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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.
Description
SpecFlow simplifies the test automation process by fostering collaboration within the team, enabling each member to leverage their unique abilities more effectively. Instead of spending time hunting for the right definitions within your binding classes, you can simply right-click to navigate directly to the corresponding code. Additionally, you can utilize hooks, or event bindings, to implement extra automation logic at designated moments, such as performing necessary setup before a scenario runs. The framework also incorporates a dependency injection system that facilitates the creation and injection of context into scenarios. This capability allows for the organization of shared state within context classes, making it easy to inject them into every binding class that requires access to that common state. By streamlining these processes, SpecFlow enhances overall efficiency and collaboration in testing efforts.
API Access
Has API
No
API Access
Has API
Yes
Integrations
AWS CodeBuild
No
AppVeyor
No
Appium
No
Azure DevOps Server
No
Azure Repos
No
BrowserStack
No
Buddy
No
CircleCI
No
CloudBees
No
Git
No
Integrations
AWS CodeBuild
Yes
AppVeyor
Yes
Appium
Yes
Azure DevOps Server
Yes
Azure Repos
Yes
BrowserStack
Yes
Buddy
Yes
CircleCI
Yes
CloudBees
Yes
Git
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Emmi AI
Country
Austria
Website
www.emmi.ai/models/neuralmould
Vendor Details
Company Name
SpecFlow
Country
Austria
Website
specflow.org
Product Features
Engineering
2D Drawing
No
3D Modeling
No
Chemical Engineering
No
Civil Engineering
No
Collaboration
No
Design Analysis
No
Design Export
No
Document Management
No
Electrical Engineering
No
Mechanical Engineering
No
Mechatronics
No
Presentation Tools
No
Structural Engineering
No
