EDP Sciences logo
Submit your paper
Search
Menu
All issues Volume 9 (2025) Acta Acust., 9 (2025) 65 References
Open Access
Issue
Acta Acust.
Volume 9, 2025
Article Number 65
Number of page(s) 14
Section Physical Acoustics
DOI https://doi.org/10.1051/aacus/2025044
Published online 27 October 2025
  1. IEEE: Standard on Piezoelectricity. 176-1987. American National Standards Institute, 1987. [Google Scholar]
  2. T. Lahmer, B. Kaltenbacher, M. Mohr: Simulation based determination of piezoelectric material parameters, in: PAMM: Proceedings in Applied Mathematics and Mechanics. Vol. 5, 2005, pp. 59–62. DOI: https://doi.org/10.1002/pamm.200510016. [Google Scholar]
  3. M.A.B. Andrade, E.C.N. Silva, F. Buioch, J.C. Adamowski: Characterization of piezoelectric materials by using an optimization algorithm, in: Proceedings of the Interntional Congress on Ultrasonics, 2007 ICU Vienna. Vienna University of Technology, 2007. DOI: https://doi.org/10.3728/icultrasonics.2007.vienna.1615_andrade. [Google Scholar]
  4. D. Kybartas, A. Lukosevicius: Determination of piezoceramics parameters by the use of mode interaction and fitting of impedance characteristics. ULTRAGARSAS 45, 4 (2002) 22–28. Available from: https://www.ultragarsas.ktu.lt/index.php/USnd/article/view/8149. [Google Scholar]
  5. S.J. Rupitsch, J. Ilg: Complete characterization of piezoceramic materials by means of two block-shaped test samples. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 62, 7 (2015) 1403–1413. [Google Scholar]
  6. K. Kulshreshtha, B. Jurgelucks, F. Bause, J. Rautenberg, C. Unverzagt: Increasing the sensitivity of electrical impedance to piezoelectric material parameters with non-uniform electrical excitation. Journal of Sensors and Sensor Systems 4 (2015) 217–227. [Google Scholar]
  7. B. Jurgelucks, L. Claes, A. Walther, B. Henning: Optimization of triple-ring electrodes on piezoceramic transducers using algorithmic differentiation. Optimization Methods and Software 33, 4, 6 (2018) 868–888. [Google Scholar]
  8. L. Claes, N. Feldmann, V. Schulze, L. Meihost, H. Kuhlmann, B. Jurgelucks, A. Walther, B. Henning: Inverse procedure for measuring piezoelectric material parameters using a single multi-electrode sample. Journal of Sensors and Sensor Systems 12, 1 (2023) 163–173. [Google Scholar]
  9. V. Schulze: Modeling and optimization of electrode configurations for piezoelectric material. PhD thesis, Humboldt-Universität zu Berlin, 2023. [Google Scholar]
  10. N. Feldmann, V. Schulze, L. Claes, B. Jurgelucks, L. Meihost, A. Walther, B. Henning: Modeling and optimization of electrode configurations. tm – Technisches Messen 88, 5 (2021) 294–302. [Google Scholar]
  11. O. Friesen, L. Claes, N. Feldmann, B. Henning: Estimation of piezoelectric material parameters of ring-shaped specimens. tm – Technisches Messen 92 (2025) 203–213. [Google Scholar]
  12. A. Iula, N. Lamberti, M. Pappalardo: A model for the theoretical characterization of thin piezoceramic rings. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 43 (1996) 370–375. [Google Scholar]
  13. W. Heywang, K. Lubitz, W. Wersing: Piezoelectricity: Evolution and Future of a Technology. Vol. 114. Springer, Berlin, 2008. [Google Scholar]
  14. W. Voigt: Lehrbuch der Kristallphysik (mit Ausschluss der Kristalloptik). Vieweg+Teubner Verlag, 1966 edn., 1928. [Google Scholar]
  15. R.R. Craig, A. Kurdila: Fundamentals of Structural Dynamics. John Wiley, Hoboken, 2006. [Google Scholar]
  16. S. Schoder, K. Roppert: openCFS: open source finite element software for coupled field simulation – part acoustics, 2022. Preprint https://arxiv.org/abs/2207.04443. [Google Scholar]
  17. K. Koch, O. Friesen, L. Claes: Randomised material parameter impedance dataset of piezoelectric rings (RaPIDring), 2024. Available from: https://zenodo.org/records/11207805. [Google Scholar]
  18. N. Feldmann: Ein modellbasiertes Messverfahren zur Charakterisierung von Piezokeramiken unter Verwendung eines einzelnen scheibenförmigen Probekörpers. PhD thesis, Universität Paderborn, 2021. [Google Scholar]
  19. K. Koch, L. Claes: Randomised material parameter piezoelectric impedance dataset with structured electrodes (RaPIDstruc), 2024. Available from: https://zenodo.org/records/11064206. [Google Scholar]
  20. N. Feldmann, B. Jurgelucks, L. Claes, B. Henning: A sensitivity-based optimisation procedure for the characterisation of piezoelectric discs, in: Proceedings of Meetings on Acoustics. Vol. 38. ASA, 2019, p. 030004. [Google Scholar]
  21. K. Koch, L. Claes, B. Jurgelucks, L. Meihost: Neural networks for initial value estimation in the identification of piezoelectric material parameters (Neuronale Netze zur Startwertschätzung bei der Identifikation piezoelektrischer Materialparameter). tm – Technisches Messen 91, 12 (2024) 638–647. [Google Scholar]
  22. I. Goodfellow, Y. Bengio, A. Courville: Deep Learning. MIT Press, 2016. Available from: https://www.deeplearningbook.org. [Google Scholar]
  23. D.P. Kingma, J. Ba: Adam: a method for stochastic optimization, 2014. Preprint: https://arxiv.org/abs/1412.6980. [Google Scholar]
  24. J. Gu, Z. Wang, J. Kuen, L. Ma, A. Shahroudy, B. Shuai, T. Liu, X. Wang, G. Wang, J. Cai, T. Chen: Recent advances in convolutional neural networks. Pattern Recognition 77 (2018) 354–377. [CrossRef] [Google Scholar]
  25. M.A. Branch, T.F. Coleman, Y. Li: A subspace, interior, and conjugate gradient method for large-scale bound-constrained minimization problems. SIAM Journal on Scientific Computing 21, 1 (1999) 1–23. [Google Scholar]
  26. O. Friesen, L. Claes, C. Scheidemann, N. Feldmann, T. Hemsel, B. Henning: Estimation of temperature-dependent piezoelectric material parameters using ring-shaped specimens, in: 2023 International Congress on Ultrasonics, Beijing, China. Vol. 2822. IOP Publishing, 2024, p. 012125. [Google Scholar]
  27. N. Feldmann, F. Bause, B. Henning: Uncertainty estimation for linearised inverse problems comparing Bayesian inference and a pseudoinverse approach for acoustic transmission measurements. tm – Technisches Messen 84, 4 (2016) 217–224. [Google Scholar]
  28. D. Gutierrez-Lemini: Engineering Viscoelasticity. Springer US, Boston, MA and S.L., 2014. [Google Scholar]
  29. F. Bause, J. Rautenberg, N. Feldmann, M. Webersen, L. Claes, H. Gravenkamp, B. Henning: Ultrasonic transmission measurements in the characterization of viscoelasticity utilizing polymeric waveguides. Measurement Science and Technology 27, 10 (2016) 105601. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.