CN111199123A - Simulation optimization method for high-concentration full-tailing thickening process - Google Patents
Simulation optimization method for high-concentration full-tailing thickening process Download PDFInfo
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Abstract
The invention discloses a simulation optimization method for a high-concentration full-tailings thickening process, which belongs to the technical field of mine filling and comprises the following steps: 1) preliminarily determining a high-concentration full-tailing thickening process; 2) establishing a physical model of the thickener; 3) calibrating simulation parameters; 4) carrying out simulation operation in a thickening process; 5) analyzing and evaluating a simulation result; 6) and optimizing and determining the thickening process. By adopting the method, full-scale modeling can be carried out on the thickening device, then simulation operation is carried out by combining with dynamic operation parameters of the thickening machine and by Coupling discrete elements with smooth particle hydromechanics (Coupling of DEM-SPH), simulation results are analyzed and evaluated, the high-concentration tailing thickening process is accurately optimized, various indexes meet the requirements of high efficiency, environmental protection and economy, design and industrial tests are effectively guided, investment is saved, efficiency is improved, and cost is reduced.
Description
Technical Field
The invention belongs to the technical field of mine filling, and particularly relates to a simulation optimization method for a high-concentration full-tailing thickening process.
Background
The filling mining method can prepare tailings generated by a mine into slurry and fill the slurry to a goaf, so that the stockpiling of surface tailings is reduced or eliminated, and the deformation and movement of surrounding rocks after the goaf is filled are controlled, so that the contradiction between mine resource development and safety and environmental protection can be effectively solved, and the scientific connotation of 'treating two hazards by one waste' is reflected. The high-concentration tailing filling is beneficial to improving the strength of a filling body and reducing the consumption of cementing materials, and provides effective technical support for safe, environment-friendly, efficient and low-cost mining of mines. When the tailings from the plant selection are conveyed to a filling station, the initial mass concentration of the tailings is generally low, and the tailings need to be thickened and dehydrated to obtain high-concentration underflow, and meanwhile, overflow water is clarified to meet the requirements of discharge or recycling. Therefore, the tailing concentration is the core link of the whole filling system.
The tailing thickening process is a complex dynamic process, the thickening effect is influenced by the combined action of multiple factors, and the most widely applied research methods at present are a static sedimentation test and a dynamic flocculation sedimentation test. The former greatly simplifies the test process and ignores the influence of the rotation of a dynamic thickening equipment rake frame represented by a deep cone thickener on the disturbed dehydration of a compression bed; although the latter test device is similar to an industrial thickener in structural form, the scaling of the model does not strictly accord with the principle of similar simulation, and the similar simulation of the tailing thickening effect under the condition of the structural size of the differential thickener can not be met. The settlement mathematical model established through the test can usually reflect the influence of the tailing particle size grade on the settlement characteristic to a certain extent, but is difficult to obtain accurate quantitative parameters of the dense underflow, so the test result is often of little guiding significance to the design and can not be used as an effective basis for the design, finally, the poor matching between the tailing material property and the dense equipment after the system is built can be caused, long-time and high-cost system debugging is needed, and the mine enterprise is not favorable for improving the control level and the production efficiency and reducing the production cost and the accident risk.
Aiming at the full-tailings thickening process, the simulation software is adopted for numerical simulation, a full-size physical model can be established, the influence of the size effect of the test device is reduced, the structure and the input condition of the model can be dynamically adjusted, the influence rule of each factor on the output result can be studied in multiple dimensions, the visual analysis method can help people to understand the mechanism of problem generation more deeply, the basis is provided for semi-industrial tests, the manpower, material resources and time required by conventional tests are saved, the guidance effect on test result arrangement and rule discovery is achieved, and meanwhile, the quantitative optimal parameters can be obtained. In the tail sand thickening aspect, researchers do simulation of optimization of a local structure of a feed well aiming at a thickener for low-concentration materials, and uniformly regard solid particles and liquid in tail sand slurry as a single continuous medium without considering the sedimentation characteristic of the particles. However, based on the whole process of high-concentration tailing thickening, the movement behavior characteristics of tailing particles such as solid particle-particle friction, solid particle-wall surface friction and solid particle rolling friction are considered at the same time, and two-phase flow coupling calculation of solid-liquid separation under a concentrated phase system is also considered, and the thickening effect is represented through the concentration of thickening underflow and the solid content of overflow water, so that the process parameters of the thickener are optimized, and no relevant research report is found at present.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a simulation optimization method of a high-concentration full-tailings thickening process, so as to accurately optimize the thickening process, scientifically guide system design, effectively shorten the test and debugging period and reduce the accident risk and the treatment cost.
