Mountain torrent debris flow process simulation method based on rheological evolution characteristics

Abstract

The invention belongs to the field of mountain torrent and debris flow disaster prevention and reduction, and provides a mountain torrent and debris flow process simulation method based on rheological evolution characteristics, which comprises the following steps: establishing a target channel generalized numerical model, and simulating the transportation process of sediment particles in the generalized numerical model under the action of water flow or debris flow slurry by adopting a CFD-DEM coupling model, in the simulation process, on the basis of the semi-empirical relation, obtained through derivation, of the resistance coefficient and Reynolds number of the sediment particles carried by the mountain torrent debris flow in the movement process, real-time adjustment of rheological parameters in the simulated mountain torrent debris flow transportation process is achieved through a bidirectional coupling mechanism of a CFD-DEM coupling model. According to the method, the spatial distribution of the sediment particles in the mountain torrent debris flow transportation process can be simulated more truly, the accuracy of mountain torrent debris flow process simulation is improved, and the rheological evolution phenomenon of the mountain torrent debris flow caused by the fact that the volume sediment content change of the mountain torrent debris flow is difficult to simulate in the prior art is solved.

Description

Technical Field

[0001] The present invention belongs to the field of flood and debris flow disaster prevention and mitigation, and relates to a method for simulating the process of flood and debris flow based on rheological evolution characteristics. Background Art

[0002] Flood and debris flow, which is composed of a large amount of sediment, stones and water, has powerful erosion and destructive power. The rheological properties of flood and debris flow reflect its physical properties and movement characteristics, and will directly affect its movement and erosion process. At present, the research on the rheological properties of debris flow mostly relies on experimental measurement techniques and empirical rheological models. In the prior art, the Bingham model, power-law model, etc. are often used to describe the rheological properties of flood and debris flow, and the key parameters of these models mainly include the yield stress and viscosity coefficient of the slurry. For example, Huang Jiangcheng et al. carried out debris flow experiments using representative soils in the Xiaojiang River Basin in Yunnan and the Bailong River Basin in Gansu, and explored the influence of particle size distribution, clay content and mineral composition on the rheological properties of the slurry. Contreras and Davies revealed the influence of coarse particles on the change of yield stress by analyzing the rheological properties of flood and debris flow carrying coarse particles. Yu Jie et al. revealed the relationship between the fractal characteristics of episodic flood and debris flow and its movement parameters such as discharge and sediment transport rate. Kaitna et al. studied the influence of sediment gradation and content on the internal pressure distribution of flood and debris flow slurry, and explained the role of sediment in increasing the fluidity and long-distance movement ability of flood and debris flow. Sun et al. used numerical simulation methods to explore the evolution range of flood and debris flow processes under different pore water pressure ratios in the Izu Mountains of Shizuoka Prefecture, Japan. Nie Yipin et al. simulated the deposition process of sediment particles with different particle sizes at the outlet of a flood and debris flow gully, and discussed the influence of volume sediment concentration (Cv) on the distribution characteristics of sediment particles. Han et al. improved the simulation effect of flood and debris flow erosion patterns and inundation areas based on the cellular automata model.

[0003] At present, in the numerical simulation of flash flood debris flow widely used at home and abroad, fixed rheological parameters are mostly used, that is, the rheological parameters of flash flood debris flow need to be preset before the simulation begins, and the rheological parameters remain unchanged during the simulation process, while the parameter values ​​vary greatly between different simulations. However, during the transport of flash flood debris flow, its volumetric sediment content (Cv) will change, and the change of volumetric sediment content (Cv) will cause the rheological parameters of flash flood debris flow to change. Therefore, the existing numerical simulation method of flash flood debris flow uses fixed rheological parameters, which is difficult to reflect the rheological evolution of flash flood debris flow caused by the change of volumetric sediment content (Cv) during the transport process. To this end, Shen et al. proposed to consider the rheological evolution of flash flood debris flow caused by bed erosion, revealing the significant influence of rheological properties and terrain changes caused by bed erosion on the propagation of mobile flash flood debris flow. Meyrat et al. introduced the Voellmy mixed rheological model in the numerical model, obtained the erosion pattern and density distribution of flash flood debris flow, and reproduced the transformation process between flash flood debris flow and flood or super-concentrated flow. However, in these studies, the erosion rate of the solid phase still needs to be assumed in advance, which makes it difficult to simulate the movement of the eroded sediment front. In addition, although the above-mentioned single fluid model has the advantages of few calculation parameters, small calculation amount and easy use, it assumes that the velocities between the solid and liquid phases of the flash flood debris fluid are basically the same, ignoring the relative movement between the two phases. This assumption is obviously not valid when the sand content of the flash flood debris flow is low. Therefore, using a discrete medium model to calculate the movement of sediment particles and coupling the fluid movement obtained by the continuous medium model is a feasible method for simulating flash flood debris flow.

[0004] The computational fluid dynamics-discrete element method coupled simulation (CFD-DEM) method can quantify the forces between phases and capture the gully bed deformation and sediment movement from the perspective of particles. It has been widely used in the simulation of flash flood debris flow processes. Based on the CFD-DEM method, Nie et al. constructed an improved Weibull function model to quantify the instantaneous sediment transport rate variation characteristics of loosely deposited sediment particles during flash flood debris flow activities. With the help of the CFD-DEM method, Li et al. found that the protection efficiency of the protection net is closely related to the Froude number of the flash flood debris flow slurry. Lei Ming et al. used the CFD-DEM method to reveal the relationship between the water level evolution along the variable gradient flash flood debris flow channel and the gully bed scouring and silting deformation and sediment supply conditions. Kong and Guan studied the blocking effect of protective structures on different flash flood debris flows based on the CFD-DEM method. However, in these studies, rheological parameters still need to be defined in advance and kept unchanged during the simulation process. This makes it difficult to simulate the rheological evolution of flash flood debris flows caused by changes in the volumetric sediment content (Cv) of flash flood debris flows, and the accuracy of the simulation needs to be improved. Summary of the invention

[0005] In view of the problem that in the existing technology, rheological parameters need to be predefined during the coupled simulation of mountain flood and debris flow and remain unchanged during the simulation process, and it is impossible to simulate the rheological evolution characteristics of mountain flood and debris flow caused by the change in the volume sediment concentration of mountain flood and debris flow, the present invention provides a method for simulating the process of mountain flood and debris flow based on rheological evolution characteristics. When simulating, the influence of the change in the volume sediment concentration of mountain flood and debris flow on the rheological characteristics of mountain flood and debris flow during the transportation process is considered. By adjusting the rheological parameters of mountain flood and debris flow in the simulation process in real time, the simulation of the process of mountain flood and debris flow under the condition of changing volume sediment concentration is realized, so as to more realistically simulate the spatial distribution of sediment particles during the transportation process of mountain flood and debris flow, increase the accuracy of the simulation of mountain flood and debris flow, and provide more scientific guidance for the prevention and control of mountain flood and debris flow disasters.

