fluid-model

Modify control CSVs and run real_predict for gas-network scenario predictions.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/zly7/pipelineLLM --skill fluid-model
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: fluid-model
Source: https://github.com/zly7/pipelineLLM/tree/main/backend/agent/skills/fluid-model
Command: npx skills add https://github.com/zly7/pipelineLLM --skill fluid-model

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables repeatable, Windows-based execution of the fluid-model gas-network dispatch workflow by adjusting control CSVs (Boundaries, etc.), patching job-configs in place, running real_predict, and summarizing outputs for comparison.

Core Features & Use Cases

  • Modify control CSVs for predefined 001–264 scenarios and apply on-demand patches to job-configs.
  • Run the real_predict workflow from the project root, capturing and comparing results across runs.
  • Generate a concise summary of differences to support quick validation and decision making.

Quick Start

Update the Windows control CSVs and patch the in-place job-configs, then run python -m real_predict.main with the default 001 scenario.

Frequently Asked Questions about fluid-model

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate batch fluid-model predictions for gas-network scheduling on Windows?

Automate batch fluid-model predictions by modifying control CSVs, patching job-configs in place, running the real_predict workflow from the project root, and summarizing outputs for comparison across predefined scenarios.

What is the real_predict workflow for gas-pipeline simulation?

The real_predict workflow executes gas-network dispatch predictions by applying patched job-configs and modified boundary control CSVs, then generating concise summaries of output differences to support validation and decision making.

Can I run gas-pipeline batch-processing simulations outside the default 001 scenario?

Yes, gas-pipeline batch-processing applies to predefined scenarios 001 through 264, defaulting to 001, allowing you to modify control CSVs and run multiple simulation sets for comparative output analysis.

Do I need specific path conventions to run real_predict for gas-network dispatch?

Yes, real_predict requires explicit project-root path conventions on Windows to ensure correct relative access for in-place patching of job-configs and execution of the gas-network dispatch workflow.

What's the best way to compare gas-network simulation outputs across multiple runs?

Compare gas-network simulation outputs by running the real_predict workflow with modified control CSVs, which automatically generates a concise summary of differences to support quick validation and decision making.

Why does my gas-pipeline simulation fail when patching job-configs on Windows?

Gas-pipeline simulation job-config patching fails on Windows when explicit project-root path conventions are not followed, preventing correct relative access required by the real_predict workflow.