A method for predicting paste flow slope angle in a long and narrow access

Abstract

The application discloses a kind of long approach in paste flow slope angle prediction method, belong to filling technical field, solve the prediction of filling slope angle in prior art is based on experience formula or static homogeneous model, unable to consider the influence of waste rock dynamic settlement on slurry flow resistance and slope form Problem, the method includes based on paste raw material basic parameter construction paste similarity model, based on range analysis combined with interaction analysis influencing factor on the influence degree of flow slope angle, convert flow slope angle calculation model into slope angle satisfaction function, obtain slope angle optimal filling parameter;The present application can comprehensively study the influence of multiple influencing factors and their interaction on paste flow slope angle through the pre-design and implementation of orthogonal experiment scheme, avoids the one-sidedness that single factor analysis may bring, makes the influence law obtained more comprehensive and in-depth, and is different from the homogeneous flow model or simplified discrete element model that the existing numerical simulation method is mostly used.

Description

Technical Field

[0001] This invention belongs to the field of filling technology, specifically relating to a method for predicting the slope angle of paste flow in a narrow passage. Background Technology

[0002] Against the backdrop of ever-increasing global demand for mineral resources, shallow mineral resources are gradually becoming depleted, making deep ore body mining an inevitable trend in the mining industry. Compared with shallow mining, deep ore body mining faces many challenges, among which the requirements for the quality of backfill materials are significantly higher. In this context, the whole tailings-waste rock paste backfill technology has been widely used in mining due to its advantages of being safer, more environmentally friendly, and more economical. This technology adds waste rock as coarse aggregate to the backfill slurry to prepare a paste, which is then filled into the underground goaf, effectively improving the safety, environmental friendliness, and economy of backfilling operations.

[0003] Currently, research on slurry flow in stopes is mostly focused on stopes with small aspect ratios, with limited studies on slurry flow in long and narrow stopes. Furthermore, research on tailings-waste gypsum backfilling technology primarily concentrates on static slurry mix optimization, strength characterization, and flow characteristic analysis, while studies on the migration patterns of waste rock particles, slurry stratification behavior, and slope angle evolution mechanisms during dynamic backfilling are severely lacking. Existing technologies often predict backfill slope angles based on empirical formulas or static homogeneous models, failing to consider the impact of dynamic waste rock settling on slurry flow resistance and slope morphology. Moreover, during backfilling in long and narrow access routes, slurry flow exhibits typical non-Newtonian fluid characteristics and particulate two-phase flow features, with flow resistance dynamically coupled by waste rock particle size distribution, concentration gradient, and flow velocity. Existing numerical simulation methods often employ homogeneous flow models or simplified discrete element models, which cannot accurately reflect the settling, collision, and spatial distribution patterns of waste rock particles during flow, leading to a significant disconnect between predicted slope angles and actual engineering conditions. To address the above issues, we propose a method for predicting the slope angle of gypsum flow in narrow and elongated pathways. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by providing a method for predicting the slope angle of paste flow in narrow passages. This method solves the problem that existing technologies often rely on empirical formulas or static homogeneous models to predict the slope angle of filling, failing to consider the impact of dynamic sedimentation of waste rock on the flow resistance of slurry and the slope morphology.

[0005] This invention is implemented as follows: a method for predicting the slope angle of gypsum flow in a narrow and elongated path, the method comprising:

[0006] S10, Obtain the raw materials for the paste, conduct physical experiments on the raw materials for the paste to obtain the basic parameters of the raw materials for the paste;

[0007] S20, Load the basic parameters of the paste raw materials, construct a paste similarity model based on the basic parameters of the paste raw materials, pre-design an orthogonal experimental scheme, mix the paste raw materials based on the orthogonal experimental scheme, add water-reducing agent to prepare paste slurry, inject the paste slurry into the paste similarity model to simulate the experiment, and obtain the simulation experimental results;

[0008] S30, Load the simulation experiment results, and based on the range analysis combined with the interaction analysis, analyze the degree of influence of the influencing factors on the flow slope angle to obtain the multi-factor influence analysis results;

[0009] S40 sets the target constraint for the flow slope angle. Based on the target constraint for the flow slope angle and the results of multi-factor influence analysis, the flow slope angle calculation model is obtained. The flow slope angle calculation model is then converted into a slope angle satisfaction function to obtain the optimal filling parameters for the slope angle.

