Intelligent selection method, device and electronic equipment for submersible pumps in complex in-situ leaching uranium mining operations

Abstract

This application discloses an intelligent selection method, device, and electronic equipment for submersible pumps under complex conditions in in-situ leaching uranium mining. It relates to the field of intelligent selection technology for in-situ leaching mining equipment. The method includes: calculating the dynamic drawdown using a modified Theis formula based on the acquisition parameters during the in-situ leaching uranium mining process. The modified Theis formula incorporates permeability correction coefficients, wellbore structure correction coefficients, and organic matter viscosity correction coefficients. Based on the dynamic drawdown and acquisition parameters, the influence of multiple factors on the submersible pump performance is determined. A multi-factor coupling performance reduction matrix is ​​constructed based on the influence of these factors on the submersible pump performance, and the submersible pump performance parameters under actual operating conditions are calculated based on this matrix. Finally, the required power of the submersible pump under actual operating conditions is calculated based on the submersible pump performance parameters, thereby determining the target pump type. This application can improve the accuracy of submersible pump selection and enables effective control, analysis, and evaluation.

Description

Technical Field

[0001] This application relates to the field of intelligent selection technology for in-situ leaching mining equipment, and in particular to an intelligent selection method, device and electronic equipment for submersible pumps under complex working conditions in in-situ leaching uranium mining. Background Technology

[0002] In-situ leaching is a mining method that involves injecting leaching solution into the ore layer through boreholes to dissolve uranium minerals, and then extracting the uranium-bearing leachate from the extraction boreholes. Submersible pumps, as the core equipment of the extraction boreholes, directly impact production efficiency, operating costs, equipment lifespan, and production safety, especially in acid leaching mines where improper selection can easily lead to damage. Therefore, effective management, analysis, and evaluation of submersible pumps are of great significance in engineering projects.

[0003] Currently, when selecting submersible pumps, it is usually assumed that the water level is fixed. However, in the process of in-situ leaching uranium mining, the drawdown of the water level changes over time, and the permeability changes as the pumping area expands. This approach in existing technology may result in selecting a pump with insufficient power, causing difficulties in the initial pumping process, or selecting a pump with excessive power, resulting in wasted energy in the later stages. Summary of the Invention

[0004] In view of this, this application provides a method, device and electronic equipment for intelligent selection of submersible pumps under complex conditions of in-situ leaching uranium mining, which mainly improves the accuracy of submersible pump selection and thus ensures the rationality of submersible pump selection.

[0005] According to a first aspect of this application, a method for intelligent selection of submersible pumps under complex conditions in in-situ leaching uranium mining is provided, the method comprising: To obtain the acquisition parameters during the in-situ leaching uranium extraction process; Based on the collected parameters, the dynamic drawdown is calculated using the improved Theis formula, which incorporates a permeability correction factor, a well structure correction factor, and an organic viscosity correction factor. Based on the dynamic drawdown and the collected parameters, the influence of multiple factors on the performance of the submersible pump is determined. Based on the influence of the multiple factors on the performance of the submersible pump, a multi-factor coupling performance reduction matrix is ​​constructed, and the performance parameters of the submersible pump under actual working conditions are calculated based on the multi-factor coupling performance reduction matrix. Based on the submersible pump performance parameters, calculate the submersible pump power requirement under the actual operating conditions; Based on the power requirements of the submersible pump, the target pump type is determined.

[0006] According to a second aspect of this application, an intelligent selection device for submersible pumps under complex conditions in in-situ leaching uranium mining is provided, the device comprising: Acquisition unit, used to acquire acquisition parameters during the in-situ leaching uranium mining process; The first calculation unit is used to calculate the dynamic drawdown based on the collected parameters using the improved Theis formula, wherein the improved Theis formula introduces a permeability correction coefficient, a well structure correction coefficient, and an organic viscosity correction coefficient. The first determining unit is used to determine the impact of multiple factors on the performance of the submersible pump based on the dynamic drawdown and the collected parameters. The second calculation unit is used to construct a multi-factor coupling performance reduction matrix based on the influence of the multi-factors on the submersible pump performance, and to calculate the submersible pump performance parameters under actual working conditions based on the multi-factor coupling performance reduction matrix. The third calculation unit is used to calculate the submersible pump power requirement under the actual operating conditions based on the submersible pump performance parameters. The second determining unit is used to determine the target pump type of the submersible pump based on the power requirement of the submersible pump.

