Details werden geladen...
Physics-Informed Neural Networks for Thermohydrodynamic Modeling of Fuel Injection Pumps with Fuel-Dependent Properties - RWTH Publications
Brumand, Faras; Puntigam, Georg Michael; Hofmeister, Marius; Kotte, Tim; Schmitz, Katharina
Ähnliche Seiten
A physics-informed neural network approach for predicting fatigue life of SLM 316L stainless steel based on defect features - RWTH Publications
https://publications.rwth-aachen.de/record/1042336Perspectives on Sustainable Computational Science and Engineering - RWTH Publications
https://publications.rwth-aachen.de/record/1042328Pyrolysis of aircraft cabin materials for chemical recycling - RWTH Publications
https://publications.rwth-aachen.de/record/1042299Sustainability and Energy Efficiency in Fluid Power - Recent Advancements in Research and Industry - RWTH Publications
https://publications.rwth-aachen.de/record/1042321Defining Microstructural Features of Additively Manufactured Hot Work Steels and Predicting Mechanical Properties Using CNNs - RWTH Publications
https://publications.rwth-aachen.de/record/1042332