Typical Flow Research Articles

CFD and experimental investigations of a novel vertical axis omni-flow wind turbine shroud system operating at low Reynolds numbers, typical urban flow conditions

CFD and experimental investigations of a novel vertical axis omni-flow wind turbine shroud system operating at low Reynolds numbers, typical urban flow conditions

Versatile hydrogels prepared by microfluidics technology for bone tissue engineering applications.

Bone defects are a prevalent issue resulting from various factors, such as trauma, degenerative diseases, congenital disabilities, and the surgical removal of tumors. Current methods for bone regeneration have limitations. In this context, the fusion of tissue engineering and microfluidics has emerged as a promising strategy in the field of bone regeneration. This study describes the classification of microfluidic devices based on the nature of flow and channel type, as well as the materials and techniques required. An overview of microfluidic methods used to prepare hydrogels and the advantages of using these hydrogels in bone tissue engineering (BTE) combining several basic elements of BTE to highlight its advantages is provided. Furthermore, this work emphasizes the benefits of using hydrogels prepared via microfluidics over conventional hydrogels in BTE because of their controlled release of cargo, they can be used for in situ injection, simplify the steps of single-cell encapsulation and have the advantages of high-throughput and precise preparation. Additionally, organ-on-a-chip models fabricated via microfluidics offer a platform for studying cell and tissue behaviors in an authentic and dynamic environment. Moreover, microfluidic devices can be utilized for noninvasive diagnosis and therapy. Finally, this paper summarizes the preclinical and clinical applications of hydrogels prepared via microfluidics for bone regeneration by focusing on their current developmental status, limitations associated with their application, and future challenges, which underscore their potential impacts on advancing regenerative medicine practices.

The Impact of Fluid Flow on Microbial Growth and Distribution in Food Processing Systems

This article examines the impact of fluid flow dynamics on microbial growth, distribution, and control within food processing systems. Fluid flows, specifically laminar and turbulent flows, significantly influence microbial behaviors, such as biofilm development and microbial adhesion. Laminar flow is highly conducive to biofilm formation and microbial attachment because the flow is smooth and steady. This smooth flow makes it much more difficult to sterilize the surface. Turbulent flow, however, due to its chaotic motion and the shear forces that are present, inhibits microbial growth because it disrupts attachment; however, it also has the potential to contaminate surfaces by dispersing microorganisms. Computational fluid dynamics (CFD) is highlighted as an essential component for food processors to predict fluid movement and enhance numerous fluid-dependent operations, including mixing, cooling, spray drying, and heat transfer. This analysis underscores the significance of fluid dynamics in controlling microbial hazards in food settings, and it discusses some interventions, such as antimicrobial surface treatments and properly designed equipment. Each process step from mixing to cooling, which influences heat transfer and microbial control by ensuring uniform heat distribution and optimizing heat removal, presents unique fluid flow requirements affecting microbial distribution, biofilm formation, and contamination control. Food processors can improve microbial management and enhance product safety by adjusting flow rates, types, and equipment configurations. This article helps provide an understanding of fluid–microbe interactions and offers actionable insights to advance food processing practices, ensuring higher standards of food safety and quality control.

Endothelial cells under disturbed flow release extracellular vesicles to promote inflammatory polarization of macrophages and accelerate atherosclerosis

BackgroundExtracellular vesicles (EVs) derived from endothelial cells (ECs) are increasingly recognized for their role in the initiation and progression of atherosclerosis. ECs experience varying degrees and types of blood flow depending on their specific arterial locations. In regions of disturbed flow, which are predominant sites for atherosclerotic plaque formation, the impact of disturbed flow on the secretion and function of ECs-derived EVs remains unclear. This study aims to assess the role of disturbed flow in the secretion of EVs from ECs and to evaluate their proatherogenic function.ResultsOur comprehensive experiments revealed that disturbed flow facilitated the secretion of ECs-derived EVs both in vivo and in vitro. Mechanistically, the MAPK pathway transduces mechanical cues from disturbed flow in ECs, leading to increased secretion of EVs. Pharmacological inhibition of the MAPK pathway reduced the secretion of EVs even under disturbed flow conditions. Interestingly, under disturbed flow stimulation, ECs-derived EVs promoted monocyte accumulation and enhanced their invasion of the endothelium. More important, these EVs initiated the inflammatory polarization of macrophages from the M2 to the M1 phenotype. However, the phenotypic switching of vascular smooth muscle cells was not affected by exposure to these EVs.ConclusionsTaken together, targeting the MAPK signaling pathway holds potential as a novel therapeutic strategy for inhibiting the secretion of EC-derived EVs and mitigating the inflammatory polarization of macrophages, ultimately ameliorating the progression of atherosclerosis.Graphical

Cytokine Hemoadsorption versus Standard Care in Cardiac Surgery Using the Oxiris® Membrane: the OXICARD single center randomized trial.

