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1. Effect of Channel Roughness on Micro-Droplet Distribution in Internal Minimum Quantity Lubrication

   https://doi.org/10.3390/dynamics2040019  

   Craig, Michael; Raval, Jay; Tai, Bruce; Patterson, Albert; Hung, Wayne (December 2022, Dynamics)

   This research studied the effect of channel roughness on micro-droplet distributions in internal minimum quantity lubrication for effective machining. Mixtures of different oils and air were flown though internal channels with simulated different roughness: as fabricated, partially threaded, and fully threaded. The airborne droplets were collected, analyzed, and compared with simulated results by computational fluid dynamics. For low-viscous lubricant, the rough channel surface helped to break large droplets in the boundary layer into smaller droplets and reintroduce them into the main downstream flow. The opposite trend was found for the higher viscous lubricant. The study also performed chemical etching to roughen selected surfaces of carbide cutting tools. The synergy of hand and ultrasonic agitation successfully roughened a carbide surface within twelve minutes. Scanning electron microscopy examination showed deep etching that removed all grinding marks on a WC–Co cutting tool surface. 

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2. A mathematical model for bedrock incision in near‐threshold gravel‐bed rivers

   https://doi.org/10.1002/esp.5957  

   Gabel, Vanessa; Tucker, Gregory E; Campforts, Benjamin (July 2025, Earth Surface Processes and Landforms)

   Gravel‐bed rivers that incise into bedrock are common worldwide. These systems have many similarities with other alluvial channels: they transport large amounts of sediment and adjust their forms in response to discharge and sediment supply. At the same time, the occurrence of bedrock incision implies behaviour that falls on a spectrum between fully detachment‐limited ‘bedrock channels’ and fully transport‐limited ‘alluvial channels’. Here, we present a mathematical model of river profile evolution that integrates bedrock erosion, gravel transport and the formation of channels whose hydraulic geometry is consistent with that of near‐threshold alluvial channels. We combine theory for five interrelated processes: bedload sediment transport in equilibrium gravel‐bed channels, channel width adjustment to flow and sediment characteristics, abrasion of bedrock by mobile sediment, plucking of bedrock and progressive loss of gravel‐sized sediment due to grain attrition. This model contributes to a growing class of models that seek to capture the dynamics of both bedrock incision and alluvial sediment transport. We demonstrate the model's ability to reproduce expected fluvial features such as inverse power law scaling between slope and area, and width and depth consistent with near‐threshold channel theory, and we discuss the role of sediment characteristics in influencing the mode of channel behaviour, erosional mechanism, channel steepness and profile concavity. 

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3. Laboratory study of bed shear stress in gradually varied flow over a sudden change in bed roughness

   https://doi.org/10.1007/s10652-025-10024-6  

   Jamil, Muhammad Farrukh; Ting, Francis_C K; Kafle, Monika (April 2025, Environmental Fluid Mechanics)

   Abstract The evolution of bed shear stress in open-channel flow due to a sudden change in bed roughness was investigated experimentally for rough-to-smooth (RTS) and smooth-to-rough (STR) transitions. The velocity field was measured in the longitudinal-vertical plane from upstream to downstream using a Particle Image Velocimetry system. The bed shear stress was determined from the measured velocity profile and water depth using various methods. It was found that the variation of bed shear stress in gradually varied flow through a roughness transition was influenced by both flow depth and bottom roughness. In both RTS and STR transitions, the bed shear stress adjusted to the new bed condition almost immediately even though the velocity profile away from the bed was still evolving, but unlike external and close-conduit flows the bed shear stress in open-channel flows continued to evolve until the flow depth was uniform. It is shown that the evolution of bed shear stress in a STR transition is dependent on the choice of the displacement height on the rough bed, which affects the mixing length used to derive the logarithmic velocity profile and equivalent roughness. Bed shear stress variation consistent with published data was obtained when the$${k}_{s}/{d}_{90}$$ $k_s/d_{90}$ratio was determined as a function of the$$h/{d}_{90}$$ $h/d_{90}$ratio, where$${k}_{s}$$ $k_s$is the equivalent roughness height,$$h$$ $h$is the flow depth, and$${d}_{90}$$ $d_{90}$is the grain diameter with 90% of finer particles. 

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4. Machine-learning wall-model large-eddy simulation accounting for isotropic roughness under local equilibrium

   https://doi.org/10.1017/jfm.2025.29  

   Ma, Rong; Lozano-Durán, Adrián (March 2025, Journal of Fluid Mechanics)

   We introduce a wall model for large-eddy simulation (WMLES) applicable to rough surfaces with Gaussian and non-Gaussian distributions for both the transitionally and fully rough regimes. The model is applicable to arbitrary complex geometries where roughness elements are assumed to be underresolved, i.e. subgrid-scale roughness. The wall model is implemented using a multi-hidden-layer feedforward neural network, with the mean geometric properties of the roughness topology and near-wall flow quantities serving as input. The optimal set of non-dimensional input features is identified using information theory, selecting variables that maximize information about the output while minimizing redundancy among inputs. The model also incorporates a confidence score based on Gaussian process modelling, enabling the detection of potentially low model performance for untrained rough surfaces. The model is trained using a direct numerical simulation (DNS) roughness database comprising approximately 200 cases. The roughness geometries for the database are selected from a large repository through active learning. This approach ensures that the rough surfaces incorporated into the database are the most informative, achieving higher model performance with fewer DNS cases compared with passive learning techniques. The performance of the model is evaluated bothaprioriandaposterioriin WMLES of turbulent channel flows with rough walls. Over 550 channel flow cases are considered, including untrained roughness geometries, roughness Reynolds numbers and grid resolutions for both transitionally and fully rough regimes. Our rough-wall model offers higher accuracy than existing models, generally predicting wall shear stress within an accuracy range of 1%–15 %. The performance of the model is also assessed on a high-pressure turbine blade with two different rough surfaces. We show that the new wall model predicts the skin friction and the mean velocity deficit induced by the rough surface on the blade within 1%–10 % accuracy except the region with transition or shock waves. This work extends the building-block flow wall model (BFWM) introduced by Lozano-Durán & Bae (2023.J. Fluid Mech.963, A35) for smooth walls, expanding the BFWM framework to account for rough-wall scenarios. 

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5. Ablation‐Limited Erosion Rates of Permafrost Riverbanks

   https://doi.org/10.1029/2023JF007098  

   Douglas, Madison M.; Miller, Kimberly Litwin; Schmeer, Maria N.; Lamb, Michael P. (July 2023, Journal of Geophysical Research: Earth Surface)

   Abstract Permafrost thaw is hypothesized to increase riverbank erosion rates, which threatens Arctic communities and infrastructure. However, existing erosion models have not been tested against controlled flume experiments with open‐channel flow past an erodible, hydraulically rough permafrost bank. We conducted temperature‐controlled flume experiments where turbulent water eroded laterally into riverbanks consisting of sand and pore ice. The experiments were designed to produce ablation‐limited erosion such that any thawed sediment was quickly transported away from the bank. Bank erosion rates increased linearly with water temperature, decreased with pore ice content, and were insensitive to changes in bank temperature, consistent with theory. However, erosion rates were approximately a factor of three greater than expected. The heightened erosion rates were due to a greater coefficient of heat transfer from the turbulent water to the permafrost bank caused by bank grain roughness. A revised ablation‐limited bank erosion model with a heat transfer coefficient that includes bank roughness matched our experimental results well. Results indicate that bank erosion along Arctic rivers can accelerate under scenarios of warming river water temperatures for cases where the cadence of bank erosion is set by pore‐ice melting rather than sediment entrainment. 

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