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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

The mesh significantly impacts the precision, convergence, and speed of a simulation. Ansys offers a suite of tools designed to create the most suitable mesh for delivering precise and efficient solutions. Their general-purpose, high-performance, automated, and intelligent meshing software is capable of generating the optimal mesh for accurate multiphysics solutions, ranging from straightforward automatic meshing to meticulously crafted mesh designs. The software incorporates smart defaults that simplify the meshing process, making it intuitive and effortless, while ensuring the necessary resolution to effectively capture solution gradients for reliable outcomes. Ansys’s meshing solutions cater to a wide variety of needs, from basic automated meshing techniques to advanced, custom meshing options. The available methods encompass a broad range of meshing techniques, including high-order and linear elements, as well as rapid tetrahedral and polyhedral meshes, alongside high-quality hexahedral and mosaic configurations. By leveraging Ansys's meshing capabilities, users can significantly minimize the time and resources required to achieve accurate simulation results, ultimately enhancing productivity and efficiency in their projects. Thus, the integration of Ansys meshing tools can transform the simulation process, leading to a more streamlined workflow and improved outcomes.

Description

NVIDIA Modulus is an advanced neural network framework that integrates the principles of physics, represented through governing partial differential equations (PDEs), with data to create accurate, parameterized surrogate models that operate with near-instantaneous latency. This framework is ideal for those venturing into AI-enhanced physics challenges or for those crafting digital twin models to navigate intricate non-linear, multi-physics systems, offering robust support throughout the process. It provides essential components for constructing physics-based machine learning surrogate models that effectively merge physics principles with data insights. Its versatility ensures applicability across various fields, including engineering simulations and life sciences, while accommodating both forward simulations and inverse/data assimilation tasks. Furthermore, NVIDIA Modulus enables parameterized representations of systems that can tackle multiple scenarios in real time, allowing users to train offline once and subsequently perform real-time inference repeatedly. As such, it empowers researchers and engineers to explore innovative solutions across a spectrum of complex problems with unprecedented efficiency.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Azore CFD

Integrations

Azore CFD

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Ansys

Founded

1970

Country

United States

Website

www.ansys.com/products/meshing

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/modulus

Product Features

CAD

2 1/2-Axis Milling
2D Drawing
3-Axis Milling
3D Modeling
4-Axis Milling
5-Axis Milling
Civil
Collaboration
Database Connectivity
Design Analysis
Design Export
Document Management
Electrical
Hole Making
Mechanical
Mechatronics
Presentation Tools
Simulate Cycles
Spiral Output
Structural Engineering
Toolpath Simulation
User Defined Cycles

Alternatives

Alternatives

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