The invention provides a simulation optimization method for a high-concentration full-tailing thickening process, which comprises the following steps of:
step S1, preliminarily determining a thickening process: preliminarily determining tailing thickening process conditions according to the production capacity of a filling system, daily average tailing treatment capacity, and data such as flocculant addition amount, tailing sedimentation solid flux and the like determined by a basic experiment, and calculating and preliminarily selecting the key size of a thickener;
s2, establishing a physical model: establishing a physical model of the thickener according to the calculated key size of the thickener and the physical equipment structure of the industrial thickener;
s3, calibrating simulation parameters: comparing the simulation result of the simulation platform with the experiment result of the rheometer to obtain the physical property parameters of the particles matched with the rheological parameters, thereby realizing the simulation parameter calibration of the tailings slurry in the sedimentation process;
s4, simulation operation of a thickening process: inputting basic physical properties of the filling material and simulation parameters of the solid-liquid two-phase flow slurry into a simulation platform, setting simulation initial conditions, performing coupling calculation by adopting a Discrete Element Method (DEM) and Smooth Particle Hydrodynamics (SPH), and starting simulation of the tailing sedimentation process;
s5, simulation result analysis and evaluation: analyzing mass concentration of underflow of the thickener and solid content of overflow water on the upper layer according to a simulation operation result of the thickener, evaluating the tailing thickening effect, and finishing simulation if the simulation result meets the design requirement, wherein the input condition and the output result of the simulation are parameters of a high-concentration tailing thickening process;
s6, optimizing and determining a thickening process: if the simulation result does not meet the design requirement, the structural size parameters of the thickener can be changed, and the simulation is carried out again until the result meets the design requirement, so that the optimization of the thickening process is completed.
Preferably, in step S2, the thickener physical model is a three-dimensional physical model, and in order to improve the subsequent flow field calculation efficiency, the model of the structure that does not affect the tailing sedimentation process may be appropriately simplified.
Preferably, in step S3, the rheometer test is performed using a laboratory rotational rheometer.
Preferably, in step S3, the particle property parameters include a solid particle-to-particle friction coefficient, a solid particle-to-wall friction coefficient, a solid particle rolling friction coefficient, an initial yield stress, and a flow continuity coefficient.
Preferably, in step S4, the basic physical properties of the filling material include solid particle density, liquid particle density, solid particle size and liquid particle size.
Preferably, in step S4, the simulation preliminary conditions include a feed flow rate and a rake operating speed.
Preferably, in step S4, in the discrete element method, the contact mechanical model between the particles is composed of a normal force and a tangential force:
F＝Fn+Ft(I)
F＝(knδnij-γnvnij)+(ktδtij-γtvtij) (2)
in the formula:
f represents the interparticle contact force;
Fnrepresenting a normal contact force;
Ftrepresenting the tangential contact force;
knrepresents the normal contact elastic constant;
δnijindicates the normal particle contact overlap area;
γnrepresents the elasto-plastic damping constant of normal contact;
vnijrepresents the relative velocity of the normal direction;
ktrepresents the tangential contact elastic constant;
δtijrepresents the tangential particle contact overlap area;
γtrepresents the elasto-plastic damping constant of the tangential contact;
vtijrepresenting the relative velocity of the tangential direction;
the coefficients of the contact mechanics model can be calculated by the following formula:
wherein:
in the above expression, e is the elastic recovery coefficient, Y is the Young's modulus, v is the Poisson's ratio, δnIs the coefficient of static friction, murIs the coefficient of rolling friction, m is the mass of the particle, R is the radius of the particle, and subscripts 1 and 2 represent the two particles in contact.
