NeuralMould

NeuralMould

Emmi AI
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About

NVIDIA PhysicsNeMo is an open source Python deep-learning framework for building, training, fine-tuning, and inferring physics-AI models that combine physics knowledge with data to accelerate simulations, create high-fidelity surrogate models, and enable near-real-time predictions across domains such as computational fluid dynamics, structural mechanics, electromagnetics, weather and climate, and digital twin applications. It provides scalable, GPU-accelerated tools and Python APIs built on PyTorch and released under the Apache 2.0 license, offering curated model architectures including physics-informed neural networks, neural operators, graph neural networks, and generative AI–based approaches so developers can harness physics-driven causality alongside observed data for engineering-grade modeling. PhysicsNeMo includes end-to-end training pipelines from geometry ingestion to differential equations, reference application recipes to jump-start workflows.

About

NeuralMould is Emmi AI’s Large Engineering Model for injection molding, described as a new gold standard in AI for engineering: any geometry, any material, any injection gates, one model. It lets users select from a range of geometries and test injection, material, and gate placement parameters to simulate filling behavior in seconds, rapidly compare multiple scenarios, optimize process KPIs, and avoid frozen flow fronts. Injection molding simulation is highly complex because it involves multi-physics calculations that model transient flow of viscous plastic through thin-walled geometries under extreme temperature and pressure conditions. NeuralMould captures these phenomena across a wide range of injecting conditions and mold geometries, achieving performance comparable to traditional solvers with a fraction of the computation time. The model supports multi-material scenarios, fast prototyping, multi-gate configurations, and multiple process parameters.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Researchers, engineers, and developers who need an open source Python AI framework to build, train, fine-tune, and deploy physics-informed machine learning models for simulation, digital twins, and real-time prediction

Audience

Molding engineers and manufacturing teams that need to simulate filling behavior, optimize mold parameters, and test process scenarios in seconds

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

NVIDIA
Founded: 1993
United States
developer.nvidia.com/physicsnemo

Company Information

Emmi AI
Austria
www.emmi.ai/models/neuralmould

Alternatives

Alternatives

PowerMill

PowerMill

Autodesk
Alchemite

Alchemite

Intellegens
NeuralWing

NeuralWing

Emmi AI
NeuralWing

NeuralWing

Emmi AI
Moldflow

Moldflow

Autodesk
NeuralMould

NeuralMould

Emmi AI

Categories

Categories

Integrations

PyTorch
Python

Integrations

PyTorch
Python
Claim NVIDIA PhysicsNeMo and update features and information
Claim NVIDIA PhysicsNeMo and update features and information
Claim NeuralMould and update features and information
Claim NeuralMould and update features and information