Channel Roughness Research Articles

A simple framework for calibrating hydraulic flood inundation models using Crowd-sourced water levels

Floods are the most commonly occurring natural disaster, with the Centre for Research on the Epidemiology of Disasters 2021 report on “The Non-COVID Year in Disasters” estimating economic losses worth over USD 51 million and more than 6000 fatalities in 2020. The hydrodynamic models which are used for flood forecasting need to be evaluated and constrained using observations of water depth and extent. While remotely sensed estimates of these variables have already facilitated model evaluation, citizen sensing is emerging as a popular technique to complement real-time flood observations. However, its value for hydraulic model evaluation has not yet been demonstrated. This paper tests the use of crowd-sourced flood observations to quantitatively assess model performance for the first time. The observation set used for performance assessment consists of 32 distributed high water marks and wrack marks provided by the Clarence Valley Council for the 2013 flood event, whose timings of acquisition were unknown. Assuming that these provide information on the peak flow, maximum simulated water levels were compared at observation locations, to calibrate the channel roughness for the hydraulic model LISFLOOD-FP. For each realization of the model, absolute and relative simulation errors were quantified through the root mean squared error (RMSE) and the mean percentage difference (MPD), respectively. Similar information was extracted from 11 hydrometric gauges along the Clarence River and used to constrain the roughness parameter. The calibrated parameter values were identical for both data types and a mean RMSE value of ∼50 cm for peak flow simulation was obtained across all gauges. Results indicate that integrating uncertain flood observations from crowd-sourcing can indeed generate a useful dataset for hydraulic model calibration in ungauged catchments, despite the lack of associated timing information.

Reynolds number and submergence ratio effects on turbulence structures in the shallow wake of a horizontal pipe located on a rough bed

The effects of Reynolds number and submergence ratio on mean velocity, separation length, Reynolds shear stresses (RSS), correlation coefficient, anisotropy, and turbulent kinetic energy (TKE) are evaluated by modifying the free-stream velocity and pipe diameter to understand the fluid–structure interaction in the presence of a rough channel bed. Acoustic Doppler velocimetry is used to acquire three-dimensional velocity data in the experiments. The experimental data demonstrate that the non-dimensional separation length is linearly varying with the Reynolds number up to a critical Reynolds number, and after that, it becomes independent of the Reynolds number. The vertical profiles of the mean velocity, RSS, correlation coefficient, anisotropy, and TKE are not affected by the Reynolds number; however, their profiles are affected by the submergence ratio. The RSS and TKE are found to be larger for the higher submergence ratio below the top level of the pipe throughout the wake region. The reattachment point is found to be the most turbulent as the most pronounced peaks of RSS and TKE are occurring at this point. The quadrant analysis reveals that the RSS contribution of ejection events is higher for a lower submergence ratio, whereas the RSS contribution of the sweep events is higher for a higher submergence ratio. In conclusion, this study provides an in-depth understanding of the turbulent flow characteristics in the wake region of a bed-mounted horizontal circular pipe located on a fixed sand bed, especially the modification of the turbulence properties due to changes in the Reynolds number and submergence ratio.

Highly porous double network hydrogel having fast responding time and high mechanical strength via emulsion template polymerization

AbstractPorous polymer hydrogels with high mechanical properties and response time is such a unique coalition that may open up many new application avenues especially in biomaterials, nevertheless which is a challenging task to achieve. This work highlighted a novel yet simple approach on developing highly porous, fast swelling hydrogels having high mechanical performance by slightly twisting the traditional double network concept following emulsion template polymerization. The fabricated acrylamide hydrogel structure entails 40–70 micrometer size pores while having ultimate compressive strength of 5–7 MPa. Further, it exhibited approximately 400 wt% water absorptivity compared to the dry weight of the sample in 15 s at 30°C. Such enhanced swelling properties of the developed hydrogel are due to the surface roughness of interconnected capillary channels.

