CN111199123B - Simulation optimization method for high-concentration full-tailing thickening process - Google Patents
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Abstract
The invention discloses a simulation optimization method of a high-concentration full-tailing thickening process, which belongs to the technical field of mine filling and comprises the following steps of: 1) Preliminarily determining a high-concentration full-tailing thickening process; 2) Establishing a physical model of the thickener; 3) Calibrating simulation parameters; 4) Simulating and running a thickening process; 5) Analyzing and evaluating simulation results; 6) And (5) optimizing and determining a thickening process. The method can be used for carrying out full-size modeling on the thickening device, then combining dynamic operation parameters of the thickening device, carrying out simulation operation through Coupling of discrete elements and smooth particle fluid mechanics (Coupling of DEM-SPH), analyzing and evaluating simulation results, accurately optimizing the high-concentration tailing thickening process, meeting the requirements of high efficiency, environmental protection and economy by various indexes, effectively guiding design and industrial experiments, being beneficial to saving investment, improving efficiency and reducing cost.
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 mines into slurry and fill the slurry into the goaf, so that on one hand, the surface tailings piling is reduced or eliminated, and on the other hand, the surrounding rock deformation movement is controlled after the goaf is filled, so that the contradiction between mine resource development and safety and environmental protection can be effectively solved, and the scientific connotation of 'one waste is used for controlling two pests' is embodied. The high-concentration tailing filling is beneficial to improving the strength of the filling body and reducing the consumption of cementing materials, and provides effective technical support for mining safety, environmental protection, high efficiency and low cost. When the mill tailings are conveyed to a filling station, the initial mass concentration of the tailings is generally low, dense dehydration is needed, high-concentration underflow is obtained, and meanwhile, overflow water is clarified to meet the discharge or recycling requirements. Therefore, tailing thickening is a key element 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 used 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 dynamic thickening equipment harrow frame rotation represented by a deep cone thickener on disturbance dehydration of a compression bed; the latter test device is similar to an industrial thickener in structural form, but the scaling of the model does not strictly conform to the principle of similarity simulation, and the simulation of the tailing thickening effect under the condition of the structural size of a differential thickener cannot be satisfied. The sedimentation mathematical model established through the test can generally reflect the influence of the sand grain size grade on the sedimentation characteristics of the sand, but the accurate quantitative parameter of the dense underflow is difficult to obtain, so that the test result is not great in meaning to the design, cannot be taken as an effective basis for the design, and finally can cause poor matching of the sand material property and the dense equipment after the system is built, so that the system is required to be debugged for a long time and at high cost, and the improvement of the control level and the production efficiency of mine enterprises and the reduction of the production cost and the accident risk are not facilitated.
Aiming at the full-tailing thickening process, simulation software is adopted to carry out numerical simulation, a full-size physical model can be established, the influence of the size effect of a test device is reduced, the model structure and the input condition can be dynamically adjusted, the influence rule of each factor on the output result can be researched in multiple dimensions, the visual analysis method can help people to understand the mechanism of problem generation more deeply, provide basis for semi-industrial tests, save manpower, material resources and time required by conventional experiments, play a guiding role in the arrangement and rule discovery of the test result, and meanwhile, the quantitative optimal parameters can be obtained. In the aspect of tailing thickening, researchers do simulation of partial structure optimization of a feeding well aiming at a thickener of low-concentration materials, and unify solid particles and liquid in tailing slurry as a single continuous medium without considering sedimentation characteristics of the particles. But based on the whole process of high-concentration tailing thickening, the motion behavior characteristics of the tailing particles such as solid particle-particle friction, solid particle-wall friction, solid particle rolling friction and the like are considered, and the two-phase flow coupling calculation of solid-liquid separation under a dense phase system is performed, the thickening effect is represented through the concentration of thickening bottom flow and the solid content of overflow water, so that the technological parameters of a thickener are optimized, and related research reports are not yet seen.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a simulation optimization method for a high-concentration full-tailing thickening process, so as to accurately optimize the thickening process, scientifically guide the system design, effectively shorten the test and debugging period and reduce the accident risk and the processing cost.
