Severe equipment degradation in production piping can occur for gas–solid flows. Advances in modeling and solid particle erosion simulations are gained through matching computer generated predictions ...to real-world experimental results. This paper presents a comprehensive approach in modeling and computational study to determine erosion in elbows due to sand particles entrained in air. Firstly, utilizing a particle image velocimetry (PIV) technique, the slip velocity between the gas and sand particles in a direct impact geometry has been measured. Secondly, an erosion equation has been generated based on PIV results and erosion testing of stainless steel in air. Thirdly, erosion patterns are measured in a 76.2mm ID standard elbow for air-sand flows using a state-of-the-art non-invasive Ultrasonic Technology (UT) device. The metal loss is measured at 16 different locations in the elbow using dual element ultrasonic transducers. Erosion experiments in the vertical to horizontal elbow are performed with gas velocities ranging from 11m/s to 27m/s at nearly atmospheric pressure. Two different sand sizes (150 and 300μm sand) were used for performing tests. The shapes of the sand are also different with the 300μm sand being sharper than the 150μm sand. Finally, the new erosion equation has been implemented into a commercially available Computational Fluid Dynamics (CFD) code to predict erosion ratios in elbows for a variety of flow conditions and particle sizes. The predicted CFD erosion magnitudes are compared with present and previous UT erosion data in elbows. The comparisons show that CFD predictions are within a factor of two of present and previous UT single-phase erosion data. Four correlations for erosion from literature are also studied and validated in simulations. The correlation developed and validated in this work can be used to predict the bend lifetime for particular operating conditions.
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•The slip velocity between the gas and sand particles has been measured using PIV.•An erosion equation has been generated based on PIV results and erosion testing.•Sand erosion is measured in a 76.2mm ID standard elbow using ultrasonic probes.•Predicted CFD erosion magnitudes are compared with UT erosion data in elbows.•CFD predictions are within a factor of two of present and previous UT erosion data.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The prediction of erosion damage caused by solid particles within flow lines is crucial for many industries. In most erosion modeling approaches, empirical erosion equations are commonly used to ...relate particle impact information to erosion magnitude. These equations are usually generated from jet impingement testing in air, since the particle impact speed and angle are assumed not to deviate from conditions in the jet. However, in slurry flows, a wide range of particle impact angles and speeds are produced on the target surface. In this work combining CFD simulation results with experimental data obtained from a normal slurry jet test, an erosion equation has been developed. In this methodology, a computational fluid dynamics (CFD) simulation is used to characterize the particle impact speed, angle and frequency at specific locations on the specimen. Then, the particle impact data are related to the measured erosion depth to achieve an erosion equation from submerged testing. The erosion equation has been validated for oblique impingement configurations and it has been shown that, the equation is well suited for various test conditions and it can successfully predict the local erosion depth.
Furthermore, a series of dry impinging jet tests for normal and oblique configurations has been performed. Utilizing a particle image velocimetry (PIV) technique, the slip velocity between the gas and sand particles has been determined. In order to gain a better understanding of the erosion pattern, local erosion depth has been measured using a 3D surface profilometer. The effect of gas velocity and impingement angle on erosion profile has also been investigated.