[0010] Preferably, the method for physical experimental measurement of the raw materials for the paste includes:

[0011] S101, Obtain paste raw materials and conduct physicochemical property tests on the paste raw materials. The physicochemical property tests include moisture content specific gravity, loose / compact bulk density, porosity, and particle size distribution tests. The paste raw materials include tailings, waste rock, and water-reducing agent.

[0012] S102, the particle size analysis of the tailings in the paste raw material was performed using a laser particle size analyzer, and the particle size analysis results of the tailings were obtained.

[0013] S103, the particle size of waste rock was analyzed by sieving test, and the particle size analysis results of waste rock were obtained.

[0014] Preferably, the method for constructing a paste similarity model based on the basic parameters of the paste raw materials includes:

[0015] S201, based on the actual mining area size, a similarity model of the paste with a narrow and long approach is made to recreate the actual mining area at a similarity ratio of 1:40.

[0016] S202, the similar model of the paste is raised by 20mm to prevent the paste from overflowing;

[0017] Preferably, when designing the orthogonal experimental scheme, the experimental influencing factors and levels are determined. The experimental influencing factors are mass concentration, water-reducing agent dosage, and waste rock dosage, and three levels are set for each of the experimental influencing factors.

[0018] Preferably, the method for analyzing the influence of factors on the flow slope angle based on range analysis combined with interaction analysis includes:

[0019] S301, Load the simulation experiment results, and use the range analysis method to analyze the simulation experiment results, and analyze the influence of mass concentration, water reducing agent dosage, and waste rock dosage on yield stress, K value, bleeding rate, and deposition slope angle SSA.

[0020] S302, based on the simulation experimental results, establish a multivariate nonlinear regression model between yield stress, K value, BR, SSA and MC, WAD, WRD;

[0021] S303 uses Origin numerical processing software and a multiple linear regression model to construct a three-dimensional visualization model of yield stress, K value, BR, and SSA.

[0022] S304 obtains a three-dimensional visualization model of yield stress, K value, BR, and SSA. Combines the three-dimensional visualization model of yield stress, K value, BR, and SSA to analyze the interaction effect between influencing factors and obtain the results of multi-factor influence analysis.

[0023] Preferably, the method for obtaining the flow slope angle calculation model based on the target constraint of the flow slope angle and the results of multi-factor influence analysis includes:

[0024] S401 defines the optimal range of the flow slope angle based on engineering specifications, with the optimal range of the flow slope angle as the target constraint;

[0025] S402, Apply the target constraint of the flow slope angle, and obtain the flow slope angle calculation model based on the target constraint of the flow slope angle and the results of multi-factor influence analysis;

[0026] S403 sets weighting factors to transform multi-objective optimization problems into single-objective optimization problems and converts the flow slope angle calculation model into a slope angle satisfaction function.

[0027] S404, based on the weighted geometric mean method, treats response variables as equally important and calculates the overall satisfaction function of the flow slope angle;

[0028] S405. Using MATLAB software, the overall satisfaction function is solved, the extreme value of the overall satisfaction function is found, and the optimal filling parameters for the slope angle are obtained.

[0029] Compared with the prior art, the embodiments of this application have the following main advantages:

[0030] In this invention embodiment, a comprehensive research system is formed, encompassing multiple stages from acquiring basic raw material parameters, constructing similar models, designing and implementing orthogonal experiments, to range analysis and interaction analysis. Through the pre-design and implementation of orthogonal experimental schemes, the influence of multiple factors and their interactions on the slope angle of slurry flow can be comprehensively studied, avoiding the one-sidedness that may result from single-factor analysis. This leads to a more comprehensive and in-depth understanding of the influence patterns. Unlike existing numerical simulation methods that often use homogeneous flow models or simplified discrete element models, this method obtains the basic parameters of the slurry raw materials through physical experiments and then constructs a slurry similarity model based on these parameters for experimentation. This approach, combining actual physical experiments with similarity simulation, can more realistically reflect the sedimentation, collision, and spatial distribution patterns of waste rock particles in the flow, greatly improving the accuracy and reliability of the prediction results and effectively solving the problem of the disconnect between existing methods' predicted slope angles and actual engineering conditions.

