Our Technology for engineering
“I have not failed. I’ve just found 10,000 ways that won’t work”
(attributed to Thomas Edison referring to the creation of the light bulb)
During engineering design process only one sample of the analyzed becomes the CHOSEN ONE
The major part of know-how present in the discarded samples fades away, only a small part of it remains in the designer expertise
With Deepyt all this know-how can be stored permanently through Machine Learning algorithms and reused for future designs
Our technology for engineering
Deepyt forecasts and optimizes product performance based on past know how
Our technology for engineering
Key features and workflow
Deepyt uses your historical data from previous datasets and design cycles.
You can export your simulation data (FEA or CFD) and load it directly into Deepyt, using the raw CAD itself or tabular data.
Parameterization is based on parameters manually defined by the designer and for this reason are typically a limited number of macroscopic geometrical parameters. The use of Engineering Design Parameters (EDPs) requires a uniform parameterization of each case study in order to obtain uniform tabulated data that can be used for analysis, possibly requiring reparameterization of the available geometries
Our advanced autoencoders automatically convert and compress your 3D designs into a set of latent parameters, that can be used for subsequent optimization.
You can build forecasting machine learning models and train them on your performance data, you will be able to exploit the metamodel to predict field quantities on surfaces and volumes for new geometries with a very high accuracy, speeding up the design process!
For a known target performance, the autoencoder can provide the parameters for the performance-optimized 3D design and even rebuild your geometry in a ready to export format, reducing the number of simulations required to achieve peak performance. With our technology it is possible to have a clean CAD that can be automatically meshed and evaluated through CFD or FEM, it is an automatic optimization based on non parameterized geometries!
Working on latent parameters, it is possible the exploration of design space that is difficult to exploit with traditional parameters optimization.