A New Fractal Permeability Model for Porous Media Based on Rough Capillary Channels

Porous media are assumed as a bunch of curved capillaries of rough pore-solid surface, with capillary size distributions and surface roughness following the fractal scaling laws, for which a permeability model is derived to capture both tortuosity and roughness of the pore space in this work. First, the fractal geometry theory and the regarding methods are used to simulate tortuosity and roughness, and then, the permeability of porous media is linked to pore area fractal dimension, tortuosity fractal dimension, relative mean roughness, and other structural parameters (e.g., characteristic length and maximum and minimum pore size). Each parameter in the proposed model has specific physical meaning, which is able to reveal certain mechanisms that affect permeability comprehensively. For several porous media samples, the predicted permeability data based on the current fractal model are compared with the experimental measurement data and the permeability model predictions for other porous media with smooth capillary channels. A good agreement was found between the predicted values of the new permeability fractal model and the experimental data.

Low-complexity trainable denoising filter structure for image recognition applications

Even in modern imaging equipment, different types of noise make their way into the images especially under bad lighting conditions and rough communication channels. While applying denoising filters, the preservation of the edge in images has always been an essential albeit a difficult task. This is particularly important for accuracy of further image processing tasks, such as recognition. We described a denoising approach to process noisy images specific for the task of classification with minimal impact on image resolution using low-complexity operations. Specifically, support vector machine-based machine learning classifiers have been proposed to dynamically select an appropriate filtering kernel while processing individual pixels in the input image. The selection is based on the image features in a local window. The provided experimental results on standard dataset prove that the proposed scheme performs as well as contemporary complex convolutional neural network (CNN)-based approaches for the task of denoising images before classification in the presence of a variety of mixed-type noise. Moreover, the proposed filtering approach can run at much higher speeds than their CNN-based counterparts while delivering similar or better performance. The proposed framework has been made publicly available as open-source code to facilitate further work by researchers and practitioners interested in this area.

Deriving River Discharge Using Remotely Sensed Water Surface Characteristics and Satellite Altimetry in the Mississippi River Basin

River discharges are critical for understanding hydrologic and ecological systems, yet in situ data are limited in many regions of the world. While approximating river discharge using satellite-derived water surface characteristics is possible, the key challenges are unknown channel bathymetry and roughness. Here, we present an application for merging mean river-reach characteristics and time-varying altimetry measurements to estimate river discharge for sites within the Mississippi River Basin (USA). This project leverages the Surface Water and Ocean Topography (SWOT) River Database (SWORD) for approximating mean river-reach widths and slopes and altimetry data from JASON-2/3 (2008–Present) and Sentinel-3A/B (2015–Present) obtained from the Hydroweb Theia virtual stations. River discharge is calculated using Manning’s Equation, with optimized parameters for surface roughness, bottom elevation, and channel shape determined using the Kling–Gupta Efficiency (KGE). The results of this study indicate the use of optimized characteristics return 87% of sites with KGE > −0.41, which indicates that the approach provides discharges that outperform using the mean discharge. The use of precipitation to approximate missing flows not observed by satellites results in 66% of sites with KGE > −0.41, while the use of TWSA results in 65% of sites with KGE > −0.41. Future research will focus on extending this application for all available sites in the United States, as well as trying to understand how climate and landscape factors (e.g., precipitation, temperature, soil moisture, landcover) relate to river and watershed characteristics.

Assessment of Uncertainty in Grid-Based Rainfall-Runoff Model Based on Formal and Informal Likelihood Measures

Damage prevention from the local storms and typhoons in Korea, the development of a rainfall-runoff model reflecting local geological, meteorological and physical characteristics is necessary. The accuracy of the rainfall-runoff model is influenced by the various uncertainty factors that can occur in the modeling processes, including input data, model parameters, modeling simplification, and so on. Thus, the objectives of this study are (1) to estimate runoff for two rainfall events using Grid Rainfall-Runoff Model (GRM); (2) to quantify the uncertainty of the GRM model using the Generalized Likelihood Uncertainty Estimation (GLUE) method, and (3) to assess the uncertainty ranges of the GRM based on different likelihood functions. For this, two rainfall events were implemented to the GRM in the Cheongmicheon watershed, and informal likelihood functions (LNSE, LPBIAS, LRSR, and LLOG) based on the fitness indices (NSE, PBIAS, RSR, and Log-normal) were used for uncertainty analysis and quantification using GLUE method. As a result, the GRM parameters varied according to the different rainfall patterns even in the same watershed. In addition, among the GRM parameters, the CRC (Channel Roughness Coefficient) and CSHC (Correction factor for Soil Hydraulic Conductivity) characteristics are the most sensitive. Moreover, this study showed that the uncertainty range of the GRM model can be changed with the subjective selection of likelihood functions and thresholds. The GRM model is open source and has good accessibility. Especially, this open-source model allows various approaches to disaster prevention plans such as flood forecasting and flood insurance policies. In addition, if the parameter range of GRM is quantified and standardized at domestic watersheds, it is expected that the reliability of the rainfall-runoff simulation can be increased by the reduction of the uncertainty factors.

