SciML / SciML/ModelOrderReduction.jl
Modal Truncation
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 43
- Forks
- 8
- Avg merge
- 11h 47m
- Merged PRs (30d)
- 14
Description
From the catch-all tracking issue https://github.com/SciML/ModelOrderReduction.jl/issues/78
Implement modal truncation / dominant-pole model reduction for LTI systems.
https://people.kth.se/~hsan/modred_files/intro_modred.pdf
Reference list (pyMOR LTI MOR checklist): https://github.com/pymor/pymor/issues/388#issuecomment-892486556
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the catch-all tracking issue #78 and review the linked modal-reduction paper and pyMOR LTI MOR checklist. Define the scope and expected integration for modal truncation or dominant-pole model reduction of LTI systems before identifying the implementation entry points and validation needed.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- hpc
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100