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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Fire Dynamics Simulator (FDS) serves as a free and open-source platform for the modeling and visualization of flows influenced by fire. This computational fluid dynamics code effectively solves a variant of the Navier–Stokes equations tailored for low-speed, thermally-driven airflow, focusing particularly on the transport of smoke and heat resulting from fires. Employing large-eddy simulation, it captures the intricacies of fire-plume dynamics and can be utilized in diverse scenarios, such as those involving wind, sprinklers, ventilation systems, and various materials that affect fire behavior. Users create scenarios by utilizing text-based input files, execute the calculations within FDS, and subsequently evaluate the output data. The simulator presents results from both FDS and CFAST simulations through advanced OpenGL-based 3D graphics, incorporating scientific visualization techniques that include animated representations of smoke and tracer particles, two- and three-dimensional shaded contours, iso-surfaces, temperature distributions, and flow vectors that display both direction and intensity. In addition to these features, FDS is continually updated to enhance user experience and functionality, making it a vital tool for researchers and safety professionals alike.

Description

NeuralMould, developed by Emmi AI, is an advanced Large Engineering Model specifically designed for injection molding, setting a new benchmark in AI-driven engineering solutions by accommodating any geometry, material, and injection gate configuration within a single framework. Users can easily choose from various geometries while testing different parameters related to injection, materials, and gate placement, allowing for quick simulations of filling behavior, rapid scenario comparisons, optimization of key performance indicators, and the prevention of frozen flow fronts. The complexity of injection molding simulations arises from the necessity to conduct multi-physics calculations, which accurately model the transient flow of viscous plastics through intricately designed thin-walled shapes under high-pressure and high-temperature conditions. NeuralMould effectively captures these critical phenomena across diverse injection scenarios and mold designs, achieving results that rival traditional solvers but with significantly reduced computation times. Additionally, the model is capable of handling multi-material applications, facilitating quick prototyping, accommodating multi-gate setups, and managing a variety of processing parameters thanks to its scalable transformer-based architecture. This innovative approach uniquely positions NeuralMould as a vital tool for engineers seeking to enhance efficiency and precision in the injection molding process.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

FireFlow Studio for FDS
OpenGL

Integrations

FireFlow Studio for FDS
OpenGL

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
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

NIST

Founded

1901

Country

United States

Website

pages.nist.gov/fds-smv/

Vendor Details

Company Name

Emmi AI

Country

Austria

Website

www.emmi.ai/models/neuralmould

Product Features

Product Features

Engineering

2D Drawing
3D Modeling
Chemical Engineering
Civil Engineering
Collaboration
Design Analysis
Design Export
Document Management
Electrical Engineering
Mechanical Engineering
Mechatronics
Presentation Tools
Structural Engineering

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