Hybrid Quantum Computing-GPU Acceleration algorithms development for fluid structure interaction
Abstract
Fluid-structure interaction (FSI) is common for a wide range of air force applications, e.g., turbomachinery blades, airplane wings, or the entire fuselage of highly flexible aircraft. In many cases, FSI needs to be suppressed to prevent its detrimental effect on the structure (e.g., flutter) ¹. Recently, FSI is also being increasingly explored in flexible structures for their advantages of high mass efficiency and potentially better aerodynamic performance 2. However, high-fidelity computational modeling of FSI, especially for dynamic deformations, often poses an enormous challenge due to intense computational fluid dynamics (CFD) simulations of the unsteady aerodynamics caused by varying structural configurations. In most fully coupled FSI solving processes, CFD consumes the majority of the computational resources- the computational costs for the coupling and structure modeling are one order of magnitude lower than that for the fluid solver. Therefore, the key to improve the computational efficiency in FSI is to speed-up the CFD. There has been continuous effort in the classical CPU-GPU parallel computing acceleration for CFD with only up to a linear speedup, which limits the application of FSI in the realistic air force applications. Quantum computing (QC) is a computing technology that promises to perform various computations that would be impossible for classical computers. Because of the enormous cost of CFD simulations and the potential for exponential or polynomial speed-ups from quantum computers, there is tremendous potential to use QC to enable new possibilities for CFD. Current QC for CFD is limited to a few specific applications. To extend the QC for CFD applications, many fundamental problems need to be addressed, such as the quantum algorithm to recover the Navier-Stokes equation (NSE) for two-dimensional-three-dimensional (2D-3D) spaces. for CFD with only up to a linear speedup, which limits the application of FSI in the realistic air force applications. Quantum computing (QC) is a computing technology that promises to perform various computations that would be impossible for classical computers. Because of the enormous cost of CFD simulations and the potential for exponential or polynomial speed-ups from quantum computers, there is tremendous potential to use QC to enable new possibilities for CFD. Current QC for CFD is limited to a few specific applications. To extend the QC for CFD applications, many fundamental problems need to be addressed, such as the quantum algorithm to recover the Navier-Stokes equation (NSE) for two-dimensional-three-dimensional (2D-3D) spaces. for CFD with only up to a linear speedup, which limits the application of FSI in the realistic air force applications. Quantum computing (QC) is a computing technology that promises to perform various computations that would be impossible for classical computers. Because of the enormous cost of CFD simulations and the potential for exponential or polynomial speed-ups from quantum computers, there is tremendous potential to use QC to enable new possibilities for CFD. Current QC for CFD is limited to a few specific applications. To extend the QC for CFD applications, many fundamental problems need to be addressed, such as the quantum algorithm to recover the Navier-Stokes equation (NSE) for two-dimensional-three-dimensional (2D-3D) spaces.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 06, 2025
- Source ID
- FA95502510030
Entities
People
- Zheng Li
Organizations
- Air Force Office of Scientific Research
- Morgan State University
- United States Air Force