laboratory equipment and services Environment and Pollution

Modeling Reduction Aeroacoustics Tender

πŸ›οΈ TECHNISCHE UNIVERSITEIT DELFT NETHERLANDS
πŸ“„ Tender ID: 505055226 πŸ“… Published: 19 Jun 2024

πŸ“‹ Tender Overview

Modeling And Reduction Of Aeroacoustics Sources Of Interaction Noise In Aviation
The Target Of Climate-Neutral Aviation Has Led To A Strong Increase In The Size Of New Propulsion Systems, Resulting In Their Lowered Distance To The Airframe Components. This Causes New Aerodynamic Interactions With Heavy Distortion Of The Turbulent Flow, Determining Unpredictable Sources Of Noise. Mitigating This Interaction Noise Would Allow To Deploy Radically New Aircraft Configurations Capable Of Reducing Up To 20% Of The Current Aviation Emissions.
While Studies From Literature Have Tried To Correct Discrepancies Larger Than 10 Db From Acoustic Predictions By A-Posteriori Tuning The Models To Very Specific Flow Patterns, Recent Results From My Team Have Shed Light On The Physics Behind The Unpredictability Of These Noise Sources. Results Hinted That The Geometrical Deformation Of The Turbulent Flow From Its Original Pattern Might Explain The Origin Of Interaction Noise.
To Solve This Puzzle, With Morasina I Aim At First Understanding How The Flow And The Turbulence Are Distorted In Archetypal Interactions Between Rotating And Stationary Aerodynamic Objects. My Objective Is To Discover The Unknown Mathematical Formulation To Model This Distortion Mechanism And To Use It To Create The First Holistic Acoustic Model For Predictions Of Interaction Noise.
By Innovatively Describing The Interaction Mechanisms With Mathematical Functions Related To The Geometrical Distortion Of The Flow, I Will Find An Answer To Whether Different Flow Fields Can Be Assimilated In A Unique Fundamental Flow Pattern. With This Knowledge, I Will Create The First Acoustic Model Based On A Mathematical Flow Twin To Accurately Predict Interaction Noise.
For Maximum Impact On The Society, I Will Extend The Model To Equipollent Interaction Mechanisms With A Neural Network Approach Trained On The Results, Allowing The Use Of The Prediction Framework For Reducing Interaction Noise In The Design Of The Next Generation Of Zero-Emission And Silent Aircraft.
Funded Under
European Research Council (Erc)
Total Cost
€ 1 988 158,00
Eu Contribution
€ 1 988 158,00
Coordinated By
Technische Universiteit Delft
Netherlands
Start Date
1 October 2024
End Date
30 September 2029

Objective

The target of climate-neutral aviation has led to a strong increase in the size of new propulsion systems, resulting in their lowered distance to the airframe components. This causes new aerodynamic interactions with heavy distortion of the turbulent flow, determining unpredictable sources of noise. Mitigating this interaction noise would allow to deploy radically new aircraft configurations capable of reducing up to 20% of the current aviation emissions.
While studies from literature have tried to correct discrepancies larger than 10 dB from acoustic predictions by a-posteriori tuning the models to very specific flow patterns, recent results from my team have shed light on the physics behind the unpr

πŸ” Key Information

πŸ“„
Tender Reference No.
505055226
πŸ“…
Publication Date
19 Jun 2024
πŸ’°
Estimated Value
EUR 198815800
🌐
Sector
laboratory equipment and services
πŸ“…
Deadline
30 Sep 2029
πŸ“
Notice Type
Projects
πŸ“
Location
Netherlands
πŸ“‘
Contract Duration
5 Years 3 Months 11 Days

πŸ“ Documents & Downloads

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🧭 Quick Facts

Authority TECHNISCHE UNIVERSITEIT DELFT NETHERLANDS
Country Netherlands
State / UT N/A
Tender Type Project Information
Currency EUR
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