The invention provides a simulation optimization method of a high-concentration full-tailing thickening process, which comprises the following steps:
s1, preliminarily determining a thickening process: according to the production capacity of a filling system, daily average tailing handling capacity, flocculant addition amount determined by basic experiments, tailing sedimentation solid flux and other data, primarily determining the tailing thickening process conditions, and calculating and primarily selecting the critical dimension of a thickener;
s2, building 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 rheological simulation result of the simulation platform with the experimental result of the rheometer to obtain physical property parameters of particles matched with the rheological parameters, and realizing simulation parameter calibration of the tailing slurry in the sedimentation process;
s4, simulation operation of the thickening process: inputting the 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 fluid mechanics (SPH), and starting the simulation of the tailing sedimentation process;
s5, analyzing and evaluating simulation results: analyzing the underflow mass concentration of the thickener, the solid content of overflow water at the upper layer, and evaluating the tailing thickening effect according to the simulation operation result of the thickener, wherein if the simulation result meets the design requirement, the simulation is ended, and 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 to perform simulation again until the result meets the design requirement, and the optimization of the thickener process is completed.
In the preferred scheme, in step S2, the physical model of the thickener is a three-dimensional physical model, so that in order to improve the subsequent flow field resolving efficiency, the structure which does not affect the settling process of the tailings can be properly model-simplified.
In a preferred embodiment, in step S3, the rheometer test is performed using a laboratory rotational rheometer.
In a preferred embodiment, in step S3, the particle physical parameters include 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.
In a preferred embodiment, 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.
In a preferred scheme, in step S4, the simulated preliminary conditions include a feeding flow rate and a rake operating speed.
In a preferred embodiment, in step S4, in the discrete element method, the contact mechanical model between each particle is composed of a normal force and a tangential force:
F＝F n +F t (I)
F＝(k n δn ij -γ n vn ij )+(k t δt ij -γ t vt ij ) (2)
wherein:
f represents the contact force between particles;
F n representing normal contact force;
F t represents tangential contact force;
k n representing the normal contact spring constant;
δn ij particle junction representing normal directionA touch overlap area;
γ n an elastoplastic damping constant representing normal contact;
vn ij representing the relative velocity of the normal direction;
k t represents the tangential contact spring constant;
δt ij represents the tangential particle contact overlap area;
γ t an elastoplastic damping constant representing tangential contact;
vt ij represents the tangential relative velocity;
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 Young's modulus, v is Poisson's ratio, δ n Is the static friction coefficient, mu r Is the rolling friction coefficient, m is the mass of the particle, R is the radius of the particle, and subscripts 1 and 2 represent two particles in contact.
In a preferred embodiment, in step S4, the continuity equation of the smooth particle fluid mechanics (SPH) is:
wherein ρ is a Is the density of the particles a, v a Is the velocity of particle a, m b Is the mass of particle b, v b Is the velocity of particle b, # W ab Representing a smooth kernel function describing the properties of the fluid between particles a and b;
the acceleration of particle a in the momentum equation in SPH is obtained:
where P is the pressure, μ is the dynamic viscosity of the particle, the calibration factor of the viscosity term of ζ, g is the gravity vector, v ab Is the relative velocity between particles a and b, r ab Is the relative position vector of particle b to particle a, η is the avoidance of r ab Singular coefficient of =0.
Further, the discrete element method and the smooth particle hydrodynamic coupling calculation method apply drag force to solid particles by liquid particles as follows:
wherein:
wherein C is d Is the drag coefficient to which the particle is subjected, ρ is the fluid density, u r Representing the relative flow velocity between the items, ε is the local fluid fraction, A ⊥ Representing the projected area of the particles in the direction of relative velocity;
the Reynolds number of the fluid is
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 simulation optimization method of the high-concentration full-tailing thickening process can simulate the complete migration behavior of the sedimentation of the tailings in a thickener, accurately obtain key parameters such as underflow concentration and overflow water solid content after the thickening of the tailings, obtain the influence rules of factors such as the feeding speed of the tailings, the structural size of the thickener and the like on the thickening effect of the tailings, and quantitatively obtain parameter characterization, and finally accurately optimize the thickening process of the tailings based on the basic properties of the tailings materials by carrying out multiple industrial tests on a computer, scientifically guide the system design, effectively shorten the test and debugging period and reduce the accident risk and the treatment cost.
The beneficial effects of the invention are as follows: compared with the existing tailings thickening process research, the invention adopts a simulation mode to model the thickening device in full size, combines dynamic operation parameters of the thickening device, performs simulation operation through fluid simulation software, finds problems in the operation process, solves the problems one by adjusting the process parameters, and accurately optimizes the high-concentration tailings thickening process, so that each index meets the requirements of high efficiency, environmental protection and economy, effectively guides design and industrial test, is beneficial to improving the efficiency and reduces the cost.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention.
Fig. 2 is a physical model of a thickener in an embodiment of the invention.
FIG. 3 is a flow chart of fluid simulation parameter calibration in an embodiment of the invention.
