Using high temperature processes is a key tool in real-time manufacturing to manufacture metal products which are very hard for analysis, modeling, and control. The development of artificial intelligence (AI)-aided computer modeling and simulation tools is the key tool for movement of materials in corrosive environments. Advanced control algorithms developed from AI-led computer systems combines computer simulations and topology-driven optimization methods and marches forward to the next phase of furnace design. Developed AI methods based on deep neural networks utilize high-fidelity simulation results to perform real-time critical solutions.
This book provides future projections of AI techniques in high temperature materials, training in machine learning tools, graphical user interface for fast-running AI model of glass-melt furnace operations, setting the furnace temperatures based on complex computation fluid dynamics models, and examples from float-glass, metal casting industries. It opens doors for AI experts to use high temperature materials as an effective tool in real-world problems in high performance computing for energy innovation and high-performance computing for materials. This book is a key reference for students, practitioners, professionals, scientists, engineers, and researchers to improve industry competitiveness and to combat the shortcomings of energy consumption.