Ahmed Mostafa Shaaban, Dr.-Ing.

DFG Postdoktorand

Development of isogeometric and deep learning analysis in the design of acoustic metamaterials as real vibroacoustic applications

In most of previous research works, acoustic metamaterials were treated as infinite sound-hard structures ignoring their complex 3D shapes and their structural properties as well, where the results cannot enrich the real applications.

From that point, this research project is aimed to overcome these deficiencies by investigating acoustic metamaterials as a coupled acoustic-structural system with fully 3D geometry considering the acoustic-fluid interaction with total losses using Deep Neural Networks (DNN) and Isogeometric Analysis (IGA) approaches. It is also planned to implement a dynamic analysis on the metamaterials for high frequency problems. Moreover, DNNs will be utilized as a surrogate model to identify multivariate uncertainties in acoustic-vibration interaction of the metamaterials system where DNNs can improve the sampling efficiency of uncertainty methods.


  • Computational Mechanics
  • Boundary Element Method
  • Isogeometric Analysis
  • Acoustic Metamaterials



  • Shaaban, Ahmed Mostafa; Preuss, Simone; Marburg, Steffen: Isogeometric boundary element analysis for thermoviscous acoustics. Fortschritte der Akustik - DAGA 2024, 50. Jahrestagung für Akustik, 18.-21. März, Hannover, Deutsche Gesellschaft für Akustik e.V. (DEGA), 2024 mehr… BibTeX