Computation and Big Data for Transport

Preliminary Table of Contents: Reviews and perspectives.- White paper: Computational models for the model shift: a State of the art review, by Sara Ahetze Puignau, Jordi Pons-Prats, Sergi Sauri.- Part 1. Maritime.- Shipping 4.0 - Digitalization of maritime industry, by Trond Kvamsdal.- Challenges on computational models for ship design and navigation: Ongoing projects at CIMNE, by Julio Garcia.- Fast Simulation-Assisted Shape Correction after Machining, by Ramiro Mena.- Part 2. Automotive.- Design optimization challenges and opportunities for mobility applications, by Carlo Poloni.- PGD for interactive aerodynamic optimization, by Vasilis Tsiolakis and Henry Bensler.-  Parametric wave progation for radar simulation, by Rubén Ibañez.- Application of Big Data Analytics for Understanding the Complexity of Vehicle Routing Problems, by Jussi Rasku and Tommi Karkkainen.- Part 3. Logistics.- Transport management with LogiApps: Maximizing efficiency with optimization and simplicity, by Jyri Leskinen, Panu Silvasti, and Jukka Toivanen.- Optimization of fleets and their Propulsive alternatives by operating under Motorways of the Sea conditions to Improve their Environmental Results and the Feasibility of the intermodal chains, by  Alba Martínez-López and Lourdes Trujillo.- Part 4. Aeronautics.- Public Health Concerns Regarding Modern Transportation, by William E. Fitzgibbon.- Aircraft Multidisciplinary Design chain Opportunities and Transport Challenges, by Adel Abbas.- Part 5. White paper: Computation and Big Data Challenges and perspectives for Transport.