Flow Patterns Research Articles

A novel additive regression model for streamflow forecasting in German rivers

Forecasting streamflows, essential for flood mitigation and the efficient management of water resources for drinking, agriculture and hydroelectric power generation, presents a formidable challenge in most real-world scenarios. In this study, two models, the first based on the Additive Regression of Radial Basis Function Neural Networks (AR-RBF) and the second based on the stacking with the Pace Regression of the Multilayer Perceptron and Random Forest (MLP-RF-PR), were compared for the prediction of short-term (1–3 days ahead) and medium-term (7 days ahead) daily streamflow rates of three different rivers in Germany: the Elbe River at Wittenberge, the Leine River at Herrenhausen, and the Saale River at Hof. The lagged values of streamflow rate, precipitation and temperature were considered for the modeling. Moreover, the Bayesian Optimization (BO) algorithm was used to assess the optimal number of lagged values and hyperparameters. Both models showed accurate predictions for short-term forecasting, with R2 for 1-day ahead predictions ranging from 0.939 to 0.998 for AR-RBF and from 0.930 to 0.996 for MLP-RF-PR, while MAPE ranged from 2.02 % to 8.99 % for AR-RBF and from 2.14 % to 9.68 % for MLP-RF-PR, when exogeneous variables were included. As the forecast horizon increased, a reduction in forecasting accuracy was observed. However, both models could still predict the overall flow pattern, even for 7-day-ahead predictions, with R2 ranging from 0.772 to 0.871 for AR-RBF and from 0.703 to 0.840 for MLP-RF-PR, while MAPE ranged from 10.60 % to 20.45 % for AR-RBF and from 10.44 % to 19.65 % for MLP-RF-PR. Overall, the outcomes of this study suggest that both AR-RBF and MLP-RF-PR can be reliable tools for the short- and medium-term streamflow rate prediction, requiring a short number of parameters to be optimized, making them easy to implement while reducing the calculation time required.

Multiphase flow dynamics in metal foam proton exchange membrane fuel cell

Porous metal foam holds substantial promise as a material for bipolar plates in high-performance proton exchange membrane fuel cells (PEMFC) due to its exceptional properties in reactant redistribution. However, the intricate structure of metal foam flow field (MFF) presents challenges for mass transfer and water management. In this study, a three-dimensional two-phase flow model for metal foam is developed to analyze and capture flow patterns. MFFs are reconstructed based on detailed structural analysis and various pore sizes are discussed. Employing the Volume of Fluid (VOF) method, we delve into multiphase flow dynamics, specifically focusing on the removal of liquid droplets within the MFF. It reveals the MFF with moderate pore sizes exhibit a trade-off performance, striking a balance between optimal mass transfer and minimal parasitic loss. The porous structure's pivotal role is highlighted, contributing significantly to both through-plane and in-plane mass transfer and convection. Furthermore, we classify three flow patterns of liquid droplet, with the “split-up” pattern emerging as the most effective for water management and mass transfer. This study illuminates water behavior in porous metal foam bipolar plates, introduces a systematic methodology for assessing mass transfer and water management capabilities in MFFs for PEMFC.

Flow across a circular cylinder in an inclined channel stabilized by buoyancy

In this study, flow across a circular cylinder confined in an inclined channel is considered, with account taken of mixed convection. Cases with opposing or aiding buoyancy that is not in alignment with the incoming flow are considered, and it is found that the flow around and in the wake of the cylinder is affected. The effects of inclination and buoyancy on the flow and heat transfer patterns are investigated, with a focus on the stabilization and destabilization of flow by these two factors. Simulation results are analyzed with regard to the flow field, lift and drag forces, heat transfer, the deviation of separation and through-flow in the channel, and the temperatures on the channel walls. The flow is more strongly destabilized by an opposing buoyancy, but can be fully stabilized by an aiding buoyancy in an inclined channel. The drag on the cylinder is minimized around a critical Richardson number Ricr. The inclination of the channel has significant effects on the local heat transfer on the cylinder and on the characteristics of the through-flow. The pattern of the wake flow, i.e., whether it is steady or unsteady, affects the heating of the channel walls.