[0006] To achieve the above-mentioned invention purpose, the technical solution adopted by the present invention is as follows:

[0007] A method for simulating the process of mountain flood and debris flow based on rheological evolution characteristics, comprising the following steps:

[0008] S1. Take the gully in the mountainous area to be simulated for the process of mountain flood and debris flow as the target gully. The target gully includes a debris flow formation area and a debris flow flow area that are connected to each other. The debris flow flow area has loose accumulations; establish a generalized numerical model of the target gully according to the topographic information of the target gully and the grading information of the sediment particles in the loose accumulations.

[0009] S2. Use the CFD-DEM coupling model to simulate the transportation process of sediment particles in the generalized numerical model under the action of water flow or debris flow slurry. The steps are as follows:

[0010] S21. Read the generalized numerical model of the target gully.

[0011] S22. The DEM module executes the DEM solution loop. In the DEM solution loop, first read the particle neighbor list and identify the contacts and collisions between particles, calculate the forces on each particle, then determine the motion state of each particle, update the position and velocity of each particle, and transmit the position and velocity information of the particles to the coupling module of the CFD-DEM coupling model.

[0012] S23. Transmit the position and velocity information of the particles obtained by the DEM module to the CFD module through the coupling module of the CFD-DEM coupling model. In the CFD module, execute the CFD solution loop. In the CFD solution loop, solve the fluid control equation and update the flow field information. When the flow field converges, transmit the flow field information to the coupling module of the CFD-DEM coupling model.

[0013] S24. In the coupling module of the CFD-DEM coupling model, obtain the fluid velocity and grid porosity at the location of each particle, calculate the relative velocity between the particle and the fluid, and determine whether the particle is in the water flow. If the particle is in the water flow, calculate the rheological parameters including the yield stress and viscosity according to the porosity of each grid. If the particle is in the air, calculate the drag coefficient of the particle according to the DiFelice formula. For the particles in the water flow, determine whether the particle has started to move. If the particle has not started to move, calculate the drag coefficient of the particle according to the Di Felice formula. If the particle has started to move, calculate the equivalent Reynolds number of the particle according to Equation (4), then calculate the separation angle and the projected area coefficient through Equations (11) and (13), and then calculate the drag coefficient of the particle through Equation (17). Finally, calculate the total drag force on each particle and transfer the information of the total drag force on the particle back to the DEM module.

[0014]

[0015] In the formula, Re * is the equivalent Reynolds number of the particle, ρ f is the density of the fluid where the particle is located, d is the particle diameter, v max is the maximum settling velocity of the particle in the Bingham fluid, η 0 is the viscosity, ε* is the dimensionless settling velocity, Re' is the Reynolds number of the particle, η * is the dimensionless apparent viscosity, θ is the separation angle, is the projected area coefficient of the separation zone, and Cd is the drag coefficient of the particle.

[0016] S25. Repeat the operations of S22 to S24 to continue the calculation of the next time step.

[0017] In step S2 of the above technical solution, when using the CFD-DEM coupling model to simulate the sediment particle transport process in the generalized numerical model under the action of water flow or debris flow slurry, the water flow rate or debris flow slurry flow rate used is determined by analyzing the historical rainfall data at the target channel.

[0018] The water flow rate can be determined by the following steps: According to the design flood control index of the area where the target channel is located, combined with historical rainfall data and hydrological analysis, determine the flood flow rate with a specific recurrence period, use the flood flow rate with the specific recurrence period as the original flow rate, and scale the original flow rate according to the model scale to obtain the water flow rate used in the generalized numerical model.

[0019] The debris flow slurry flow rate can be determined by the following steps: Based on the historical rainfall data and hydrological analysis results of the area where the target gully is located, combined with the correlation analysis data between historical rainfall and debris flow flow rate, determine the debris flow flow rate caused by rainfall with a specific return period, use the debris flow flow rate with this specific return period as the original flow rate, and scale the original flow rate according to the scale of the generalized numerical model, that is, obtain the flow rate of the debris flow slurry used in the generalized numerical model.

[0020] In the above technical solution, when the CFD-DEM coupling model is used in step S2 to simulate the transport process of sediment particles in the generalized model under the action of the debris flow slurry, the volume concentration of the debris flow slurry used is determined by analyzing the historical rainfall data, debris flow sediment yield and scale at the target gully.

[0021] In step S22 of the above technical solution, the calculation of the force on each particle refers to calculating the non-linear elastic normal force and tangential force between particle-particle and particle-boundary based on Hertzian contact theory and Mindlin and Deresiewicz theory respectively; after determining the force on each particle, determine the motion state of each particle according to Newton's second law. The method of calculating the force on each particle and determining the motion state of each particle is an existing method.

[0022] In step S23 of the above technical solution, the fluid control equations are the fluid continuity equation and the N-S equation. When solving the fluid control equations, the PISO algorithm is used to solve the fluid control equations, and the method of using the PISO algorithm to solve the fluid control equations is an existing method.

[0023] In step S24 of the above technical solution, when judging whether a particle is in the water flow, it is judged whether the particle is in the water flow according to the density value obtained by weighted averaging the fluid volume fraction of the grid where the particle is located. This judgment method is an existing method.

[0024] In step S1 of the above technical solution, a generalized numerical model of the target gully is established in the open-source software Gmsh according to the topographic information of the target gully and the grading information of the sediment particles of the loose accumulation body.

