Plasma State Simulation
Using twinLab to efficiently build robust emulators for prediction of computationally intensive gyro-kinetic simulations - enabling an understanding of the formation of plasma turbulences
The Machine Learning Partner for Fusion
From plasma physics to engineering design and material science, our pioneering Bayesian methods enable your engineers and scientists to leverage expert opinion for mission-critical fusion applications.
Organisations are transitioning towards capturing and utilising data to make decisions throughout the R&D cycle. digiLab have expertise in guiding organisations to do this effectively, as well as digital solutions for making informed and optimal decisions.
twinLab, our intuitive ML platform, helps engineers and scientists utilise ML alongside their current workflows. twinLab integrates with your scientific and commercial simulation tools and leverages Bayesian statistics to elicit expert knowledge.
Our Expertise in Fusion
A lot of SMEs are specialising in AI and data science, but digiLab is the only one we know of built around state-of-the art methods of uncertainty quantification.
Explore our case studies and technical demos
Using twinLab to efficiently build robust emulators for prediction of computationally intensive gyro-kinetic simulations - enabling an understanding of the formation of plasma turbulences
Leveraging transfer learning and physical constraints to optimise the knowledge gain of how materials will operate, while quantifying which physical properties are driving the uncertainty in operation
Optimising diagnostic response data to optimise the control of precision actuators to accurately operate a fusion reactor within a desired experimental regime
UQ in systems level design enables an understanding of the risk posed by uncertainty in a system, and a way to direct resource to the significant source of that uncertainty.
How twinLab powers Fusion?