Turbomachinery Blade Surrogate Modeling Using Deep Learning
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-90539-2_6
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3. Cho, S.-Y., Yoon, E.-S., Choi, B.-S.: A Study on an axial-type 2-D turbine blade shape for reducing the blade profile loss. KSME Int. J. 16(8), 1154–1164 (2002)
4. Rai, M.M., Madavan, N.K.: Aerodynamic design using neural networks. AIAA J. 38(1), 173–182 (2000)
5. Rai, M.M., Madavan, N.K.: Application of artificial neural networks to the design of turbomachinery airfoils. J. Propul. Power 17(1), 176–183 (2001)
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