Investigation on Heat Transfer Characteristics of Rectangular Channels With Internal Rough Surface Naturally Formed by Selective Laser Melting Three-Dimensional Printing

Abstract As a metal three-dimensional (3D) printing technology, selective laser melting (SLM) has been extensively applied to manufacture complex-shaped parts in industries. It is well known that the naturally formed surface by SLM processing is usually rough and irregular. The effects of the rough surface on heat transfer and fluid flow cannot be neglected when SLM is applied to fields such as heat exchangers and cooling equipment. In this paper, a novel bottom-up approach was proposed to build the naturally formed rough surface by SLM 3D printing. Numerical investigation on pressure loss and heat transfer characteristics of rectangular channels has been carried out based on the naturally formed rough model. Constant thermal boundary and symmetry boundary conditions were employed in the procedure of numerical computation. For comparison, a variety of typical surfaces with different roughness elements in previous studies have been introduced and analyzed. Results confirmed that the proposed rough surface modeling method was fully capable of descripting the real 3D-printed surface topography. Compared with the smooth surface, the heat transfer capacity of the 3D-printed rough channel was increased by 8.99%, while the pressure loss was increased by 25.02%. Additionally, 3D-printed rough surface had better overall thermal performance compared to rough surfaces with regular roughness element.

High-throughput screening of surface roughness during additive manufacturing

Smooth surfaces in the printed parts are essential for long fatigue life and high dimensional accuracy. They are currently achieved by post-process machining and grinding of external surfaces that add extra costs. Mitigating the surface roughness of internal channels remains a challenge. Here we use a high-throughput screening approach that analyzes the value of a dimensionless index for many experiments and provides a pathway for reducing the surface roughness without the need for post-processing. The index is derived by dimensional analysis of causative variables that affect the roughness of the surface such as heat input, powder diameter, layer thickness, pool aspect ratio, Marangoni force, contact angle, and enthalpy of melting of alloys. Using the results of high-throughput screening, we develop easy-to-use process maps that are consistent with the experimental observations. Among the causative variables, heat input and the contact angle of the molten material with the substrate have the highest and lowest influence on the smoothness of printed surfaces. An aluminum alloy, AlSi10Mg is found to be the best choice for printing smooth surfaces among the four alloys considered here. These findings can improve the surface quality of additively manufactured parts that now significantly hinder their wider industrial adaptation.

OPTIMIZATION OF THE HOLLOW CHANNELS FORMATION PARAMETERS INSIDE GLASS BY DIRECT LASER WRITING AND SELECTIVE ETCHING

Two-stage method of hollow channels formation inside glass by direct laser writing and selective etching is perspective way for microfluidics devices manufacturing. In this work the influence of the etching solution concentration and laser writing conditions (the laser beam scanning speed, pulse energy) on the etching rate, selectivity and roughness of hollow channels in quartz glass is studied. The use of 1M NaOH makes it possible to increase the etching rate of hollow channels up to 300 µm/h while maintaining high selectivity up to 680.