Preferably, in step S4, the continuous equation of the Smooth Particle Hydrodynamics (SPH) is:
where ρ isaIs the density of the particles a, vaIs the velocity of the particle a, mbIs the mass of the particles b, vbIs the velocity of the particles b, ▽ WabRepresenting a smooth kernel function describing properties of a fluid between particle a and particle b;
the acceleration of particle a in the momentum equation in the form of SPH is obtained:
where P is pressure, μ is the kinetic viscosity of the particle, a calibration factor for the viscosity term of ξ, g is the gravity vector, vabIs the relative velocity between particles a and b, rabIs the relative position vector of particle b to particle a, η is to avoid rabA singularity coefficient of 0.
Further, in the discrete element method and the smooth particle hydrodynamics coupling calculation method, the drag force applied to the solid particle by the liquid particle is as follows:
wherein:
in the formula, CdIs the drag coefficient experienced by the particle, ρ is the fluid density, urRepresenting the relative flow rates between the items, ε being the local fluid fraction, A⊥Representing the projected area of the particle in the direction of the relative velocity;
reynolds number of the fluid
Where r is the spherical radius of the particle and μ is the dynamic viscosity of the fluid.
The principle of the invention is as follows: the invention relates to a simulation optimization method for a high-concentration full-tailing thickening process, which can simulate the complete migration behavior of tailing sedimentation in a thickener, accurately obtain key parameters such as underflow concentration and overflow water solid content after thickening of the tailing, simultaneously obtain the influence rule of factors such as tailing feeding speed and thickener structure size on the tailing thickening effect and quantitative parameter representation, and finally carry out accurate optimization on the thickening process based on the basic properties of the tailing materials by carrying out multiple times of industrial tests on a computer, scientifically guide system design, effectively shorten the test and debugging period and reduce accident risk and treatment cost.
The invention has the beneficial effects that: compared with the existing research on the tailing thickening process, the method adopts an analog simulation mode to carry out full-scale modeling on the thickening device, then combines dynamic operation parameters of the thickening machine, carries out simulation operation through fluid simulation software, finds problems in the operation process, solves the problems one by adjusting the process parameters, accurately optimizes the high-concentration tailing thickening process, meets the requirements of high efficiency, environmental protection and economy for each index, effectively guides design and industrial tests, is favorable for improving the efficiency and reducing the cost.
Drawings
FIG. 1 is a schematic flow chart of an embodiment of the present invention.
Fig. 2 is a thickener physical model in an embodiment of the invention.
FIG. 3 is a flow chart of calibration of fluid simulation parameters according to an embodiment of the present invention.
FIG. 4 is a schematic view of the mass concentration profile of the slurry in the thickener in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and all other embodiments obtained by those skilled in the art without any creative work based on the embodiments of the present invention belong to the protection scope of the present invention.
Examples
As shown in fig. 1, a simulation optimization method for a high-concentration full tailings thickening process in an embodiment of the present invention includes the following steps:
step S1, preliminarily determining a high-concentration tailing thickening process. The production capacity of a certain mine is 400 ten thousand tons per year, the proportion of full tailings to 200-mesh particles is 83 percent, and the proportion of-800-mesh particles is 42 percent, and the mine belongs to superfine full tailings. The tailings from the plant selection enter the thickener of the filling systemThe mass concentration of the slurry is 27 percent, and the flow rate is 1000m3Determining that the initial mass concentration is 15 percent and the tailing sedimentation efficiency is highest when the addition amount of the flocculating agent is 20g/t and the tailing sedimentation solid flux is 0.65t/h/m through a small-scale similarity test2The initial calculation and selection of the thickener are that the diameter is 26m and the height of the side wall is 5 m;
and S2, establishing a physical model of the thickener. Establishing a three-dimensional physical model according to the calculated key size of the thickener and the physical equipment structure of the industrial thickener, and canceling an external ladder frame of the thickener by the model in order to improve the subsequent model resolving efficiency as shown in figure 2;
and S3, calibrating simulation parameters, wherein the calibration process is as shown in the figure 3. And testing rheological parameters of the tailings under the condition of initial concentration by using a rheometer, and simultaneously establishing a container and rotor model with the same specification as that of a rheological experiment in a DEM simulation platform and simulating to run. Comparing the simulation platform rheological simulation result with the rheometer experiment result, and obtaining a solid particle-particle friction coefficient of 0.5, a solid particle-wall surface friction coefficient of 0.3, a solid particle rolling friction coefficient of 0.2, an initial yield stress of 4Pa and a flow continuity coefficient of 11.6 which are matched with the rheological parameters when the simulation platform rheological simulation result is approximate to the rheometer experiment result, so as to realize the simulation parameter calibration of the tailing slurry in the sedimentation process;
