Transonic Aerodynamic Force Calculation via POD Shock Decomposition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for predicting aerodynamic forces on aircraft components in transonic conditions require numerous lengthy computations due to the dependence on multiple parameters, especially when shock waves are involved, leading to inaccurate results or the need for large POD manifolds.
Innovation Solution
A method and system that decompose the flow field into smooth and shock wave fields, using POD modes and a genetic algorithm to minimize errors, allowing for quick calculation of aerodynamic forces by reconstructing CFD computations with a reduced-order model, applicable to aircraft components in transonic conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If numerous CFD computations are performed to accurately predict aerodynamic forces in transonic conditions, then prediction accuracy is improved, but computational time and resources increase significantly
Solution Approach 1:
The method performs preliminary CFD computations at selected parameter points to generate training data for a reduced-order model. This preliminary action allows the model to be trained once and then quickly predict aerodynamic forces for many other parameter combinations without requiring additional full CFD computations, thus resolving the contradiction between accuracy and computational time.
Solution Approach 2:
The reduced-order model creates a simplified copy of the full CFD computational process. Instead of performing numerous complex CFD computations, the model replicates the essential aerodynamic force predictions using a much simpler computational approach, maintaining acceptable accuracy while dramatically reducing computational time and resources.
2Measurement precision
If the number of POD modes is increased to accurately represent shock wave structures in transonic flow, then flow field accuracy is improved, but the dimension of the POD manifold and computational complexity increase
Solution Approach 1:
The method segments the flow field into distinct regions: shock wave regions and non-shock regions. Different POD mode requirements are applied to each segment, allowing accurate representation of shock structures only where needed while using fewer modes in other regions, thus reducing overall POD manifold dimension while maintaining flow field accuracy.
Solution Approach 2:
The method applies different levels of POD mode resolution to different spatial locations. In shock wave regions, higher-resolution POD modes are used to capture discontinuities, while in smooth flow regions, lower-resolution modes suffice. This local quality approach maintains accuracy where critical while reducing overall computational complexity.
Data Source
AI summary
A computer-aided method suitable for assisting in the design of an aircraft by providing relevant dimensioning values corresponding to an aircraft component in transonic conditions inside a predefined parameter space by means of a reconstruction of the CFD computations for an initial group of points in the parameter space using a POD reduced-order model, comprising the following steps: a) Decomposing for each flow variable the complete flow field into a smooth field and a shock wave field in each of said computations; b) Obtaining the POD modes associated with the smooth field and the shock wave field considering all said computations; c) Obtaining the POD coefficients using a genetic algorithm (GA) that minimizes a fitness function; d) Calculating said dimensioning values for whatever combination of values of said parameters using the reduced-order model. The invention also refers to a system able to perform the method.