Tag: Simulation
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Multi-scale simulation with physics-informed neural networks
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Overview Physics-informed neural networks (PINNs) have emerged as a promising tool for solving differential equations. They have been applied to many scientific problems and a large number of approaches extending their capabilities have been proposed. PINNs work by using a neural network to directly approximate the solution and training it to satisfy the differential equation.…
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Efficient and differentiable population balance modelling with JAX
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Overview Population balance equations (PBEs) are used to model the evolution of populations of particles over time, such as in crystallisation processes, chemical reactors, and biological cell growth. Solving these equations are crucial in sectors like pharmaceuticals, where they allow us to optimise manufacturing processes involving crystallisation and shorten drug development timelines. However, traditional PBE…
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Weather and climate modelling with neural differential equations
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Overview This is a new direction for the lab – more to come! Team & collaborators