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neqsim-two-phase-flow-regime-screening

neqsim-two-phase-flow-regime-screening is a skill for Claude Code, Codex from equinor/neqsim-community-skills. It costs 87 tokens per session (1,265 once invoked), scanned A, original, Apache-2.0.

An educational calculator that classifies the likely gas-and-liquid flow pattern in a horizontal pipe from their superficial velocities. Superficial velocity is the speed a phase would have if it alone filled the pipe.

In plain words
What is it for?
Use it to screen a horizontal line from phase velocities or basic flow and pipe data, and to decide whether a validated multiphase-flow study is needed.
Why use it?
It gives an early indication of patterns such as stratified, slug, annular, or bubble flow and flags possible slugging before detailed pipeline modelling.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 4repo 4d ago A scan 87 tokens original Apache-2.0

Good fit Use it to screen a horizontal line from phase velocities or basic flow and pipe data, and to decide whether a validated multiphase-flow study is needed.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/equinor/neqsim-community-skills/neqsim-two-phase-flow-regime-screening
View source ↗ equinor/neqsim-community-skills equinor.github.io
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add equinor/neqsim-community-skills --skill neqsim-two-phase-flow-regime-screening
Clone the repo
git clone --depth 1 https://github.com/equinor/neqsim-community-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for neqsim-two-phase-flow-regime-screening

README.md
[![agentmods](https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-two-phase-flow-regime-screening/github.svg)](https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-two-phase-flow-regime-screening)
Your own site
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-two-phase-flow-regime-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-two-phase-flow-regime-screening/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-two-phase-flow-regime-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-two-phase-flow-regime-screening.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,265 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00087 $0.01265
Opus 5.5 $0.00035 $0.00506
Sonnet 5.5 $0.00017 $0.00253
Haiku 4.5 $0.00009 $0.00127

Measured 1mo ago against content hash b38c22925d02, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

neqsim-two-phase-flow-regime-screening scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 4 executable files (examples/basic_two_phase_flow_regime_screening.py, src/two_phase_flow_regime_screening/__init__.py, src/two_phase_flow_regime_screening/model.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/flow-assurance/neqsim-two-phase-flow-regime-screening/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Two-Phase Flow Regime Screening

Use this skill for public, educational two-phase flow-regime screening. It classifies a horizontal gas-liquid flow pattern from the superficial gas and liquid velocities using a simplified Mandhane-style decision tree and flags slug risk so an agent can decide whether to invoke validated NeqSim multiphase pipe-flow modelling.

When to Use

  • When a user asks what flow regime a horizontal line is likely in.
  • When an agent needs a quick slug-risk flag before slug or vibration work.
  • When examples must run without confidential pipeline models or field data.

Inputs

Provide either the superficial velocities directly, or enough data to compute them:

  • superficial_gas_velocity: gas superficial velocity Vsg in m/s.
  • superficial_liquid_velocity: liquid superficial velocity Vsl in m/s.

or

  • pipe_inner_diameter: pipe inner diameter in m.
  • gas_mass_flow: gas mass flow in kg/s.
  • liquid_mass_flow: liquid mass flow in kg/s.
  • gas_density: gas density in kg/m3.
  • liquid_density: liquid density in kg/m3.

Outputs

  • superficial_gas_velocity_m_s: gas superficial velocity used.
  • superficial_liquid_velocity_m_s: liquid superficial velocity used.
  • mixture_velocity_m_s: Vsg + Vsl.
  • flow_regime: stratified-smooth, stratified-wavy, elongated-bubble, slug, dispersed-bubble, or annular-mist.
  • slug_risk: true when the regime is slug or elongated-bubble.
  • regime_warning: ok, slug-risk, or high-velocity.
  • assumptions: public assumptions used by the placeholder model.

Engineering Method

The Python class TwoPhaseRegimeModel uses a simplified public Mandhane-style classifier for horizontal flow:

  • superficial velocities use Vs = (mdot / rho) / (pi/4 * D^2) when computed from flows.
  • the regime is selected from public approximate boundaries: annular-mist above Vsg = 10 m/s, dispersed-bubble above Vsl = 2 m/s, stratified below Vsl = 0.1 m/s, elongated-bubble for low gas velocity, otherwise slug.
  • slug_risk is flagged for the slug and elongated-bubble regimes.

Read the full file on GitHub · 113 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 113 lines · 87 tokens per session scan A b38c22925d02

Subscribe to this mod's changes

neqsim-two-phase-flow-regime-screening is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed 4d ago), licensed Apache-2.0. It adds 87 tokens to every session and 1,265 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-19.

Scientific
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