{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/44209"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/44209","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Multidisciplinary design optimization of dynamic systems using surrogate modeling approach","abstract":"This thesis aims to explore a new paradigm for efficient solution of multi-disciplinary design optimization (MDO) of dynamic systems. Many of the MDO problems in dynamic systems design often involve computationally expensive system simulations, severely limiting their design optimization. This work demonstrates a novel method which approximates the expensive system dynamics by cheap-to-evaluate surrogate models for system derivative functions. This is advantageous to do, since it preserves the inherent nature of dynamic system to certain accuracy and enables the effi cient solution of MDO problems at the same time. The proposed method is demonstrated on a real world example of wind turbine design and obtained results are very encouraging.","abstract_html":"This thesis aims to explore a new paradigm for efficient solution of multi-disciplinary design optimization (MDO) of dynamic systems. Many of the MDO problems in dynamic systems design often involve computationally expensive system simulations, severely limiting their design optimization. This work demonstrates a novel method which approximates the expensive system dynamics by cheap-to-evaluate surrogate models for system derivative functions. This is advantageous to do, since it preserves the inherent nature of dynamic system to certain accuracy and enables the effi cient solution of MDO problems at the same time. 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