scale-up-analyzer

Solid

Process scale-up analysis skill for dimensional analysis, similarity criteria, and pilot-to-production transitions

AI & Automation 814 stars 53 forks Updated today MIT

Install

View on GitHub

Quality Score: 93/100

Stars 20%
97
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
72
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Scale-Up Analyzer Skill ## Purpose The Scale-Up Analyzer Skill supports process scale-up from laboratory to pilot to production scale using dimensional analysis, similarity criteria, and scale-up correlations. ## Capabilities - Dimensional analysis - Similarity criteria evaluation - Scale-up factor calculation - Heat transfer scale-up - Mass transfer scale-up - Mixing scale-up (power per volume, tip speed) - Reaction scale-up considerations - Risk assessment for scale-up ## Usage Guidelines ### When to Use - Scaling from lab to pilot - Scaling from pilot to production - Evaluating scale-up feasibility - Identifying scale-sensitive parameters ### Prerequisites - Lab/pilot data available - Process fundamentals understood - Critical parameters identified - Target scale defined ### Best Practices - Identify controlling mechanisms - Maintain appropriate similarity criteria - Plan incremental scale-up steps - Validate at each scale ## Process Integration This skill integrates with: - Scale-Up Analysis - Process Simulation Model Development - Performance Testing and Validation ## Configuration ```yaml scale-up-analyzer: scale-up-methods: - geometric-similarity - dynamic-similarity - thermal-similarity scale-factors: - 10x - 100x - 1000x ``` ## Output Artifacts - Scale-up calculations - Similarity analysis - Risk assessments - Scale-up recommendations - Parameter predictions

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

Related Skills