Vortex Tracking for Flow-Induced Noise Source Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for identifying and reducing flow-induced noise sources, such as those from jets, airframes, and HVAC systems, are often time-consuming and expensive, relying on trial-and-error approaches and physical prototyping, and lack efficient computational tools for noise source identification and characterization.
Innovation Solution
A method and system for simulating fluid activity to track vortices and identify potential sound-generating vortex structures, using computational fluid dynamics to model transient and turbulent flows, and applying transfer functions to determine noise source contributions, allowing for data-driven modifications to geometric features to reduce noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If trial-and-error approaches and physical prototyping are used to identify and reduce flow-induced noise sources, then noise reduction solutions can be developed, but the process becomes time-consuming and expensive
Solution Approach 1:
The patent applies preliminary action by performing computational noise source identification and characterization before physical prototyping and testing. The system uses CAA simulations to predict noise sources and their contributions, allowing designers to make informed modifications upfront rather than through iterative trial-and-error with physical models.
Solution Approach 2:
The patent uses computational models and simulations as virtual copies of the physical system to identify noise sources. Instead of building physical prototypes for each iteration, the system creates digital representations that can be analyzed repeatedly and modified efficiently, reducing the need for physical copying and testing.
2Reliability
If trial-and-error approaches and physical prototyping are used to identify and reduce flow-induced noise sources, then noise reduction solutions can be developed, but the process becomes expensive
Solution Approach 1:
The patent uses computational models and simulations as virtual copies of the physical system to identify noise sources. Instead of building physical prototypes for each iteration, the system creates digital representations that can be analyzed repeatedly and modified efficiently, reducing the need for physical copying and testing.
Solution Approach 2:
The patent replaces physical mechanical testing and prototyping with computational simulations. The CAA simulations and vortex tracking algorithms substitute for wind tunnel testing and physical model experimentation, eliminating the high costs associated with facilities, materials, and iterative manufacturing.
3Measurement precision
If comprehensive CAA simulations are performed to identify noise sources, then accurate noise source characterization is achieved, but computational resources and processing time increase
Solution Approach 1:
The patent extracts and focuses computational resources on identifying and analyzing only the relevant noise-generating vortex structures rather than simulating and analyzing the entire flow field in detail. The vortex tracking methodology isolates the coherent structures that contribute to noise, allowing for targeted analysis that reduces overall computational burden while maintaining accuracy for the critical noise sources.
Solution Approach 2:
The patent segments the complex flow field into discrete vortex structures that can be individually tracked and analyzed. By decomposing the continuous flow into distinct vortex entities with specific properties (strength, position, trajectory), the system can focus computational effort on the noise-relevant segments rather than processing the entire flow field uniformly.
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 enables efficient identification and characterization of noise sources, reducing processing requirements and costs by simulating noise generation mechanisms, allowing for targeted design modifications to minimize noise contributions effectively.
Implementation Method 1
simulating activity of a fluid in a volume to generate flow data, the activity of the fluid in the volume being simulated so as to model movement of elements within the volume
Implementation Method 2
at a first time in the fluid flow simulation, identifying a first set of vortices in a transient and turbulent flow modeled by the fluid flow. The method also includes, at a second time in the fluid flow simulation that is subsequent to the first time, identifying a second set of vortices
Data Source
Figure 1A
Figure 1B
Figure 1C
AI summary
A system and method for simulating activity of a fluid in a volume that represents a physical space, the activity of the fluid in the volume being simulated so as to model movement of elements within the volume. The method includes at a first time, identifying a first set of vortices in a transient and turbulent flow. The method includes at a second time that is subsequent to the first time, identifying a second set of vortices. The method includes tracking changes in the vortices by comparing the first set and the second set of discrete vortices. The method includes identifying one or more noise sources based on the tracking. The method includes determining the contribution of one or more noise sources at a receiver. The method also includes outputting data indicating one or more modifications to one or more geometric features of a device or an entity.