Kiran Bhaganagar

Application of proper orthogonal decomposition (POD) to investigate a turbulent boundary layer in a channel with rough walls

Snapshot proper orthogonal decomposition (POD) is used to investigate a rough-wall turbulent boundary layer in a channel. One- and two-dimensional POD decompositions have been performed using 3D velocity database from direct numerical simulations (DNS). DNS of a turbulent channel flow with rough walls consisting of 3D roughness elements have been performed at Reτ = 180. 1D analysis has revealed that convergence of the POD for a rough wall is slower compared to the smooth wall, which is attributed to the increase in range of length scales due to roughness. For the egg-carton roughness elements, the depth of a roughness sublayer (ζmode n ) for POD mode n decays with increasing mode number in an exponential manner as ζmode n = 14e −0.86 n h for roughness of height h. The reconstruction of turbulence intensities and shear stress has revealed that the inner layer which includes the roughness sublayer is well captured by first 10 POD modes. 2D POD analysis has revealed that roughness alters the size and spacing...

Direct numerical simulation of unsteady flow in channel with rough walls

A fundamental study has been performed to understand the effect of unsteady forcing on turbulence statistics in channel flow with rough walls using direct numerical simulation. Unsteady flows have been generated by applying an unsteady nonzero mean forcing in the form of time varying pressure gradient such that the amplitude of oscillations is between 19% and 26% of mean centerline velocity and covering a range of forcing frequencies. The analysis has revealed unsteady forcing, depending on the forcing frequency, results in enhanced roughness compared to steady channel flow. The rough-wall flow dynamics have been categorized into high-, intermediate-, and low-frequency regimes. In the regime of high-frequency forcing, unsteadiness alters the mean velocity and turbulence intensities only in the inner layer of the turbulent boundary layer. Further, the turbulence intensities are out of phase with each other and also with the external forcing. In the regime of intermediate-frequency forcing, mean velocity an...

Effect of roughness on pressure fluctuations in a turbulent channel flow

Direct numerical simulation is used to investigate the nature of pressure fluctuations induced by surface roughness in a turbulent channel flow at Reτ=400 for three-dimensional periodic roughness elements, whose peaks overlap approximately 25% of the logarithmic layer. The three-dimensional roughness elements alter the pressure statistics significantly, compared to the corresponding smooth-wall flow, in both the inner and outer (core) regions of the channel. The direct consequence of roughness is an increased form drag, associated with more intense pressure fluctuations. However, it also alters the pressure fluctuations in the outer layer of the flow, and modifies the length scales defined by two-point correlations. We also find that the depth of the roughness sublayer defined by the pressure fluctuations is very different from that given by the large- and small-scale statistics from the velocity field.

Understanding turbulent flow over ripple-shaped random roughness in a channel

Direct numerical simulation is used to understand the flow over ripple-shaped random rough elements. The random roughness has been generated using the model for sand ripples consisting of saltation, creep and suspension processes. A set of metrics based on both the geometrical and statistical properties of roughness was derived to characterize random roughness. The eight cases that have been studied with varied asymmetric distribution and “peakedness” as specified by the skewness and kurtosis of the height distribution varying from 0.28 to 0.7, and from 1.8 to 2.2, respectively. Analogous to λ/h for canonical (regular) roughness, λavg/hmax was selected as the geometrical parameter to characterize the surface, ranging from 4 to 26. The results have revealed that roughness significantly alters the mean velocity as well as turbulence in the inner layer. The outer layer is relatively unaffected due to the presence of roughness. The results further revealed that roughness distribution that is symmetric and whi...

Using fuzzy logic for morphological classification of IVUS-based plaques in diseased coronary artery in the context of flow-dynamics

Plaque morphology in a diseased coronary artery plays a significant role in the modification of the fluid flow characteristics. The plaque morphology of 42 patients who underwent IVUS (intravascular ultrasound) procedure was quantified by degree of membership in four fuzzy logic sets, which we refer as type I: protruding, type II: ascending, type III: descending, and type IV: diffuse. Of 42 cases, 28% were of type I, 18% type II, 20% type III and 23% type IV, 6% belonged to hybrid types (partial members of multiple types) and the remaining 5% did not fit in any category. The degree of membership is of significance as the inter-class blood flow patterns (those strongly members of the same set) are similar to each other compared to the intra-class behavior, indicating plaque morphology (shape of blockage) is an important metric in addition to the degree of stenosis to represent the flow characteristics in a diseased stenotic coronary artery.

Role of head of turbulent 3-D density currents in mixing during slumping regime

A fundamental study was conducted to shed light on entrainment and mixing in buoyancy-driven Boussinesq density currents. Large-eddy simulation was performed on lock-exchange (LE) release density currents—an idealized test bed to generate density currents. As dense fluid was released over a sloping surface into an ambient lighter fluid, the dense fluid slumps to the bottom and forms a characteristic head of the current. The dynamics of the head dictated the mixing processes in LE currents. The key contribution of this study is to resolve an ongoing debate on mixing: We demonstrate that substantial mixing occurs in the early stages of evolution in an LE experiment and that entrainment is highly inhomogeneous and unsteady during the slumping regime. Guided by the flow physics, entrainment is calculated using two different but related perspectives. In the first approach, the entrainment parameter (E) is defined as the fraction of ambient fluid displaced by the head that entrains into the current. It is an in...