OptiML PSE
OptiML PSE
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Bayesian Optimization
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Supply Chain Optimization
Reinforcement Learning
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Hierarchical planning-scheduling-control -- Optimality surrogates and derivative-free optimization
Planning, scheduling, and control typically constitute separate decision-making units within chemical companies. Traditionally, their …
Damien van de Berg
,
Nilay Shah
,
Dr. Ehecatl Antonio del Rio Chanona
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DOI
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Machine Learning-Assisted Discovery of Novel Reactor Designs
Additive manufacturing has enabled the fabrication of advanced reactor geometries, permitting larger, more complex design spaces. …
Tom Savage
,
Nausheen Basha
,
Jonathan McDonough
,
Omar K. Matar
,
Dr. Ehecatl Antonio del Rio Chanona
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DOI
URL
The Automated Discovery of Kinetic Rate Models -- Methodological Frameworks
The industrialization of catalytic processes is of far more importance today than it has ever been before and kinetic models are …
Miguel Ángel de Carvalho Servia
,
Ilya Orson Sandoval
,
Klaus Hellgardt
,
King Kuok
,
Hii
,
Dongda Zhang
,
Ehecatl Antonio del Rio-Chanona
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DOI
URL
Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for Simulated Chemical Reactors
New manufacturing techniques such as 3D printing have recently enabled the creation of previously infeasible chemical reactor designs. …
Tom Savage
,
Nausheen Basha
,
Omar Matar
,
Dr. Ehecatl Antonio del Rio Chanona
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DOI
URL
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