LES of Flow past Circular Cylinder at Re = 3900

Rajani, BN; Kandasamy, A.

doi:10.18869/acadpub.jafm.68.228.24178

Cited by 33 publications

(20 citation statements)

References 33 publications

(58 reference statements)

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“…The vestiges of onset of instability at higher Re numbers (Re = 1000) is observed from the asymmetry in mode 3. This is consistent with the observations in [71], where the laminar vortex shedding happens at around Re = 47, and becomes unstable at ∼ 190 which deforms the small-scale structures at higher POD modes. On the other hand, the temporal evolution of POD coefficients show periodic limit-cycle behavior for all the Re numbers with the characteristic frequencies increasing with Re as shown in fig.…”

Section: Cylinder Wake Limit-cycle Dynamicssupporting

confidence: 92%

Interplay of Sensor Quantity, Placement and System Dimension in POD-based Sparse Reconstruction of Fluid Flows

Jayaraman¹,

Mamun²,

Chen³

2019

Preprint

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Sparse recovery of fluid flows using data-driven proper orthogonal decomposition (POD) basis is systematically explored in this work. Fluid flows are manifestations of nonlinear multiscale PDE dynamical systems with inherent scale separation that impact the system dimensionality. Given that sparse reconstruction is inherently an ill-posed problem, the most successful approaches require the knowledge of the underlying basis space spanning the manifold in which the system resides. In this study, we employ an approach that learns basis from singular value decomposition (SVD) of training data to reconstruct sparsely sensed information. This results in a set of four control parameters for sparse recovery, namely, the choice of basis, system dimension required for sufficiently accurate reconstruction, sensor budget and their placement. The choice of control parameters implicitly determines the choice of algorithm as either $l_2$ minimization reconstruction or sparsity promoting $l_1$ norm minimization reconstruction. In this work, we systematically explore the implications of these control parameters on reconstruction accuracy so that practical recommendations can be identified. We observe that greedy-smart sensor placement provides the best balance of computational complexity and robust reconstruction for marginally oversampled cases which happens to be the most challenging regime in the explored parameter design space.

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Section: Cylinder Wake Limit-cycle Dynamicssupporting

confidence: 92%

Interplay of Sensor Quantity, Placement and System Dimension in POD-based Sparse Reconstruction of Fluid Flows

Jayaraman¹,

Mamun²,

Chen³

2019

Preprint

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“…The symbols are explained in the nomenclature in the beginning of the paper. The characteristics from [11] are from the high-resolution LES case and the data from [18] are from 'run 7'. Recirculation length and vortex formation length are measured from the base of the cylinder.…”

Section: Resultsmentioning

confidence: 99%

Influence of spanwise no-slip boundary conditions on the flow around a cylinder

et al. 2017

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First we present high resolution large eddy simulations (LES) for the flow past a circular cylinder at Reynolds number 3900 to prove the quality of the simulations. A thorough grid convergence study is presented, and the agreement in the mean flow statistics between our simulations and the references is excellent. Then we apply a no-slip boundary condition at the spanwise boundaries of the cylinder, with aspect ratios of 6, 12 and 24. This results in large changes in the shear layers and wake topology, even for an aspect ratio of 24. Even though the boundary layers along the side walls are only about 0.4 diameters thick, they nevertheless manage to stabilize the shear layers all the way through the channel, thus effectively delaying the roll-up and transition to a turbulent wake.

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“…In this section, validation of the present obtained results for the fixed cylinder are demonstrated. For this purpose, the results are validated comparing the calculated pressure coefficient with the data reported in [31]. Also, the validation of the thermal part is performed via comparing the obtained local Nusselt number distribution with the available data reported in [32].…”

Section: Fixed Cylindermentioning

confidence: 98%

“…Also, the validation of the thermal part is performed via comparing the obtained local Nusselt number distribution with the available data reported in [32]. In [31], the flow around the cylinder in subcritical regime is simulated utilizing the large eddy simulation method. The results obtained for the pressure coefficient are, respectively, validated and verified with the reported findings in [31] and [33].…”

Section: Fixed Cylindermentioning

confidence: 99%

Combined active-passive heat transfer control using slotted fins and oscillation in turbulent flow: the cases of single cylinder and tube banks

Soheibi,

Shomali,

Ghazanfarian

2021

Preprint

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In heat transfer augmenting methods such as radial fins, the heat transfer enhancement commonly leads to the drag force increment. In the present paper, slots are inserted over the fins to simultaneously reduce the drag coefficient. Turbulent convection heat transfer around a cylinder, as well as oscillating bundle of tubes including the slotted radial fins have been investigated. The governing equations are solved in two-dimension utilizing OpenFOAM software based on k-ω SST closure model. The cases with various slot location, slot width, the number of the slots, the fin height, and oscillation frequencies are examined. In all cases, the Reynolds number is taken to be equal to 5000. Presence of three slots on the fins reduces the drag coefficient by 23% and augments the Nusselt number by 76%. In order to enhance the heat transfer from the bundle of tube, oscillation of tubes and utilization of the slotted fins are applied. The optimum situation occurs for a sample with the oscillating third column that shows 3% increment in heat transfer relative to that of the fixed case. This is while adding the slotted fins to the oscillating tube bank increases the heat transfer up to 2.5 times.

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LES of Flow past Circular Cylinder at Re = 3900

Cited by 33 publications

References 33 publications

Interplay of Sensor Quantity, Placement and System Dimension in POD-based Sparse Reconstruction of Fluid Flows

Interplay of Sensor Quantity, Placement and System Dimension in POD-based Sparse Reconstruction of Fluid Flows

Influence of spanwise no-slip boundary conditions on the flow around a cylinder

Combined active-passive heat transfer control using slotted fins and oscillation in turbulent flow: the cases of single cylinder and tube banks

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