Emerging Technologies in Computational Sciences for Industry, Sustainability and Innovation

Reduced Order Modeling in computational fluid dynamics: an overview of methods and applications.-  Digital Twins for Predictive Maintenance in Industry: A Statistical and Deep Learning-Based Approach.- Hybrid energy system based on constrained optimization using simulated annealing.-  Investigating ANN accuracy changes through cluster-based cost function modification.- On the use of manifold learning tools for coherent object interpolation based on geometrical and topological descriptors.- Design of a checkerboard counter flow heat exchanger for industrial applications.-  A PINN framework for perturbed poromechanical models.- Exploiting scientific machine learning on embedded digital twins.- Review of: Simulations of thermally-driven winds on Mars:the Gale crater case.-  Industrial applications of lift and drag forces  in chaotic flow.- T8code- Scalable Adaptive Mesh Refinement.

• Erscheinungsdatum: 22.11.2025
• Autor/Autorin: Matteo Giacomini
• Reihe: Springer Nature Proceedings excluding Computer Science
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 31.7 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 382 Seiten
• ISBN: 9783031957093
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.