Toggle navigation
iDesign Lab
Home
People
Projects
Publications
Education
Software
Openings
Multidisciplinary design optimization for sea, land, and air vehicles
1. Aircraft aerodynamic design optimization
Wing-body-tail aerodynamic shape optimization for a transonic aircraft configuration
Gradient-based optimization with hundreds of design variables and constraints
Single- and multi-point aerodynamic shape optimization with full and transitional turbulence
References:
AIAA Journal 2020 Paper [
doi
][
preprint
]
AIAA Scitech 2020 Paper [
doi
][
preprint
][
slides
]
Comput. Fluids 2018 Paper [
doi
][
preprint
]
2. Compressor aerostructural optimization
Design optimization for Rotor 67 blade considering both aerodynamics and structure
Gradient-based optimization with hundreds of shape design variables
Minimizing torque while maintaining mass flow rate, total pressure ratio, and max von-Mises stress
References:
AIAA Journal 2020 Paper [
doi
][
preprint
]
3. Aerothermal optimization for turbine internal cooling passage
Design optimization for U bend internal cooling channel for rib-free and ribbed configurations
Hundreds of shape design variables to modify channel shape while allowing all ribs to change independently
Simultaneous improvement for aerodynamic loss reduction and heat transfer enhancement
References:
Int. J. Heat Mass Tranf. 2019 Paper [
doi
][
preprint
]
AIAA Aviation 2018 Paper
doi
][
preprint
]
4. Car aerodynamic shape optimization
Aerodynamic shape optimization for a full sedan car model
Imposing manufactoring constraint to ensure practical design
Aerodynamic drag reduces by more than 10%
References:
Comput. Fluids 2018 Paper [
doi
][
preprint
]
5. Design optimization for self-propulsion of a bulk carrier hull
Simultaneously considering hydrodynamic resistance and wake distortion
Gradient-based optimization method allows large design freedom for hull shape
Imposing proper geometric constraints ensures practical hull shapes
References:
Comput. Fluids 2019 Paper [
doi
][
preprint
]
IMDC 2018 Paper [
preprint
]
The above research was conducted at the University of Michigan, Ann Arbor between 2016 and 2020, supported by funding from the Ford Motor Company.