[0025] Compared with the prior art, the technical solution of the present invention has the following beneficial technical effects:

[0026] 1. The present invention provides a method for simulating the process of mountain flood and debris flow based on rheological evolution characteristics. This method is proposed based on the semi-empirical relationship between the drag coefficient and the Reynolds number of the sediment particles carried by mountain flood and debris flow obtained through theoretical derivation. When simulating, this method takes into account the influence of the change in the volume sediment concentration of mountain flood and debris flow during the transportation process on the rheological characteristics of mountain flood and debris flow, and realizes the simulation of the process of mountain flood and debris flow under the condition of changing volume sediment concentration by adjusting the rheological parameters of mountain flood and debris flow in the simulation process in real time. Compared with the prior art that requires predefining rheological parameters before the coupled simulation of mountain flood and debris flow and keeping the rheological parameters unchanged during the simulation process, which makes it difficult to simulate the rheological evolution phenomenon of mountain flood and debris flow caused by the change in the volume sediment concentration of mountain flood and debris flow, the method of the present invention can more realistically simulate the spatial distribution of sediment particles during the transportation process of mountain flood and debris flow, improve the accuracy of the simulation of the mountain flood and debris flow process, provide more scientific guidance for the prevention and control of mountain flood and debris flow disasters, and also contribute to the in-depth study of the microscopic mechanism of the transportation of mountain flood and debris flow in the streams and gullies of mountainous areas.

[0027] 2. Based on the semi-empirical relationship between the drag coefficient and the Reynolds number of the sediment particles carried by mountain flood and debris flow obtained through theoretical derivation, the method of the present invention realizes the real-time adjustment of the rheological parameters during the simulation of the transportation process of mountain flood and debris flow through the two-way coupling mechanism of the CFD-DEM coupling model. This real-time adjustment helps to more accurately capture the interaction between the solid phase and the fluid phase, and provides a more accurate prediction for the erosion process of mountain flood and debris flow movement.

[0028] 3. When simulating the movement process of mountain flood and debris flow, the method of the present invention takes into account the influence of the sediment volume fraction on the fluid rheological parameters and the change in the sediment volume fraction during the movement process of mountain flood and debris flow, which can more realistically simulate the spatial distribution of sediment particles during the transportation process of mountain flood and debris flow. The method of the present invention can reveal the spatial distribution law of the rheological parameters of mountain flood and debris flow, and provide strong technical support for the prevention and control of mountain flood and debris flow disasters. Description of the Drawings

[0029] Figure 1 It is the relationship between the equivalent Reynolds number and the drag coefficient when particles settle in Bingham fluid. The data points in the figure show the experimental results of reference [4], and the curve in the figure shows the theoretical calculation results of equation (17).

[0030] Figure 2 It is a schematic diagram of the experimental device for the dam-break experiment in reference [5].

[0031] Figure 3 It is a comparison chart of the experimental data in reference [5] and the simulation results in the present invention.

[0032] Figure 4 Schematic diagram of the calculation process of the method of the present invention.

[0033] Figure 5 It is a schematic diagram of the mobile bed model of mountain flood and debris flow.

[0034] Figure 6 It is the characteristics of gully bed erosion considering rheological evolution after the contact between mountain flood and debris flow and particles.

[0035] Figure 7 It is the characteristics of gully bed erosion without considering rheological evolution after the contact between mountain flood and debris flow and sediment.

[0036] Figure 8 It is the characteristics of the change of gully bed and water surface elevation during the movement of mountain flood and debris flow considering rheology.

[0037] Figure 9 It is the characteristics of the change of gully bed and water surface elevation during the movement of mountain flood and debris flow without considering rheology.

[0038] Figure 10 It is the simulation result of the spatial distribution of the volume fraction of sediment particles in mountain flood and debris flow considering rheological evolution (t = 2 s). The cloud map and contour lines in it represent the numerical values of the sediment volume fraction.

[0039] Figure 11 It is the simulation result of the spatial distribution of the volume fraction of sediment particles in mountain flood and debris flow without considering rheological evolution (t = 2 s). The cloud map and contour lines in it represent the numerical values of the sediment volume fraction.

[0040] Figure 12 It is the spatial distribution of the rheological parameters of mountain flood and debris flow during the process simulation (t = 2 s). In the figure (A), the spatial distribution of the yield stress is shown, and in the figure (B), the spatial distribution of the viscosity is shown. Detailed implementation mode

[0041] The following further illustrates the method for simulating the process of mountain flood and debris flow based on rheological evolution characteristics provided by the present invention through embodiments. It is necessary to point out that the following embodiments are only used to further illustrate the present invention and cannot be understood as limiting the protection scope of the present invention. Those skilled in the art make some non-essential improvements and adjustments to the present invention according to the above-mentioned invention content and carry out specific implementation, which still belongs to the protection scope of the invention.

[0042] Embodiment

[0043] In this embodiment, the method for simulating the process of mountain flood and debris flow based on rheological evolution characteristics described in the present invention is described in detail as follows:

[0044] 1. The method for simulating the process of mountain flood and debris flow based on rheological evolution characteristics is proposed based on the relationship between the resistance coefficient and Reynolds number of sediment particles carried by mountain flood and debris flow in motion (resistance coefficient - Reynolds number relationship) derived in the present invention. Here, the derivation process of the resistance coefficient - Reynolds number relationship is first described.

[0045] Since the mountain flood and debris flow slurry has the characteristics of Bingham fluid (see reference [1]: Huang Jiangcheng, Ou Guoqiang, Pan Huali, et al. Comparative study on rheological characteristics of typical soil slurries in debris flow prone areas [J]. Journal of Sichuan University (Engineering Science Edition), 2015, 47(06): 49–53.), for Bingham fluid, its apparent viscosity η is expressed by Equation (1):

[0046]

[0047] In Equation (1), η is the apparent viscosity, η 0 is the viscosity, τ 0 is the yield stress, is the shear rate.

[0048] Assume that a spherical particle with a diameter of d (hereinafter referred to as the particle) settles in an infinite Bingham fluid and reaches its maximum settling velocity v max , and a dimensionless settling velocity ε* can be defined based on the units of each parameter in the Bingham fluid. Its expression is as shown in Equation (2):

[0049]

[0050] In Equation (2), ε* is the dimensionless settling velocity, η 0 is the viscosity, τ 0 is the yield stress, d is the diameter of the particle, and v max is the maximum settling velocity of the particle in the Bingham fluid.

[0051] Using the form of Equation (1) and the dimensional analysis result of Equation (2), the apparent viscosity is made dimensionless to obtain the dimensionless apparent viscosity η*, and its expression is as shown in Equation (3):

[0052] η * =1+ε * (3)

[0053] In Equation (3), η* is the dimensionless apparent viscosity, and ε* is the dimensionless settling velocity.

