Fluid · Renewable Energy
GPU-Accelerated Turbulence Modeling (RANS/LES) for Renewable Energy
Apply the gpu-accelerated turbulence modeling (rans/les) to real renewable energy problems — in the browser, with AI assistance.
This is the gpu-accelerated variant of the Turbulence Modeling (RANS/LES). RANS averages the flow and models turbulence, while LES resolves large eddies and models the small ones — trading cost for fidelity.
In renewable energy, teams face challenges like intermittency, thermal cycling, grid integration. The gpu-accelerated turbulence modeling (rans/les) directly supports use cases such as wind-farm cfd, pv thermal modeling, battery storage sizing, and PolySim's AI Copilot can recommend settings and catch common setup errors before you run.
Typical Renewable Energy use cases
- Wind-farm CFD
- PV thermal modeling
- Battery storage sizing
Upgrade your workspace
Educator Classroom Kit — $45
Set up a class of 30 students for one term with shared projects.
Recommended products
Independent Researcher
$24/moThe independent researcher's plan with publication rights.
Sponsored Library Listing
$49/moFeature your model or service in the Community Library.
Long-Run Extension +2h
$5Extend a single cloud job's wall-clock limit by two hours.
Surrogate Instant Preview
$14Build an AI surrogate model for near-instant parameter previews.
CFD Pro Pack
$39A professional computational-fluid-dynamics toolset and templates.
Grant / Publication Figure Package
$85Publication-ready figures and animations from your results.