Conference Objectives
This conference on Design in Transport is motivated by the urgency to address climate change, to design innovative solutions related to transport and energy using new digitalized optimization methods and tools. The integration of Artificial Intelligence (AI) tools into advanced multi-disciplinary simulations, optimization, and big data analysis is expected to significantly impact systemic procedures in industrial processes and various aspects of modern societies, such as mobility. Multi-disciplinary scientific computing is becoming one of the powerful design instruments used both in academic research and industrial innovations. The challenge of the conference is to increase digitalization procedures change design optimization methods, tools, and technologies, targeting new greener transport in the world.
CM3 – Computational Multi-Physics, Multi-Scales and Multi Big Data
new opportunities for innovative optimization methods supported by AI (e. g., machine or deep learning, digital twins).
CM3 enables innovative design processes in the industry and research community in view of the ambitious goal of zero or low-emission future transport systems. Novel design concepts include full electric and hybrid-electric solutions, green hydrogen or low carbon fuel-powered aviation and surface transport means, advanced transport and logistic system architectures, including autonomously operating vehicles.
Conference Topics
Areas of application are:
• Transport Systems
• Aviation
• Automotive
• Maritime
• Urban transport
• Logistics
• Energy efficiency
• Full electric and hybrid-electric solutions
• Green Hydrogen
• Low-carbon fuel-powered architectures
• Materials and manufacturing
• MDO (aero-acoustics, aero-elasticity, …)
• Education
Conference topics of computational methods:
• Modelling
• Simulation
• Optimization
• Uncertainty Quantification
• Data-Driven Computing
• Neural Networks
• Machine Learning (AI)
• Industrial Computing
• Digital twins
• Validation