[0054] Based on the dimensionless apparent viscosity η * , the particle equivalent Reynolds number Re* is defined by Equation (4):

[0055]

[0056] In Equation (4), Re * is the equivalent Reynolds number of the particle, ρ f is the density of the fluid where the particle is located, d is the particle diameter, v max is the maximum settling velocity of the particle in the Bingham fluid, η 0 is the viscosity, ε* is the dimensionless settling velocity, Re' is the Reynolds number of the particle, and η* is the dimensionless apparent viscosity.

[0057] According to the research of Yue Xiang'an et al. (see Reference [2]: Yue Xiang'an, Hao Jiangping, Chen Jialang. Drag Coefficient and Settling Velocity of Solid Particles in Bingham Fluids [J]. Petroleum Drilling & Production Technology, 1993(1): 1–8.), the drag acting on the particle in the Bingham fluid is a function of the equivalent Reynolds number Re * of the particle, the maximum settling velocity v max of the particle in the Bingham fluid, the density ρ f of the fluid where the particle is located, as well as the particle diameter d and its related quantities, and can be expressed by Equation (5):

[0058]

[0059] In Equation (5), Re * is the equivalent Reynolds number of the particle, ρ f is the density of the fluid where the particle is located, v max is the maximum settling velocity of the particle in the Bingham fluid, and d is the particle diameter.

[0060] Given that the particle has reached the maximum settling velocity in the Bingham fluid and the drag it experiences is the same as its own gravity (see Reference [3]: Zhang Xiaofeng, Liu Xingnian. River Dynamics [M]. Beijing: China Water & Power Press, 2010.), the expression for the drag coefficient of the particle is as shown in Equation (6):

[0061]

[0062] In Equation (6), Cd is the drag coefficient of the particle, ρ p is the particle density, ρ f is the density of the fluid where the particle is located, v max is the maximum settling velocity of the particle in the Bingham fluid, d is the particle diameter, and g is the acceleration due to gravity.

[0063] The experimental data of the sphere sedimentation experiment conducted by Valentik and Whitmore in Bingham fluid (see reference [4]: Valentik L, Whitmore R L. The terminal velocity of spheres in Bingham plastics[J]. British Journal of Applied Physics, 1965, 16(8):1197.) are as Figure 1 shown by the data points in. As Figure 1 shown, at lower Re * , Cd and Re * show an obvious linear relationship on the double logarithmic coordinate. When Re * is large enough, Cd tends to a constant value. When Re * > 500, Cd is about 0.4. This trend is similar to the relationship observed for spherical particles settling in Newtonian fluid.

[0064] During the process of particle settlement in Newtonian fluid, when the particle Reynolds number Re' is low, the relationship between the drag coefficient Cd of the particle and the particle Reynolds number Re' satisfies the relationship shown in Equation (7):

[0065]

[0066] In Equation (7), a and b are coefficients, Re' is the particle Reynolds number, and Cd is the drag coefficient of the particle.

[0067] From Figure 1 the experimental data in, it can be seen that when Re * < 10, the drag coefficient Cd of the particle and the equivalent Reynolds number Re of the particle * show a significant linear relationship on the double logarithmic coordinate. Therefore, adopting the form of Equation (7) and calibrating with the experimental results of the above reference [4], the drag coefficient - equivalent Reynolds number relationship of the particle at this stage (Re * < 10) is as shown in Equation (8):

[0068]

[0069] In Equation (8), Re' is the particle Reynolds number, and Cd is the drag coefficient of the particle.

[0070] Existing studies have shown that when the settling velocity of spherical particles in a Bingham fluid is relatively high, the flow field around the spherical particles becomes significantly asymmetric, resulting in the formation of a negative wake behind the spherical particles. At this time, the drag force acting on the spherical particles mainly consists of pressure drag and turbulent friction drag. However, at lower Reynolds numbers, there is no obvious separation between the fluid and the spherical particles. A low Reynolds number indicates that the viscous force in the fluid dominates, resulting in a smooth laminar flow, where the fluid adheres tightly to the surface of the spherical particles, thereby reducing the possibility of the formation of a separation zone.

[0071] The central angle of the low-pressure region projected behind the spherical particle is defined as the separation angle θ. It can be observed that for any spherical particle moving in a fluid, the range of the separation angle is 0 ≤ θ ≤ 2π. Since the Reynolds number Re' of the particle (or the equivalent Reynolds number Re of the aforementioned particle) reflects the relative influence of turbulent drag and laminar viscous force, as the Reynolds number Re' of the particle increases, the influence of turbulent drag also increases. Therefore, the separation angle θ is directly related to the Reynolds number Re' of the particle. Existing studies have shown that the rate of increase of the separation angle θ decreases as the Reynolds number Re' of the particle increases (see Reference [3]: Zhang Xiaofeng, Liu Xingnian. River Dynamics [M]. Beijing: China Water & Power Press, 2010.), so it is assumed that the derivative of the separation angle θ with respect to the equivalent Reynolds number Re of the particle is inversely proportional to the equivalent Reynolds number of the particle, that is, as shown in Equation (9): * ) reflects the relative influence of turbulent drag and laminar viscous force, as the Reynolds number Re' of the particle increases, the influence of turbulent drag also increases. Therefore, the separation angle θ is directly related to the Reynolds number Re' of the particle. Existing studies have shown that the rate of increase of the separation angle θ decreases as the Reynolds number Re' of the particle increases (see Reference [3]: Zhang Xiaofeng, Liu Xingnian. River Dynamics [M]. Beijing: China Water & Power Press, 2010.), so it is assumed that the derivative of the separation angle θ with respect to the equivalent Reynolds number Re of the particle is inversely proportional to the equivalent Reynolds number of the particle, that is, as shown in Equation (9): * of the derivative of the separation angle θ with respect to the equivalent Reynolds number Re of the particle is inversely proportional to the equivalent Reynolds number of the particle, that is, as shown in Equation (9):

[0072]

[0073] In Equation (9), C is a constant, Re * is the equivalent Reynolds number of the particle, is the derivative of the separation angle with respect to the equivalent Reynolds number of the particle.

[0074] Denote the Re when separation is about to occur between the fluid and the spherical particle as Re * as Re *1 . When Re * reaches Re *2 , the eddy current around the spherical particle is fully developed and a negative wake is formed. Therefore, the equation needs to satisfy the boundary condition shown in Equation (10):

[0075]

[0076] According to Figure 1 the experimental data analysis in, determine the value of Re *1 to be 10 and the value of Re *2 to be 500. Therefore, the boundary condition shown in Equation (10) can be expressed by Equation (11):

[0077]

[0078] In Equation (11), θ is the separation angle, and Re * is the equivalent Reynolds number of the particle.