[0031] This invention provides a method for analyzing the influence of factors on the flow slope angle based on range analysis combined with interaction analysis. Using range analysis, the influence of factors such as mass concentration, water-reducing agent dosage, and waste rock dosage on yield stress, K-value, bleeding rate, and sedimentary slope angle (SSA) can be accurately quantified. This helps identify key factors that significantly affect the flow slope angle, providing a clear direction and focus for subsequent optimization work. Analysis reveals an inherent correlation between the yield stress of the paste and its mass concentration, and a negative correlation with the water-reducing agent dosage and waste rock dosage. These patterns provide a theoretical basis for understanding the flow characteristics of paste and the slope angle formation mechanism, deepening the understanding of the paste filling process. Furthermore, based on a three-dimensional visualization model, the flow slope angle under different parameter combinations can be predicted more accurately, providing a scientific basis for paste filling operations in actual mine production. By inputting specific parameters such as mass concentration, water-reducing agent dosage, and waste rock dosage, the model predicts the corresponding flow slope angle, thereby guiding construction personnel to adjust the mix ratio of filling slurry and filling process to optimize filling effect and improve filling quality and efficiency.

[0032] This invention provides a method for obtaining a flow slope angle calculation model based on the target constraint of the flow slope angle and the results of multi-factor influence analysis. The optimal range of the flow slope angle is defined based on engineering specifications, providing clear and quantifiable target constraints for optimization. This helps ensure that the optimized flow slope angle meets actual engineering needs and specification requirements, avoiding optimization results that do not conform to engineering reality, and improving the targeting and practicality of the optimization. By setting weighting factors, the multi-objective optimization problem is transformed into a single-objective optimization problem, that is, the flow slope angle calculation model is converted into a slope angle satisfaction function. This transformation method simplifies the complexity of the optimization problem, enabling the finding of a balance point among multiple interrelated objectives, facilitating subsequent solution using optimization algorithms, and improving optimization efficiency. Using MATLAB software to solve the overall satisfaction function can efficiently find the extreme value of the overall satisfaction function, thereby obtaining the optimal filling parameters for the slope angle. MATLAB software has powerful numerical calculation and optimization functions, which can quickly and accurately solve complex optimization models, providing strong technical support for practical engineering applications, making this method highly practical and operable. Attached Figure Description

[0033] Figure 1 The results show the effects of mass concentration, water-reducing agent dosage, and waste rock dosage on yield stress.

[0034] Figure 2 The effects of mass concentration, water-reducing agent dosage, and waste rock dosage on the K value are shown.

[0035] Figure 3 The results show the effects of mass concentration, water-reducing agent dosage, and waste rock dosage on the bleeding rate.

[0036] Figure 4 The results show the effects of mass concentration, water-reducing agent dosage, and waste rock dosage on the deposition slope angle.

[0037] Figure 5 The diagram illustrates the effects of MC-WAD interaction, MC-WRD interaction, and WAD-WRD interaction on the deposition slope angle. Detailed Implementation

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0039] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0040] Existing numerical simulation methods mostly employ homogeneous flow models or simplified discrete element models, which cannot accurately reflect the settling, collision, and spatial distribution patterns of waste rock particles during flow, leading to a significant discrepancy between predicted slope angles and actual engineering conditions. To address this issue, we propose a method for predicting the slope angle of slurry flow in narrow pathways. In short, the method first involves physical experiments to measure the basic parameters of the slurry raw materials. Then, a similar model of the slurry is constructed based on these parameters. An orthogonal experimental scheme is pre-designed. Based on this scheme, the slurry raw materials are mixed, and a water-reducing agent is added to prepare a slurry. This slurry is injected into the similar model to simulate the experiment, obtaining the simulation results. Range analysis combined with interaction analysis is used to analyze the influence of various factors on the flow slope angle. Finally, a target constraint for the flow slope angle is set. Based on this target constraint and the results of multi-factor influence analysis, a calculation model for the flow slope angle is obtained. This model is then converted into a slope angle satisfaction function to obtain the optimal filling parameters for the slope angle. In this invention embodiment, a comprehensive research system is formed, encompassing multiple stages from acquiring basic raw material parameters, constructing similar models, designing and implementing orthogonal experiments, to range analysis and interaction analysis. Through the pre-design and implementation of orthogonal experimental schemes, the influence of multiple factors and their interactions on the slope angle of slurry flow can be comprehensively studied, avoiding the one-sidedness that may result from single-factor analysis. This leads to a more comprehensive and in-depth understanding of the influence patterns. Unlike existing numerical simulation methods that often use homogeneous flow models or simplified discrete element models, this method obtains the basic parameters of the slurry raw materials through physical experiments and then constructs a slurry similarity model based on these parameters for experimentation. This approach, combining actual physical experiments with similarity simulation, can more realistically reflect the sedimentation, collision, and spatial distribution patterns of waste rock particles in the flow, greatly improving the accuracy and reliability of the prediction results and effectively solving the problem of the disconnect between existing methods' predicted slope angles and actual engineering conditions.