Evidence that uniform momentum zones originate from roughness sublayer structure interactions in fully rough channel turbulence

Fully rough wall-sheared turbulence is composed of an inner and outer layer, the former occupied by sinuous structures sustained by the well-known autonomous inner cycle, the latter occupied by inclined parcels of momentum deviations relative to the average. The outer-layer structures are also known as uniform momentum zones (UMZs), where the presence of successive UMZs manifests instantaneously with a distinct ‘staircase’ pattern in streamwise velocity. Direct numerical simulation (DNS) of fully rough channel turbulence was recently used to interpret UMZs as wakes originating from antecedent bluff-body-like interactions within the inner layer (Anderson & Salesky, J. Fluid Mech., vol. 906, 2020, A8). Wake-scaling arguments agreed precisely with instantaneous results from DNS. Foremost among these results was evidence that the instantaneous wall-normal gradient of streamwise velocity exhibited scaling of ${\sim }x_3^{-1/2}$ , where $x_3$ is wall-normal location; this is in contrast to logarithmic scaling, which requires the wall-normal gradient of streamwise velocity to scale as ${\sim }x_3^{-1}$ . Herein, wake-scaling arguments have been advanced and compared against results from wall-modelled large-eddy simulation (LES). New results from the ‘bottom up’ wake-scaling arguments agree with LES results, such that the shear associated with the instantaneous staircase-like streamwise velocity follows a clear trend. We have leveraged conditional sampling during LES – predicated upon instantaneous low-frequency, high-magnitude surface stress values known to correspond to large-scale inertial-layer coherence – to further assess the predictive value of the wake-scaling arguments. Model results compare favourably.

Modeling liquid rocket engine coolant flow and heat transfer in high roughness channels

The design of thrust chambers of modern liquid rocket engines is moving towards the use of additive layer manufacturing techniques, which are replacing traditional techniques because of its inherent advantages of customization and flexibility of design and prototyping phase that in the end leads to advantages in terms of production costs and times. In this framework, the realization of suitable cooling channels, which are characterized by tiny cross section, can lead to high relative surface roughness, as a result of the manufacturing process. Despite the increased friction loss, high roughness channels are considered often with interest because of the corresponding increase of heat transfer and thus cooling efficiency. However, the correlation between the increase of friction and heat transfer changes at high roughness. As a consequence, the commonly used assumption for heat transfer prediction at low roughness may lead to order of magnitude errors if extended to high roughness channels. To respond to the request of a reliable heat transfer prediction model, the correction introduced by Aupoix to the Spalart-Allmaras turbulence model to take into account for high roughness in external flows is extended and validated here for the application to high roughness channels. The implementation of the proposed correction allows to predict realistic values of the convective heat transfer coefficient, in agreement with the correlations reported in the literature.

Investigating the Granulometric Distribution of Fluvial Sediments through the Hybrid Technique: Case Study of the Baganza River (Italy)

Sediment characterization is a key parameter to understand the geomorphological attributes of a catchment (i.e., assessing the variability of the sediment transport capacity and surface roughness of a hydraulic channel). This assessment can be performed in several ways, for instance, through numerous sampling techniques (i.e., pebble count and zig-zag methods). Sediment sampling using manual sieving inside a laboratory is a hectic process as it requires ample time and physical effort, particularly when the scale of interest is at the catchment level. In order to find the granulometric distribution of some sections of the Baganza streambed (northern Italy), in order to carry out analysis at the catchment scale, a hybrid technique (a combination of the conventional and photogrammetric method) is introduced. Different grain size distribution curves (GSDs) obtained from the image processing technique using Digital Gravelometer software and traditional sediment sieve analysis (sieve-by-weight method) were compared. Sediment sampling was limited to sections of the streambed that were visible during lower flows in the dry summer season. Sediment samples including fine soil fraction, were collected up to a depth of 30 cm, although the exposed areas behaved as gravels and cobble bars. The adopted hybrid technique approach for the characterization of fluvial sediments is desirable in order to accommodate the full range of particle sizes inside the riverbed. Digital photography was performed at ten different cross sections, along the longitudinal profile of the 30 km long reach of the Baganza River, to examine the sediment distribution, grading, and representative particle sizes (D10, D50, D90) at each of the respective cross sections. A comparison of the photogrammetric method and traditional sieve analysis revealed strong agreement in coarser segments of the grain size distributions, but it was deficient in the finer part (<2 mm) due to the shielding effect produced by bigger particles. However, the adopted hybrid technique appears to be quite efficient and promising in determining the GSD by reducing the costs and the sediment sample collection time in the field.

