JuliaSim is a next generation cloud-based simulation platform, combining the latest techniques in SciML with equation-based digital twin modeling and simulation. Our modern ML-based techniques accelerate simulation by up to 500x, changing the paradigm of what is possible with computational design.
Accelerate with Surrogates
Generate fast approximate models using the latest techniques from scientific machine learning and model order reduction.
Integrate with Uncertainty Quantification and Noise
Use advanced techniques like Polynomial Chaos and Koopman Operator approaches to create designs robust to uncertainty and stochasticity.
Parameter Estimation and Optimal Control
Integrate with Julia’s differentiable programming for high-performance stable adjoints to accelerate parameter estimation and optimizing controls.
Combine models with tools like DiffEqFlux and NeuralPDE to discover missing physics and generate digital twins.
Combine with Pre-Built Models and Digital Twins
Grab complete models from the JuliaSim Model Store and compose the pieces to accelerate the design process.
Specialized Numerical Environments
Use the latest numerical tools, like discontinuity-aware differential equation solvers, high-performance steady state solvers, and domain-specific environments.