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What is STOCHOS?

STOCHOS is a cutting-edge probabilistic AI tool tailored for engineering and research and development sectors. It efficiently utilizes available simulation, testing, and measurement data to quickly forecast new variants while offering uncertainty assessments for each outcome, enabling engineers to determine when they can rely on the findings or revert to conventional solvers. Using the DIM-GP framework, STOCHOS proves effective even with smaller datasets, accommodating samples ranging from a handful to several hundred, and is capable of managing diverse data types, including scalars, signals, 2D and 3D fields, meshes, geometries, and images. Among its features are surrogate modeling, uncertainty quantification, Bayesian and multi-objective optimization, as well as multi-fidelity modeling and sensitivity analysis, in addition to generative geometry techniques. The user-friendly STOCHOS Flow visual workbench allows users to build workflows without requiring programming skills, enabling teams to implement these workflows as web applications easily. The software can be installed on local hardware and works offline, thus ensuring both accessibility and privacy for users. Established in 2018 in Grafing bei München, PI Probaligence operates as part of the CADFEM Group and has emerged as a key technology partner with Ansys, fostering pioneering solutions in the engineering domain. Moreover, its seamless integration into existing workflows not only boosts productivity but also enhances operational efficiency within engineering teams, making it a valuable asset in today's fast-paced technological landscape.

What is NeuralWing?

NeuralWing stands out as an advanced model designed for real-time neural simulation and design refinement specifically focused on transonic aircraft aerodynamics. It utilizes an extensive 3D transonic wing dataset, consisting of 30,000 steady-state CFD simulations that explore a 3D wing's behavior in the transonic regime, factoring in variations across four unique geometry parameters and two distinct inflow conditions. By employing Emmi’s AB-UPT surrogate model, which has been thoroughly trained on this vast dataset, NeuralWing allows users to seamlessly modify wing geometries, perform optimizations, and improve aerodynamic efficiency in a matter of seconds. The model is crafted to enable transonic 3D wing simulations, accommodating changes in geometry and inflow while delivering real-time inference and design parameter optimization. Users can input a geometry mesh in STL format along with speed and angle of attack, and they receive comprehensive outputs that include pressure, friction, velocity fields, and integral forces such as lift and drag. Geometry meshes are generated dynamically based on four design parameters, utilizing a differentiable approach that facilitates rapid evaluation of design changes. Moreover, NeuralWing achieves an exceptional accuracy rate of 99.5%, rendering it an essential asset for aerodynamics research and development. This remarkable level of precision instills confidence in engineers as they refine their designs, ensuring that each iteration is backed by reliable data. As a result, NeuralWing not only enhances the design process but also accelerates innovation in the field of aerodynamics.

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Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Quote on request

Pricing Information

Free
Free Version

Supported Platforms

Windows
On-Prem
Linux

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

PI Probaligence GmbH

Date Founded

2018

Company Location

Germany

Company Website

probaligence.com

Company Facts

Organization Name

Emmi AI

Company Location

Austria

Company Website

www.emmi.ai/models/neuralwing

Categories and Features

Machine Learning

Not specified

Categories and Features

AI Models

Not specified

Engineering

Not specified

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