[0007] According to a third aspect of this application, a storage medium is provided that stores a computer program thereon, which, when executed by a processor, implements the above-described intelligent selection method for submersible pumps under complex conditions in in-situ leaching uranium mining.

[0008] According to a fourth aspect of this application, an electronic device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the program to implement the above-described intelligent selection method for submersible pumps under complex conditions in uranium leaching mining.

[0009] By employing the above technical solutions, this application provides an intelligent selection method, device, and electronic equipment for submersible pumps under complex in-situ leaching uranium mining conditions. Compared with existing technologies, by using an improved Theis formula to calculate the dynamic drawdown in real time, it avoids the inaccurate selection problem caused by fixed water level values ​​in existing technologies, thereby improving the accuracy of submersible pump selection and ensuring its rationality. Simultaneously, this application analyzes the influence of multiple factors on submersible pump performance through dynamic drawdown and parameter acquisition, and constructs a multi-factor coupled performance reduction matrix to calculate the submersible pump performance parameters under actual operating conditions. This considers the multi-factor coupling effect, further improving the accuracy of submersible pump selection.

[0010] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0011] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 A flowchart illustrating an intelligent selection method for submersible pumps under complex conditions in in-situ leaching uranium mining, as provided in an embodiment of this application, is shown. Figure 2 A schematic flowchart of the analysis method for the influence of multiple factors on the performance of submersible pumps provided in the embodiments of this application is shown. Figure 3 A schematic diagram showing the residual reactive gases in the leachate provided in the embodiments of this application is shown; Figure 4 This illustration shows a schematic diagram of a pump flow channel being blocked under high sand content conditions, as provided in an embodiment of this application. Figure 5 A schematic diagram showing the impeller with sediment adhering to it, provided in an embodiment of this application, is shown. Figure 6 This illustration shows a schematic diagram of iron-containing organic matter adhering to the inside of the pump tube provided in an embodiment of this application; Figure 7 A schematic diagram of needle-like organic matter provided in an embodiment of this application is shown; Figure 8 A schematic flowchart of the method for calculating the performance parameters of a submersible pump provided in an embodiment of this application is shown; Figure 9 This paper presents a schematic diagram of a submersible pump intelligent selection device for complex uranium leaching operations provided in an embodiment of this application. Detailed Implementation

[0012] The present application will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present application can be combined with each other.

[0013] The existing method of fixing the water level may result in the selection of power that is too small, causing difficulties in the initial pumping, or it may result in the selection of power that is too large, causing energy waste in the later stage.

[0014] To address the aforementioned problems, embodiments of the present invention provide an intelligent selection method for submersible pumps under complex conditions in in-situ leaching uranium mining, such as... Figure 1 As shown, the method includes: Step 10: Obtain the acquisition parameters during the in-situ leaching uranium extraction process.

[0015] The collected parameters include geological parameters, wellbore parameters, operating condition parameters, and leachate parameters.

[0016] For embodiments of the present invention, it is necessary to collect geological parameters, wellbore parameters, operating condition parameters, and leachate parameters, and to standardize these parameters. Specifically, the geological parameters include: ore layer permeability coefficient. k (Unit: meters / day) Thickness of mineral-bearing aquifer b (Unit: meter), water storage coefficient S (Dimensionless) Initial static water level depth (Unit: meters), etc.; specific wellbore parameters include: wellbore diameter. D well (Unit: mm) Pump body diameter D pump (Unit: mm) Filter Length L screen (Unit: meters) Well depth L well (Unit: meter), etc.; specific operating parameters include: design pumping capacity. Q (Unit: cubic meters / hour), Daily operating time t op (Unit: hours / day) Radius of influence of pumping well r (Unit: meters) Target water level drawdown S target (Unit: meter), etc.; Leachate parameters specifically include: gas content. C g (Unit: volume percentage), Oxygen percentage (O2%) (Unit: percentage), Carbon dioxide percentage (CO2%) (Unit: percentage), Sand concentration C s (Unit: kg / m³), median particle size of sand d 50 (Unit: mm), Organic matter content C org (Unit: g / L), Organic matter adhesion index SI (Range 0-1, dimensionless) Degree of organic matter decomposition DD (Range 0-1, dimensionless) Fiber content FC (Unit: percentage), pH value (dimensionless), temperature T (Unit: degrees Celsius), chloride ion concentration Cl - (Unit: mg / L), Net Positive Hypothesis (NPSHa) (Unit: m), etc.