and S4, simulating and operating the thickening process. The density of the fed solid particles was set to 2700kg/m3The density of the feed liquid particles is 1000kg/m3The diameter of the solid particles of the feed is 40mm, and the diameter of the particles of the liquid of the feed is 40 mm. Inputting the simulation initial condition that the feed flow is 1000m3The rotation speed of the rake frame is 0.2 RPM; starting the DEM-SPH to perform coupling calculation, and starting the simulation of the tailing sedimentation process, as shown in FIG. 4;
and S5, analyzing and evaluating a simulation result. According to the simulation operation result of the thickener, the mass concentration of the underflow of the thickener is 66.5 percent, the solid content of the overflow water is 0.004 percent, namely 65ppm, and the process requirement is met. However, smaller size thickeners will have better economics, and whether there is room for optimization in thickener size will require further investigation;
and S6, optimizing the thickening process. According to simulation results, thickener models with the diameters of 30m, 26m, 24m, 20m and 18m and the heights of the vertical walls of 8m are respectively established, simulation operation is carried out according to the steps, and the concentration of the thickened underflow and the solid content of the overflow water are shown in table 1. Through comprehensive comparison and analysis, the thickener with the diameter of 20m can simultaneously meet the requirements of higher underflow concentration (required to be higher than 66%) and lower overflow water solid content (required to be lower than 200ppm), and is determined to be the optimal size of the thickener. And finishing the optimization of the process parameters of the thickener.
Through the process simulation based on the full-size thickening equipment, the digital industrial test is carried out, the optimal size parameters of the thickening machine are obtained on the premise that the underflow concentration and the solid content of overflow water meet the requirements, the matching performance of materials and the equipment is improved, the system debugging period is greatly shortened, the investment and the treatment cost are saved, and an effective basis is provided for the high-efficiency thickening accurate control of a filling system.
TABLE 1
| Serial number | Thickener diameter (m) | Underflow concentration (%) | Solid content (ppm) of overflow water |
| 1 | 30 | 66.8 | 40 |
| 2 | 26 | 66.5 | 65 |
| 3 | 24 | 66.4 | 88 |
| 4 | 20 | 66.3 | 120 |
| 5 | 18 | 64.1 | 268 |
The embodiment shows that a certain mine has good practical use effect by installing and debugging a deep cone thickener with the diameter of 20m, the concentration of underflow is basically stabilized at 66-67%, and the solid content of overflow water is controlled within 200 ppm.
The present invention and its embodiments have been described above, and the description is not intended to be limiting, and the drawings are only one embodiment of the present invention, and the actual configuration is not limited thereto. Without departing from the spirit of the invention, it is within the scope of the invention to suggest and appreciate that structural embodiments and examples similar to the technical solutions can be devised without inventing.
Claims (9)
1. A simulation optimization method for a high-concentration full-tailings thickening process is characterized by comprising the following steps:
step S1, preliminarily determining a thickening process: preliminarily determining tailing thickening process conditions according to the production capacity of a filling system, daily average tailing treatment capacity, and data such as flocculant addition amount, tailing sedimentation solid flux and the like determined by a basic experiment, and calculating and preliminarily selecting the key size of a thickener;
s2, establishing a physical model: establishing a physical model of the thickener according to the calculated key size of the thickener and the physical equipment structure of the industrial thickener;
s3, calibrating simulation parameters: comparing the simulation result of the simulation platform with the experiment result of the rheometer to obtain the physical property parameters of the particles matched with the rheological parameters, thereby realizing the simulation parameter calibration of the tailings slurry in the sedimentation process;
s4, simulation operation of a thickening process: inputting basic physical properties of the filling material and simulation parameters of the solid-liquid two-phase flow slurry into a simulation platform, setting simulation initial conditions, performing coupling calculation by adopting a Discrete Element Method (DEM) and Smooth Particle Hydrodynamics (SPH), and starting simulation of the tailing sedimentation process;
s5, simulation result analysis and evaluation: analyzing mass concentration of underflow of the thickener and solid content of overflow water on the upper layer according to a simulation operation result of the thickener, evaluating the tailing thickening effect, and finishing simulation if the simulation result meets the design requirement, wherein the input condition and the output result of the simulation are parameters of a high-concentration tailing thickening process;
s6, optimizing and determining a thickening process: if the simulation result does not meet the design requirement, the structural size parameters of the thickener can be changed, and the simulation is carried out again until the result meets the design requirement, so that the optimization of the thickening process is completed.
