analyze-magnetic-field

Solid

Calculate and visualize magnetic fields produced by current distributions using the Biot-Savart law, Ampere's law, and magnetic dipole approximations. Use when computing B-fields from arbitrary current geometries, exploiting symmetry with Ampere's law, analyzing superposition of multiple sources, or characterizing magnetic materials through permeability, B-H curves, and hysteresis behavior.

AI & Automation 33 stars 4 forks Updated today MIT

Install

View on GitHub

Quality Score: 81/100

Stars 20%
51
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Analyze Magnetic Field Calculate the magnetic field produced by a given current distribution by characterizing the source geometry, selecting the appropriate law (Biot-Savart for arbitrary geometries, Ampere's law for high-symmetry configurations), evaluating field integrals, checking limiting cases, incorporating magnetic material effects where relevant, and visualizing the resulting field-line topology. ## When to Use - Computing the B-field from an arbitrary current-carrying conductor (wire loop, helix, irregular path) - Exploiting cylindrical, planar, or toroidal symmetry to apply Ampere's law directly - Estimating far-field behavior via the magnetic dipole approximation - Superposing fields from multiple current sources - Analyzing magnetic materials: linear permeability, B-H curves, hysteresis, saturation ## Inputs - **Required**: Current distribution specification (geometry, current magnitude and direction) - **Required**: Region of interest where the field is needed (observation points or volume) - **Optional**: Material properties (relative permeability, B-H curve data, coercivity, remanence) - **Optional**: Desired accuracy level (exact integral, multipole expansion order, numerical resolution) - **Optional**: Visualization requirements (2D cross-section, 3D field lines, magnitude contour map) ## Procedure ### Step 1: Characterize Current Distribution and Geometry Fully specify the source before selecting a method: 1. **Current path**: Describe the geomet...

Details

Author
pjt222
Repository
pjt222/agent-almanac
Created
1 years ago
Last Updated
today
Language
JavaScript
License
MIT

Similar Skills

Semantically similar based on skill content — not just same category

AI & Automation Solid

analyze-magnetic-levitation

Analyze magnetic levitation systems by applying Earnshaw's theorem to determine whether passive static levitation is possible, then identifying the appropriate circumvention mechanism (diamagnetic, superconducting, active feedback, or spin-stabilized). Use when evaluating maglev transport, magnetic bearings, superconducting levitation, diamagnetic suspension, or Levitron-type devices. Covers force balance calculations, stability analysis in all spatial and tilting modes, and Meissner effect versus flux pinning distinctions.

33 Updated today
pjt222
Code & Development Solid

analyze-diffusion-dynamics

Analyze the dynamics of diffusion processes using stochastic differential equations, Fokker-Planck equations, first-passage time distributions, and parameter sensitivity analysis. Use when deriving probability density evolution for a continuous-time diffusion process, computing mean first-passage times for bounded diffusion, analyzing how drift and diffusion parameters affect process behavior, or validating closed-form solutions against stochastic simulation.

33 Updated today
pjt222
AI & Automation Listed

academic-plotting

Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.

1 Updated 1 months ago
NITISH-R-G