[0079] The magnitude of the turbulent drag depends on the projected area of the spherical particle in the flow direction within the separation zone (see Reference [3]: Zhang Xiaofeng, Liu Xingnian. River Dynamics [M]. Beijing: China Water & Power Press, 2010.), and the area A affected by this turbulent drag t is given by Equation (12):

[0080]

[0081] In Equation (12), A t is the area affected by the turbulent drag, d is the particle diameter, is the projection area coefficient of the separation zone, and its expression is as shown in Equation (13):

[0082]

[0083] In Equation (13), is the projection area coefficient of the separation zone.

[0084] Once flow separation occurs, the laminar viscous force is limited to the surface area outside the separation zone. Therefore, the effective area A of the laminar viscous force l is given by Equation (14):

[0085]

[0086] In Equation (14), A l is the effective area of the laminar viscous force, θ is the separation angle, and d is the particle diameter.

[0087] Since the surface of the spherical particle is divided into regions where the laminar viscous force and the turbulent drag act, the total drag acting on the particle is the sum of these two forces, that is, the total drag acting on the particle is as shown in Equation (15):

[0088] F d = F t + F l (15)

[0089] In Equation (15), F d is the total drag acting on the particle, F t is the turbulent drag acting on the particle, and F l is the laminar viscous force acting on the particle.

[0090] Therefore, the total drag F acting on the particle d can be expressed by Equation (16):

[0091]

[0092] In Equation (16), F d is the total drag force acting on the particle, A l is the effective area of the laminar viscous force, A t is the area affected by the turbulent drag, ρ f is the density of the fluid where the particle is located, v max is the maximum settling velocity of the particle in the Bingham fluid, Re * is the equivalent Reynolds number of the particle.

[0093] Therefore, the semi-empirical formula for the drag coefficient of the particle can be expressed by Equation (17):

[0094]

[0095] In Equation (17), Cd is the drag coefficient of the particle, Re * is the equivalent Reynolds number of the particle, θ is the separation angle, is the projection area coefficient of the separation zone.

[0096] During the derivation of Equation (17), the experimental data in the range of 10 ≤ Re* ≤ 500 in Figure 1 was not explicitly introduced. However, when the theoretical calculation results of Equation (17) are plotted in Figure 1 it can be seen that, as shown by the curve "theoretical derivation result of the formula" in Figure 1 , the calculated values (curves) in Figure 1 are in good agreement with the experimental data (data points), thus verifying the applicability of Equation (17) in calculating the drag coefficient of particles in Bingham fluids.

[0097] 2. Verify the rationality of the drag coefficient - equivalent Reynolds number relationship shown in Equation (17) through experiments

[0098] To test the rationality of the drag coefficient - equivalent Reynolds number relationship shown in Equation (17) derived in Step 1, the experimental data of the dam-break of non-Newtonian fluid (mud) reported by Komatina and Jovanovic (see Reference [5]: Komatina D, Jovanovic M. Experimental study of steady and unsteady free surface flows with water - clay mixtures[J]. Journal of Hydraulic Research, 1997, 35(5): 579–590.) was used for verification. The experimental apparatus and experimental methods used for verification are all referred to in Reference [5], and the schematic diagram of the specific apparatus structure is as shown in Figure 2 shown.

[0099] To reduce the computational effort, the coarse-grained model proposed by Zhao et al. (see reference [6]: Zhao T, Utili S, Crosta G B. Rockslide and impulse wave modelling in the vajont reservoir by dem-cfd analyses[J]. Rock Mechanics and Rock Engineering, 2016, 49(6): 2437–2456.) was used to simulate the experiment with a volume sediment concentration Cv = 20.1%, and a process diagram of the mud front position changing with time was plotted. The results are as Figure 3 shown. From Figure 3 this, it can be seen that the numerical simulation is in good agreement with the experimental data, indicating that it is feasible to use the drag coefficient - equivalent Reynolds number relationship shown in Equation (17) derived in the above step 1 in the CFD-DEM coupling method to calculate the motion problem of particles in non-Newtonian fluids.

[0100] 3. Flowchart of the method for simulating the process of mountain torrents and debris flows based on rheological evolution characteristics of the present invention

[0101] The method for simulating the process of mountain torrents and debris flows based on rheological evolution characteristics of the present invention is to establish a generalized numerical model of the target channel on the basis of the target channel, and use the CFD-DEM coupling model (CFDEM coupling engine) to simulate the sediment transport process of sediment particles in the generalized numerical model under the action of water flow or debris flow slurry. The calculation process of the method of the present invention is as Figure 4 shown, Figure 4 showing the calculation process within one time step, which is specifically as follows:

[0102] S1. Take the mountainous channel to be simulated for the process of mountain torrents and debris flows as the target channel. The target channel includes a debris flow formation area and a debris flow flow area that are connected to each other. The debris flow flow area has loose accumulations; according to the topographic information of the target channel and the grading information of the sediment particles in the loose accumulations, establish a generalized numerical model of the target channel in the open-source software Gmsh.

[0103] S2. Use the CFD-DEM coupling model to simulate the sediment transport process of sediment particles in the generalized numerical model under the action of water flow or debris flow slurry. The steps are as follows:

[0104] S21. Read the generalized numerical model of the target channel.

[0105] S22. The DEM module executes the DEM solution loop. In the DEM solution loop, first, the particle neighbor list is read, and the contacts and collisions between particles are identified. Based on the Hertzian contact theory and the Mindlin and Deresiewicz theories, the nonlinear elastic normal and tangential forces between particle-particle and particle-boundary are calculated respectively. Then, according to Newton's second law, the motion state of each particle is determined, the position and velocity of each particle are updated, and the position and velocity information of the particles are passed into the coupling module of the CFD-DEM coupling model. The DEM solution loop process in this step is prior art. Referring to the prior art, open-source LIGGGHTS is used as the calculation software to simulate the movement of sediment particles.

