- Engineering Workflow Automation
- Design Space Exploration
nvision is an open, solver-agnostic, and data-based modelling tool that enables simulation engineers, designers, and product owners to reduce design time. nvision leverages existing knowledge from simulation data and performs real-time what-if analysis to speed up product development while saving time and resources.
nvision fulfils this offer by providing a platform to train a surrogate model with a database of simulations and then evaluate new design points based on this model rather than new simulations.
Large, high-fidelity nonlinear models can take hours or even days to simulate. System analysis and design can require numerous simulations, presenting a significant computational challenge. Replacing conventional simulations with nvision models will enable engineers to predict the performance of their designs in real-time and much faster. Shorter design cycles also means that complexity is less of a barrier and engineering teams can tackle larger and more elaborate systems and optimize simultaneously across multiple domains.
Many complex R&D projects require experience with various CAE (Computer Aided Engineering) tools. Often this is blocking product teams and slows down innovation. Using nvision the users can explore the design space more than with conventional simulation and improve the efficiency of the design process with advanced search algorithms derived from the work of the wider AI (Artificial Intelligence) research community. The platform enables users to easily access the data from the simulation process and make data-driven decisions spontaneously.
Existing simulation results from previous design cycles contain significant knowledge that is often not leveraged for future innovative designs. It slows down the teams’ efficiency and creates repetitive tasks. A nvision model could be trained using real-world data from existing products in the field. That could transform the way companies improve their products, by leveraging knowledge from previous product generations.
Scan and Import simulation data from the most widely used CAD/CAE tools and select among scalar, field and time dependent variables for your study.
Use the selected training dataset and the variables definition to train a new model. Build the model based on the selected data with our AI-based modeling algorithms and evaluate the quality based on relevant metrics.
Gain insights on how design parameters affect the performance and visualize them with the 3D rendered results to explore different designs and refine your ideas.
Export results to native CAD/CAE tools file format and reuse the surrogate model in a standard industry format. Perform design optimization studies using nvision model in an Optimus workflow.
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