Scientific ML · Mining & Geotech
Physics-Informed Neural Networks (PINNs) for Mining & Geotech
Apply the physics-informed neural networks (pinns) to real mining & geotech problems — in the browser, with AI assistance.
PINNs embed PDE residuals in the loss so the network learns solutions consistent with physics from sparse data.
In mining & geotech, teams face challenges like slope stability, groundwater, comminution. The physics-informed neural networks (pinns) directly supports use cases such as slope fea, groundwater flow, particle dem, and PolySim's AI Copilot can recommend settings and catch common setup errors before you run.
Typical Mining & Geotech use cases
- Slope FEA
- Groundwater flow
- Particle DEM
Upgrade your workspace
Physics Starter Kit — $19
Everything you need to start simulating classical & modern physics.
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$120A two-hour guided onboarding for you or your team.
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$5A soft-cap buffer so a job never fails mid-run on token limits.
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$12Learn to build simulations with the visual node graph.
Institution
$360/moFor universities: SSO, up to 500 seats, admin analytics.
Render Export Credit ×10
$3Export ten high-resolution simulation renders at publication quality.