[0017] The embodiments of this invention construct a complete parameter system, including 25 parameters in four categories: geology, wellbore, operating conditions, and leachate. Compared with the prior art, this can further improve the accuracy of selection.

[0018] Step 20: Based on the collected parameters, calculate the dynamic drawdown using the improved Theis formula.

[0019] The improved Tess formula incorporates a permeability correction factor, a wellbore structure correction factor, and an organic viscosity correction factor.

[0020] In this embodiment of the invention, when specifically calculating the dynamic drawdown, step 20 specifically includes: correcting the basic permeability coefficient to obtain the permeability correction coefficient; calculating the wellbore structure correction coefficient based on the wellbore parameters; calculating the organic viscosity correction coefficient based on the leachate parameters; and substituting the operating condition parameters, the geological parameters, the permeability correction coefficient, the wellbore structure correction coefficient, and the organic viscosity correction coefficient into the improved Thys formula for calculation to obtain the dynamic drawdown. The improved Thys formula is as follows.

[0021] in, Represents time t Distance from pumping well r Dynamic water level drawdown at the location, in meters; Q This represents the liquid extraction volume, expressed in cubic meters per hour (m³ / h), which needs to be converted to cubic meters per day. Represents the hydraulic conductivity. The unit is square meters per day; Represents the well function. , u For dimensionless parameters, ,in, S The water storage coefficient, r This refers to the distance from the point to the pumping well, typically taken as the radius of influence of the pumping well, expressed in meters. t This refers to the time for fluid extraction, expressed in days. This is the permeability correction factor; This is a correction factor for the wellbore structure; This is the viscosity correction factor for organic matter.

[0022] Furthermore, the permeability correction coefficient The specific calculation formula is as follows:

[0023] Permeability correction factor The physical meaning is when the permeability coefficient of the ore layer... k When the flow rate is relatively low (e.g., less than 5 m / d), the drawdown increases significantly; when the permeability coefficient of the ore layer... k When it is large, the permeability correction factor The value approaches 1, reflecting the nonlinear effect of increased water flow resistance in low-permeability formations.

[0024] Furthermore, the wellbore structure correction factor The specific calculation formula is as follows:

[0025] Wellbore structure correction factor The physical meaning is the filter length. L screen With the thickness of the mineral-bearing aquifer b The larger the ratio between them, the stronger the water intake capacity and the smaller the drawdown; well diameter D well With the outer diameter of the pump body D pump The smaller the ratio between them, the smaller the flow area, the greater the flow resistance, and the greater the drawdown.

[0026] Furthermore, the viscosity correction factor for organic matter The specific calculation formula is as follows:

[0027] Organic viscosity correction factor The physical meaning of organic matter is that it increases the viscosity of the leachate, which is equivalent to reducing the formation permeability, thereby increasing the drawdown. The organic matter adhesion index... SI The larger the value, the more significant the increase in viscosity.

[0028] Furthermore, the final determined dynamic water level drawdown Specifically:

[0029] The maximum water level drawdown is limited to 200 meters, which is in line with the actual conditions of most land immersion projects.

[0030] Step 30: Based on the dynamic drawdown and the collected parameters, determine the impact of multiple factors on the performance of the submersible pump.

[0031] Among these factors are gas content, sand content, corrosion, and organic matter.

[0032] In this embodiment of the invention, after calculating the dynamic drawdown, the effects of air content, sand content, corrosion, and organic matter on the performance of the submersible pump are analyzed. Regarding this analysis process, as follows... Figure 2 As shown, it includes: Step 31: Calculate the total head of the foundation based on the dynamic drawdown.

