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| Main Authors: | , |
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| Format: | Preprint |
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2024
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| Online Access: | https://arxiv.org/abs/2411.05617 |
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| _version_ | 1866915009936752640 |
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| author | Mushtaq, Talha Hemati, Maziar S. |
| author_facet | Mushtaq, Talha Hemati, Maziar S. |
| contents | Recent investigations have established the physical relevance of spatially-localized instability mechanisms in fluid dynamics and their potential for technological innovations in flow control. In this letter, we show that the mathematical problem of identifying spatially-localized optimal perturbations that maximize perturbation-energy amplification can be cast as a sparse (cardinality-constrained) optimization problem. Unfortunately, cardinality constrained optimization problems are non-convex and combinatorially hard to solve in general. To make the analysis viable within the context of fluid dynamics problems, we propose an efficient iterative method for computing sub-optimal spatially-localized perturbations. Our approach is based on a generalized Rayleigh quotient iteration algorithm followed by a variational renormalization procedure that reduces the optimality gap in the resulting solution. The approach is demonstrated on a sub-critical plane Poiseuille flow at Re = 4000, which has been a benchmark problem studied in prior investigations on identifying spatially-localized flow structures. Remarkably, we find that a subset of the perturbations identified by our method yield a comparable degree of energy amplification as their global counterparts. We anticipate our proposed analysis tools will facilitate further investigations into spatially-localized flow instabilities, including within the resolvent and input-output analysis frameworks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_05617 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Identifying spatially-localized instability mechanisms using sparse optimization Mushtaq, Talha Hemati, Maziar S. Fluid Dynamics Mathematical Physics Recent investigations have established the physical relevance of spatially-localized instability mechanisms in fluid dynamics and their potential for technological innovations in flow control. In this letter, we show that the mathematical problem of identifying spatially-localized optimal perturbations that maximize perturbation-energy amplification can be cast as a sparse (cardinality-constrained) optimization problem. Unfortunately, cardinality constrained optimization problems are non-convex and combinatorially hard to solve in general. To make the analysis viable within the context of fluid dynamics problems, we propose an efficient iterative method for computing sub-optimal spatially-localized perturbations. Our approach is based on a generalized Rayleigh quotient iteration algorithm followed by a variational renormalization procedure that reduces the optimality gap in the resulting solution. The approach is demonstrated on a sub-critical plane Poiseuille flow at Re = 4000, which has been a benchmark problem studied in prior investigations on identifying spatially-localized flow structures. Remarkably, we find that a subset of the perturbations identified by our method yield a comparable degree of energy amplification as their global counterparts. We anticipate our proposed analysis tools will facilitate further investigations into spatially-localized flow instabilities, including within the resolvent and input-output analysis frameworks. |
| title | Identifying spatially-localized instability mechanisms using sparse optimization |
| topic | Fluid Dynamics Mathematical Physics |
| url | https://arxiv.org/abs/2411.05617 |