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Large Eddy Simulation of Complex Flo...

Kumar, Praveen.

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Large Eddy Simulation of Complex Flow Oover Submerged Bodies.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Large Eddy Simulation of Complex Flow Oover Submerged Bodies./
作者:	Kumar, Praveen.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	194 p.
附註:	Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
Contained By:	Dissertation Abstracts International79-08B(E).
標題:	Aerospace engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10746711
ISBN:	9780355807424

Large Eddy Simulation of Complex Flow Oover Submerged Bodies.
Kumar, Praveen.

Large Eddy Simulation of Complex Flow Oover Submerged Bodies. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 194 p.

Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.

Thesis (Ph.D.)--University of Minnesota, 2018.

Predicting the complex flow over a submerged marine vessel in maneuver has two major challenges: the hull boundary layer and the flow due to the propeller. Large eddy simulation (LES) using the dynamic Smagorinsky model (DSM) (Germano et al. 1991, Lilly 1992) and discrete kinetic energy conserving numerical method of Mahesh et al. (2004) has successfully predicted complex flows in the past. This dissertation discusses four advancements towards reliably using LES to predict and understand the complex flows encountered during maneuvers of submerged marine vessels: (1) understanding skin-friction in axisymmetric boundary layers evolving under pressure gradients, (2) simulating attached flow over axisymmetric hulls and wake evolution, (3) assessing the dependence of the stern flow and axisymmetric wake on hull boundary layer characteristics, and (4) simulating flow through a propeller at design operating condition.

ISBN: 9780355807424Subjects--Topical Terms:

1002622
Aerospace engineering.

Large Eddy Simulation of Complex Flow Oover Submerged Bodies.
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100 1 $a Kumar, Praveen. $3 3431420
245 1 0 $a Large Eddy Simulation of Complex Flow Oover Submerged Bodies.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 194 p.
500 $a Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
500 $a Adviser: Krishnan Mahesh.
502 $a Thesis (Ph.D.)--University of Minnesota, 2018.
520 $a Predicting the complex flow over a submerged marine vessel in maneuver has two major challenges: the hull boundary layer and the flow due to the propeller. Large eddy simulation (LES) using the dynamic Smagorinsky model (DSM) (Germano et al. 1991, Lilly 1992) and discrete kinetic energy conserving numerical method of Mahesh et al. (2004) has successfully predicted complex flows in the past. This dissertation discusses four advancements towards reliably using LES to predict and understand the complex flows encountered during maneuvers of submerged marine vessels: (1) understanding skin-friction in axisymmetric boundary layers evolving under pressure gradients, (2) simulating attached flow over axisymmetric hulls and wake evolution, (3) assessing the dependence of the stern flow and axisymmetric wake on hull boundary layer characteristics, and (4) simulating flow through a propeller at design operating condition.
520 $a Axisymmetric boundary layers are studied using integral analysis of the governing equations for axial flow over a circular cylinder. The analysis includes the effect of pressure gradient and focuses on the effect of transverse curvature on boundary layer parameters such as shape factor (H) and skin-friction coefficient (Cf), defined as H = delta*/theta and Cf = tau w/(0.5rhoUe2) respectively, where delta* is displacement thickness, theta is momentum thickness, tauw is the shear stress at the wall, rho is density and Ue is the streamwise velocity at the edge of the boundary layer. Useful relations are obtained relating the mean wall-normal velocity at the edge of the boundary layer (V e) and Cf to the boundary layer and pressure gradient parameters. The analytical relations reduce to established results for planar boundary layers in the limit of infinite radius of curvature. The relations are used to obtain Cf which shows good agreement with the data reported in the literature. The analytical results are used to discuss different flow regimes of axisymmetric boundary layers in the presence of pressure gradients.
520 $a Wall-resolved LES is used to simulate flow over an axisymmetric body of revolution at a Reynolds number, Re = 1.1 x 10 6, based on freestream velocity and the length of the body. The geometry used in the present work is an idealized submarine hull (DARPA SUBOFF without appendages) at zero angle of pitch and yaw. The computational domain is chosen to avoid confinement effects and capture the wake up to fifteen diameters downstream of the body. The unstructured computational grid is designed to capture the fine near-wall structures as well as the wake. LES results show good agreement with the available experimental data. The axisymmetric turbulent boundary layer has higher skin-friction and higher radial decay of turbulence away from the wall, compared to a planar turbulent boundary layer under similar conditions. The mean streamwise velocity exhibits self-similarity, but the turbulent intensities are not self-similar over the length of the simulated wake, consistent with previous studies reported in the literature. The axisymmetric wake transitions from high-Re to low-Re equilibrium self-similar solutions, as theoretically proposed and observed for axisymmetric wakes in the past.
520 $a The recycle-rescale method of Lund is first implemented for unstructured grids and massively parallel platforms and then extended to spatially developing thin axisymmetric turbulent boundary layers. LES of flow over the stern portion of the hull is performed with a prescribed turbulent inflow at a momentum thickness theta/a=0.078 and a momentum thickness-based Reynolds number Retheta=2000, where a is the radius of curvature, to understand the dependence of the flow field in the stern region and the wake, on hull boundary layer characteristics. Additional simulations are performed to study the effect of Retheta and theta/a at the inflow. The turbulent inflows needed for the simulations are generated from auxiliary simulations employing the recycle-rescale methodology. Results are compared to past studies, and used to describe the effect of incoming TBL on the overall flow field. The pressure coefficient on the body is largely insensitive to the incoming boundary layer characteristics, except in the vicinity of flow separation, where it is more sensitive to theta/a . Skin-friction on the other hand, is very sensitive to the boundary layer characteristics. The boundary layer characteristics determine the location of flow separation and hence, the flow field in the stern region and the wake.
520 $a The wake of the body is more sensitive to Retheta compared to theta/a . The wake of a five-bladed marine propeller at design operating condition is studied using LES. The mean loads and phase-averaged flow field show good agreement with experiments. Phase-averaged and azimuthal-averaged flow fields are analyzed in detail to examine the mechanisms of wake instability. The propeller wake consisting of tip and hub vortices undergoes streamtube contraction, which is followed by the onset of instabilities as evident from the oscillations of the tip vortices. Simulation results reveal a mutual induction mechanism of instability where instead of the tip vortices interacting among themselves, they interact with the smaller vortices generated by the roll-up of the blade trailing edge wake in the near wake. It is argued that although the mutual-inductance mode is the dominant mode of instability in propellers, the actual mechanism depends on the propeller geometry and the operating conditions. The axial evolution of the propeller wake from near to far field is discussed. Once the propeller wake becomes unstable, the coherent vortical structures break up and evolve into the far wake composed of a fluid mass swirling around an oscillating hub vortex. The hub vortex remains coherent over the length of the computational domain.
590 $a School code: 0130.
650 4 $a Aerospace engineering. $3 1002622
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710 2 $a University of Minnesota. $b Aerospace Engineering and Mechanics. $3 1681609
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793 $a English
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