[0033] For embodiments of the present invention, the theoretical head requirement under clear water conditions is calculated, wherein the static head is... The specific formula is as follows:

[0034] Dynamic lifting range The specific calculation formulas for (friction losses, etc.) are as follows:

[0035] in, This represents friction loss along the flow path, calculated based on the Darcy-Weisbach formula for head loss along the flow path in a circular pipe. and These are local losses (elbow losses, valve losses, etc.) and pump-well clearance losses. These local losses and pump-well clearance losses can be determined by referring to tables or by actual measurement.

[0036] Furthermore, based on the dynamic head and static head, the total foundation head is calculated. The specific formula is as follows:

[0037] Therefore, the total head of the foundation can be calculated using the above formula. The total head can be utilized subsequently. The effects of four factors—gas content, sand content, corrosion, and organic matter—on the performance of submersible pumps were analyzed.

[0038] Step 32: Based on the collected parameters and the basic total head, calculate the increase in head and efficiency reduction rate caused by gas inclusion, and determine the power increment caused by gas inclusion. Based on the increase in head, efficiency reduction rate and power increment caused by gas inclusion, determine the impact of gas inclusion on the performance of the submersible pump.

[0039] For embodiments of the present invention, such as Figure 3 As shown, the leachate contains residual reacting gases (O2 and CO2), which can affect the performance of the submersible pump. When calculating the increase in head and efficiency reduction rate due to gas content, based on the collected data, the critical gas content, bubble size influence factor, and gas composition influence index are calculated respectively; based on the collected data, the critical gas content, the bubble size influence factor, and the gas composition influence index, the efficiency under gas-containing conditions is calculated; based on the efficiency under gas-containing conditions and the efficiency under clear water conditions, the efficiency reduction rate due to gas content is calculated; based on the collected data, the critical gas content, the bubble size influence factor, the gas composition influence index, and the basic total head, the increase in head due to gas content is calculated.

[0040] Specifically, critical gas content The specific calculation formula is as follows:

[0041] The physical meaning of critical gas content is that the larger the effective net positive suction head (NPSHa), the stronger the pump's resistance to cavitation, and the higher the critical gas content.

[0042] Furthermore, the bubble size influence factor The specific calculation formula is as follows:

[0043] in, The average diameter of the bubble is expressed in millimeters. Physically, the larger the bubble diameter, the more significant its impact on the performance of the submersible pump.

[0044] Furthermore, the gas composition influence index The specific calculation formula is as follows:

[0045] Among them, the physical meaning of the gas composition influence index is that the higher the oxygen content, the worse the bubble stability, and the greater the influence index on the performance of the submersible pump.

[0046] Furthermore, efficiency under gas-containing conditions The specific calculation formula is as follows:

[0047] in, For clean water operation, the efficiency is typically taken as 0.78-0.82; C g This represents the gas content, expressed as a volume percentage (%).

[0048] Furthermore, based on efficiency under gas-containing operating conditions and efficiency under clear water conditions Calculate the efficiency reduction rate caused by gas content. The specific formula is as follows:

[0049] Furthermore, the increase in head due to gas content The specific calculation formula is as follows:

[0050] Among them, the increase in head caused by gas content The unit is meters; The head influence coefficient, ; For the head-affected index, .

[0051] Therefore, the efficiency reduction rate caused by gas content can be calculated using the above formula. and the increase in head due to gas content Power increment due to gas content It can be determined based on practical experience.

[0052] Step 33: Based on the collected parameters and the basic total head, calculate the increase in head and efficiency reduction rate caused by sand, and determine the power increment caused by sand. Based on the increase in head, efficiency reduction rate and power increment caused by sand, determine the impact of sand on the performance of the submersible pump.

[0053] In the embodiments of the present invention, sand content can have a significant impact on the performance of submersible pumps, such as... Figure 4 As shown, high sand content conditions can clog the pump flow channel, such as... Figure 5 As shown, the impeller is covered with silt, affecting the mechanical efficiency of the pump. When calculating the increase in head and efficiency reduction rate caused by sand, the particle impact velocity is calculated based on the collected data; the wear coefficient is calculated based on the particle impact velocity and the collected parameters; the efficiency under sand-containing conditions is calculated based on the wear coefficient; the efficiency reduction rate caused by sand is calculated based on the efficiency under sand-containing conditions and the efficiency under clear water conditions; and the increase in head caused by sand is calculated based on the total head and the wear coefficient.

