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Dokumenttyp:
Masterarbeit
Autor(en):
Vaishali Ravishankar
eMail-Adresse:
vaishali.ravishankar@tum.de
Titel:
Exploratory Analysis of Turbulent Flow Data using GNN-based Surrogate Model
Abstract:
Turbulent flows, characterized by their complex and chaotic nature, play a pivotal role in various engineering and natural systems. Understanding and analyzing these phenomena is essential for optimizing design, predicting crucial outcomes and addressing real-world challenges. Therefore, obtaining accurate, efficient and rapid predictions of turbulent behaviors is of utmost importance. Data-driven methods such as deep learning algorithms are being increasingly implemented to speed up flow predic...     »
Aufgabensteller:
Bungartz, Hans-Joachim
Betreuer:
Kislaya Ravi
Kooperationspartner:
Fraunhofer SCAI
Jahr:
2024
Quartal:
2. Quartal
Jahr / Monat:
2024-04
Monat:
Mar
Sprache:
en
Hochschule / Universität:
Technical University of Munich
Fakultät:
TUM School of Computation, Information and Technology
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