[0041] This invention provides a method for predicting the slope angle of gypsum flow in a narrow and elongated approach. The method specifically includes:

[0042] S10, Obtain the raw materials for the paste, conduct physical experiments on the raw materials for the paste to obtain the basic parameters of the raw materials for the paste;

[0043] S20, Load the basic parameters of the paste raw materials, construct a paste similarity model based on the basic parameters of the paste raw materials, pre-design an orthogonal experimental scheme, mix the paste raw materials based on the orthogonal experimental scheme, add water-reducing agent to prepare paste slurry, inject the paste slurry into the paste similarity model to simulate the experiment, and obtain the simulation experimental results;

[0044] S30, Load the simulation experiment results, and based on the range analysis combined with the interaction analysis, analyze the degree of influence of the influencing factors on the flow slope angle to obtain the multi-factor influence analysis results;

[0045] S40 sets the target constraint for the flow slope angle. Based on the target constraint for the flow slope angle and the results of multi-factor influence analysis, the flow slope angle calculation model is obtained. The flow slope angle calculation model is then converted into a slope angle satisfaction function to obtain the optimal filling parameters for the slope angle.

[0046] In this invention embodiment, a comprehensive research system is formed, encompassing multiple stages from acquiring basic raw material parameters, constructing similar models, designing and implementing orthogonal experiments, to range analysis and interaction analysis. Through the pre-design and implementation of orthogonal experimental schemes, the influence of multiple factors and their interactions on the slope angle of slurry flow can be comprehensively studied, avoiding the one-sidedness that may result from single-factor analysis. This leads to a more comprehensive and in-depth understanding of the influence patterns. Unlike existing numerical simulation methods that often use homogeneous flow models or simplified discrete element models, this method obtains the basic parameters of the slurry raw materials through physical experiments and then constructs a slurry similarity model based on these parameters for experimentation. This approach, combining actual physical experiments with similarity simulation, can more realistically reflect the sedimentation, collision, and spatial distribution patterns of waste rock particles in the flow, greatly improving the accuracy and reliability of the prediction results and effectively solving the problem of the disconnect between existing methods' predicted slope angles and actual engineering conditions.

[0047] Example 1

[0048] This invention provides a method for physical experimental measurement of raw materials for ointments. The method specifically includes:

[0049] S101, Obtain the raw materials for the paste and conduct physicochemical property tests on the raw materials for the paste;

[0050] Among them, the physicochemical property tests include, but are not limited to, moisture content specific gravity, loose / compact bulk density, porosity, and particle size distribution tests; the raw materials for the paste include, but are not limited to, tailings, waste rock, water-reducing agent, and cement.

[0051] It should be noted that the cement used in the paste is 32.5R fly ash cement, and the densities of the tailings and waste rock are 2.81 and 2.91 g / cm³, respectively. -3 The water-reducing agent used is Sika 3301MK polycarboxylate water-reducing agent.

[0052] S102, the particle size analysis of the tailings in the paste raw material was performed using a laser particle size analyzer, and the particle size analysis results of the tailings were obtained.

[0053] S103, the particle size of waste rock was analyzed by sieving test, and the particle size analysis results of waste rock were obtained.