Chaotic-flow-driven mixing in T- and V-shaped micromixers

T- and V-shaped (or arrow-shaped) micromixers enable the control of rapid chemical reactions by permitting accelerated mixing. Their mixing performance has been extensively investigated at moderate flow rates, which correspond to Reynolds numbers of the order of several hundreds. However, this operating range does not align with the recent applications of microreactors in organic synthesis. Therefore, this study examined mixing times in T- and V-shaped micromixers with 250-µm-wide channels at high flow rates (Reynolds numbers of up to 1500). The progress of mixing between an acidic solution and a basic solution containing a pH-sensitive fluorescent molecule was visualized by fluorescence microscopy imaging. An image analysis of 200 frames for each condition helped evaluate the degree of mixing and its stability over time under chaotic flow. The performance and stability of the V-shaped micromixer were significantly enhanced when the flow-rate ratio was changed from 1:1 to 1:2. The difference in momentum between the two inlet streams suppressed the undesirable alternation of the flow patterns at the junction. The effects of the choice of fluids (in the lower- and higher-flow-rate sides) on the reaction selectivity were explored through a numerical analysis. It was clarified that the substrate-side flow rate has to be set lower than that of the reactant side in the competing consecutive reaction system. Moreover, a short mixing time of 1 ms was achieved using the V-shaped micromixer at a flow-rate ratio of 1:2 and Re of 1500. These findings provide practical guidelines for the design and operation of microreactor systems.

Atypical connectome topography and signal flow in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most common pharmaco-resistant epilepsy in adults. While primarily associated with mesiotemporal pathology, recent evidence suggests that brain alterations in TLE extend beyond the paralimbic epicenter and impact macroscale function and cognitive functions, particularly memory. Using connectome-wide manifold learning and generative models of effective connectivity, we examined functional topography and directional signal flow patterns between large-scale neural circuits in TLE at rest. Studying a multisite cohort of 95 patients with TLE and 95 healthy controls, we observed atypical functional topographies in the former group, characterized by reduced differentiation between sensory and transmodal association cortices, with most marked effects in bilateral temporo-limbic and ventromedial prefrontal cortices. These findings were consistent across all study sites, present in left and right lateralized patients, and validated in a subgroup of patients with histopathological validation of mesiotemporal sclerosis and post-surgical seizure freedom. Moreover, they were replicated in an independent cohort of 30 TLE patients and 40 healthy controls. Further analyses demonstrated that reduced differentiation related to decreased functional signal flow into and out of temporolimbic cortical systems and other brain networks. Parallel analyses of structural and diffusion-weighted MRI data revealed that topographic alterations were independent of TLE-related cortical thinning but partially mediated by white matter microstructural changes that radiated away from paralimbic circuits. Finally, we found a strong association between the degree of functional alterations and behavioral markers of memory dysfunction. Our work illustrates the complex landscape of macroscale functional imbalances in TLE, which can serve as intermediate markers bridging microstructural changes and cognitive impairment.

FGM vs ATF: A comparative LES analysis in predicting the flame characteristics of an industrial lean premixed burner for gas turbine applications

In the pursuit of decarbonization, the reduction of greenhouse gas emissions from power generation through gas turbine (GT) engines plays a crucial role in the whole industrial sector. As industries strive to transition towards cleaner energy sources, the design and optimization of novel GT burners require a deep comprehension of the complex interaction between fluid dynamics and combustion processes embedded within the system. Computational Fluid Dynamics (CFD) plays a pivotal role in these processes by providing valuable insights into the complex flow patterns, flame topology, and stability limits within the combustor. Concurrently, the burner design phase necessitates a considerable number of simulations to ascertain flame stability limits under various burner designs and operating conditions. Therefore, it is imperative to control computational costs while ensuring a high level of accuracy. The present work is focused on a comprehensive comparative analysis of two widely employed turbulent combustion closure models: the Flamelet Generated Manifold (FGM) and the Artificially Thickened Flame (ATF). Both models utilize extended versions with specific modifications aimed at effectively addressing their respective limitations. The investigation is performed through a Large Eddy Simulation (LES) based CFD analysis within the context of a lean premixed burner designed by Baker Hughes and operated with methane at atmospheric pressure. The primary benchmark for numerical validation will be provided by detailed chemiluminescence images from a test campaign conducted by the University of Florence, thereby yielding valuable insights into flame topology and positioning. Furthermore, potential disparities in the flow field and fuel concentration at the burner exit between the two models will be revealed.

