Detuning Optimization of Nonlinear Mistuned Bladed Disks Using a Probabilistic Learning Tool
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-37003-8_26
Reference7 articles.
1. Bladh, R., Castanier, M.P., Pierre, C.: Component-mode-based reduced order modeling techniques for mistuned bladed disks. Part 2: application. ASME J. Eng. Gas Turbines Power 123(1), 100–108 (2001)
2. Han, Y., Murthy, R., Mignolet, M.P., Lentz, J.: Optimization of intentional mistuning patterns for the mitigation of the effects of random mistuning. ASME J. Eng. Gas Turbines Power 136(6), 062505 (2014)
3. Capiez-Lernout, E., Soize, C.: Nonlinear stochastic dynamics of detuned bladed-disks with uncertain mistuning and detuning optimization using a probabilistic machine learning tool. Int. J. Non Linear Mech. 143, 104023 (2022)
4. Picou, A., Capiez-Lernout, E., Soize, C., Mbaye, M.: Robust dynamic analysis of detuned-mistuned rotating bladed disks with geometric nonlinearities. Comput. Mech. 65(3), 711–730 (2020)
5. Soize, C., Ghanem, R.: Data-driven probability concentration and sampling on manifold. J. Comput. Phys. 321, 242–258 (2016)
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