[0054] In this embodiment, after particle size analysis of the tailings using a laser particle size analyzer, it was found that the uniformity coefficient of the tailings was 12.038 and the curvature coefficient was 3.459, indicating that the tailings had good gradation and relatively uniform particle distribution. Simultaneously, analysis of the waste rock particle size through sieving experiments revealed that the waste rock was mainly composed of medium to coarse particles, with particles ranging from 1 to 10 mm accounting for approximately 67.6% of the total. Particles larger than 10 mm accounted for only 11.24%, but fine particles constituted a large proportion of the waste rock, with particles <1 mm accounting for approximately 21.2% of the total.

[0055] Example 2

[0056] This invention provides a method for constructing a paste similarity model based on the basic parameters of paste raw materials. The method specifically includes:

[0057] S201, based on the actual mining area size, a similarity model of the paste with a narrow and long approach is made to recreate the actual mining area at a similarity ratio of 1:40.

[0058] S202, the similar model of the paste is raised by 20mm to prevent the paste from overflowing.

[0059] In this embodiment, after the simulation is completed, the deposition slope angle is measured and the waste rock particles are screened. Since it is difficult to screen waste rock particles <1mm, waste rock <1mm is not analyzed. After complete screening, the slurry uniformity coefficient (K value) is calculated. The smaller the K value, the more uniform it is.

[0060] It should be noted that when designing the orthogonal experimental scheme, the influencing factors and their levels were determined. The influencing factors were mass concentration, water-reducing agent dosage, and waste rock dosage, with three levels set for each factor. During the simulation experiment of injecting the paste slurry into the paste-like model, the prepared paste slurry was injected into the similar model through the discharge port to simulate the flow and deposition process of the paste slurry in a narrow channel. During the slurry injection process, the liquid level in the filling funnel was kept consistent to ensure continuous filling. After the slurry deposition stabilized, the deposition slope angle (SSA) was measured to obtain the simulation experimental results.

[0061] Example 3

[0062] This invention provides a method for analyzing the influence of factors on the flow slope angle based on range analysis combined with interaction analysis. Specifically, this method includes:

[0063] S301, Load the simulation experiment results, and use the range analysis method to analyze the simulation experiment results, and analyze the influence of mass concentration, water reducing agent dosage, and waste rock dosage on yield stress, K value, bleeding rate, and deposition slope angle SSA.

[0064] It should be noted that the simulation results were analyzed using SPSS software to determine the influence of three factors on the response values. Figure 1 The results show the effects of mass concentration, water-reducing agent dosage, and waste rock dosage on yield stress. Figure 2 The results show the effects of mass concentration, water-reducing agent dosage, and waste rock dosage on the K value. Figure 3 The results show the effects of mass concentration, water-reducing agent dosage, and waste rock dosage on the bleeding rate. Figure 4 The effects of mass concentration, water-reducing agent dosage, and waste rock dosage on the deposition slope angle are shown. From Figures 1-4 It can be seen that the yield stress of the paste is positively correlated with the mass concentration and negatively correlated with the amount of water-reducing agent and waste rock. Increasing the mass concentration reduces the free water in the slurry and intensifies the friction between particles, thus increasing the yield stress. The addition of the water-reducing agent causes the slurry to release more free water, and the steric hindrance effect between the polycarboxylate water-reducing agent groups enhances the fluidity of the slurry, thereby reducing the yield stress. The figure also shows that the K value and bleeding rate of the slurry decrease with increasing mass concentration and with increasing waste rock content. The K value increases with the increase of admixture dosage, but the K value and the bleeding rate are not simply positively or negatively correlated with the admixture dosage. Instead, under the influence of multiple factors, it shows a trend of first decreasing and then increasing. The sedimentation slope angle of the slurry is positively correlated with the mass concentration and negatively correlated with the admixture dosage of water-reducing agent and waste rock. However, it can be seen from the figure that when the admixture dosage of water-reducing agent increases from 0.25% to 0.35% and the admixture dosage of waste rock increases from 50% to 60%, the sedimentation slope angle decreases significantly. This indicates that water-reducing agent and waste rock need to be added to a certain amount to significantly change the sedimentation slope angle.

[0065] Range analysis showed that the significance of the three factors on the four response variables was as follows: waste rock dosage > mass concentration > water-reducing agent dosage.

[0066] S302, based on the simulation experimental results, establish a multivariate nonlinear regression model between yield stress, K value, BR, SSA and MC, WAD, WRD;

[0067] S303 uses Origin numerical processing software and a multiple linear regression model to construct a three-dimensional visualization model of yield stress, K value, BR, and SSA.