Polymeric field synergy principle: Revealing the intrinsic mechanism of screw channel optimization to enhance thermal management and process efficiency

The process efficiency and energy efficiency of extrusion equipment emerge as pivotal challenges constraining the development of the polymer extrusion industry. This article presents a new principle of polymeric field synergy to guide the solution to the low mixing efficiency and energy utilization efficiency of traditional extrusion equipment. Finite element analysis was conducted on four novel unconventional screw configurations and compared with the traditional single-thread screw. Results revealed that more complicated melt flow patterns generated in the modified novel screw configurations enhanced the stretching deformation or helical flow. The stretching or helical flows to varying degrees during the melt extrusion process thereby improved the mixing and heat transport efficiency. Among them, helical flow induced by the Maddock element exhibited the most significant impact on stretching flow and ductile deformation in the flow field. Simultaneously, the helical flow caused radial motion of the internal material, significantly promoting the synergy between the velocity field, velocity gradient field, and temperature gradient field. This enhanced radial heat and mass transport efficiency within the screw channel, subsequently improving the overall operational efficiency of the equipment. The results of the finite element analysis have substantiated the scientific validity of the polymeric field synergy principle.

Digital payment, money market fund and investment behavior

Does digital payment affect the flow patterns in money market funds? In recent years, some money market funds (MMFs) have been introduced to digital payment platforms. The users can hold these MMFs and directly use them for transactions. This additional liquidity may influence investor behavior. Using individual-level data from the world's largest digital payment platform Alipay, this paper investigates the impact of digital payment on flow patterns in MMFs. We show that compared with traditional MMFs, the MMFs combined with digital payment are more attractive to investors, and flows in these MMFs are less sensitive to their past performances. Furthermore, in the period with high illiquidity, digital payment decreases the outflows from MMFs, indicating that digital payment potentially decreases liquidity risk and enhances the stability of the money market.

Spatial distribution of CO2 Impact on the indoor air quality of classrooms within a University

Indoor air quality (IAQ) remains a public and global concern. While CO2 does not pose health risks to occupants, high CO2 levels indicate insufficient ventilation, potentially accumulating pollutant concentrations. In buildings, occupants are identified as the main source of indoor carbon dioxide (CO2) through exhalation. Standard classrooms may have occupant density between 1.8 and 2.4m2/person. Therefore, the IAQ of classrooms and lecture theatres remain a concern. This study investigated airflow and contaminant (using CO2 as a proxy) distribution in two classrooms modelled using CFX a Computational Fluid Dynamics (CFD) software, verified against experimental measurements. The model provides the visualization of flow patterns so that the effects of external and internal flow fields in the classroom can be studied. The results show that there are large differences in classroom indoor ventilation performance due to the effects of wind direction and wind speed on building surface wind pressure from outdoor wind speeds. Windward high-pressure surfaces and leeward vortices created by building shading promote indoor air quality in buildings with windcatcher openings. The concentration distribution of CO in the classrooms showed an upward convergence with the thermal plume generated by the respiratory differences of the personnel and the temperature of the lighting equipment. The results of this study have important implications for improving classroom design guidelines for school buildings, especially in terms of ventilation strategies and air quality monitoring.

Role of Earliest Arrival Flow in an Evacuation Network

Traffic route guidance, destination optimization, and optimal route choice are some of the approaches to accelerate the evacuation process of transit-based evacuation problems. Their effectiveness depends upon the evacuee arrival patterns at the pickup locations and their assignment in an appropriate way to the resources in the network. The arrival patterns of the evacuees at different pickup locations might be a constant or random variable, deterministic or stochastic, time-dependent, or flow-dependent, or can be categorized either way. In this work, we are focused on the collections of evacuees at the pickup locations from the danger zone in the earliest arrival flow patterns, which can be further assigned to the transit vehicles in the integrated evacuation network by treating such pickup locations as the sources for the subsequent process to minimize the overall network clearance time from the danger zone to the safety.