Cardiac surgery can lead to dysregulation with a pro-inflammatory state, resulting in adverse outcomes. Hemadsorption using the AN69 membrane (Oxiris membrane) has the properties to chelate inflammatory cytokines. We hypothesized that in patients at high risk of inflammation, the use of the Oxiris membrane could decrease inflammation, preserve endothelial function, and improve postoperative outcomes. We conducted a randomized single-center study at Amiens University Hospital. The study population consisted of adult patients admitted for scheduled cardiac surgery with an expected cardiopulmonary bypass (CPB) time over 90 minutes. The patients were allocated to either the standard group or the Oxiris group. The intervention consisted of using the Oxiris membrane on a Prismaflex device at a blood flow rate of 450 ml/min during CPB. The primary outcome was the assessment of microcirculation on day 1 after surgery by measuring sublingual microcirculation using the microvascular flow index (MFI). MFI reflects the microcirculation flow type and is graded from 0 to 3 as follows: 0: no flow; 1: intermittent flow; 2: sluggish flow; 3: continuous flow. The secondary outcome was a composite adverse outcome within 30 days after surgery. Cytokines and endothelial biomarkers were measured in all patients at different time points. An intention-to-treat analysis was performed. From October 2019 to November 2022, we included 70 patients. Two patients were excluded from the Oxiris group: one patient did not undergo surgery and one procedure was performed under deep hypothermia. The MFI did not differ between groups on day 1 from baseline: difference Oxiris-standard at -0.17 [-0.44; 0.10]; P=0.2. The occurrence of a composite adverse outcome did not significantly differ between groups (14 [42%] for the Oxiris group vs 12 [35%] for the standard group; P=0.7). The overall variation in cytokines and angiopoietins did not significantly differ between groups. In patients scheduled for a cardiac surgery with prolonged CPB, we could not demonstrate the benefit on microcirculation and major cardiovascular events. URL: https://clinicaltrials.gov/study/NCT04201119. Identifier: NCT04201119.

Multi-faceted examination of a deepwater seamount reveals ecological patterns among coral and sponge communities in the equatorial Pacific

Spatial changes in benthic community structure have been observed across natural gradients in deep-sea ecosystems, but these patterns remain under-sampled on seamounts. Here, we identify the spatial composition and distribution of coral and sponge taxa on four sides of a single central Pacific equatorial “model” seamount within the US EEZ surrounding the Howland and Baker unit of the Pacific Islands Heritage Marine National Monument. This seamount rises from 5,000 + m to mesophotic depths of 196 m, and is influenced by the Equatorial Undercurrent. Four remotely operated vehicle (ROV) transects were completed, one on each flank of the seamount. Shallower than ~ 250 m, the mesophotic seafloor was composed of scoured carbonate pavement with sediment accumulation only found in rocky depressions. Waters below 500 m hosted communities predominantly composed of octocorals, however, several coral taxa showed seamount flank preference (higher abundance on one or more flanks than the others) even though strong vertical (depth) zonation of corals and sponges was observed on all flanks. Euplectellidae, Plexauridae and ​​Chrysogorgia spp. corals each showed a distinct preference for flank. To help visualize the influence of current flow, oxygen, depth, and substrate type on the zonation of seamounts, we created an Alexander Von Humboldt-style infographic to illustrate the observed biodiversity patterns. Given the importance of seamounts to ocean biodiversity and productivity, this study is an early attempt at a holistic visualization of seamount biology that can advance new hypotheses about seamount ecology.

