Direct effects of boundary permeability on turbulent flows: observations from an experimental study using zero-mean-shear turbulence

McCorquodale, Mark W.; Munro, R. G.

doi:10.1017/jfm.2021.160

Cited by 4 publications

(2 citation statements)

References 72 publications

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“…The flow and transport processes involved are characterised by complex interactions between the porous medium and the free flow, including the two-way exchange of mass, momentum and energy across the interface (Breugem, Boersma & Uittenbogaard 2006;Manes, Poggi & Ridolfi 2011;Fang et al 2018;Suga, Okazaki & Kuwata 2020). Understanding the transport behaviour at the permeable interface is a non-trivial challenge, which involves a wide range of properties of the porous medium, such as permeability (Suga, Nakagawa & Kaneda 2017;Voermans, Ghisalberti & Ivey 2017;Rosti, Brandt & Pinelli 2018), surface roughness ) and pore geometry (Suga et al 2020;Shen, Yuan & Phanikumar 2020;McCorquodale & Munro 2021;Xu et al 2021). The early works have (Finnigan 2000;Jiménez et al 2001;Breugem et al 2006) established a framework for the coupling dynamics across the interface, which can be summarized as competing mechanisms in the flow: the formation of wall-attached eddies and the disruption by shear layer instabilities.…”

Section: Introductionmentioning

confidence: 99%

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Spatial and spectral characteristics of information flux between turbulent boundary layers and porous media

et al. 2022

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The interaction between boundary layer turbulence and a porous layer is the cornerstone of interface engineering. In this study, the spatial and spectral-resolved transfer entropy is used to assess the asymmetry of the causal interaction next to the permeable wall. The analysis is based on pore-resolved direct numerical simulation of turbulent channel flow over cylinder arrays. The spatial map of transfer entropy reveals the information flux between the porous medium and arbitrary nearby positions, and paths connecting locations with maximum information transfer are identified. The paths in the ‘top-down’ and ‘bottom-up’ directions, respectively, lean upstream and downstream, demonstrating that the coupling process is directionally dependent. The scale dependence of transfer entropy is inspected with a surrogate data strategy. As wall permeability increases, the active scale range in causal interaction shifts from near-wall vortices to Kelvin–Helmholtz type eddies. In addition, linear stochastic estimation is used to determine the statistical velocity field for a local informative event. In an average sense, the interaction between a convecting sweep or ejection event and the up/down-welling motions at the pore unit is the core mechanism that contributes to the causal coupling. The statistical findings derived from the transfer entropy are then validated using a neural network-based remote sensing model.

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Section: Introductionmentioning

confidence: 99%

“…2020) and pore geometry (Suga et al. 2020; Shen, Yuan & Phanikumar 2020; McCorquodale & Munro 2021; Xu et al. 2021).…”

Section: Introductionmentioning

confidence: 99%

Spatial and spectral characteristics of information flux between turbulent boundary layers and porous media

et al. 2022

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Artificial neural network-based wall-modeled large-eddy simulations of turbulent channel and separated boundary layer flows

Lee

2023

Aerospace Science and Technology

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An assessment of turbulence transportation near regular and random permeable interfaces

et al. 2021

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Turbulent channel flow with a porous wall is investigated using direct numerical simulation, where the porous media domain consists of regular or random circular cylinder arrays. We compare the statistics and structure of the mean flow and turbulence in the channel flow with a bulk Reynolds number of 2500 and two porosities (φ=0.6 and 0.8) for the porous media. It is shown that the random interface significantly affects the dynamics of turbulence and the time-averaged flow. More intense mixing is observed near the random interface due to augmented form-induced shear stresses. Due to the strong dependence of induced flow direction on the interface geometry, we segmented the flow field into two types of areas based on the slope angle formed by the top-layer cylinders: the windward area and leeward area. The conditional average of turbulence kinematic energy budget over each type of area reveals their respective role in turbulence transportation more explicitly. In addition, we use finite-time Lyapunov exponents to inspect the Lagrangian coherent structures in the flow fields, which reveal the preferential fluid trajectories in the random porous medium geometry.

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Direct effects of boundary permeability on turbulent flows: observations from an experimental study using zero-mean-shear turbulence

Abstract: Abstract

Cited by 4 publications

References 72 publications

Spatial and spectral characteristics of information flux between turbulent boundary layers and porous media

Spatial and spectral characteristics of information flux between turbulent boundary layers and porous media

Artificial neural network-based wall-modeled large-eddy simulations of turbulent channel and separated boundary layer flows

An assessment of turbulence transportation near regular and random permeable interfaces

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