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Wright State University

1. Boyd, Ian M. Adaptive Identification of Classification Decision Boundary of Turbine Blade Mode Shape under Geometric Uncertainty.

Degree: MSME, Mechanical Engineering, 2019, Wright State University

Integrally Bladed Rotors (IBR) of aircraft turbine engines suffer from fluctuations in the dynamic response that occurs due to blade to blade geometric deviations. The Stochastic Approach for Blade and Rotor Emulation (SABRE) framework has been used to enable a probabilistic study of mistuned blades in which a reduced order modeling technique is applied in conjunction with sets of surrogate models, called emulators, to make predictions of mistuned mode shapes. SABRE has proven useful for non-switching mode shapes. However, switching mode shapes have non-stationary or discontinuous response surfaces which reduce the accuracy of the surrogate models used in SABRE. To improve emulator accuracy, the methodology proposed in this thesis was developed. This methodology improves prediction quality by identifying and eliminating non-stationary and discontinuous portions of the response with the classification decision boundary methodology, efficiently identifying areas of inaccuracy while improving the surrogate as efficiently as possible with adaptive sampling, and alleviating the computational burden associated with large numbers of finite element samples required to build accurate emulators. Advisors/Committee Members: Bae, Harok (Advisor).

Subjects/Keywords: Mechanical Engineering; Surrogate Modeling; Mistuning; Non-stationary response; Classification; Clustering; Adaptive Sampling

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Boyd, I. M. (2019). Adaptive Identification of Classification Decision Boundary of Turbine Blade Mode Shape under Geometric Uncertainty. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1567013848919062

Chicago Manual of Style (16th Edition):

Boyd, Ian M. “Adaptive Identification of Classification Decision Boundary of Turbine Blade Mode Shape under Geometric Uncertainty.” 2019. Masters Thesis, Wright State University. Accessed September 19, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1567013848919062.

MLA Handbook (7th Edition):

Boyd, Ian M. “Adaptive Identification of Classification Decision Boundary of Turbine Blade Mode Shape under Geometric Uncertainty.” 2019. Web. 19 Sep 2019.

Vancouver:

Boyd IM. Adaptive Identification of Classification Decision Boundary of Turbine Blade Mode Shape under Geometric Uncertainty. [Internet] [Masters thesis]. Wright State University; 2019. [cited 2019 Sep 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1567013848919062.

Council of Science Editors:

Boyd IM. Adaptive Identification of Classification Decision Boundary of Turbine Blade Mode Shape under Geometric Uncertainty. [Masters Thesis]. Wright State University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1567013848919062

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