Impact of Spatial Configuration of Bioretention Cells on Catchment Hydrological Performance Under Extreme Rainfall Conditions with Different Stormwater Flow Paths

Bioretention cells (BCs) are widely used to manage urban runoff due to their positive impact on runoff control. Current research primarily focuses on optimizing the internal structural design of bioretention cells, while studies on the interactions between their spatial configuration, topography, and land use types are limited. This study employs the Storm Water Management Model (SWMM) and uses extreme rainfall to analyze the influence of typical stormwater flow paths, determined by various land use types and topography, as well as the spatial configurations of bioretention cells on catchment hydrological performance. The results show the following: (1) Different stormwater flow paths significantly affect catchment hydrological performance, with series-type pathways performing best. (2) The spatial configuration of bioretention cells significantly influences catchment hydrological performance. Decentralized BCs under series-type pathways showed better performance for reducing total outflow and peak runoff, with reduction rates increasing by 7.1% and 8.8%, while centralized BCs better delayed peak times. (3) Stormwater flow paths affect BC efficiency in catchment hydrological performance. Decentralized BCs under a series-type stormwater flow path are recommended for priority use. This study provides a novel perspective for optimizing the spatial arrangement of BCs and urban stormwater management, thereby contributing to flood risk mitigation.

Numerical research on two typical flow structures and aerodynamic drag characteristics of blunt-nosed trains

Purpose This study aims to provide new insights into aerodynamic drag reduction for increasingly faster blunt-nosed trains, such as urban and freight trains. Specifically, this work investigates two distinctly different wake structures and associated aerodynamic drag of blunt-nosed trains. Design/methodology/approach Three typical cases of blunt-nosed trains with 1-, 2- and 3-m nose lengths are selected. The time-averaged and unsteady flow structures around the trains are analyzed using the improved delayed detached eddy simulation model and proper orthogonal decomposition method. Findings The simulation results indicate that for 2- and 3-m nose lengths, the flow separates at first and then reattaches to the slanted surface of the tail, with a pair of longitudinal vortices dominating the wake. In contrast, for the 1-m nose length case, the wake structure is characterized by complete separation, attributed to the larger curvature of the slanted tail surface. Consequently, the total time-averaged drag coefficient is reduced by 27.2% and 19.2% for the 1-m nose length case compared to the 2- and 3-m cases, respectively. Moreover, the predominant unsteady structures with Strouhal numbers St = 0.30 and St = 0.28 are detected in the near-wake of the 2- and 3-m nose length cases, respectively. These structures result from periodic vortex shedding at the lower slanted tail surface. In contrast, for the 1-m nose length case, the predominant unsteady structure with St = 0.19 is induced by the nearly periodic expansion and contraction of the upper bubbles. Originality/value Two distinctly different wake structures in blunt-nosed trains are identified. Unlike high-speed trains with longer, streamlined noses, for blunt-nosed trains, shorter nose lengths result in lower aerodynamic drag. Insights for reducing energy consumption in blunt-nosed trains are provided.

Large-scale-aware data augmentation for reduced-order models of high-dimensional flows

Convolutional autoencoders have proven to be an adequate tool to perform reduced-order modeling for high-dimensional nonlinear dynamical systems. Their goal is to reduce dimensionality strongly while preserving the most characteristic features of the system. Here, we show that these models rely sensitively on the completeness of the provided data. This is particularly challenging for fully turbulent flows with their coherent structures ranging from large-scale superstructures to dissipative eddies over orders of magnitude in time and space. As a result, an unrealistically large number of data snapshots would be required to properly cover all the essential dynamics, whereas the features on small time and length scales require only a small number of snapshots of the respective flow, especially the long lasting large-scale structures that are difficult to characterize either numerically or experimentally. We demonstrate for three types of flows that a missing representation of large-scale turbulent structures leads to failures in the training process. We suggest a method to mitigate this shortcoming. This includes the transformation of data samples to new large-scale structures, which enhance the data. Furthermore, we skip augmentations that are more detrimental to the model performance. We evaluate our method for three datasets, two from numerical simulations of turbulent Rayleigh–Bénard convection flows and one from laboratory experiment for the flow past an array of cylinders. We show that the method can substantially improve model utility for high-dimensional data. In this way, we avoid an intensive grid search through possible augmentation combinations without further knowledge about the underlying system.

