Simulation Acceleration

Engineering Simulation Optimization uses AI to compute faster and more accurate results for complex engineering simulations, enabling shorter design iteration cycles, by predicting and optimising simulation outcomes from historical run data, across product design and engineering workflows.

Complex engineering simulations are slow and computationally expensive, creating bottlenecks in design iteration and delaying engineering decisions.

The AI optimises simulation execution by learning from historical simulation data to predict outcomes, reducing redundant computation and producing faster convergence toward accurate results.

Reduces simulation runtime and computational cost; measured as reduction in simulation wall-clock time and compute cost per design iteration.

• •Historical simulation runs with input parameters and results are stored and accessible
• •Simulation workloads are structured consistently enough to allow model training across runs