Direct numerical simulation-based characterization of pseudo-random roughness in minimal channels

Direct numerical simulations (DNS) are used to systematically investigate the applicability of the minimal-channel approach (Chung et al., J. Fluid Mech., vol. 773, 2015, pp. 418–431) for the characterization of roughness-induced drag on irregular rough surfaces. Roughness is generated mathematically using a random algorithm, in which the power spectrum (PS) and probability density function (p.d.f.) of the surface height can be prescribed. Twelve different combinations of PS and p.d.f. are examined, and both transitionally and fully rough regimes are investigated (roughness height varies in the range $k^+ = 25$ –100). It is demonstrated that both the roughness function ( ${\rm \Delta} U^+$ ) and the zero-plane displacement can be predicted with ${\pm }5\,\%$ accuracy using DNS in properly sized minimal channels. Notably, when reducing the domain size, the predictions remain accurate as long as 90 % of the roughness height variance is retained. Additionally, examining the results obtained from different random realizations of roughness shows that a fixed combination of p.d.f. and PS leads to a nearly unique ${\rm \Delta} U^+$ for deterministically different surface topographies. In addition to the global flow properties, the distribution of time-averaged surface force exerted by the roughness onto the fluid is calculated. It is shown that patterns of surface force distribution over irregular roughness can be well captured when the sheltering effect is taken into account. This is made possible by applying the sheltering model of Yang et al. (J. Fluid Mech., vol. 789, 2016, pp. 127–165) to each specific roughness topography. Furthermore, an analysis of the coherence function between the roughness height and the surface force distributions reveals that the coherence drops at larger streamwise wavelengths, which can be an indication that very large horizontal scales contribute less to the skin-friction drag.

Near-Optimal BEM OTFS Receiver With Low Pilot Overhead for High-Mobility Communications

In this paper, a new receiver design based on basis expansion model (BEM) orthogonal time frequency space (OTFS) is presented for high-mobility communications with Doppler-spread channel. By deriving an analytical BEM OTFS system model, a low-order generalized complex exponential BEM (GCE-BEM) aided rough channel estimation is proposed at the initial stage with low pilot overhead, followed by equalization. Then, the refinement of channel estimation and equalization is conducted iteratively, in which a high-resolution GCE-BEM model with a large BEM order is adopted and the detected data symbols are exploited as pseudo-pilots, leading to higher estimation accuracy. Simulation results show that the proposed BEM OTFS receiver significantly outperforms the existing OTFS receivers in terms of the mean square error (MSE) of channel estimation and bit error rate (BER), while featuring low pilot overhead. Results also show the near-optimal performance of the novel solution, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , achieved BER is very close to the case of perfect channel estimation. The theoretical lower bound on MSE of channel estimation is derived to verify the effectiveness of the proposed BEM OTFS receiver, which is shown to be close to simulation results.

Effect of Macrorough Sidewalls on Flow Resistance in Steep Rough Channels

AbstractPrevious studies showed that macrorough sidewalls increase the stability of step‐pool sequences in steep narrow channels due to grain‐sidewall interactions (i.e., jamming) and bed shear stress reduction due to sidewall friction. The main goal of this study was to quantify sidewall and bed shear stress for six types of macrorough sidewalls using physical model tests. Experiments were conducted in a tilting flume with initial slopes of 4%–10% with fixed rough beds without step‐pool sequences and mobile rough beds containing step‐pool sequences. A hydraulic geometry relation to predict mean flow velocity was extended with the relative sidewall roughness to account for friction effects of macrorough sidewalls, resulting in mean prediction errors below 8% for the mobile bed experiments. Furthermore, the study presents a method to estimate flow resistance caused by the macrorough sidewalls by applying a modified sidewall correction. For the fixed rough bed, the macrorough sidewalls accounted for 10%–70% of the total shear stress. In the mobile bed experiments, the bed freely adjusted to the flow leading to the formation of step‐pool sequences. Consequently, sidewall friction accounted for 5%–40% of the total shear stress because the step‐pool structures induced larger flow resistance compared to the fixed bed experiments. Overall, the results allow to determine bed and sidewall shear stress in steep channels with macrorough bed and sidewalls, thereby enabling future studies to better quantify the mechanisms responsible for the increase in bed stability in step‐pool channels with macrorough sidewalls.

