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Sonic Boom Minimization Using Improved Linearized Tools and Probabilistic Propagation
Author(s) -
Sriram K. Rallabhandi,
Dimitri N. Mavris
Publication year - 2005
Publication title -
43rd aiaa aerospace sciences meeting and exhibit
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2005-1019
Subject(s) - sonic boom , probabilistic logic , minification , boom , computer science , mathematical optimization , geology , engineering , mathematics , aerospace engineering , artificial intelligence , supersonic speed , oceanography
Sonic boom modelling is multidisciplinary involving aerodynamic and aero-acoustics analyses. The near eld pressure signature is rst obtained using either linearized or non-linear methods. This is then converted into a F-function, which is then propagated to the ground using aero-acoustic routines. Existing linearized methods operate on simple approximations of true geometry. Using improved linearized tools that operate on unstructured water-tight geometries, the accuracy and ecacy of shape optimization can be greatly improved. The sonic boom minimization technique is reformulated as an optimization problem and boom propagation is carried out in a probabilistic fashion. A bi-level reverse optimization is conducted to design aircraft to meet low sonic boom requirements under atmospheric uncertainty.

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