[0068] S304 obtains a three-dimensional visualization model of yield stress, K value, BR, and SSA. Combines the three-dimensional visualization model of yield stress, K value, BR, and SSA to analyze the interaction effect between influencing factors and obtain the results of multi-factor influence analysis.

[0069] In this embodiment, Figure 5 The diagram illustrates the effects of MC-WAD interaction, MC-WRD interaction, and WAD-WRD interaction on the depositional slope angle. Figure 5 (a) is a schematic diagram showing the effect of the interaction between MC and WAD on the depositional slope angle. Figure 5 (b) is a schematic diagram showing the effect of the interaction between MC and WRD on the depositional slope angle. Figure 5 (c) is a schematic diagram illustrating the influence of the interaction between WAD and WRD on the depositional slope angle. Figure 5 (a) It can be seen that when the mass concentration is 78%, the change in the amount of water-reducing agent does not have a significant effect on the deposition slope angle. However, when the mass concentration is 80%, the deposition slope angle of the slurry decreases significantly with the increase of the amount of water-reducing agent. This indicates that the influence of the amount of water-reducing agent on the deposition slope angle increases with the increase of the mass concentration. This is because at lower mass concentrations, the slurry itself has good fluidity, and the change in fluidity brought about by the water-reducing agent is not significant. However, at high concentrations, the slurry itself has poor fluidity, and the change in the amount of water-reducing agent can significantly change the fluidity of the slurry. The fluidity is closely related to the size of the deposition slope angle. Figure 5 As shown in (b), the depositional slope angle is positively correlated with the mass concentration and negatively correlated with the amount of water-reducing agent and waste rock. When both the mass concentration and the amount of waste rock increase simultaneously, the slope angle tends to decrease. This indicates that increasing the amount of waste rock helps to mitigate the adverse effects of increased concentration. Figure 5 (c) It can be seen that when the dosage of water-reducing agent and waste rock are increased at the same time, the slope angle is significantly reduced under the combined effect of the two, and the reduction brought about by the dosage of waste rock is more obvious.

[0070] This invention provides a method for analyzing the influence of factors on the flow slope angle based on range analysis combined with interaction analysis. Using range analysis, the influence of factors such as mass concentration, water-reducing agent dosage, and waste rock dosage on yield stress, K-value, bleeding rate, and sedimentary slope angle (SSA) can be accurately quantified. This helps identify key factors that significantly affect the flow slope angle, providing a clear direction and focus for subsequent optimization work. Analysis reveals an inherent correlation between the yield stress of the paste and its mass concentration, and a negative correlation with the water-reducing agent dosage and waste rock dosage. These patterns provide a theoretical basis for understanding the flow characteristics of paste and the slope angle formation mechanism, deepening the understanding of the paste filling process. Furthermore, based on a three-dimensional visualization model, the flow slope angle under different parameter combinations can be predicted more accurately, providing a scientific basis for paste filling operations in actual mine production. By inputting specific parameters such as mass concentration, water-reducing agent dosage, and waste rock dosage, the model predicts the corresponding flow slope angle, thereby guiding construction personnel to adjust the mix ratio of filling slurry and filling process to optimize filling effect and improve filling quality and efficiency.

[0071] Example 4

[0072] This invention provides a method for obtaining a flow slope angle calculation model based on target constraints and multi-factor influence analysis results. The method specifically includes:

[0073] S401 defines the optimal range of the flow slope angle based on engineering specifications, with the optimal range of the flow slope angle as the target constraint;

[0074] It should be noted that when defining the optimal range of the flow slope angle based on engineering specifications, according to the "Technical Specification for Tailings Paste Backfilling", the value of the response target is not better the larger or the smaller the better, but there is an optimal range. In this embodiment, the optimal range of the flow slope angle is 0-5°.