Impact of length and radius of carbon nanotubes on flow and heat transfer in converging and diverging channels with entropy generation

This research examines the complex interplay between the carbon nanotubes' length and radius and how that affects flow patterns, heat transfer properties, and entropy creation in both convergent and divergent channels. Our research elucidates the mechanisms at play by revealing a crucial link between carbon nanotube dimensions and the efficacy of heat transfer processes. In particular, carbon nanotubes with a longer length have better heat transmission properties, while carbon nanotubes with a smaller radius generate less entropy. From microfluidics to energy-efficient materials, these results show significant promise for optimizing thermal systems and improving performance. This research looks on the differences between the thermal transports of single- and multi-walled carbon nanotubes in water. Thermo physical characteristics of carbon nanoparticles are one of a kind and essential for this purpose. The fluid is assumed to be incompressible and to flow steadily a two-dimensional plane. The effects of thermal radiation on the heat transfer of a water-based fluid in convergent and divergent channels with decreasing and expanding walls have been studied. In order to quickly sketch the equations, the RK-4 method with shooting approach is used, and similarity transformation is employed to reduce their dimensionality. The key factors influencing hydrothermal performance have been visualized through the use of graphs. The production numbers of entropy are also shown and explained at length. The obtained data supports the reliability of the approach used. Surface heat transport was found to be negatively impacted by elongation. Colloidal single-walled carbon nanotube (SWCNT) suspensions in water had higher thermal conductivity than water itself.

Numerical modelling of diaphragm wall construction

AbstractDiaphragm walls are rectangular shaped cast in place deep foundations. There are two critical phenomena occurring, according to which the final quality can be affected: bentonite suspension exfiltration and concrete placement. Some imperfections seem to appear recurrently on the surface of the final wall. The defects are known as shadowing pathologies. The main reasons can be attributed to the dual effect of exfiltration mechanisms and kinematics of concrete flow. The objective of this study is developing a numerical tool to prevent the appearance of shadowing pathologies by visualizing the concrete flow in the presence of a bentonite suspension. This paper presents the results obtained from 2D and 3D models of diaphragm wall construction using COMSOL Multiphysics. The CFD model helped in solving a multifluid and particularly a two‐phase flow. The 2D modeling has considered a fresh slurry and an exfiltrated (or polluted) suspension neighboring soil and followed concrete flow with two rheological behaviors in two reinforcement configurations. Then, 3D simulations were compared to actual experimentation results, which were undertaken to construct diaphragm walls in the laboratory. By comparing the results of the simulations to the experimental outcomes, it has been possible to validate the model. The resulting simulations could clearly explain the occurrence of the pathology where the flow pattern and volume fraction of the fluid flow were determined. From the results obtained, it can be conducted that a compliant concrete mix but at the lower limit for the consistency recommendations, leads to pathologies, just like a polluted slurry.

A tripe diffusion bioconvective model for thixotropic nanofluid with applications of induced magnetic field

Owing to enhanced thermal characteristics of nanomaterials, multidisciplinary applications of such particles have been utilized in the industrial and engineering processes, chemical systems, solar energy, extrusion processes, nuclear systems etc. The aim of current work is to suggests the thermal performances of thixotropic nanofluid with interaction of magnetic force. The suspension of microorganisms in thixotropic nanofluid is assumed. The investigation is further supported with the triple diffusion flow. The motivations for considering the triple diffusion phenomenon are associated to attaining more thermal applications. The flow pattern is subject to novel stagnation point flow. The convective thermal constraints are incorporated. The modeled problem is numerically evaluated by using shooting technique. Different consequences of physical parameters involving the problem are graphically attributed. The insight analysis is presented for proposed problem with different engineering applications. It is claimed that induced magnetic field enhanced due to magnetic parameter while declining results are observed for thixotropic parameter. The heat transfer enhances due to variation of Dufour number. Furthermore, low profile of nanoparticles concentration has been observed for thixotropic parameter and nano-Lewis number.

Pairwise interaction of spherical particles aligned in high-frequency oscillatory flow

We present a systematic simulation campaign to investigate the pairwise interaction of two mobile, monodisperse particles submerged in a viscous fluid and subjected to monochromatic oscillating flows. To this end, we employ the immersed boundary method to geometrically resolve the flow around the two particles in a non-inertial reference frame. We neglect gravity to focus on fluid–particle interactions associated with particle inertia and consider particles of three different density ratios aligned along the axis of oscillation. We systematically vary the initial particle distance and the frequency based on which the particles show either attractive or repulsive behaviour by approaching or moving away from each other, respectively. This behaviour is consistently confirmed for the three density ratios investigated, although particle inertia dictates the overall magnitude of the particle dynamics. Based on this, threshold conditions for the transition from attraction to repulsion are introduced that obey the same power law for all density ratios investigated. We furthermore analyse the flow patterns by suitable averaging and decomposition of the flow fields and find competing effects of the vorticity induced by the fluid–particle interactions. Based on these flow patterns, we derive a circulation-based criterion that provides a quantitative measure to categorize the different cases. It is shown that such a criterion provides a consistent measure to distinguish the attractive and repulsive arrangements.

