networkx-flow-networks

Name: networkx-flow-networks
Availability: InStock
Author: Soljourner

Model hydraulic networks and pump configurations using NetworkX graph analysis.

45|14|Updated Nov 7, 2025

Search Tags:#flow-analysis #networkx #hydraulics #graph-theory #piping-network #max-flow

Ready to run

npx skills add https://github.com/Soljourner/claude-engineering-skills --skill networkx-flow-networks

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: networkx-flow-networks
Source: https://github.com/Soljourner/claude-engineering-skills/tree/main/skills/packages/networkx-flow-networks
Command: npx skills add https://github.com/Soljourner/claude-engineering-skills --skill networkx-flow-networks

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enables modeling of hydraulic networks and multi-pump configurations using graph theory, allowing rapid insight into flow distribution, bottlenecks, and reliability.

Core Features & Use Cases

Build directed graphs to represent pipes, junctions, and pumps using NetworkX.
Perform flow analyses (max-flow/min-cut), path analysis, and redundancy checks to optimize system design.
Visualize networks and simulate simple pump configurations for planning and education.

Quick Start

Install the required Python packages and run the bundled examples to model a representative piping network.

Frequently Asked Questions about networkx-flow-networks

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

FAQPage Schema

How do I model a hydraulic network using graph theory in Python?▼

Model a hydraulic network by building directed graphs with NetworkX to represent pipes, junctions, and pumps. This graph theory approach maps flow paths and pump configurations to analyze water distribution.

Can I perform a max-flow analysis on a piping network with NetworkX?▼

Yes, you can perform max-flow analysis on a piping network using NetworkX. The skill applies max-flow and min-cut algorithms to your directed graph to identify flow bottlenecks and optimize pipe layouts.

Does this graph theory approach support redundancy checks for water distribution networks?▼

Yes, graph theory supports redundancy checks for water distribution networks. By analyzing path connectivity within your NetworkX directed graph, you can assess system reliability and identify alternative flow paths.

What is the best way to optimize pump arrangements in a multi-pump configuration?▼

Optimize pump arrangements by simulating multi-pump configurations within a NetworkX directed graph. This allows rapid insight into flow distribution and helps you plan the most efficient setup for your piping network.

Are there limitations when using NetworkX to simulate simple pump configurations?▼

NetworkX simulates simple pump configurations suitable for planning and education. It focuses on graph-based flow analysis rather than complex fluid dynamics, making it best for layout optimization rather than detailed hydraulic engineering.

Can I visualize flow paths and bottlenecks in my piping network?▼

Yes, you can visualize flow paths and bottlenecks in your piping network. The skill uses NetworkX to visualize the directed graph structure, helping you see flow distribution and identify critical areas for system reliability.