Downstream evolution of grain size in extremely mobile post-earthquake debris flows, China

2021 ◽  
Author(s):  
Erin L. Harvey ◽  
Tristram C. Hales ◽  
Daniel E. J. Hobley ◽  
Xuanmei Fan ◽  
Jie Liu ◽  
...  
Keyword(s):  
Grain Size ◽  
Debris Flow ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Debris Flows ◽  
Fine Fraction ◽  
Excess Pore Pressure ◽  
Extreme Rainfall Event ◽  
2008 Wenchuan Earthquake ◽  
Grain Sizes

<p>Large, catchment transitioning debris flows are an important mechanism for transporting sediment from hillslopes into higher order channels. Extremely large flows can exceed volumes of 10<sup>9</sup> m<sup>3</sup>, however even flows with volumes of  ~10<sup>3</sup> m<sup>3</sup> can lead to fatalities and extensive damage. Few processes transport a wider range of grain sizes than debris flows, which can transport grains from clays to 10 m boulders. While the structure of debris flows can often be inferred by their deposits, the range of grain sizes presents a challenge for their interpretation. Debris flow grain size distributions can be used to constrain debris flow runout due to their effect on excess pore pressure dissipation. Currently, there is limited data available for the entire grain size distribution of debris flow deposits in the field.</p><p>We constrained the entire grain size distribution for two extremely large (>1 km in length) post-earthquake debris flows in Sichuan Province, China. These debris flows were triggered in August 2019 after an extreme rainfall event occurred close to the epicentre of the 2008 Wenchuan earthquake. We sampled the debris flows in November 2019 at intervals of 200 m and 500 m, respectively. At each site, we used a combination of field and laboratory sieving to obtain the coarse and fine fraction for both the surface and subsurface. We dug 1 m x 1 m x 0.5 m pits, excavating each layer at 10 cm depth increments. We sieved these increments into five size fractions in the field, including < 1 cm. We sieved 1 kg of the <1 cm fraction in the laboratory to estimate the distribution of the finest grains. The coarse surface fraction was then independently constrained using photogrammetry. Preliminary results for one debris flow show that the distribution of fine grains (~<4 mm) is consistent both laterally and vertically across the runout. This suggests that the processes occurring vertically and laterally during deposition result in the consistent distribution of fines.</p>

Calculating debris flow density based on grain-size distribution

Landslides ◽  
2019 ◽  
Vol 16 (3) ◽  
pp. 515-522
Author(s):  
Taiqiang Yang ◽  
Yong Li ◽  
Qishu Zhang ◽  
Yu Jiang
Keyword(s):  
Grain Size ◽  
Debris Flow ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Flow Density

scholarly journals Modified Gompertz sigmoidal model removing fine-ending of grain-size distribution

2019 ◽  
Vol 11 (1) ◽  
pp. 29-36 ◽  
Author(s):  
Rui Yuan ◽  
Bo Yang ◽  
Yingfei Liu ◽  
Lingyu Huang
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Cumulative Probability ◽  
Second Stage ◽  
Grain Sizes ◽  
Third Stage ◽  
Moments Method ◽  
Sigmoidal Model ◽  
Parameters Calculation

Abstract Because of the laboratory operating, the fineending of grain-size distribution (GSD) are simply combined as one point, which results in the information loss of the fine and very-fine clastic particles, and affects the geological parameters calculation of GSD. To remove the fine-endings, a modified Gompertz sigmoidal model is proposed in this paper. The first stage is establishing and solving the modified Gompertz sigmoidal model; the second stage is fitting and evaluating the cumulative probability and frequency of GSD; the third stage is calculating the geological parameters. Taking 113 samples for example, coefficients of determination (COD) between measured and fitted individual cumulative probability and frequency are bigger than 0.98980 and 0.97000 respectively, which proves the goodness of fitting results. By moments method using frequency data, the COD between fitted and measured mean is 0.97578, while CODs of sorting, skewness and kurtosis are in low values, which suggest that the fine-endings has little influence on the average grain-sizes of GSD and large influence on its geometry. Besides, modified Gompertz sigmoidal model offers another quick numerical way to calculate median, mean and sorting of GSD by graphical method using cumulative probability data. The proposed method is useful to remove the fine-endings and contribute to calculate the geological parameters of GDS.