Global sensitivity analysis in hydrodynamic modeling and flood inundation mapping

Flood simulation with two-dimensional hydrodynamic models is subject to different sources of uncertainties in model configuration, boundary conditions, and model parametrization. HEC-RAS 2D is a widely used hydrodynamic model. Here, we assess the sensitivity of the HEC-RAS 2D to its configuration factors and parameters. We evaluate the impacts of different model configuration factors, including the floodplain and channel roughness coefficients, terrain and mesh size, as well as river boundary conditions on the dynamic of water levels, maximum water level, and flood extent, and determine the importance of these contributing factors for reliable flood inundation modeling using both variogram and variance-based analyses. For our case study, we found that depending on the perturbation scale, the performance measure, and the predicted output, the sensitivity to input factors changes. While for simulation of water level dynamics, the DEM and mesh resolutions are the most important factors, for flood extent mapping the floodplain roughness coefficient and the upstream boundary condition are the key factors. In addition, our analyses indicated that for a reliable simulation of maximum flood water level, modelers need to spend resources on the calibration of floodplain roughness coefficient while using fine DEM and mesh resolutions. Here, we also investigate the role of computational time interval and mesh resolution on the model's run time and accuracy. Our results suggested that reducing the computational time interval has minimum impact, as it increases the model run time without much improving the model accuracy.

Two‐dimensional‐numerical investigation on the influence of first rib distance from the entrance of channel on Nusselt number and pressure drop

AbstractEnhancing the heat transfer coefficient in heat sinks can be achieved by surface modification techniques. Although the addition of ribs increases heat transfer capacity, it also increases pressure drop, lowering the channel's thermohydraulic performance (THP) factor. Rib research began a decade ago, with the majority of studies focusing on new rib designs or factors such as relative roughness pitch, relative roughness height, channel width, and channel height (geometric optimization) to improve THP. The goal of this study is to investigate the influence of the positioning of the first rib from the channel entrance on the Nusselt number, pressure drop, and THP factor with a simple design that could be manufactured easily. Three distinct rib designs are evaluated with rib positioning from the channel entrance, rib thickness, pitch, and Reynolds number as the parameters. It was found that the fluid starts settling up at the ribs as the ribs are moved closer to the channel entry point, thus increasing the pressure drop and reducing the fluid velocity. For the proposed design and dimensions, the Nusselt number increases by 3%–5%, and the pressure drop lowers by 4%–14% when the first rib is placed away from the channel entrance.

Development of New Correlations and Parametric Optimization in Nanofluid Flow through Protruded Roughened Square Channel

This study discusses the optimization of heat-transfer parameters in nanofluid flow through a rough square surface channel including a protruded rib compound transverse pattern using response surface methodology (RSM). Flow and geometrical characteristics are optimized, resulting in optimal flow friction and heat transfer performances. The comparison of RSM’s estimated values to experimentally observed values was abandoned. The results demonstrate that the RSM-calculated values agree with the observed values and are within the 5.5 percent uncertainty limitations. Statistical correlations for Nusselt number and friction factor have been developed as functions of protrusion transverse rib height, protrusion transverse rib diameter, X-axis pitch, Y-axis pitch, and Reynolds number. These correlations have been found to predict the values within the error limits of ±8.9% and ±8.7%, respectively. On the basis of correlations developed for Nusselt number and friction factor, an attempt has been made to compare the thermohydraulic performance of protruded roughened square channel.

Influence of wall roughness on two-phase displacement

In the development of oil and gas fields, water flooding is still the most important development method. The influence of the existence of rough channel on two-phase flow cannot be ignored. To study the flow of oil-water two-phase in rough channel, the method of solving Navier-Stokes (N-S) equation directly is used to simulate the displacement process of two-phase fluid in a single rough channel, and the phase field method is used to trace the interface of two-phase fluid in real time. The effects of a series of factors, such as relative roughness height, horizontal roughness unit clearance ratio, viscosity ratio, and so on, on the displacement velocity and the length of two-phase interface are studied by establishing a simple and regular rough channel model. By establishing a smooth channel model as a control experiment, the overall effect of wall roughness on two-phase displacement is studied. Finally, the complex rough channel model is established to verify the correctness of the law obtained by the simple model. The results show that the existence of wall roughness will greatly increase the two-phase flow resistance, promote the occurrence of fingering problem, and reduce the displacement efficiency.