By Emiliano Iuliano, Esther Andrés Pérez
ISBN-10: 3319215051
ISBN-13: 9783319215051
ISBN-10: 331921506X
ISBN-13: 9783319215068
Aerodynamic layout, like many different engineering purposes, is more and more counting on computational strength. The turning out to be desire for multi-disciplinarity and excessive constancy in layout optimization for commercial purposes calls for a massive variety of repeated simulations with the intention to locate an optimum layout candidate. the most quandary is that every simulation should be computationally pricey – this turns into a much bigger factor while used inside parametric reviews, automatic seek or optimization loops, which generally could require hundreds of thousands of study evaluations.
The center factor of a design-optimization challenge is the quest approach concerned. even though, whilst dealing with complicated difficulties, the high-dimensionality of the layout house and the high-multi-modality of the objective services can't be tackled with normal techniques.
In contemporary years, international optimization utilizing meta-models has been largely utilized to layout exploration with a view to quickly examine the layout house and locate sub-optimal suggestions. certainly, surrogate and reduced-order versions gives you a invaluable substitute at a miles reduce computational cost.
In this context, this quantity bargains complex surrogate modeling functions and optimization options that includes moderate computational assets. It additionally discusses simple concept strategies and their software to aerodynamic layout instances. it really is aimed toward researchers and engineers who care for advanced aerodynamic layout difficulties each day and hire pricey simulations to unravel them.
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Additional info for Application of Surrogate-based Global Optimization to Aerodynamic Design
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Prog Aerosp Sci 45(1–3):50–79. 001 5. Gutmann HM (2001) A radial basis function method for global optimization. J Glob Optim 19:201–227. 1023/A:1011255519438. 596381 6. Iuliano E (2011) Towards a POD-based surrogate model for CFD optimization. In: Proceedings of the ECCOMAS CFD & optimization conference, Antalya 7. Iuliano E, Quagliarella D (2011) Surrogate-based aerodynamic optimization via a zonal pod model. In: Proceedings of the EUROGEN 2011 conference, Capua 8. Iuliano E, Quagliarella D (2013) Aerodynamic shape optimization via non-intrusive pod-based surrogate modelling.
This approach is normally preferred to the eigenvalue/eigenvector solution as it is faster and easier to implement. The discussion will unfold with specific reference to compressible aerodynamic problems, hence the space domain will be the discretized volume 30 E. Iuliano occupied by the flowing air and the snapshot vectors will be defined from computed flow fields. Given the three spatial components . g. e. sgrid ; sflow /T sgrid D . 1 ; : : : ; q ; 1 ; : : : ; q ; 1 ; : : : ; q / sflow D . 1 ; : : : ; q ; 10 ; : : : ; q0 ; 10 ; : : : ; 0 q; 0 1; : : : ; 0 q ; p1 ; : : : ; pq / where q is the number of mesh nodes involved in the POD computation, .
The first aims at unveiling promising regions of the design space where global/local minima might reside; the second consists in giving the surrogate model confidence on the prediction of minima locations and, as a result, sampling in the surroundings. For the sake of clarity, an evenlyspaced dense sampling could be classified as purely exploratory, while a properly clustered sampling could fall in the exploitative class. As a consequence, a trade-off exist between the exploration of the design solutions and the trust in surrogate accuracy near predicted minima.
Application of Surrogate-based Global Optimization to Aerodynamic Design by Emiliano Iuliano, Esther Andrés Pérez
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