2. The simulation optimization method for the high-consistency full tailings thickening process of claim 1, wherein in step S2, the thickener physical model is a three-dimensional physical model.
3. The simulation optimization method for the high-concentration full tailings thickening process according to claim 1, wherein in step S3, the rheometer experiment is performed by using a laboratory rotational rheometer.
4. The simulation optimization method for the high-concentration full tailings thickening process of claim 1, wherein in step S3, the particle physical parameters comprise a solid particle-particle friction coefficient, a solid particle-wall friction coefficient, a solid particle rolling friction coefficient, an initial yield stress and a flow continuity coefficient.
5. The simulation optimization method for the high-consistency full tailings concentration process of claim 1, wherein in step S4, the basic physical properties of the filling material comprise solid particle density, liquid particle density, solid particle size and liquid particle size.
6. The simulation optimization method for the high-consistency full tailings thickening process of claim 1, wherein in step S4, the simulation preliminary conditions comprise a feed flow rate and a rake operating speed.
7. The simulation optimization method for the high-consistency full tailings thickening process according to claim 1, wherein in step S4, the discrete element method, the contact mechanical model between each particle, is composed of a normal force and a tangential force:
F＝Fn+Ft(1)
F＝(knδnij-γnvij)+(ktδtij-γtvtij) (2)
in the formula:
f represents the interparticle contact force;
Fnrepresenting a normal contact force;
Ftrepresenting the tangential contact force;
knrepresents the normal contact elastic constant;
δnijindicates the normal particle contact overlap area;
γnrepresents the elasto-plastic damping constant of normal contact;
vnijrepresents the relative velocity of the normal direction;
ktrepresents the tangential contact elastic constant;
δtijrepresents the tangential particle contact overlap area;
γtindicating tangential connectionsElastic-plastic damping constant of touch;
vtijrepresenting the relative velocity of the tangential direction;
the coefficients of the contact mechanics model can be calculated by the following formula:
wherein:
in the above expression, e is the elastic recovery coefficient, Y is the Young's modulus, v is the Poisson's ratio, δnIs the coefficient of static friction, murIs the coefficient of rolling friction, m is the mass of the particle, R is the radius of the particle, and subscripts 1 and 2 represent the two particles in contact.
8. The simulation optimization method for the high-consistency full tailings thickening process of claim 1, wherein in step S4, the continuity equation of the Smooth Particle Hydrodynamics (SPH) is:
where ρ isaIs the density of the particles a, vaIs the velocity of the particle a, mbIs the mass of the particles b, vbIs the velocity of the particles b and is,
representing a smooth kernel function describing properties of a fluid between particle a and particle b;
the acceleration of particle a in the momentum equation in the form of SPH is obtained:
where P is pressure, μ is the kinetic viscosity of the particle, a calibration factor for the viscosity term of ξ, g is the gravity vector, vabIs the relative velocity between particles a and b, rabIs the relative position vector of particle b to particle a, η is to avoid rabA singularity coefficient of 0.
9. The simulation optimization method for the high-concentration full-tailings thickening process of claim 1, wherein in the discrete element method and the smooth particle hydrodynamics coupling calculation method, the drag force applied to the solid particles by the liquid particles is as follows:
wherein:
in the formula, CdIs the drag coefficient experienced by the particle, ρ is the fluid density, urRepresenting the relative flow rates between the items, ε being the local fluid fraction, A⊥Representing the projected area of the particle in the direction of the relative velocity;
reynolds number of the fluid
Where r is the spherical radius of the particle and μ is the dynamic viscosity of the fluid.
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