•A new method to predict the erosion depth due to slurry flow is presented.•Erosion profile of gas–solid tests is compared with liquid–solid ones.•The slip velocity between the particles and gas flow is measured via PIV technique.•The effect of impingement angle on erosion profile is investigated.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Slurry erosion is a severe problem and a major concern for slurry handling equipment, as it leads to considerable expense caused by failures, downtime and material replacement costs. Slurry erosion ...is dependent on several parameters such as slurry properties, service conditions, and material properties. Hence, much high-quality research has been aimed at obtaining a fundamental understanding of this complex failure mode and developing new test methodologies and erosion resistant materials to minimize erosion rates. This is a review of the literature covering research into the effects of the main parameters influencing the slurry erosion of different types of steels, focusing on those which have been developed for pipeline applications. The types of bench-scale erosion test rigs, the mechanisms involved, and the behavior of different microstructures under slurry erosion conditions are discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Planar erosion is an important mode of soil erosion, which occurs in the process of loess slope erosion, gully erosion, and cave erosion. It is of great significance to understand the characteristics ...and mechanism of planar erosion to reveal the mechanism of loess erosion and the prevention and treatment of soil and water loss. In this paper, a series of loess planar erosion tests have been carried out through self-developed large-scale loess scour instrument. The erosion process and stage characteristics of subsurface erosion under different conditions have been analyzed and summarized, and the internal mechanism of the loess planar erosion process in different erosion characteristic stages has been revealed. Furthermore, based on the special "core (powder) + coat" microstructure characteristics of loess, a numerical model of inter particle linkage was established to characterize the characteristics of loess microstructure and anti-erosion properties. The numerical simulation results carried out based on the numerical model of inter particle linkage established in this paper are in good agreement with the main results of the physical simulation of planar erosion. The results all show that the loess planar erosion at the scale of large test blocks can be divided into three characteristic stages: uniform planar erosion stage, micro gully erosion stage, and collapse failure stage. This indicates that the fluid–solid coupling simulation method of CFD–DEM proposed in this paper has high simulation accuracy and has great application potential in the research and application of loess erosion. This provides a new and feasible idea for the study of loess slope erosion and hydraulic loss control on the Loess Plateau, which is worthy of further promotion.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Loess‐roads (LR) still experience severe soil erosion due to concentrated flow during rainstorms in watersheds on the Chinese Loess Plateau, where soil erosion in sloping farmland, abandoned land, ...and grassland has been controlled. However, road erosion is commonly overlooked because unpaved roads represent a small part of the catchment area. In situ scouring‐erosion experiments were performed on LR surfaces in the Liuaogou watershed on the Loess Plateau. The erosion rate of the LR was 14.1–234.6 g m−2 min−1, which is 10.8–57.5‐times higher than that on an adjacent grassy hillslope. In most experiments, the LR erosion rate generally increased linearly with increasing concentrated flow and slope gradient (R2 > .85; significance p < .05). Concentrated flow had a greater impact on road erosion than the road surface slope. Rill erosion occurred in our road plots, with rill area densities of 0.03–0.38 m2 m−2. The total amount of road erosion was significantly correlated linearly with the rill area density (R2 = .61, p < .01), indicating that high rill density led to high total erosion on the LR. A road erosion equation based on concentrated flow and slope gradient was established and validated. The R2, p, and NSE results were .91, <.01 and 0.93, respectively, implying that the fitted equation can be considered acceptable. Our findings can provide references for the prevention of road erosion and the establishment of road erosion models.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
27.
How fast do gully headcuts retreat? Vanmaercke, Matthias; Poesen, Jean; Van Mele, Bert ...
Earth-science reviews,
03/2016, Volume:
154
Journal Article, Web Resource
Peer reviewed
Gully erosion has important on and off site effects. Therefore, several studies have been conducted over the past decades to quantify gully headcut retreat (GHR) in different environments. Although ...these led to important site-specific and regional insights, the overall importance of this erosion process or the factors that control it at a global scale remain poorly understood. This study aims to bridge this gap by reviewing research on GHR and conducting a meta-analysis of measured GHR rates worldwide. Through an extensive literature review, GHR rates for 933 individual and actively retreating gullies have been compiled from more than 70 study areas worldwide (comprising a total measuring period of >19 600years). Each GHR rate was measured through repeated field surveys and/or analyses of aerial photographs over a period of at least one year (maximum: 97years, median: 17years). The data show a very large variability, both in terms of gully dimensions (cross-sectional areas ranging between 0.11 and 816m2 with a median of 4m2) and volumetric GHR rates (ranging between 0.002 and 47 430m3year−1 with a median of 2.2m3year−1). Linear GHR rates vary between 0.01 and 135myear−1 (median: 0.89myear−1), while areal GHR rates vary between 0.01 and 3628m2year−1 (median: 3.12m2year−1). An empirical relationship allows estimating volumetric retreat rates from areal retreat rates with acceptable uncertainties. By means of statistical analyses for a subset of 724 gullies with a known contributing area, we explored the factors most relevant in explaining