Embed AI
in your scripts

Assess the performance of your product under any kind of physics (Fluids, Mechanics, Thermics, Electromagnetism ...) in minutes by integrating our SDK directly in your team’s tools.
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SDK

/ How it works?

Upload a geometry
Input your 3D geometry and choose boundary conditions
Run simulation
Choose which simulations you want to run regarding your conditions and run them with a single click
Get a result
In minutes, get your outputs : volume, surface, evolution curves, coefficients

/ Setup phase

Data
Design data from your past simulations and trials
Physics Eq
Concepts for solving Physics PDE
Extrality
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/ Benefits

Faster time-to-market
More reliable numerical prototypes means hitting production with more confidence
Save engineers time for value-added tasks
Relief your team from the time-consuming hassles
Ease collaboration around product design
Easy collaboration between departments, designers, engineers, and business. Experts and non-experts can use the same tool
Leverage on your simulation investment
Get valuable insights today out of your past data
Reduce computation costs
Cut down expenses spent on CPU power
Test all your designs without constraints
Tolerant to imperfect geometry, no need to it clean up, sparing preparation time

/ Uses cases

If you are a naval architect, you probably know how long the ship design process takes. In this article, you will learn how Extrality can help you perform resistance calculations much earlier on while relying on your existing simulation tools, thus reducing the risk of project deviations and opening up more opportunities to evaluate new designs.
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In this study, we are using Deep Learning Physics (DLP) to build a generic AI-model for hydrodynamic studies of tankers.‍ First we will introduce the Deep Learning Physics technology, then we will describe the dataset used to build a tanker boat DLP-model and finally assess this model vs CFD.
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The objective of this study is to minimize the resistance of a ship at the target operational speed and to show that it can be done in a short time with few computing resources. First we will recall the context of the global shipping industry and a way to cut down emissions, then we will describe the procedure of hull form optimization and finally we will show how to effectively do it with Extrality Deep Learning Physics Platform.
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Need to hit production with short go-to-market and better control?
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