Potentialities of AI-Based Models for Lagrangian CFD
The integration of Artificial Intelligence (AI) techniques with Lagrangian Computational Fluid Dynamics (CFD) models presents a promising opportunity for expanding the field of CFD simulations. Here, we provide a review of current trends and approaches in AI-based Lagrangian modeling. We categorize these approaches based on the conceptual level of application of AI algorithms, ranging from local emulation of particle interaction to global reconstruction of fluid dynamics. Then, we discuss challenges and potentialities for enhancing model functionalities, including simulation time reduction and physical quantities estimation and data assimilation. By examining recent developments and future directions, we aim to provide insights into the potentialities and applications of AI-based models in Lagrangian CFD.
Authors
- Vito Zago (ORCID: https://orcid.org/0000-0002-0610-9504)
- Ciro Del Negro (ORCID: https://orcid.org/0000-0001-5734-9025)
- Eleonora Amato (ORCID: https://orcid.org/0000-0002-4244-3972)
Institutions
- Istituto Nazionale di Geofisica e Vulcanologia (IT)
- University of Palermo (IT)
Publication Details
- Published
- 2024-09-18
- DOI
- https://doi.org/10.1109/rtsi61910.2024.10761408
- Primary Topic
- Wind and Air Flow Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00