Fig. 4 is a schematic diagram of mass concentration distribution of slurry in a thickener according to an embodiment of the present invention.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below, and it is apparent that the described embodiments are only some embodiments, but not all embodiments of the present invention, and all other embodiments obtained by those skilled in the art without making any inventive effort based on the embodiments of the present invention are within the scope of protection of the present invention.
Examples
As shown in fig. 1, the simulation optimization method for the high-concentration full-tailing thickening process according to the embodiment of the invention comprises the following steps:
s1, preliminarily determining a high-concentration tailing thickening process. The production capacity of a mine is 400 ten thousand tons/year, the proportion of the particles with the particle size of-200 meshes is 83 percent, and the proportion of the particles with the particle size of-800 meshes is 42 percent, and the production belongs to superfine whole tailings. The mass concentration of slurry of the mill tailings entering the thickener of the filling system is 27%, and the flow is 1000m 3 And/h, determining that the initial mass concentration is 15% through a small-sized similarity test, wherein the tailing sedimentation efficiency is highest when the addition amount of the flocculant is 20g/t, and the tailing sedimentation solid flux is 0.65t/h/m 2 The thickener is primarily calculated and selected to be 26m in diameter and 5m in side wall height;
s2, 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, a three-dimensional physical model is established, as shown in figure 2, and in order to improve the subsequent model calculation efficiency, the model cancels the external ladder frame of the thickener;
s3, calibrating simulation parameters, wherein the calibrating flow is shown in figure 3. And (3) testing rheological parameters of the tailings under the condition of initial concentration by adopting 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 operation. Comparing the rheological simulation result of the simulation platform with the experimental result of the rheometer, and when the rheological simulation result and the experimental result are similar, obtaining solid particle-particle friction coefficient 0.5, solid particle-wall friction coefficient 0.3, solid particle rolling friction coefficient 0.2, initial yield stress 4Pa and flow continuity coefficient 11.6 matched with rheological parameters, so as to realize simulation parameter calibration of the tailing slurry in the sedimentation process;
and S4, simulating and running the thickening process. Setting the density of the solid particles of the feed material to 2700kg/m 3 The density of the feed liquid particles was 1000kg/m 3 The diameter of the solid particles of the feed is 40mm, and the diameter of the liquid particles of the feed is 40mm. Inputting initial simulation condition, i.e. feeding flow is 1000m 3 H, harrow rotating speed is 0.2RPM; starting DEM-SPH to perform coupling calculation, and starting simulation of the tailing sedimentation process, as shown in FIG. 4;
s5, analyzing and evaluating simulation results. According to the simulation operation result of the thickener, the mass concentration of the underflow of the thickener is 66.5%, the solid content of overflow water is 0.004%, namely 65ppm, and the process requirement is met. However, a smaller size thickener will have better economies, and whether the thickener size has an optimization space requires further investigation;
s6, optimizing a thickening process. According to simulation results, thickener models with diameters of 30m, 26m, 24m, 20m and 18m and straight wall heights of 8m are respectively established, simulation operation is carried out according to the steps, and the solid content parameters of the dense underflow concentration and the overflow water are shown in table 1. Through comprehensive comparison analysis, the thickener with the diameter of 20m can simultaneously meet the requirements of higher underflow concentration (higher than 66 percent required) and lower solid content of overflow water (lower than 200ppm required), and is determined to be the optimal thickener size. So far, the optimization of the process parameters of the thickening process is finished.
Through the process simulation based on the full-size thickening equipment, the digital industrial test is carried out, and on the premise that the underflow concentration and the solid content of overflow water of the thickener meet the requirements, the optimal size parameters of the thickener are obtained, the matching property of materials and equipment is improved, the system debugging period is greatly shortened, the investment and the processing cost are saved, and an effective basis is provided for the efficient and precise control of a filling system.
TABLE 1
| Sequence number | Thickener diameter (m) | Concentration of underflow (%) | 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 |
According to the embodiment, a deep cone thickener with the diameter of 20m is installed and adjusted in a certain mine, so that the actual use effect is good, the concentration of the underflow is basically stabilized at 66-67%, and the solid content of the overflow water is controlled within 200 ppm.
The invention and its embodiments have been described above with no limitation, and the actual construction is not limited to the embodiments of the invention as shown in the drawings. If one of ordinary skill in the art is informed by this disclosure, the structural mode and the embodiments similar to the technical scheme are not creatively designed without departing from the gist of the present invention, and all the structural modes and the embodiments belong to the protection scope of the present invention.
