neqsim-optimization-and-doe
neqsim-optimization-and-doe is a Physics, mathematics & simulation skill for AI agents, published by equinor in the neqsim repository on GitHub. Skillspace rates neqsim-optimization-and-doe C (71/100) and it passed the safety scan; the rating is based on static analysis only.
Process flowsheet optimization and Design of Experiments using NeqSim's built-in stack — SQP for constrained NLP, Particle Swarm / Nelder-Mead for global / non-smooth, ProductionOptimizer for throughput, MultiObjectiveOptimizer for Pareto, BatchStudy for parallel sweeps, MonteCarloSimulator for uncertainty, ProcessSimulationEvaluator for SciPy/NLopt/Pyomo bridging. USE WHEN: a task involves minimize/maximize over decision variables, sensitivity studies, Pareto trade-offs, max throughput, parameter screening, or DoE — distinct from `neqsim-production-optimization` which covers reservoir-level decline / gas-lift / network problems.
- Grade
- C
- Quality
- 71 / 100
- Safety
- Passed
- GitHub stars
- 132
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 93 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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