Structurally Independent AIC Matrix Generation for Aeroelastic Analysis
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Solution Overview
Problem
Current CFD methods for aeroelastic analysis are costly and inefficient, requiring repeated computations with structural design changes and limited to determining only the first flutter mode due to high computational costs and divergent oscillatory responses, which hinders the aerospace industry's ability to analyze all critical flutter modes and optimize structural design effectively.
Innovation Solution
A CFD-based method for generating structurally independent aerodynamic influence coefficient (AIC) matrices using high-fidelity solvers like FUN3D or Fluent, employing Finite Difference and Complex Variable Differentiation techniques to linearize unsteady aerodynamic pressure distributions, and a Master Point Excitation approach to reduce computational time, allowing for efficient generation and reuse of AIC matrices across structural design cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time-marching CFD approach is used for aeroelastic analysis, then unsteady aerodynamic forces can be computed, but computational cost increases significantly and only the first flutter mode can be determined
Solution Approach 1:
The patent segments the aeroelastic analysis into two independent parts: (1) CFD computation to generate aerodynamic influence coefficient (AIC) matrices for a reference structure, and (2) structural analysis using these pre-generated AIC matrices. This segmentation allows the expensive CFD computations to be performed once and reused, rather than repeating them for each structural design iteration, thereby significantly improving computational efficiency while maintaining analysis accuracy.
Solution Approach 2:
The patent performs preliminary CFD computations to generate AIC matrices before the structural design optimization process. These pre-generated AIC matrices capture the unsteady aerodynamic characteristics and can be directly used in subsequent structural analysis without requiring additional CFD computations, thus reducing overall computational cost and enabling comprehensive flutter mode analysis.
2Manufacturing precision
If CFD computation is executed for each structural design change, then accurate aerodynamic forces are obtained, but computational time and cost increase significantly
Solution Approach 1:
The patent creates universal AIC matrices that are independent of specific structural configurations. These matrices are generated once using CFD for a reference aerodynamic configuration and then universally applied to multiple different structural designs through the structural analysis module. This multi-functionality eliminates the need to re-run CFD computations for each structural variant, significantly reducing computational time while maintaining aerodynamic force accuracy.
Solution Approach 2:
The patent uses the AIC matrices as a computational copy or representation of the aerodynamic characteristics. Instead of directly computing aerodynamic forces through CFD for each structural design, the AIC matrices serve as a simplified but accurate model that can be repeatedly applied to different structures without requiring original CFD computations, thus reducing time loss while preserving accuracy.
3Reliability
If time-marching CFD is used to determine flutter modes, then unsteady aerodynamic response is captured, but the analysis is limited to the lowest flutter mode due to divergent oscillatory response
Solution Approach 1:
The patent segments the flutter analysis into two stages: (1) CFD-based generation of AIC matrices that capture unsteady aerodynamic characteristics, and (2) structural analysis using these matrices to identify multiple flutter modes. This segmentation allows the analysis to proceed beyond the first flutter mode by decoupling the aerodynamic computation from the structural analysis, enabling comprehensive multi-mode flutter investigation.
Solution Approach 2:
The AIC matrices serve as an intermediary that bridges the CFD computations and structural analysis. These matrices contain the essential unsteady aerodynamic information in a format that can be directly used by structural solvers to analyze multiple flutter modes. This intermediary representation enables versatile flutter mode identification without the limitations of direct time-marching CFD approaches.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces computational time and cost by enabling rapid generation and reuse of AIC matrices, facilitating comprehensive aeroelastic analysis, flutter mode identification, and structural optimization without the need for repeated CFD computations, thus enhancing the efficiency of the aerospace industry's design processes.
Implementation Method 1
accurate unsteady aerodynamic forces only can be obtained by solving the Euler or Navier-Stokes (N-S) equations
Implementation Method 2
accurate unsteady aerodynamic forces only can be obtained by solving the Euler or Navier-Stokes (N-S) equations
Implementation Method 3
The first approach is the Finite Difference (FD) method that is applied to a CFD solver in which all floating numbers are programmed in the real variables
Implementation Method 4
The second approach for generating the linearized unsteady pressure distribution is to apply the Complex Variable Differentiation (CVD) technique to a CFD solver
Data Source
AI summary
This invention is a methodology, called CFD-based AIC generator, that can generate CFD-based structurally-independent Aerodynamic Influence Coefficient (AIC) matrices. Because the AIC matrices are independent of structure, they can be repeatedly used during the flight vehicle's structural design cycle for a fixed aerodynamic configuration to rapidly generate flutter, aeroservoelastic (ASE), and dynamic loads solutions. Inputs to processing include a CFD surface mesh, a coarsening ratio criterion, and a mid-layer panel model. The coarsening ratio criterion is computed from the CFD mesh. The mid-layer panel model is comprised of coarsened grid points derived from the CFD mesh and the coarsening ratio criterion.