Study on the downcutting rate of a debris flow dam based on grain-size distribution

Geomorphology ◽  
2021 ◽  
pp. 107891
Author(s):  
Hechun Ruan ◽  
Huayong Chen ◽  
Yong Li ◽  
Jiangang Chen ◽  
Huibin Li
Keyword(s):  
Grain Size ◽  
Debris Flow ◽  
Size Distribution ◽  
Grain Size Distribution

The Inverse Hall-Petch Effect—Fact or Artifact?

2000 ◽  
Vol 634 ◽  
Author(s):  
Carl C. Koch ◽  
J. Narayan
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Computer Simulations ◽  
Nanocrystalline Materials ◽  
Grain Sizes ◽  
Average Grain Size

ABSTRACTThis paper critically reviews the data in the literature which gives softening—the inverse Hall-Petch effect—at the finest nanoscale grain sizes. The difficulties with obtaining artifactfree samples of nanocrystalline materials will be discussed along with the problems of measurement of the average grain size distribution. Computer simulations which predict the inverse Hall-Petch effect are also noted as well as the models which have been proposed for the effect. It is concluded that while only a few of the experiments which have reported the inverse Hall-Petch effect are free from obvious or possible artifacts, these few along with the predictions of computer simulations suggest it is real. However, it seems that it should only be observed for grain sizes less than about 10 nm.

Topology Based Growth Law and New Analytical Grain Size Distribution Function of 3D Grain Growth

2007 ◽  
Vol 558-559 ◽  
pp. 1183-1188 ◽  
Author(s):  
Peter Streitenberger ◽  
Dana Zöllner
Keyword(s):  
Grain Size ◽  
Distribution Function ◽  
Size Distribution ◽  
Grain Growth ◽  
Grain Size Distribution ◽  
Three Dimensional ◽  
Size Distribution Function ◽  
Change Rate ◽  
Grain Sizes ◽  
Self Similar

Based on topological considerations and results of Monte Carlo Potts model simulations of three-dimensional normal grain growth it is shown that, contrary to Hillert’s assumption, the average self-similar volume change rate is a non-linear function of the relative grain size, which in the range of observed grain sizes can be approximated by a quadratic polynomial. In particular, based on an adequate modification of the effective growth law, a new analytical grain size distribution function is derived, which yields an excellent representation of the simulated grain size distribution.

Statistical analysis of the parameters and grain size distribution functions of single-phase polycrystalline materials

2020 ◽  
Vol 86 (4) ◽  
pp. 39-45
Author(s):  
S. I. Arkhangelskiy ◽  
D. M. Levin
Keyword(s):  
Grain Size ◽  
Distribution Function ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Single Phase ◽  
Distribution Functions ◽  
Grain Structure ◽  
Polycrystalline Materials ◽  
Grain Sizes ◽  
Average Grain Size

A statistical analysis of the grain size distribution is important both for developing theories of the grain growth and microstructure formation, and for describing the size dependences of various characteristics of the physical and mechanical properties of polycrystalline materials. The grain size distribution is also an important characteristic of the structure uniformity and, therefore, stability of the properties of the products during operation. Statistical Monte Carlo modeling of single-phase and equiaxed polycrystalline microstructures was carried out to determine the type of statistically valid distribution function and reliable estimates of the average grain size. Statistical parameters (mean values, variances, variation coefficient) and distribution functions of the characteristics of the grain microstructure were obtained. It is shown that the distribution function of the effective grain sizes for the studied polycrystal model is most adequately described by γ-distribution, which is recommended to be used in analysis of the experimental distribution functions of grain sizes of single-phase polycrystalline materials with equiaxed grains. The general average (mathematical expectation) of the effective grain size (projection diameter) with γ-distribution function (parameters of the distribution function are to be previously determined in analysis of the grain structure of polycrystalline materials) should be taken as a statistically valid and reliable estimate of the average grain size. The results of statistical modeling are proved by the experimental data of metallographic study of the microstructures of single-phase model and industrial materials with different degree of the grain structure heterogeneity.