Claims (9)
1. The simulation optimization method of the high-concentration full-tailing thickening process is characterized by comprising the following steps of:
s1, preliminarily determining a thickening process: according to the production capacity of a filling system, daily average tailing handling capacity, flocculant addition amount and tailing sedimentation solid flux data determined by basic experiments, primarily determining a tailing thickening process condition, and calculating and primarily selecting key dimensions of a thickener;
s2, building 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 rheological simulation result of the simulation platform with the experimental result of the rheometer to obtain physical property parameters of particles matched with the rheological parameters, and realizing simulation parameter calibration of the tailing slurry in the sedimentation process;
s4, simulation operation of the thickening process: inputting the 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 and smooth particle fluid mechanics, and starting simulation of a tailing sedimentation process;
s5, analyzing and evaluating simulation results: analyzing the underflow mass concentration of the thickener, the solid content of overflow water at the upper layer, and evaluating the tailing thickening effect according to the simulation operation result of the thickener, wherein if the simulation result meets the design requirement, the simulation is ended, and 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 to perform simulation again until the result meets the design requirement, and the optimization of the thickener process is completed.
2. The simulation optimization method of the high-concentration whole-tailing thickening process according to claim 1, wherein in the step S2, the thickener physical model is a three-dimensional physical model.
3. The method for optimizing the simulation of the high-concentration whole-tailing thickening process according to claim 1, wherein in the step S3, the rheometer experiment is performed by using a laboratory rotary rheometer.
4. The method for optimizing the simulation of the high-concentration whole tailings densification process according to claim 1, wherein in the step S3, the particle physical parameters include solid particle-particle friction coefficient, solid particle-wall friction coefficient, solid particle rolling friction coefficient, initial yield stress and flow continuity coefficient.
5. The method for optimizing the simulation of the high-concentration whole tailings densification process of claim 1 wherein in step S4, the basic physical properties of the packing material include solid particle density, liquid particle density, solid particle size, and liquid particle size.
6. The method for optimizing the simulation of the high-concentration whole-tailings thickening process according to claim 1, wherein in the step S4, the simulated preliminary conditions comprise feeding flow and harrow operation rotation speed.
7. The method for optimizing the simulation of the high-concentration whole-tailing thickening process according to claim 1, wherein in the step S4, the discrete element method, the contact mechanics model between each particle consists of a normal force and a tangential force:
F＝F n +F t (1)
F＝(k n δn ij -γ n vn ij )+(k t δt ij -γ t vt ij ) (2)
wherein:
f represents the contact force between particles;
F n representing normal contact force;
F t represents tangential contact force;
k n representing the normal contact spring constant;
δn ij representing the normal particle contact overlap area;
γ n an elastoplastic damping constant representing normal contact;
vn ij representing the relative velocity of the normal direction;
k t represents the tangential contact spring constant;
δt ij represents the tangential particle contact overlap area;
γ t an elastoplastic damping constant representing tangential contact;
vt ij represents the tangential relative velocity;
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 Young's modulus, v is Poisson's ratio, δ n Is the coefficient of static friction, m is the mass of the particle, R is the radius of the particle, and subscripts 1 and 2 represent two particles in contact.
8. The method for optimizing the simulation of the high-concentration whole-tailing thickening process according to claim 1, wherein in the step S4, the continuity equation of the smooth particle fluid mechanics is:
wherein ρ is a Is the density of the particles a, v a Is the velocity of particle a, m b Is the mass of particle b, v b Is the velocity of particle b, # W ab Representing a smooth kernel function describing the properties of the fluid between particles a and b;
the acceleration of particle a in the momentum equation of the smooth particle hydrodynamic form is obtained:
where P is the pressure, μ is the dynamic viscosity of the particle, the calibration factor of the viscosity term of ζ, g is the gravity vector, v ab Is the relative velocity between particles a and b, r ab Is the relative position vector of particle b to particle a, η is the avoidance of r ab Singular coefficient of =0.
9. The simulation optimization method of the high-concentration full-tailing thickening process according to claim 1, wherein the discrete element method and the smooth particle fluid mechanical coupling calculation method apply drag force from liquid particles to solid particles as follows:
wherein:
wherein C is d Is the drag coefficient to which the particle is subjected, ρ is the fluid density, u r Representing the relative flow velocity between the items, ε is the local fluid fraction, A ⊥ Representing the projected area of the particles in the direction of relative velocity;
the Reynolds number of the fluid is
Where r is the spherical radius of the particle and μ is the dynamic viscosity of the fluid. />
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