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Differentiable Hybrid Modelling for Learning and Optimising Chemical Transport Processes from Experimental Data
Reliable transport models are essential when modelling and optimising many chemical engineering processes, yet, most models assume hand-picked constitutive laws which may not reflect reality, and often assume initial conditions are known exactly. Both restrictions can significantly bias model predic
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