[0075] S402, Apply the target constraint of the flow slope angle, and obtain the flow slope angle calculation model based on the target constraint of the flow slope angle and the results of multi-factor influence analysis;

[0076] In this embodiment of the invention, the flow slope angle calculation model y4 is expressed as:

[0077] y4=49.333x1+4501.667x2+25.767x3-60x1x2-0.35x1x3

[0078] +3x2x3-3753.139R 2 =0.996

[0079] The yield stress calculation model y1, the K value calculation model y2, and the BR calculation model y3 are respectively expressed as follows:

[0080] y1=447.289x1+46939.056x2+200.277x3-614.00x1x2-2.745x1x3

[0081] +18.967x2x3-34051.018R 2 =0.982

[0082] y2=8.298x1-510.842x2+19.768x3+6.625x1x2-0.242x1x3

[0083] -0.248x2x3-685.123R 2 =0.913

[0084] y3=-3.984x1-1211.771x2+4.895x3+15.138x1x2-0.06x1x3

[0085] +0.216x2x3+310.527R 2 =0.963

[0086] S403 sets a weighting factor to transform a multi-objective problem into a single-objective optimization problem and converts the flow slope angle calculation model into a slope angle satisfaction function. The weighting factor can be set to 0.3.

[0087] In this embodiment of the invention, the flow slope angle calculation model is converted into a slope angle satisfaction function as follows:

[0088]

[0089] The yield stress satisfaction function d1, the K value satisfaction function d2, and the BR satisfaction function d3 are respectively expressed as:

[0090]

[0091] S404, based on the weighted geometric mean method, treats response variables as equally important and calculates the overall satisfaction function of the flow slope angle;

[0092] In this embodiment of the invention, the overall satisfaction function is expressed as:

[0093] D = (d1 × d2 × d3 × d4) 1 / 4

[0094] S405. Using MATLAB software, the overall satisfaction function is solved, the extreme value of the overall satisfaction function is found, and the optimal filling parameters for the slope angle are obtained.

[0095] In this embodiment, the overall satisfaction function has a maximum value when the mass concentration is 78%, the water-reducing agent dosage is 0.45%, and the waste rock dosage is 52.64%.

[0096] This invention provides a method for obtaining a flow slope angle calculation model based on the target constraint of the flow slope angle and the results of multi-factor influence analysis. The optimal range of the flow slope angle is defined based on engineering specifications, providing clear and quantifiable target constraints for optimization. This helps ensure that the optimized flow slope angle meets actual engineering needs and specification requirements, avoiding optimization results that do not conform to engineering reality, and improving the targeting and practicality of the optimization. By setting weighting factors, the multi-objective optimization problem is transformed into a single-objective optimization problem, that is, the flow slope angle calculation model is converted into a slope angle satisfaction function. This transformation method simplifies the complexity of the optimization problem, enabling the finding of a balance point among multiple interrelated objectives, facilitating subsequent solution using optimization algorithms, and improving optimization efficiency. Using MATLAB software to solve the overall satisfaction function can efficiently find the extreme value of the overall satisfaction function, thereby obtaining the optimal filling parameters for the slope angle. MATLAB software has powerful numerical calculation and optimization functions, which can quickly and accurately solve complex optimization models, providing strong technical support for practical engineering applications, making this method highly practical and operable.

[0097] In summary, this invention provides a method for predicting the slope angle of gypsum flow in narrow pathways. In this embodiment, a comprehensive research system is formed, encompassing multiple stages from acquiring basic raw material parameters, constructing a similar model, designing and implementing orthogonal experiments, to range analysis and interaction analysis. Through the pre-design and implementation of orthogonal experimental schemes, the influence of multiple factors and their interactions on the slope angle of gypsum flow can be comprehensively studied, avoiding the one-sidedness that may result from single-factor analysis. This leads to a more comprehensive and in-depth understanding of the influence patterns. Unlike existing numerical simulation methods that often use homogeneous flow models or simplified discrete element models, this method obtains the basic parameters of the gypsum raw materials through physical experiments and then constructs a similar model based on these parameters for experimentation. This combination of actual physical experiments and similarity simulation can more realistically reflect the settling, collision, and spatial distribution patterns of waste rock particles in the flow, greatly improving the accuracy and reliability of the prediction results and effectively solving the problem of the disconnect between existing methods' predicted slope angles and actual engineering conditions.

[0098] It should be noted that, for the sake of simplicity, the foregoing embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to the present invention. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0099] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on these embodiments, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still combine, add, delete, or otherwise adjust the features of the various embodiments of the present invention according to the circumstances without conflict or creative effort, thereby obtaining different technical solutions that do not fundamentally depart from the concept of the present invention. These technical solutions also fall within the scope of protection of the present invention.

