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Computational Mechanics and Applied Mathematics: Perspectives from Young Scholars : GIMC SIMAI Young 2024 / edited by Francesco Marmo, Salvatore Cuomo, Arsenio Cutolo

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Lecture Notes in Mechanical EngineeringPublisher: Cham : Springer Nature Switzerland, 2025Publisher: Cham : Imprint: Springer, 2025Edition: 1st ed. 2025Description: 1 Online-Ressource(XIII, 289 p. 124 illus., 113 illus. in color.)ISBN:
  • 9783031765919
Subject(s): Additional physical formats: 9783031765902 | 9783031765926 | Erscheint auch als: 9783031765902 Druck-Ausgabe | Erscheint auch als: 9783031765926 Druck-Ausgabe | Erscheint auch als: Computational mechanics and applied mathematics: perspectives from young scholars. Druck-Ausgabe Cham : Springer Nature, 2025. xiii, 289 SeitenDDC classification:
  • 003.3 23
DOI: DOI: 10.1007/978-3-031-76591-9Online resources: Summary: This book collects the latest advances and innovations in the field of applied mathematics and computational mechanics, as presented at the 2nd Workshop GIMC SIMAI YOUNG, held in Naples, Italy, on July 10–12, 2024. The workshop was the joint effort of Computational Mechanics Group of the Italian Association of Theoretical and Applied Mechanics -AIMETA (GIMC) and Italian Society of Applied and Industrial Mathematics (SIMAI) and was meant to highlight the works of young researchers in the field. Topics include mathematical models for socio-epidemiological dynamics, efficient numerical methods for evolutionary PDEs, multi-scale approaches and machine learning techniques in material modelling, nonlinear material behaviour, computational methods for shells and spatial structures, assessment, monitoring, and design of masonry structures, particles in numerical simulations, non-Newtonian complex fluids, mathematical modelling in mechanobiology and oncology, mechanics of biological systems and bioinspired materials, computational approaches for complex dynamical systems, optimization methods for classical and data-driven approaches. The contributions, which were selected by means of a rigorous peer-review process, present a wealth of exciting ideas that will open novel research directions and foster multidisciplinary collaboration.PPN: PPN: 1920927247Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-ENG | ZDB-2-SXE
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