Surrogate · Sports & Wearables
Gaussian Process Regression for Sports & Wearables
Apply the gaussian process regression to real sports & wearables problems — in the browser, with AI assistance.
GPs model outputs as draws from a distribution over functions, giving both predictions and calibrated uncertainty for expensive simulations.
In sports & wearables, teams face challenges like aerodynamics, comfort and fit, battery life. The gaussian process regression directly supports use cases such as cycling aerodynamics, fabric drape, wearable thermal design, and PolySim's AI Copilot can recommend settings and catch common setup errors before you run.
Typical Sports & Wearables use cases
- Cycling aerodynamics
- Fabric drape
- Wearable thermal design
Upgrade your workspace
CFD Pro Pack — $39
A professional computational-fluid-dynamics toolset and templates.
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.