Claims

1. A method for predicting the slope angle of gypsum flow in a narrow and elongated path, characterized in that, The method includes: S10, Obtain the raw materials for the paste, conduct physical experiments on the raw materials for the paste to obtain the basic parameters of the raw materials for the paste; S20, Load the basic parameters of the paste raw materials, construct a paste similarity model based on the basic parameters of the paste raw materials, pre-design an orthogonal experimental scheme, mix the paste raw materials based on the orthogonal experimental scheme, add water-reducing agent to prepare paste slurry, inject the paste slurry into the paste similarity model to simulate the experiment, and obtain the simulation experimental results; S30, Load the simulation experiment results, and based on the range analysis combined with the interaction analysis, analyze the degree of influence of the influencing factors on the flow slope angle to obtain the multi-factor influence analysis results; S40, set the target constraint for the flow slope angle, and obtain the flow slope angle calculation model based on the target constraint and multi-factor influence analysis results. Then, convert the flow slope angle calculation model into a slope angle satisfaction function to obtain the optimal filling parameters for the slope angle. The method for analyzing the influence of factors on the flow slope angle based on range analysis combined with interaction analysis includes: S301, Load the simulation experiment results, and use the range analysis method to analyze the simulation experiment results, and analyze the influence of mass concentration, water reducing agent dosage, and waste rock dosage on yield stress, K value, bleeding rate, and deposition slope angle SSA. S302, based on the simulation experimental results, establish a multivariate nonlinear regression model between yield stress, K value, BR, SSA and MC, WAD, WRD; S303 uses Origin numerical processing software and a multiple linear regression model to construct a three-dimensional visualization model of yield stress, K value, BR, and SSA. S304: Obtain a three-dimensional visualization model of yield stress, K value, BR, and SSA. Combine the three-dimensional visualization model of yield stress, K value, BR, and SSA to analyze the interaction effect between influencing factors and obtain the results of multi-factor influence analysis. The method for obtaining a flow slope angle calculation model based on the target constraint and multi-factor influence analysis results of the flow slope angle includes: S401 defines the optimal range of the flow slope angle based on engineering specifications, with the optimal range of the flow slope angle as the target constraint; S402, Apply the target constraint of the flow slope angle, and obtain the flow slope angle calculation model based on the target constraint of the flow slope angle and the results of multi-factor influence analysis; S403, set weighting factors to transform multi-objective optimization problems into single-objective optimization problems and transform the flow slope angle calculation model into a slope angle satisfaction function; S404, based on the weighted geometric mean method, treats response variables as equally important and calculates the overall satisfaction function of the flow slope angle; S405. Using MATLAB software, the overall satisfaction function is solved, the extreme value of the overall satisfaction function is found, and the optimal filling parameters for the slope angle are obtained.

2. The method for predicting the slope angle of gypsum flow in a narrow and elongated path as described in claim 1, characterized in that: The method for physical experimental measurement of the raw materials of the paste includes: S101, Obtain paste raw materials and conduct physicochemical property tests on the paste raw materials. The physicochemical property tests include moisture content specific gravity, loose / compact bulk density, porosity, and particle size distribution tests. The paste raw materials include tailings, waste rock, and water-reducing agent. S102, the particle size analysis of the tailings in the paste raw material was performed using a laser particle size analyzer, and the particle size analysis results of the tailings were obtained. S103, the particle size of waste rock was analyzed by sieving test, and the particle size analysis results of waste rock were obtained.

3. The method for predicting the slope angle of gypsum flow in a narrow and elongated path as described in claim 1, characterized in that: The method for constructing a paste similarity model based on the basic parameters of paste raw materials includes: S201, based on the actual mining area size, a similarity model of the paste with a narrow and long approach is made to recreate the actual mining area at a similarity ratio of 1:

40. S202, the similar model of the paste is raised by 20mm to prevent the paste from overflowing.

4. The method for predicting the slope angle of gypsum flow in a narrow and elongated path as described in claim 3, characterized in that: When designing the orthogonal experimental scheme, the influencing factors and levels of the experiment are determined. The influencing factors are mass concentration, water-reducing agent dosage, and waste rock dosage. Three levels are set for each of the influencing factors.

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