, nobdy wants to deal with this via command line Input or even WebUI selection, if every decisions needs to picked via dropdown.
  • This is especially frustrating when we need to wait several minutes for the code to reach the point and then need to do all the inputs.
  • A potential solution might be to integrate a function into IfcCheck task, that checks if there are a lot of upcoming decisions and if yes, the user will be offered the choice to answer the decisions via an input sheet (excel file maybe?). This could be much more efficient due to copy paste possibility and better overview than popping up decisions one after each other. I opened a seperate issue for this #590
  • One very easy solution would be to allow to select one usage for all spaces
  • ...