CFD Simulations to study the Effect of Ambient Temperature on the Ventilation in a Metro Tunnel under Different Heat Release Rate

Urban and inter-urban rail transport provide the most favoured commuting option for millions of individuals globally. In spite of massive investments of public money to develop rail technologies and related infrastructure such as tunnel systems, there remain challenges to ensuring safety in this area. Railway tunnels present specific and serious fire safety issues, based on their length and restricted width. Smoke and other emissions from fires are a central factor to be considered in relation to both structural safety and survival where tunnel fires occur. Patterns of smoke flow can impact upon how efficient exhaust systems are, and for naturally ventilated systems, establishing shaft smoke flow patterns in tunnel fires is a significant requirement. While earlier work has considered this issue, it has been based on standard atmospheric conditions, while external temperatures can influence smoke movement properties, heat distribution, and the pattern of smoke flows within vertically constructed shafts. This study takes the case study of an underground metro tunnel, applying computational fluid dynamics through ANSYS Fluent to simulate and examine the effects of more extreme external temperatures for fires of 5 and 15 mw occurring in this environment.

Study of the flow pattern and pressure drop law of the air-water-foam three-phase flow

The inaccurate prediction of flow patterns and pressures after adding different types and concentrations of surfactants to wellbores and drainage lines is a common problem in shale gas wells and tubing foam drainage. To clarify the change rule of the air–water-foam three-phase flow pattern and pressure drop after adding different types and concentrations of surfactants, a surface tension test was conducted in this study. In addition, visual air–water-foam three-phase flow indoor simulation experiments were performed with various surfactants such as cocamidopropyl hydroxysulfobetaine (MX-1), dodecyldimethyl betaine (TCJ-1), and sodium α-alkenyl sulfonate (XJHSM), surfactant concentrations (0.3–0.6 %), oil pipe diameters, pipe inclinations, gas–liquid ratios, and oil contents on large-scale experimental equipment. Based on the gas–liquid distribution characteristics, the air–water-foam three-phase flow patterns in the inclined tube were reclassified, and the quantitative conversion boundaries of the various flow patterns were determined. Based on the pressure drop pulse characteristics, characterization parameters such as the scaling factor, foaming capacity, foam density, and gas-holding rate were introduced after considering the effects of various factors on the pressure drop weights, enabling a new pressure drop calculation method for air–water-foam three-phase flows for application to different types and concentrations of surfactants. The errors were verified using data from previous studies and field measurements that were within 15% and 5%, respectively. The results of these studies provide a better understanding of the air–water-foam three-phase flow patterns and pressure drop variations in shale gas wells and gathering lines.

Corner melting in low Pr metals: A study using lattice Boltzmann method

Evolution of melting boundary in the solid–liquid phase-change problem involves nonplanar geometry due to the presence of Rayleigh–Benard convective cells in the melted region. The transition of flow behavior from steady to oscillatory in the melt zone is particularly an interesting phenomenon to study. In this work, numerical investigation of melting of low Prandtl number materials in a square cavity with two adjacent heated walls has been carried out using total enthalpy-based lattice Boltzmann method. The local thermal and fluid flow behavior within a moving melting front has been investigated. The influence of natural convection in the melt zone has been observed for two different cases: (1) heating from a corner formed by the left and the bottom walls and (2) heating from a corner formed by the top and the right walls. The effect of Rayleigh number in the range of Ra = 102–5 × 107 on the convective flow field is evaluated for a typical parametric value of Stefan number of 0.01 and Prandtl number of 0.025. Results show distinct convection rolls at the melt zone for the cases under investigations. Evolution of flow fields in the melt zone has been described by a set of isotherms and streamlines for both the cases. The interface fronts for both the cases are initially of convex shape, and around Fourier number of 0.5 turn into concave shape, as viewed from the direction of the movement of melting front. At higher Ra, the rates of melting for top-right side and left-bottom side heated cavities are nearly the same above Fourier number of about 1.2. The average heat flux from the walls scales with Ran , where n is a constant which varies between 0.98 and 1.11. In the melt region, the instability pattern of flow and thermal field changes with the change of effective melt area. Transition to periodic flow is observed at Ra of 7.5 × 106 for case 1 and 2.2 × 107 for case 2, respectively.