[0106] S23. The position and velocity information of the particles obtained by the DEM module are passed to the CFD module through the coupling module of the CFD-DEM coupling model. In the CFD module, the CFD solution loop is executed. In the CFD solution loop, the existing PISO algorithm is used to solve the fluid continuity equation and the N-S equation and update the flow field information. When the flow field converges, the flow field information is passed into the coupling module of the CFD-DEM coupling model. The CFD solution loop process in this step is prior art. Referring to the prior art, open-source OpenFOAM is used as the calculation software to simulate the water flow.

[0107] S24. In the coupling module of the CFD-DEM coupling model, the fluid velocity and grid porosity at the position of each particle are obtained, the relative velocity of the particle-fluid is calculated, and it is judged whether the particle is located in the water flow according to the density value obtained by weighted averaging the fluid volume fraction of the grid where the particle is located. If the particle is located in the water flow, the rheological parameters are calculated according to the porosity of each grid. The rheological parameters include the yield stress τ 0 and the viscosity η 0 . If the particle is located in the air, the drag coefficient of the particle is calculated according to the Di Felice formula; for the particle located in the water flow, it is judged whether the particle has started. If the particle has not started, the drag coefficient of the particle is calculated according to the Di Felice formula. If the particle has started, the equivalent Reynolds number Re * of the particle is calculated according to Equation (4). Then, the separation angle and the projected area coefficient are calculated through Equations (11) and (13), and the drag coefficient of the particle is calculated through Equation (17); finally, the total drag force F d received by each particle is calculated, and the total drag force information received by the particle is passed back to the DEM module;

[0108]

[0109] where Re * is the equivalent Reynolds number of the particle, ρ f is the density of the fluid where the particle is located, d is the particle diameter, vmax is the maximum settling velocity of particles in Bingham fluid, η 0 is the viscosity, ε* is the dimensionless settling velocity, Re' is the Reynolds number of particles, η * is the dimensionless apparent viscosity, θ is the separation angle, is the projection area coefficient of the separation zone, Cd is the drag coefficient of particles.

[0110] The operation of this step is the main improvement and innovation of the present invention compared with the prior art.

[0111] S25. Repeat the operations of S22 - S24 to continue the calculation of the next time step.

[0112] 4. The following uses specific cases to illustrate in detail the method described in the present invention

[0113] (1) Establish a generalized numerical model of the target channel

[0114] Take the mountainous channel to be simulated for the process of mountain flood and debris flow as the target channel. The target channel includes a debris flow formation area and a debris flow flow area that are connected to each other. The debris flow flow area has loose accumulations; according to the topographic information of the target channel and the grading information of the sediment particles in the loose accumulations, establish a generalized numerical model of the target channel in the open-source software Gmsh. When constructing the generalized numerical model of the target channel, first write the position information of the midpoint of the target channel, and the composition information of lines, surfaces, and volumes into an input file containing all necessary geometric information, and then import this input file into the open-source software Gmsh. Use the mesh module to create a mesh according to the required model dimension and save the output to obtain the generalized numerical model of the target channel. Specifically, according to the topographic information of a certain actual mountainous channel stream (target channel) and the grading information of the sediment particles in the loose accumulations, a moving-bed model of mountain flood and debris flow is established, including an upstream water tank, a debris flow formation area located upstream, and a debris flow flow area connected to it. Its schematic diagram is as Figure 5 shown. This model uses the upstream water tank to supply water. When the fluid volume in the water tank is large enough, an approximately steady-state flow can be achieved at the outlet (see reference [7]: Nie Yipin, Lan Ling, Wang Xiekang. Numerical experiments on sediment accumulation characteristics at the mountain flood gully outlet in high mountain and canyon areas [J]. Engineering Science and Technology, 2024, 56(1): 237–244., reference [8]: Wang Youbiao. Research on the impact force of debris flow on bridge piers [D]. Chengdu: Southwest Jiaotong University, 2019.). Based on the objective of the present invention, that is, to simulate the process of mountain flood and debris flow considering rheological evolution characteristics, the water stored in the upstream water tank is clear water. During the process of water flow eroding the bed surface, due to the change in sediment concentration, rheological evolution occurs, and the overall flow characteristics gradually approach those of mountain flood and debris flow. That is, this step uses the CFD-DEM coupling model to simulate the transport process of sediment particles in the generalized numerical model under the action of water flow.

[0115] In the above-mentioned debris flow mobile-bed model for mountain torrents, the gradients of both the debris flow formation area and the debris flow passage area are 5%. The lengths of the debris flow formation area located upstream and the debris flow passage area located downstream are 1.0 m and 3.0 m respectively, and the widths are both 0.2 m. In the debris flow passage area, sediment with a thickness of 0.2 m is laid as an erodible bed surface, and the particle size of the bed sediment is 20 mm (using a coarse particle model with a particle size scaling ratio of 10, equivalent to sediment particles of 2 mm).

[0116] (2) Simulation of mountain torrent debris flow process

[0117] In order to compare the influence of the rheological evolution of mountain torrent debris flow caused by considering the change in the volume sediment concentration of mountain torrent debris flow on the debris flow process during the simulation of mountain torrent debris flow, an experimental group and a control group are set up for comparison in this step, as follows:

[0118] Experimental group (simulation considering rheological evolution): After establishing the generalized numerical model of the target gully in step (1), set the initial rheological parameters of the fluid in the upstream water tank as: η 0 = 10 -3 Pa·s, τ 0 = 0 Pa, and simulate the mountain torrent debris flow process according to the method of step S2 in step 3, that is, during the simulation of mountain torrent debris flow, adjust the rheological parameters η 0 and τ 0 in real time according to the change in the volume sediment concentration Cv in different fluid grids, calculate the particle force by the semi-empirical formula of the drag coefficient shown in formula (17) obtained by the present invention, and obtain the data of the position, velocity, etc. of sediment particles changing with time in the generalized numerical model.

[0119] Control group (simulation without considering rheological evolution): After establishing the generalized numerical model of the target gully in step (1), preset the rheological parameters before the simulation of mountain torrent debris flow (set the initial parameters of the fluid in the upstream water tank as: η 0 = 10 -3 Pa·s, τ 0 = 0 Pa), and keep the rheological parameters η 0 and τ 0 unchanged regardless of how the volume sediment concentration Cv changes during the simulation. Refer to the method of step S2 in step 3 above to simulate the mountain torrent debris flow process. During the simulation, directly use the Di Felice formula built into the open-source software to calculate the drag coefficient and total drag of particles, without first calculating the equivalent Reynolds number Re *, and then the separation angle and the projected area coefficient are calculated through equations (11) and (13), and then the drag coefficient of the particles is calculated through equation (17). Finally, the data of the position, velocity, etc. of the sediment particles changing with time in the generalized numerical model are obtained by simulation.