Dynamic evolution of debris flow grain composition

2021 ◽  
Author(s):  
Yong Li
Keyword(s):  
Grain Size ◽  
Debris Flow ◽  
Specific Surface ◽  
Size Distribution ◽  
Surface Area ◽  
Grain Size Distribution ◽  
Specific Surface Area ◽  
Grain Composition ◽  
Negative Power ◽  
Dynamic Rotation

<p>Debris flow is composed of solid grains of different sizes. the characteristics of grain size distribution reflect the movement mode and dynamic conditions of the fluid, and have different effects on the movement of debris flow. Due to the high variability of debris flow materials, the granular interaction is bound to affect the fluid properties. The grain size distribution (GSD) of debris flow satisfies the formula: P(D)=CD<sup>-μ</sup>exp(-D/D<sub>c</sub>), where, GSD parameters μ and D<sub>c</sub> can comprehensively reflect the change of grain composition. with μ reflecting the structure and variation characteristics of fine grains, and D<sub>c</sub> reflecting the range of grain size. Field surveys in various regions indicate that the GSD parameters are distinct in materials of flow, source, and deposition. The GSD parameters of source soil and deposition soil are random and discrete, while the GSD parameters of fluid samples show obvious negative power function form: D<sub>c</sub>= aμ<sup>b</sup> (Figure 1). This shows that the grain composition of debris flow contains some dynamic information. In this paper, we use natural soil materials in a typical debris flow valley to conduct a series dynamically mixing and rotating experiments to simulate the flow evolution, and explore the change of grains under the action of dynamics and the effect of grain adjustment on the mobility of debris flow. The results show that the GSD shows a significant regularity after dynamic rotation. The specific performance is that μ and D<sub>c</sub> change from the initial random discrete state to negative power correlation (Figure 2), and the appearance of this correlation corresponds to the best mobility of debris flow. At the same time, the Malvern laser grain size analyzer was used to analyze the specific surface area of fine grains (<0.20 mm) in the dynamic rotation experiment. The results show that with the increase of dynamic time, the specific surface area increases according to power law, and when the time reaches about 100 minutes, the growth slows down, and the specific surface area changes little. The experimental results are helpful for a deep understanding of the dynamics of debris flow.</p>

Grain sorting effects on the formation of tidal sand waves

2009 ◽  
Vol 629 ◽  
pp. 311-342 ◽  
Author(s):  
TOMAS VAN OYEN ◽  
PAOLO BLONDEAUX
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Fine Fraction ◽  
Sand Wave ◽  
Flat Bottom ◽  
Sand Waves ◽  
Sand Mixture ◽  
Sea Bed ◽  
The Stability

A model is developed to investigate the process which leads to the formation of sand waves in shallow tidal seas characterized by a heterogeneous sea bed composition. The main goal of the analysis is the evaluation of the effects that a graded sediment has on the formation of the bottom forms and the investigation of the sorting process induced by the growth of the bottom forms. The analysis is based on the study of the stability of the flat bed configuration, i.e. small amplitude perturbations are added to the flat bottom and a linear analysis of their time development is made. For an oscillatory tidal current dominated by one tidal constituent, the results show that the graded sediment can stabilize or destabilize the flat bottom configuration with respect to the uniform sediment case, depending on the standard deviation σ* of the grain size distribution and on the ratio between the horizontal tidal excursion and the water depth. For moderate values of , i.e. values just larger than the critical value for which the sediment is moved and sand waves appear, the presence of a sand mixture stabilizes the flat bed. On the other hand, for large values of , the mixture has a destabilizing effect. In both cases the effect that a sand mixture has on the stability of the flat bed configuration is relatively small. Moreover, for moderate values of , the fine fraction of the mixture tends to pile up at the crests of the bottom forms while the coarse fraction moves towards the troughs. For large values of , the grain size distribution depends on the value of σ*. The results are physically interpreted and provide a possible explanation of the apparently conflicting field observations of the grain size distribution along the sand wave profile, carried out in the North Sea.