Experimental investigation on heat transfer characteristics of a novel hypervapotron channel for divertor target in nuclear fusion reactors

In the further development of nuclear fusion energy, managing the high heat flux on a divertor target remains a significant issue. To address this, the development of innovative cooling channels capable of efficiently managing high heat loads is essential. Among various cooling techniques, the hypervapotron (HV) method stands out for its exceptional heat transfer capabilities. This study undertakes an in-depth analysis of a novel HV cooling channel, evaluating its heat transfer performance via an electron beam high heat flux testing system. The focus was on subcooled flow boiling, observing that the novel HV channel displayed varied flow patterns with increasing heat flux. Additionally, a comparative investigation was conducted to assess the heat transfer efficiency of this novel HV channel against traditional ITER-like HV channel and smooth channel. The analysis incorporated various system parameters, such as mass flow rate and system pressure, to understand their effects on heat transfer. To effectively predict the heat transfer performance of the novel HV channel, efforts have been made to evaluate existing and develop new heat transfer correlations for the channel. Furthermore, Artificial Neural Networks (ANNs) have also been utilized as a crucial approach in this predictive endeavor. The outcomes of this study hold significant implications for understanding and optimizing the design of cooling channels for divertor target in nuclear fusion reactors.

Connecting Habitats: Modelling Landscape Connectivity for Large Mammals in Omo-Shasha-Oluwa Forest Reserves, South-West Nigeria

Abstract Preserving landscape connectivity in the Omo-Shasha-Oluwa Forest Reserves is crucial due to human-induced fragmentation, shrinking habitats, and disrupted migration routes for wildlife. From 2014 to 2016, we conducted surveys to gather large mammal presence data, mapping their distribution using the MaxEnt algorithm. Employing Circuitscape software and circuit theory concepts, we predicted connectivity patterns for six large mammal species. Our results consistently showed robust predictive performance, with Area Under the Curve (AUC) values exceeding 0.75 for species distribution models. Notably, we identified suitable habitat patches for seven key species, spanning 1760 km2 for C. civetta, 1515 km2 for T. Scriptus, 729 km2 for L. cyclotis, 1693 km2 for P. porcus, 1350 km2 for C. mona, 1406 km2 for P. maxwellii, and 1379 km2 for C. torquatus. Our analysis highlighted distance to human settlements as the most significant predictor for habitat models concerning T. Scriptus, C. civetta, P. maxwellii, C. torquatus, P. porcus, and C. mona, whereas land use type emerged as a critical factor for L. cyclotis. Furthermore, examination of maximum current flow patterns revealed varying degrees of connectivity among habitat patches, indicating potential bottlenecks to species movement, particularly across major rivers and in areas affected by human activities. These findings offer crucial insights for conservation efforts, guiding strategies to preserve wildlife metapopulation dynamics in the Omo-Shasha-Oluwa Forest Reserves landscape

Modeling the morphological response of gravel–bed rivers subject to repeated sediment bypass tunnel operations

Introduction: Sediment bypass tunnels (SBTs) are operated during floods to re-establish sediment continuity past dams with the ultimate goal of decreasing accumulation in reservoirs. Depending on the location of the intake structure and operational conditions, SBTs may release either bed load-laden or bed load-free flows in the form of sudden floods (pulses). When evaluating the impacts of SBTs, the traditional approach has been to monitor channel changes in the years following project completion. However, by the time these impacts become evident, mitigation is challenging.Methods: This research adopts a forward-thinking methodology, emphasizing the prediction of potential impacts during the project’s early planning stages. We use a one-dimensional morphodynamic model to forecast the potential morphological response of a gravel-bed river with an idealized geometry to a series of SBT operations characteristic of projects in the Swiss Alps.Results: The morphological response of the downstream reach over the medium to long term is influenced by the alternating pattern of bed load-laden and bed load-free flow releases. This pattern is instrumental in forming a transition region near the SBT outlet hydrograph boundary layer (HBL).Discussion: Within the (HBL), fluctuations in bed elevation and slope are localized, while variations in grain-size distribution persist throughout the downstream region.