Linear solvers · Consumer Products
Conjugate Gradient (CG) for Consumer Products
Apply the conjugate gradient (cg) to real consumer products problems — in the browser, with AI assistance.
CG minimizes the residual over expanding Krylov subspaces, converging far faster than stationary methods for SPD systems common in FEM.
In consumer products, teams face challenges like cost vs. durability, thermal comfort, packaging. The conjugate gradient (cg) directly supports use cases such as drop-test fea, airflow in appliances, packaging optimization, and PolySim's AI Copilot can recommend settings and catch common setup errors before you run.
Typical Consumer Products use cases
- Drop-test FEA
- Airflow in appliances
- Packaging optimization
Upgrade your workspace
Physics Starter Kit — $19
Everything you need to start simulating classical & modern physics.
Recommended products
Featured Partner Placement
$99/moFeatured placement for hardware/cloud partners on guides.
High-Res Mesh Credit
$4Unlock a fine-mesh solve for higher spatial accuracy on one run.
Parameter Sweep (50 runs)
$12Run up to fifty parameter variations and compare results.
FEA / Structural Pro Pack
$39Structural, thermal, and modal finite-element analysis toolset.
Priority Bug / Model Rescue
$60Fast-turnaround help when a model is broken before a deadline.
Mesh Quality Audit Report
$7An audit of your mesh with quality metrics and fixes.