[0054] Specifically, particle impact velocity The specific calculation formula is as follows:

[0055]

[0056] Among them, particle impact velocity The unit is meters per second (m / s). It refers to the flow area, that is, the area through which the liquid flows.

[0057] Furthermore, after calculating the particle impact velocity... Subsequently, based on the particle impact velocity Calculate the wear coefficient (Dimensionless), wear coefficient The specific calculation formula is as follows:

[0058] in, The wear resistance coefficient of the material (dimensionless); The density of sand particles is usually taken as 2650 kg / m³. 3 ; The median particle size of the sand. C s Sand concentration, expressed in kilograms per cubic meter (kg / m³). Material abrasion resistance coefficient. The values ​​of are shown in Table 1. Table 1 Material wear resistance coefficient Classification table

[0059] Furthermore, based on the wear coefficient Calculate the efficiency under sand-containing conditions. The specific calculation formula is as follows:

[0060] Furthermore, based on the efficiency under sand-containing conditions and efficiency under clear water conditions Calculate the efficiency reduction rate caused by the sand content. The specific calculation formula is as follows:

[0061] At the same time, based on the basic total head and wear coefficient Calculate the increase in head caused by sand content. The specific formula is as follows:

[0062] Therefore, the efficiency reduction rate caused by sand content can be calculated using the above formula. and the increase in head due to sand content Power increase due to sand content It can be determined based on practical experience.

[0063] Step 34: Based on the collected parameters, calculate the increase in head and efficiency reduction rate caused by corrosion, and determine the power increment caused by corrosion. Based on the increase in head, efficiency reduction rate and power increment caused by corrosion, determine the impact of corrosion on the performance of the submersible pump.

[0064] In this embodiment of the invention, when calculating the increase in head and the efficiency reduction rate caused by corrosion, the acid-base influence coefficient, the flow velocity influence index, and the organic corrosion promoting factor are calculated based on the collected parameters; the corrosion rate is calculated based on the acid-base influence coefficient, the flow velocity influence index, and the organic corrosion promoting factor; and the increase in head and the efficiency reduction rate caused by corrosion are calculated based on the corrosion rate.

[0065] Specifically, the influence coefficient of pH The specific calculation formula is as follows:

[0066] in, The concentration of chloride ions is the highest concentration of chloride ions, and the higher the concentration of chloride ions, the more significant the effect of pH on the corrosion rate.

[0067] Furthermore, the flow velocity impact index b The specific calculation formula is as follows:

[0068] Among them, under low pH conditions (acidic immersion environment), the flow rate has a more significant impact on the corrosion rate.

[0069] Furthermore, organic corrosion promoters The specific calculation formula is as follows:

[0070] Organic corrosion promoters The physical meaning is that organic matter promotes microbial corrosion under acidic conditions.

[0071] Furthermore, based on the acidity / alkalinity influence coefficient Flow velocity impact index b and organic corrosion promoters Calculate the corrosion rate The specific calculation formula is as follows:

[0072] Among them, corrosion rate The unit is micrometers per year (μm / a); This is the standard corrosion rate, which is material-dependent; Represents flow velocity, measured in meters per second (m / s); For reference speed, it is usually taken as 1.0 m / s; This is the corrosion activation energy, which is material-dependent and is expressed in kilojoules per mole (kJ / mol). R The gas constant is taken as 8.314 J / (mol·K); T Temperature, measured in Kelvin (K). The reference temperature is 293.15 K (20°C). The relevant material parameters are shown in Table 2. Table 2 Material-related parameters

[0073] Furthermore, based on the corrosion rate Calculate the increase in head caused by corrosion respectively. and efficiency reduction rate The specific calculation formula is as follows:

[0074]

[0075] in, t The total running time is expressed in hours (h).

[0076] Therefore, the increase in head caused by corrosion can be calculated using the above formula. and efficiency reduction rate Power increase due to sand content It can be determined based on practical experience.