The remobilisation of seismically-sourced sediment by debris flows in Wenchuan: A grain size perspective

2020 ◽  
Author(s):  
Erin Harvey ◽  
Xuanmei Fan ◽  
Tristram Hales ◽  
Daniel Hobley ◽  
Jie Liu ◽  
...  
Keyword(s):  
Grain Size ◽  
Debris Flow ◽  
Wenchuan Earthquake ◽  
Debris Flows ◽  
Real Field ◽  
Saturation State ◽  
2008 Wenchuan Earthquake ◽  
Seismic Landslides ◽  
The 2008 Wenchuan Earthquake

<p>Co-seismic landslides can mobilise up to 3 km<sup>3</sup> of loose sediment within minutes. However, the export rate of this sediment is largely unconstrained. For example, it is estimated that a decade after the 2008 Wenchuan earthquake at least 90% of the co-seismic sediment remains stored on the hillslope. Post-earthquake debris flows are the main conduit by which such hillslope debris reaches the fluvial network but the mechanics that govern the triggering and runout of such flows remain unclear and as such they appear to behave largely unpredictably.  Material grain size is a key control on both triggering and runout, since it affects both hydrological (e.g. water loss during flow; saturation state before triggering) and frictional properties of the system. However, our understanding of the role of grain size in the genesis and evolution of debris flows remains poorly explored, largely due to limitations in real field data. Existing estimates for landslide and debris flow deposit grain size distributions (GSDs) are currently limited by 1. inconsistency of applied methods; 2. the very poor sorting of these sediments; 3. inaccessibility, and 4. inherent intra-deposit variability in GSD. </p><p>Our research aims to better understand the role of grain size using an unprecedentedly detailed set of field-constrained GSDs across the post-seismic landslides and debris flows of the 2008 Wenchuan earthquake. Here we present data quantifying the grain size distribution across two debris flows using two different techniques. The two debris flows occurred in response to prolonged rainfall in August 2019 and mobilised co-seismic debris from the 2008 earthquake. In the field, we selected four to eight 1 m x 1 m x 0.5 m pits along the centre line of each debris flow at regular intervals and sieved the pit material into 8 cm, 4 cm, 2 cm and 1 cm fractions at 10 cm depth increments. Boulders >8 cm were measured and weighed individually. Smaller samples were then collected from the finer fraction (<1 cm) and sieved further in the laboratory. The coarse fraction was independently constrained from calibrated photogrammetry, and this was coupled to drone surveying to ensure the coarsest fraction (≥1 m) was correctly represented. This study presents a detailed estimate of post-earthquake debris flow GSDs with the overarching aim to better understand sediment transport and deposition from debris flows in the years following an earthquake.</p>

On the Grain Size Distribution of MnO Doped ZnO Ceramics

2007 ◽  
Vol 336-338 ◽  
pp. 2361-2362
Author(s):  
Shu Ai Li ◽  
Da Nian Liu ◽  
Jiang Hong Gong
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Sintering Temperature ◽  
Grain Morphology ◽  
Holding Time ◽  
Grain Sizes ◽  
Different Temperatures ◽  
Doped Zno ◽  
Zno Ceramics

A series of MnO-doped ZnO with different grain sizes and grain morphologies were prepared by sintering the samples at different temperatures for different holding times. The grain size distribution for each sample was determined. It was found that, although the grain size increases and the grain morphology varies with the sintering temperature and/or the holding time, the normalized grain size distribution keeps invariable.

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