|Date||Speaker||Presentation Title & File Link|
|11/18/09||Juan Alonso||Some Examples of Uncertainty Quantification and Design Under Uncertainty in Aerospace Problems|
J.J. Alonso, Stanford University
In this brief informal talk I will highlight two examples of current interest in our research group that involve the quantification of uncertainties and their impact on the design of optimal, robust, and reliable systems. The first example is the centerpiece of the DoE Predictive Science Academic Alliance Program (PSAAP) Center at Stanford and is concerned with the quantification of margins and uncertainties in the operation of hypersonic scramjet engines. The uncertainties in this problem are both of an aleatory (manufactured geometry, operation, and other Gaussian variability) and epistemic (arising from turbulence and combustion models mostly) nature and involve very high-fidelity simulations of multi-physics problems. The second problem involves the design of high-performance, low sonic boom supersonic aircraft. In this problem, uncertainties creep in through the actual shape of the aircraft, its lift distribution, and the operating parameters (angle of attack, altitude, speed, atmospheric disturbances, etc.). Not only is important to predict the behavior of the system (both its lift, drag, and sonic boom loudness), it is also necessary to design the system in a robust fashion so that small disturbances do not result in large changes in drag and boom of the signature. Both problems have some commonality and present very significant challenges for optimization because of the nature of the design spaces.
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