[0077] Step 35: Based on the collected parameters, calculate the increase in head, efficiency reduction rate, and power increment caused by organic matter, and determine the impact of organic matter on the performance of the submersible pump based on the increase in head, efficiency reduction rate, and power increment caused by organic matter.

[0078] For embodiments of the present invention, such as Figure 6 and Figure 7 As shown, in-situ leaching mining areas often contain organic matter such as plant roots, which break down into 0-2mm fragments during the leaching process. These fragments have adhesiveness, thickening properties, clogging properties, and biological activity, which can significantly affect the performance of submersible pumps. Adhesiveness refers to their tendency to adhere to the impeller and pump casing surfaces; thickening properties refer to their tendency to increase the viscosity of the leachate; clogging properties refer to their tendency to accumulate and block narrow flow channels; and biological activity refers to their ability to promote the growth of microorganisms and accelerate corrosion. When calculating the head increase, efficiency reduction rate, and power increment caused by organic matter, the total solid volume fraction is calculated based on the collected parameters; the viscosity increase factor is calculated based on the total solid volume fraction; the mixture viscosity is calculated based on the viscosity increase factor and the total solid volume fraction; the clogging probability is calculated based on the collected parameters, particle aggregation coefficient, and the influence coefficient of temperature on organic matter; the adhesion efficiency factor is calculated based on the collected data; the adhesion wear coefficient is calculated based on the adhesion efficiency factor, material adhesion coefficient, and the collected data; and the head increase, efficiency reduction rate, and power increment caused by organic matter are calculated based on the clogging probability, the mixture viscosity, and the adhesion wear coefficient, respectively.

[0079] Specifically, total solid volume fraction The specific calculation formula is as follows:

[0080] Furthermore, viscosity increase factor The specific calculation formula is as follows:

[0081] Furthermore, based on the viscosity increase factor and total solid volume fraction Calculate the viscosity of the mixture The specific calculation formula is as follows:

[0082] in, ρ is the viscosity of water, taken as 0.001 Pa·s at 20°C.

[0083] Furthermore, based on the particle aggregation coefficient The influence coefficient of temperature on organic matter Calculate the probability of congestion The specific calculation formula is as follows:

[0084] Among them, the probability of blockage The range is 0 to 1; particle aggregation coefficient Dimensionless; This represents the mass fraction of particles with a diameter <0.1 mm; This represents the mass fraction of particles with a diameter of 0.1-0.5 mm. This represents the mass fraction of particles with a diameter of 0.5-1.0 mm. This represents the mass fraction of particles with a diameter of 1.0-2.0 mm. T This represents temperature, expressed in degrees Celsius (°C).

[0085] In some embodiments, the probability of blockage can also be considered. Classify congestion risk levels. Specifically, when When, it is low risk; when At that time, it was considered a medium risk; when This is considered high-risk.

[0086] Furthermore, based on the collected data, the adhesion efficiency factor is calculated. The specific formula is as follows:

[0087] Furthermore, based on the adhesion efficiency factor Calculate the adhesion wear coefficient The specific formula is as follows:

[0088] in, The coefficient of adhesion of the material is dimensionless. Represents flow velocity, measured in meters per second; T Represents temperature, in degrees Celsius (°C). Material adhesion coefficient. The possible values ​​for are shown below. Table 3 Material adhesion coefficient Classification table

[0089] Furthermore, based on the probability of congestion Viscosity of the mixture and adhesive wear coefficient Calculate the increase in head caused by organic matter. Efficiency reduction rate and power increment The specific formula is as follows:

[0090] in, Power output under clean water conditions, measured in kilowatts (kW).

[0091] Therefore, the increase in head caused by organic matter can be calculated using the above formula. Efficiency reduction rate and power increment .

[0092] This invention is the first to consider the influence of organic matter, and establishes a calculation model for the viscosity, adhesion, and clogging of organic debris, thereby further improving the selection accuracy of submersible pumps.

[0093] Step 40: Based on the influence of the multiple factors on the submersible pump performance, construct a multi-factor coupling performance reduction matrix, and calculate the submersible pump performance parameters under actual working conditions based on the multi-factor coupling performance reduction matrix.