Optimization of Heat Transfer Performance in Solar Radiation Collector Tubes with Circular Cross-Section: A Review

The performance of heat transfer in the solar radiation collector tube with a circular cross-section has an important potential for the promotion of solar thermal systems. This review paper discusses the parameters affecting heat transfer in these collector tubes, such as tube geometry, type of material, fluid flow, and environment. The focus of this review is on state-of-the-art methods for improving heat transfer including surface modifications, Nano fluids, and passive heat transfer enhancement strategies. Recent improvements in their material selection, nanotechnology, and new heat transfer fluids are discussed. The review seeks to offer significant references for future innovations and practical applications of those innovations in the field of solar thermal energy systems, and, thereby, provide a concise synthesis of the current state of the art in solar thermal technology. The research outcomes indicate that although considerable advancements have been realized in heat transfer performance optimization, continuous investigation into aspects like energy storage, hybrid configurations, and innovative coatings is essential for further enhancing the efficiency and cost-effectiveness of solar radiation collector tubes. .Key Words: Solar collector, heat transfer optimization, circular cross-section, heat transfer enhancement, nanofluids, thermal performance, solar energy.

A Discussion on the Critical Electric Rayleigh Number for AC Electrokinetic Flow of Binary Fluids in a Divergent Microchannel.

Electrokinetic (EK) flow is a type of flow driven or manipulated by electric body forces, influenced by various factors such as electric field intensity, electric field form, frequency, electric permittivity/conductivity, fluid viscosity, etc. The diversity of dimensionless parameters, such as the electric Rayleigh number, complicates the comparison of the EK flow stability. Consequently, comparing the performance and cost of micromixers or reactors based on EK flow is challenging, posing an obstacle to their industrial and engineering applications. In this investigation, we theoretically derived a new electric Rayleigh number (Rae) that quantifies the relationship among electric body forces, fluid viscosity, and ion diffusivity, based on a tanh model of electric conductivity distribution. The calculation results indicate that the new Rae exhibits richer variation with the control parameters and better consistency with previous experimental reports. We further conducted experimental studies on the critical electric Rayleigh number (Raec) of the AC EK flow of binary fluids in a divergent microchannel. The experimental variations align well with the theoretical predictions, particularly the existence of an optimal AC frequency and electric conductivity ratio, demonstrating that the tanh model can better elucidate the underlying physics of EK flow. With the new electric Rayleigh number, we found that EK flow in the designed divergent microchannel has a much smaller Raec than previously reported, indicating that EK flow is more unstable and thus more suitable for applications in micromixers or reactors in industry and engineering.

Analysis and Optimization of Hydraulic Calibration for Maximum Performance of Wastewater Treatment Plants

The hydraulic calibration of treatment units in wastewater treatment plants is a crucial task. It involves demonstrating the relative placement of these various units in relation to the water line that traverses the plant, and helps indicate the ground surface for establishing the optimal elevations of the plant's structures and hydraulic controls. This process is meticulous, complex, and prone to errors. Special attention must be given to the issue of varying hydraulic loads that the plant will receive, particularly at the inlet. Such variations can disrupt hydraulic operation and negatively impact the plant's performance. For these reasons, the hydraulic calibration of treatment units must always be verified and analyzed for most of the common hydraulic constraints encountered in practice. This article focuses on the different types of flow and their regimes commonly found in wastewater treatment plants, and aims to guide users on how to optimize the hydraulic profile. It highlights the impact of head losses and integrates a range of potential alternatives for achieving hydraulic efficiency in a wastewater treatment plant.

Protocol for extracting flow hydrograph shape metrics for use in time-series flood hydrology analysis.

The shape characteristics of flow hydrographs hold essential information for understanding, monitoring and assessing changes in flow and flood hydrology at reach and catchment scales. However, the analysis of individual hydrographs is time consuming, making the analysis of hundreds or thousands of them unachievable. A method or protocol is needed to ensure that the datasets being generated, and the metrics produced, have been consistently derived and validated. In this lab protocol, we present workflows in Python for extracting flow hydrographs with any available temporal resolution from any Open Access or publicly available gauging station records. The workflow identifies morphologically-defined flow and flood types (i.e. in-channel fresh, high flow and overbank flood) and uses them to classify hydrographs. It then calculates several at-a-station and upstream-to-downstream hydrograph shape metrics including kurtosis, skewness, peak hydrograph stage, peak arrival time, rate-of-rise, peak-to-peak travel time, flood wave celerity, flood peak attenuation, and flood wave attenuation index. Some metrics require GIS-derived data, such as catchment area and upstream-to-downstream channel distance between gauges. The output dataset provides quantified hydrograph shape metrics which can be used to track changes in flow and flood hydrographs over time, or to characterise the flow and flood hydrology of catchments and regions. The workflows are flexible enough to allow for additional hydrograph shape indicators to be added or swapped out, or to use a different hydrograph classification method that suits local conditions. The protocol could be considered a change detection tool to identify where changes in hydrology are occurring and where to target more sophisticated modelling exercises to explain the changes detected. We demonstrate the workflow using 117 Open Access gauging station records that are available for coastal rivers of New South Wales (NSW), Australia.

