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This study aims to enhance the robustness and computational efficiency of reduced-order models (ROMs) for fluid flows.

Improvement of Reduced-Order Model for Two-Dimensional Cylinder Flow Based on Global Proper Orthogonal Decomposition in terms of Robustness and Computational Speed

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Demonstrates a new ROM framework improving robustness and speed in fluid engineering applications, enabling faster flow predictions.

This study aims to enhance the robustness and computational efficiency of reduced-order models (ROMs) for fluid flows.
Develop a new ROM framework using a two-step order-reduction strategy based on proper orthogonal decomposition (POD).
Incorporate multiple flow conditions while minimizing computational costs.
Evaluate performance on a two-dimensional unsteady flow past a circular cylinder.
The proposed ROM maintains accuracy while reducing computational cost by approximately 50% compared to conventional POD-based models.
Accurately reproduces the relationship between vortex-shedding frequency and Reynolds number from full numerical simulations.

Nakamura et al. (2026) studied this question.

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View Full Paper

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Authors

Demonstrates a new ROM framework improving robustness and speed in fluid engineering applications, enabling faster flow predictions.

This study aims to enhance the robustness and computational efficiency of reduced-order models (ROMs) for fluid flows.
Develop a new ROM framework using a two-step order-reduction strategy based on proper orthogonal decomposition (POD).
Incorporate multiple flow conditions while minimizing computational costs.
Evaluate performance on a two-dimensional unsteady flow past a circular cylinder.
The proposed ROM maintains accuracy while reducing computational cost by approximately 50% compared to conventional POD-based models.
Accurately reproduces the relationship between vortex-shedding frequency and Reynolds number from full numerical simulations.

Nakamura et al. (2026) studied this question.

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