[0094] In this embodiment of the invention, after determining the effects of gas content, sand content, corrosion, and organic matter on the performance of the submersible pump, the coupling effect between multiple factors is considered, and a multi-factor coupling performance reduction matrix is ​​constructed to calculate the submersible pump performance parameters under actual operating conditions. For this process, as follows... Figure 8 As shown, it includes: Step 41: Based on the influence of the multi-factors on the submersible pump performance, calculate the secondary coupling effect correction term, and based on the multi-factor coupling performance reduction matrix and the secondary coupling effect correction term, calculate the total efficiency, total head, total power demand and blockage risk coefficient respectively.

[0095] Specifically, the constructed multi-factor coupling performance reduction matrix is ​​as follows:

[0096] in, Represents overall efficiency, dimensionless; Representing the total journey; Represents total power demand; Represents the congestion risk coefficient; Represents efficiency under clear water operating conditions; dimensionless. The pump head represents the head under clear water operating conditions, and the unit is meters. This represents the power output under clean water operating conditions, measured in kilowatts (kW). Represents the efficiency reduction rate caused by each factor; This represents the increase in head caused by various factors; This represents the power increment caused by various factors.

[0097] The specific formula for calculating the secondary coupling effect correction term is as follows.

[0098] in, for , , The sum of the three, for , , The sum of the three. The physical meaning of the secondary coupling effect correction term is that there is an interaction between the factors, such as gas content exacerbating sand-borne wear, and sand-borne wear areas being more prone to corrosion.

[0099] Step 42. Determine the submersible pump performance parameters under the actual operating conditions based on the total efficiency, total head, total power requirement, and blockage risk coefficient.

[0100] For embodiments of the present invention, the final calculated total efficiency Total distance Total power demand Congestion risk coefficient The performance parameters of the submersible pump under actual working conditions were determined.

[0101] Step 50: Calculate the required power of the submersible pump under the actual operating conditions based on the performance parameters of the submersible pump.

[0102] In this embodiment of the invention, after calculating the performance parameters of the submersible pump, the required power of the submersible pump under actual operating conditions is calculated based on these performance parameters. Specifically, step 50 includes: calculating the safety factor and material matching coefficient for immersion conditions based on the collected parameters; and calculating the required power of the submersible pump under the actual operating conditions based on the submersible pump performance parameters, the safety factor for immersion conditions, and the material matching coefficient.

[0103] Specifically, the safety factor for ground immersion conditions The specific calculation formula is as follows:

[0104] Among them, the safety factor for ground immersion conditions The value range is from 1 to 1.2.

[0105] Furthermore, the material matching coefficient The specific calculation formula is as follows:

[0106] in, .

[0107] Furthermore, based on the submersible pump performance parameters, the safety factor for ground immersion conditions, and the material matching coefficient, the required power of the submersible pump under actual operating conditions is calculated. The specific calculation formula is as follows.

[0108] in, The power required for the submersible pump.

[0109] Step 60: Based on the power requirement of the submersible pump, determine the target pump type of the submersible pump.

[0110] In this embodiment of the invention, after determining the required power of the submersible pump, a selection is made based on that required power. Specifically, step 60 includes: determining the required power from a preset standard power sequence based on the required power of the submersible pump; and determining the target pump type based on the required power.

[0111] Specifically, assuming the preset standard power sequence is The selected power is The selected power belongs to the preset standard power sequence and is greater than the power required by the submersible pump. Therefore, based on the determined power output, the target pump type for the submersible pump can be determined.

[0112] In some embodiments, the optimal operating parameter range corresponding to the target pump type can also be determined. Based on this, the method further includes: determining the optimal flow range corresponding to the target pump type based on the submersible pump's required power and the selected power; calculating the optimal head range corresponding to the target pump type based on the ground immersion safety factor and the total head in the submersible pump's performance parameters; calculating the efficiency operating range corresponding to the target pump type based on the total efficiency in the submersible pump's performance parameters; and determining the optimal operating parameter range corresponding to the target pump type based on the optimal flow range, the optimal head range, and the efficiency operating range.

[0113] Specifically, optimal flow The specific formula for calculating the range is as follows:

[0114] The constraints are:

[0115] Furthermore, optimal head The specific formula for calculating the range is as follows:

[0116] Furthermore, efficiency workspace The specific calculation formula is as follows:

[0117] in, The minimum value must be greater than 0.50; otherwise, the pump should be repaired or replaced.