Study of bifurcations, chaotic structures with sensitivity analysis and novel soliton solutions of non-linear dynamical model

The current work amalgamates the fascinating exploration of the Radhakrishnan–Kundu–Lakshmanan equation, which is a sophisticated mathematical framework in physics and finds applications in elucidating diverse physical phenomena. By leveraging the two recently developed computational approaches, namely the new extended direct algebraic method and the modified Sardar sub-equation method, we rigorously assess the novel soliton solutions including dark, bright-dark, dark-bright, periodic, singular, rational and mixed trigonometric forms. Furthermore, we also segregated W-shape, M-shape, bell shape, exponential, as well as hyperbolic soliton, which are not documented in the literature. We validate the stability and accuracy of extracted soliton wave solutions using the Hamiltonian property. Additionally, the Galilean transformation is applied and numerous standard types of results, including bifurcations, chaotic flows, and sensitivity analysis are presented. The obtained results are tested both numerically and with illuminating physical interpretations, which shows a better demonstration of the intricate dynamics of these models.

Renewable DG allocation in a pre-scheduled grid power supply for different types of loads with and without distribution network reconfiguration

ABSTRACT This paper suggests a technique for dispatchable and non-dispatchable renewable distributed generation (DG) unit deployment under a constant quantity of power supply from the grid. It also accounts for seasonal fluctuations in load demand, solar and wind power generation. To analyse the scenario, the typical load flow approach is changed by inserting PQVδ and zero bus into the system. Three renewable DGs are used based on solar, wind and biomass to meet the load demand. Along with meeting the load demand, DG is operating to enhance the voltage profile and reduce the power loss. The research is conducted on a 33 and 69 bus distribution networks (DNRs) for constant power, constant current, constant impedance, composite and exponential or mixed load types. To reduce the loss even further, the networks are reconfigured in the presence of three different types of DGs. The suggested solution reduces loss by up to 54 % and allows for energy savings of up to 2.5546 × 10 7 kWh and 2.0719 × 10 7 kWh in 33 bus and 69 bus DNRs, respectively. Economic effectiveness is also analysed to indicate the profit earned from the DG installation. The uncertainty of solar and wind energy is also explored in this paper to see how the network responds to such a scenario.

Discovering metro passenger flow recovery patterns under unplanned disruptions: a disruption impact quantification-based clustering approach

ABSTRACT Discovering metro passenger flow recovery patterns from historical unplanned disruptions enables operators to better prepare for a new disruption. The task is challenging as passenger flow recovery patterns are generated by different types of disruptions at different locations and times. We start with the Robust Principal Component Analysis (RPCA), a dimensionality reduction technique to calculate passenger flow change under disruption and quantify disruption impact. With this information, we modify the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) model with the tailor-made discrete input module and distance metric module, to discover the typical passenger flow recovery patterns with different shapes and sizes. Our approach is validated in the Hong Kong Mass Transit Railway system. The results show that our approach can discover interpretable recovery patterns that are easily neglected by other clustering methods, because of its ability to quantify and distinguish disruption impact on normal passenger flow.