[0120] (3) Comparison of differences in simulation results

[0121] ① Erosion characteristics of the gully bed during the movement of mountain flood debris flow

[0122] Figure 6 and Figure 7 is the evolution of the erosion characteristics of the gully bed during the movement of mountain flood debris flow. Figure 6 is the simulation result considering rheological evolution after the mountain flood debris flow contacts the particles. Figure 7 is the simulation result without considering rheological evolution after the mountain flood debris flow contacts the sediment. It can be seen from Figure 6 that when rheological evolution is considered, the mountain flood debris flow tends to move towards the bottom of the erodible bed surface after entering the erodible bed surface, and a deeper scour pit is formed at the front edge of the movable bed. Due to the rheological evolution caused by the change of the volume sediment concentration (Cv) of the mountain flood debris flow, during the downstream movement of the mixture of the mountain flood debris flow and the sediment, the energy dissipation due to viscosity increases, resulting in a decrease in the movement speed of the mountain flood debris flow. And it can be seen from Figure 7 that in the simulation without considering rheological evolution, the interaction relationship between the water flow and sediment phases remains unchanged, and the movement speed of the mountain flood debris flow is not affected by the additional viscosity caused by the change of the volume sediment concentration (Cv) of the mountain flood debris flow body. With the movement of the mountain flood debris flow, due to the decrease in the relative speed between the mountain flood debris flow and the sediment, although the volume sediment concentration (Cv) of the mountain flood debris flow is large in some fluid domains and rheological evolution occurs, the influence of the sediment particles on the movement of the mountain flood debris flow is small. At t = 5 s, regardless of whether rheological evolution is considered, the mountain flood debris flow has contacted the bottom of the movable bed area.

[0123] ② Variation characteristics of the gully bed and water surface elevation during the movement of mountain flood debris flow

[0124] Figure 8 and Figure 9 are the variation characteristics of the gully bed and water surface elevation during the movement of mountain flood debris flow. Figure 8 is the variation characteristics of the gully bed and water surface elevation during the movement of mountain flood debris flow considering rheology. Figure 9 is the variation characteristics of the gully bed and water surface elevation during the movement of mountain flood debris flow without considering rheology. It can be seen from Figures 8 - 9 that under the continuous scour of the mountain flood debris flow, scour pits with different depths and widths are formed at the front end of the movable bed area. As the simulation time prolongs, regardless of whether rheological evolution is considered, the scour pits show a trend of deepening vertically and widening along the flow path. As shown in Figure 8As shown in the figure, after the rheological evolution of the sediment on the contact bed surface of mountain torrents and debris flows, the movement resistance in the flow direction increases, and it is more inclined to move towards the bottom of the moving bed, intensifying the erosion of the underlying sediment particles, and the depth of the scouring pit at the front edge increases significantly. As Figure 9 shown, in the simulation without considering rheological evolution, the resistance of mountain torrents and debris flows in the flow direction is small, forming a scouring pit with a large length but a shallow depth. In addition, the sediment scoured and started to move forms a terrain feature similar to "sand ridges" on the bed surface. As the bed surface scouring intensifies, the mountain torrents and debris flows in the bed surface area where the "sand ridges" are located carry high-concentration sediment, enhancing the viscosity of the fluid. The decrease in the flow velocity of mountain torrents and debris flows causes sediment deposition, while the sediment deposition reduces the sediment concentration of mountain torrents and debris flows, reducing its viscosity and enhancing its sediment-carrying capacity, resulting in a gradual increase in the height of the "sand ridges" and a slow migration downstream, as Figure 8 shown. Without considering rheological evolution, the movement of sediment is restricted by its inherent properties and the relative velocity with mountain torrents and debris flows. Therefore, when mountain torrents and debris flows come into contact with the sediment on the bed surface, gravity causes the flow direction to deflect, forming a scouring pit at the front end of the moving bed and the "sand ridges" behind it. When not considering rheological evolution, the mountain torrents and debris flows crossing the "sand ridges" can still maintain a relatively high flow velocity and carry the sediment in this area downstream, causing the height of the "sand ridges" to experience a process of first increasing and then decreasing, as Figure 9 shown.

[0125] Judging from the change trend of the water surface elevation characteristics (see the water surface elevation data in Figures 8 - 9 ), when the sediment concentration of mountain torrents and debris flows changes, whether to consider rheological evolution will significantly affect the simulation results of the water surface line. As Figure 8 shown, in the simulation considering rheological evolution, the front edge of the mountain torrents and debris flows entering the moving bed area carries a large amount of sediment, concentrating its energy and forming a deeper scouring pit near the entrance. At this time, most of the sediment particles carried by the mountain torrents and debris flows move along the bed surface. The subsequent mountain torrents and debris flows entering the moving bed area cover the water flow that has entered this area, with a lower sediment concentration and viscosity, and can cross the "sand ridges" with lower energy loss, and the water surface elevation increases significantly. As Figure 9 shown, in the simulation without considering rheological evolution, the mountain torrents and debris flows scoured and formed a scouring pit with a large length but a shallow depth. The subsequent mountain torrents and debris flows are less blocked in the along-flow direction and are difficult to form a higher climb height, and the water surface elevation is also lower. However, due to less blockage in the along-flow direction, the propagation speed of the highest point of the water surface downstream is faster than the simulation result considering rheological evolution.

[0126] The simulation results of the spatial distribution of the sediment particle volume fraction in mountain torrents and debris flows at t = 2 s are as shown in Figure 10 and Figure 11 shown, where the cloud map and contour line represent the numerical values of the sediment volume fraction, Figure 10 is the simulation result considering rheological evolution, Figure 11These are the simulation results without considering rheological evolution. As Figure 10 shown, in the simulation considering rheological evolution, the sediment volume fraction is relatively high at the front of the mountain flood debris flow, while in the subsequent fluid close to the front, the sediment volume fraction is relatively low, forming a phenomenon where sediment accumulates at the front edge. As Figure 11 shown, in the simulation without considering rheological evolution, since the rheological parameters do not change, less energy is consumed due to internal viscous effects during the fluid flow process, showing a phenomenon that the movement speed of the fluid front is significantly higher than that of sediment particles, resulting in a lower sediment particle volume fraction in the front fluid and a higher sediment particle volume fraction in the subsequent fluid.

