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Title:

Advanced Collapse Clustering Algorithms for Numerical Cavitation Erosion Prediction

Document type:
Konferenzbeitrag
Contribution type:
Textbeitrag / Aufsatz
Author(s):
Theresa Trummler; Fabian Thiery; Steffen J. Schmidt and Nikolaus A. Adams
Abstract:
Cavitation erosion refers to severe material damage caused by collapsing vapor structures near walls. During the collapse of vapor structures, high intensity pressure waves up to several GPa are emitted that can lead to damage of nearby surfaces. Compressible numerical flow simulations enable the numerical prediction of cavitation erosion by spatial and temporal resolution of such pressure impacts. However, these simulations usually only provide point-based pressure data. To obtain numerical...     »
Keywords:
cavitation erosion prediction, pit size, numerical simulation, artificial intelligence (AI), machine learning (ML), clustering algorithms
Dewey Decimal Classification:
620 Ingenieurwissenschaften
Book / Congress title:
11th International Symposium on Cavitation
Congress (additional information):
May 10-13, 2021, Daejon, Korea
Date of congress:
May 10-13, 2021
Year:
2021
Language:
en
Notes:
Acknowledges The authors are grateful to acknowledge the Gauss Centre for Supercomputing e.V. for providing computing time on the GCS Supercomputers SuperMUC NG at Leibniz Supercomputing Centre (LRZ, www.lrz.de).
TUM Institution:
Lehrstuhl für Aerodynamik und Strömungsmechanik
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