Scuzer : A Scheduling Optimization Fuzzer for TVM

The concept of deep learning (DL) compiler was proposed to deploy DL models more efficiently on diverse hardware through optimization techniques. As one of the most popular DL compilers, TVM incorporates three levels (high-level, schedule, and low-level) of optimizations, which can inadvertently introduce code logic bugs and build failure bugs. Among these optimizations, scheduling optimization is the core component of DL compilers, which ensures the acceleration of models on all devices. However, the existing works only focus on the testing of high-level and low-level optimizations in TVM, fail to take the most important and challenging intermediate scheduling optimization layer into consideration. To fill the gap, we propose a Sc heduling optimization oriented f u z zer for TVM, named Scuzer , which is specially designed to effectively detect bugs introduced by the scheduling optimization. In particular, Scuzer first proposes a set of schedule-triggering mutators to actively trigger many scheduling optimizations. Meanwhile, observing that scheduling optimization is closely coupled with program data flow and operator type, Scuzer additionally proposes a set of structure-enriching mutators to enrich the structure of data flows and operators. Based on these carefully designed mutators, Scuzer then devises a multi-objective algorithm that can adaptively select different combinations of objectives at each period to guide the selection of seeds and mutators during fuzzing. We conduct extensive experiments comparing with three state-of-the-art fuzzers that can be applied in testing scheduling optimization to evaluate the effectiveness of Scuzer . The experimental results demonstrate that Scuzer outperforms the 2nd-best state-of-the-art fuzzer by 7.4% in edge coverage and achieves 7 \(\times\) improvement in rule-operator coverage. Scuzer has successfully detected 17 previously unknown bugs (9 are inconsistent results and 5 are inconsistent compilations) in TVM, out of which 10 have been confirmed and 5 been fixed.

Capital Flows to Emerging Markets: The Role of Information Transparency

Using annual capital flow data from 1990 to 2010 for 21 emerging markets, this study empirically investigates the impact of macroeconomic information transparency on capital flows, taking into account financial market uncertainty. The level of in- formation transparency is measured using the country's compliance with the IMF's SDDS. The findings reveal that SDDS compliance mitigates the negative influence of the VIX index on both net and total gross inflows. However, the positive effect of SDDS compliance on capital inflows is observed only when the VIX index reaches a sufficiently high level. This relationship is primarily driven by other in- vestment inflows, as it is the only type of capital flow significantly affected by the SDDS compliance in conjunction with VIX. The results suggest that although enhanced information transparency in emerging markets may not attract more foreign capital during normal periods, it provides stability by reducing the decline in other investment inflows during times of financial turmoil, ultimately contributing to the overall stability of total capital inflows.

Steady mathematical modeling and numerical analysis of Cross magneto‐nanofluid flow over a wavy surface with heat and mass transfer features

AbstractMixed convectively driven wavy flow of Cross‐generalized fluid is modeled on a wavy surface with the importance of wavy surface amplitude. The periodic nature of the flow is effectively configured and is declared the main theme of this study. However, some physical features are considered together with the flow of heat and mass. The effect of external magnetic field, heat generation/absorption, thermal radiation, and linear chemical reaction are comprehensively deliberated during the typical wavy flow. The low Reynolds approximation theory is utilized for the boundary layer governing equations. Specifically, the wavy surface amplitude is played an integral part in modeling the GNF. The mathematical equations are formed in terms of partial differential equations (PDEs) with the physical and chemical impacts. The nonlinear PDEs are then transformed into ordinary differential equations (ODEs) by utilizing the dimensionless local similar. The whole investigation is further extended with the features of heat and mass flows in the presence of Brownian motion and thermophoretic forces. To demonstrate the importance of the leading dimensionless physical factors, a modified version of the collocation methods, namely modified bvp4c is applied. The significant results are displayed via drag forces, heat and mass transmission rates, and velocity of the fluid. Significant uplifted behavior of skin friction is noticed by considering the higher values of wavy surface amplitude. The higher values of the newly introduced Weissenberg number are predicted an increasing velocity of the fluid. The higher Richardson number boosted the material's velocity. The rates of heat and mass flows are noticed higher for escalated values of chemical reaction and radiation parameters, respectively. The Brownian motion and thermophoretic forces enhanced the concentration of the materials. A strong comparison with the previous works is provided to ensure the validity of the entire numerical method.

Influence of Ice Fragments on the Scraping Effect of Rock–Ice Avalanches: Insights from Physical Model Experiments

Research on the scraping effects of rock–ice avalanches remains relatively limited. This study investigates the evolution of rock–ice avalanches with varying ice content and initial accumulation forms during motion, scraping, and deposition using laboratory physical model experiments. Changes in pre- scraping velocity, scraping length, scraping depth, maximum deposition length, and deposition thickness were analyzed as functions of ice content. The analysis revealed the influence of ice content and initial accumulation on scraping effects, as well as on motion and deposition characteristics. The experimental results indicate that, compared to typical debris flows (without ice), the presence of ice significantly enhances the mobility, deposition features, and scraping effects of rock–ice avalanches. Through analysis, it is shown that the low friction of ice debris enhances the kinetic energy of ice-rock debris flows, thereby increasing the energy required for scraping.