Category Archives: Computational Techniques

Perturbation techniques can provide valuable insights into flow control by identifying sensitive regions. However, performing such analyses with high-fidelity techniques, such as large eddy simulations or direct numerical simulations, can be computationally prohibitive. In this effort, we employ reduced-order modeling (ROM) of compressible Navier-Stokes equations based on the Galerkin-projection and proper orthogonal decomposition (POD) toContinue reading “Galerkin-POD Reduced-Order Modeling of Compressible Flows”

Modal decomposition finds common use in flowfield analysis, data-driven modeling and flow control. Among the more popular techniques are proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD). Modal analysis is most often performed in an Eulerian (fixed) frame of reference using unsteady flow snapshots obtained from experimental measurements or solutions to the governing equations.Continue reading “Lagrangian Modal Analysis (LMA)”

Galerkin projection of Navier–Stokes equations on proper orthogonal decomposition (POD) basis is predominantly used for model reduction in fluid dynamics. Robustness for changing operating conditions, numerical stability in long-term transient behavior and the pressure-term consideration are generally the main concerns of the Galerkin-POD reduced-order models (ROM). We develop a novel procedure to construct an off-referenceContinue reading “Galerkin-free reduced-order modeling for multiphysics systems”

The steam generator and reactor core of a nuclear power plant comprise a large number of small tubular structures with high interstitial velocities, leading to high Reynolds numbers, for instance, Figure 1 shows the internal view of the two process equipments. High-fidelity CFD simulation of the entire steam generator or reactor core is not feasibleContinue reading “Homogenization/macroscopic modeling”