the observed 7 orders of magnitudes of variation in volumetric GHR rates. Results show that measured GHR rates are significantly correlated to the runoff contributing area of the gully (r2=0.15) and the rainy day normal (RDN; i.e. the long-term average annual rainfall depth divided by the average number of rainy days; r2=0.47). Other factors (e.g. land use or soil type) showed no significant correlation with the observed GHR rates. This may be attributed to the uncertainties associated with accurately quantifying these factors. In addition, available time series data demonstrate that GHR rates are subject to very large year-to-year variations. As a result, average GHR rates measured over short (<5year) measuring periods may be subject to very large (>100%) uncertainties. We integrated our findings into a weighted regression model that simulates the volumetric retreat rate of a gully headcut as a function of upstream drainage area and RDN. When weighing each GHR observation proportional to its measuring period, this model explains 68% of the observed variance in GHR rates at a global scale. For 76% of the monitored gullies, the simulated GHR values deviate less than one order of magnitude from their corresponding observed value. Our model clearly indicates that GHR rates are very sensitive to rainfall intensity. Since these intensities are expected to increase in most areas as a result of climate change, our results suggest that gully erosion worldwide will become more intense and widespread in the following decades. Finally, we discuss research topics that will help to address these challenges.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Rainfall erosion is a complex process and good understanding of the mechanisms involved is necessary if inappropriate designs and procedures are not unwittingly used in rainfall erosion experiments. ...Numerous runoff and soil loss plots of various sizes have been installed in many parts of the world. It is essential that on any eroding surface water flows across the surface without interference from any equipment designed to collect runoff and sediment. Examples of designs that do not conform to this requirement are presented. Because sedimentation occurs in tanks, coarse material needs to be collected and measured separately from fine material which can be subsampled when suspended in the runoff water.
Despite attempts to operate in areas where soil properties are uniform, replicates are shown to produce considerable variation in the soil losses produced by the same event. Slope length and gradient influence the type of erosion that occurs on a plot. Slope lengths less than one metre encourage erosion where detachment and transport is controlled by the expenditure of the energy generated by raindrop impact but as slope lengths and gradients increase, detachment by flow may result in the development of rills. Experiments on slopes of one or two metres in length do not provide data that can be used to parameterise models like the USLE that operate on slopes up to 300m long.
Rainfall simulators have been widely used in rainfall erosion experiments on plots shorter than 10m. Given the fact that raindrop induced bed load transport is stimulated by individual raindrop impacts, spatial variations in raindrop size and impact frequency in artificial rainfall produced by sprays can lead to erroneous results. Similarly, temporal and spatial variations in flow depths in rain-impacted flows on inclined surfaces in experiments leads of variations in erosive stress that are seldom taken into account when analysing the results produced using artificial rainfall. This presents difficulties in respect to apply the results to other situations. The WEPP interrill erosion model was designed to predict soil movement from interrill areas to rills but it is shown that the ranking of soils according to their interrill erodibility varies depending on whether eroding surface is flat plot or on a ridge tillage sideslope.
•Plot design and equipment must not affect flow over eroding surface.•Coarse and fine sediment must be collected and measured separately.•Considerable variation between replicates despite same treatment•Spatial variations in erosion process influence event soil loss.•Spatial variation in artificial rainfall characteristics can produce flawed results.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving ...forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape to address the problem strategically. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviews the different sub-factors of USLE and RUSLE, and analyses how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with (R)USLE and related approaches. Within each sub-factor section, the strengths and limitations of the different equations are discussed, and guidance is given as to which equations may be most appropriate for particular climate types, spatial resolution, and temporal scale. We investigate some of the limitations of existing (R)USLE formulations, such as uncertainty issues given the simple empirical nature of the model and many of its sub-components; uncertainty issues around data availability; and its inability to account for soil loss from gully erosion, mass wasting events, or predicting potential sediment yields to streams. Recommendations on how to overcome some of the uncertainties associated with the model are given. Several key future directions to refine it are outlined: e.g. incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and compiling consistent units for the future literature to reduce confusion and errors caused by mismatching units. The potential of combining (R)USLE with the Compound Topographic Index (CTI) and sediment delivery ratio (SDR) to account for gully erosion and sediment yield to streams respectively is discussed. Overall, the aim of this paper is to review the (R)USLE and its sub-factors, and to elucidate the caveats, limitations, and recommendations for future applications of these soil erosion models. We hope these recommendations will help researchers more robustly apply (R)USLE in a range of geoclimatic regions with varying data availability, and modelling different land cover scenarios at finer spatial and temporal scales (e.g. at the field scale with different cropping options).
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