Emerging Technologies in Computational Sciences for Industry, Sustainability and Innovation

Math to Product
Erscheinungsjahr 2025
ISBN: 978-3-031-95708-6
Verlag: Springer

Buch, Englisch, 382 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 821 g

Reihe: Lecture Notes in Computational Science and Engineering

This book presents up-to-date state of the art for industrial mathematics and covers emerging topics in computational sciences. Mathematical models and computational methods have gained an increasing importance in the simulation of real-world and industrial problems. The employment of such methodologies deeply changed the standard ways of conceiving daily industrial production and strategies for sustainable exploitation of modern cities. The goal pursued by this book is twofold. On the one hand, cases of successful interaction between mathematics and industry are presented. Special emphasis is devoted to the benefits provided by the transfer of knowledge in different fields of applications, including the social challenges of sustainable development. On the other hand, groundbreaking ideas and emerging technologies in computational science are discussed to foster cross-fertilization of academic solutions and real-world problems. Math to Product (M2P) is meant to establish a platform for proposal, discussion, and promotion of current and new trends in industry, sustainability, and innovation, with the goal of supporting creative and interdisciplinary thoughts. Scientific/technical areas covered include transfer of knowledge, innovation in design, computational science and engineering, industrial optimization processes, sustainable mobility, aerospace, automotive, nautical and naval engineering.  
Target audience is made up by grad students and researchers in the field.

Zielgruppe

Research

Autoren/Hrsg.

Giacomini, Matteo

Perotto, Simona

Rozza, Gianluigi

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

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.

Über Autor(innen)

Gianluigi Rozza is Professor in numerical analysis and scientific computing at International School for Advanced Studies-SISSA, Trieste, Italy. He obtained Ph.D. in applied mathematics at EPFL in 2005, M.Sc. in aerospace engineering at Politecnico di Milano in 2002, and post-doc at MIT. At SISSA he is Coordinator of SISSA mathLab group and Lecturer in the master in high-performance computing. He is  SISSA Director’s Delegate for Valorisation, Innovation, Technology Transfer, and Industrial Cooperation. His research is mostly focused on numerical analysis and scientific computing, developing reduced order methods. He is Author of more than 130 scientific publications (editor of six books and author of two books). He is advisor of 35 master theses and Co-Director/Director of 22 Ph.D. theses since 2009.  He is Principal Investigator of the European Research Council Consolidator Grant (H2020) AROMA-CFD and PoC ARGOS (HE), as well as for the project FARE-AROMA-CFD funded by Italian Government.  Since 2022 he is co-founder and scientific director of FAST Computing, SISSA startup.

Simona Perotto is Full Professor of Numerical Analysis at the Department of Mathematics, Politecnico di Milano, Italy.
She has over 20 years of experience in mesh generation and adaptation, and more than 10 years of expertise in model reduction and adaptive techniques within the framework of finite element approximation for partial differential equations. Her applied research spans a wide range of fields, including the design of advanced materials, mathematical modeling in medical hemodynamics, image processing, and soilless cultivation in vertical farming systems.
She is the author or co-author of around 90 scientific articles in international peer-reviewed journals and has contributed to approximately 40 book chapters and conference proceedings. Prof. Perotto has supervised more than 80 Master’s theses and 9 PhD students. 
Since April 2021, she is also co-founder, shareholder and president of the spin-off ADAPTA studio of Politecnico di Milano.

Matteo Giacomini is associate professor of computational engineering at Universitat Politècnica de Catalunya (UPC). He holds a BSc (2010) and an MSc (2013) in mathematical engineering from Politecnico di Milano, and a PhD in applied mathematics from Ecole polytechnique - Université Paris-Saclay (2016). At UPC, he is member of the Laboratori de Càlcul Numèric (LaCàN), affiliated researcher at CIMNE, the International Centre for Numerical Methods in Engineering, and affiliated faculty at IMTech, the Institute of Mathematics of UPC-BarcelonaTech. His research broadly focuses on computational science and engineering, from the development of advanced discretisation and reduced order methods for parametric partial differential equations to the solution of PDE-constrained optimisation problems. He is author of 30 articles published in reputable peer-reviewed journals, he regularly contributes to ECCOMAS, IACM, and SIAM congresses, with more than 70 conference contributions and 20 organised minisymposia, and he has supervised/co-supervised 9 defended PhD theses and more than 30 students spanning from Bachelor to Master programmes. In 2022, he received the Juan Carlos Simó award by the Spanish Society of Computational Mechanics and Computational Engineering (SEMNI). He is Fellow of the Serra Húnter Progamme of the Government of Catalonia.