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Document type:
Masterarbeit
Author(s):
Vaishali Ravishankar
E-mail address:
vaishali.ravishankar@tum.de
Title:
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...     »
Supervisor:
Bungartz, Hans-Joachim
Advisor:
Kislaya Ravi
Cooperation:
Fraunhofer SCAI
Year:
2024
Quarter:
2. Quartal
Year / month:
2024-04
Month:
Mar
Language:
en
University:
Technical University of Munich
Faculty:
TUM School of Computation, Information and Technology
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