TU1.R1.2
Application of surrogate modelling to accelerate design space exploration for catalytic reactor systems
Udit Gupta, Siemens Industry Software Inc.; Stepan Spatenka, Sreekumar Maroor, Siemens Industry Software Ltd.
Session:
TU1.R1: Computational Chemistry and Catalysis, Data Science, ML I
Track:
Computational Chemistry and Catalysis, Data Science, and AI/ML in Reaction Engineering
Location:
Galleria I & II
Presentation Time:
Tue, 18 Feb, 11:05 - 11:25 CT (UTC -5)
Session Co-Chairs:
Milad Abolhasani, North Carolina State University and Gaurav Giri, University of Virginia
Presentation
Discussion
Resources
No resources available.
Session TU1.R1
TU1.R1.1: USING MOLECULAR MODELING AND MACHINE LEARNING TO ADDRESS STABILITY CHALLENGES FOR ZEOLITE CATALYSTS
Chris Paolucci, University of Virginia
TU1.R1.2: Application of surrogate modelling to accelerate design space exploration for catalytic reactor systems
Udit Gupta, Siemens Industry Software Inc.; Stepan Spatenka, Sreekumar Maroor, Siemens Industry Software Ltd.
TU1.R1.3: Advantages in the use of AI-based regressions for the kinetic modelling of industrial catalysts
EMANUELE MOIOLI, Politecnico di Milano; Hugo Petremand, Andrea Pappagallo, Paul Scherrer Institute
Contacts