[0127] Figure 12 This is the spatial distribution of the rheological parameters of the mountain flood debris flow during the simulation process (t = 2 s). Figure (A) therein shows the spatial distribution of the yield stress τ 0 , and Figure (B) shows the spatial distribution of the viscosity η 0 . Since the relationship between the drag coefficient - equivalent Reynolds number shown in Equation (17) derived is closely related to the volume sediment concentration (Cv) of the mountain flood debris flow, the shapes of the two figures are similar. Generally speaking, the rheological parameters show an increasing trend from top to bottom in the vertical direction. This is because under non-extreme hydrodynamic conditions, most sediment particles move along the bed surface, resulting in a higher sediment content of the mountain flood debris flow near the bed surface and a significant increase in the numerical values of the rheological parameters. Figure 12 It also reveals that the mountain flood debris flow front region with a travel distance exceeding 2.5 meters has a relatively high yield stress and viscosity, indicating a high enrichment of sediment particles in this region and having the potential to cause significant damage to the surrounding environment and buildings under high-speed movement. The volume sediment concentration (Cv) of the main body region of the mountain flood debris flow decreases, and the yield stress and viscosity also decrease accordingly. However, this region has a relatively high water surface elevation, and potential inundation risks should be focused on.

[0128] From the above simulation results of the mountain flood debris flow process with or without considering rheological evolution, it can be seen that whether rheological evolution is considered in the simulation process of the mountain flood debris flow process will have an obvious different impact on the simulation results including the gully bed erosion characteristics of the mountain flood debris flow movement process and the change characteristics of the gully bed and water surface elevation of the mountain flood debris flow movement.

[0129] Since in the actual transportation process of the mountain flood debris flow, the volume sediment concentration of the mountain flood debris flow will change, which in turn leads to changes in the rheological parameters of the mountain flood debris flow. Therefore, the method described in the present invention fully considers the influence of the change in the volume sediment concentration of the mountain flood debris flow during the transportation process on the rheological characteristics of the mountain flood debris flow. By adjusting the rheological parameters of the mountain flood debris flow in real time during the simulation process, the change in the rheological parameters caused by the change in the volume sediment concentration of the mountain flood debris flow can be reflected during the simulation process, so as to more realistically simulate the spatial distribution of sediment particles during the transportation process of the mountain flood debris flow.

Claims

1. A method for simulating mountain torrent debris flow processes based on rheological evolution characteristics, characterized in that: The following steps are involved: S1, taking the hilly area channel to be simulated for the flash flood debris flow process as the target channel, the target channel includes the debris flow formation area and the debris flow flow area connected to each other, and the debris flow flow area channel has loose accumulation bodies; establishing a generalized numerical model of the target channel according to the topographic information of the target channel and the gradation information of the sediment particles of the loose accumulation bodies; S2, using CFD-DEM coupled model to simulate the transport process of sediment particles in the generalized numerical model under the action of water flow or debris flow slurry, the steps are as follows: S21, read the generalized numerical model of the target channel; S22, the DEM module executes a DEM solution loop. In the DEM solution loop, firstly, the particle neighbor list is read and the contact and collision between particles are identified, the force on each particle is calculated, and then the motion state of each particle is determined, the position and velocity of each particle are updated, and the position and velocity information of the particle is transmitted to the coupling module of the CFD-DEM coupling model; S23, passing the particle position and velocity information obtained by the DEM module to the CFD module via the coupling module of the CFD-DEM coupling model, executing a CFD solution cycle in the CFD module, solving the fluid control equation and updating the flow field information in the CFD solution cycle, and passing the flow field information to the coupling module of the CFD-DEM coupling model after the flow field converges; S24, in the coupling module of the CFD-DEM coupling model, the fluid velocity and grid porosity at the location of each particle are obtained, the relative velocity of the particle fluid is calculated, and it is determined whether the particle is located in the water flow. If the particle is located in the water flow, the rheological parameters including yield stress and viscosity are calculated according to the porosity of each grid. If the particle is located in the air, the resistance coefficient of the particle is calculated according to the DiFelice formula. For particles located in the water flow, it is determined whether the particle has started. If the particle has not started, the resistance coefficient of the particle is calculated according to the DiFelice formula. If the particle has started, the equivalent Reynolds number of the particle is calculated according to formula (4), and then the separation angle and the projected area coefficient are calculated by formulas (11) and (13), and then the resistance coefficient of the particle is calculated by formula (17); Finally, the total resistance of each particle is calculated and the total resistance information of the particle is passed back to the DEM module; In the formula, Re * is the equivalent Reynolds number of the particle, ρ f is the density of the fluid in which the particle is located, d is the particle diameter, v max is the maximum sedimentation velocity of the particle in the Bingham fluid, η0 is the viscosity, ε* is the dimensionless sedimentation velocity, Re' is the Reynolds number of the particle, η * is the dimensionless apparent viscosity, θ is the separation angle, is the projection area coefficient of the separation zone, and Cd is the resistance coefficient of the particles. S25, repeat the operations of S22 to S24 and continue the calculation of the next time step.

2. The method for simulating mountain torrent and debris flow processes based on rheological evolution characteristics according to claim 1 is characterized in that: In step S2, when the CFD-DEM coupling model is used to simulate the transport process of sediment particles in the generalized numerical model under the action of water flow, the water flow rate or debris flow slurry flow rate used is analyzed and determined based on the historical rainfall data at the target channel.

3. The method for simulating mountain torrent and debris flow processes based on rheological evolution characteristics according to claim 1 is characterized in that: In step S22, the calculation of the force on each particle refers to calculating the nonlinear elastic normal force and tangential force between particles and particles and between particles and boundaries based on the Hertzian contact theory and the Mindlin and Deresiewicz theory respectively; after determining the force on each particle, the motion state of each particle is determined according to Newton's second law.

4. The method for simulating mountain torrent and debris flow processes based on rheological evolution characteristics according to claim 1 is characterized in that: In step S23, the fluid control equations are the fluid continuity equation and the NS equation, and the PISO algorithm is used to solve the fluid control equations.

5. The method for simulating mountain torrent and debris flow processes based on rheological evolution characteristics according to any one of claims 1 to 4, characterized in that: In step S1, a generalized numerical model of the target channel is established in the open source software Gmsh according to the topographic information of the target channel and the gradation information of the sediment particles in the loose accumulation body.

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