Multidisciplinary design optimization of dynamic systems using surrogate modeling approach

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Industrial Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2013

Author dc:creator

• Deshmukh, Anand

Contributors dc:contributor

• Allison, James T.

• Dynamical Systems
• Surrogate Modeling
• Multidisciplinary Design Optimization
• Wind Turbine Design

Statement dc:rights

• Copyright 2013 Anand Deshmukh

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/44209

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/44209