[0118] In some embodiments, the optimal impeller material can also be recommended based on a multi-dimensional scoring system. Based on this, the method includes: scoring each material from wear, corrosion, adhesion, cost, and versatility dimensions respectively, to obtain wear score, corrosion score, adhesion score, cost score, and versatility score for each material; determining a comprehensive score for each material based on the wear score, corrosion score, adhesion score, cost score, and versatility score; determining the highest comprehensive score based on the comprehensive scores for each material, and using the material with the highest comprehensive score as the recommended material.

[0119] Specifically, no. i The comprehensive score calculation formula for this material is as follows:

[0120] in, , , , and All are weighting coefficients; Representing the i Wear rating of the material; Representing the i Corrosion rating of the material; Representing the i Adhesion score of the material; Representing the i Cost rating of the materials; Representing the i The universality score of the material.

[0121] The specific calculation formulas for the scores in each dimension are as follows:

[0122] in, Representing the i The wear resistance coefficient of this material and These represent the maximum and minimum wear resistance coefficients for all materials, respectively. Representing the i The adhesion coefficient of the material and These represent the maximum and minimum adhesion coefficients of all materials, respectively. Representing the i The corrosion rate of this material and These represent the minimum and maximum corrosion rates for all materials, respectively. Representing the i The cost of this material and These represent the maximum and minimum costs of all materials, respectively. After calculating the overall score for all materials, the material with the highest overall score is selected as the recommended material.

[0123] In some embodiments, a comprehensive selection report for the submersible pump can be generated based on recommended pump type, optimal operating parameter range, recommended materials, etc. Based on this, the method further includes: generating a comprehensive selection report for the submersible pump based on the selected power, the target pump type, the optimal flow range, the optimal head range, the efficiency operating range, and the recommended materials.

[0124] Specifically, the generated comprehensive selection report includes recommended pump types (such as power and model), optimal operating parameter ranges (such as optimal flow range, optimal head range, and efficiency operating range), recommended materials (such as impeller and pump casing materials), risk warnings (such as blockage risk level and corrosion risk level), operating suggestions (such as start-up and shutdown frequency and cleaning cycle), and maintenance cycles (such as inspection cycle and overhaul cycle).

[0125] To illustrate the selection process of the embodiments of the present invention in detail, three specific calculation examples for selecting submersible pumps are given below.

[0126] Example calculation 1: A conventional sandstone uranium deposit (without organic matter), where the geological parameters include the ore layer permeability coefficient. k= 8.5 m / d, thickness of mineral-bearing aquifer b= 25m, initial still water level depth = 150m; wellbore diameter in wellbore parameters D well = 200mm, pump body diameter D pump =102mm, filter length L screen =20m; Design pumping capacity in operating parameters Q=8.0 m³ / h, daily operating time t op =20 h / d, radius of influence of pumping well r =15m; Gas content in leachate parameters C g =8%, oxygen content (O2%) is 60%, carbon dioxide content (CO2%) is 40%, sand concentration C s = 15 kg / m³, median particle size of sand d 50 =0.3mm, pH value is 2.5, temperature T At 25°C, Cl - =150 mg / L, NPSHa=5.0 m.

[0127] When calculating dynamic drawdown, the hydraulic conductivity... ,parameter , Specifically: 25²×0.0002 / (4×212.5×20 / 24) = 0.125 / (212.5×0.833) = 0.00011296, Well function (Look up a table or calculate numerically) Permeability correction factor for: 1.2×e^{-0.05×8.5}+0.8×tanh(0.1×8.5)=1.2×0.654+0.8×0.682=0.785+0.546=1.331, Wellbore structure correction factor for: 1 + 0.3 × (20 / 25) + 0.1 × (200 / 102) = 1.044 Organic viscosity correction factor Equal to 1 (no organic matter), dynamic drawdown for: (8×24) / (4π×212.5)×6.842×1.331×1.044=0.0720×6.842×1.331×1.044=0.685m, the final dynamic drawdown. It equals min(0.685, 50) = 0.685 m.

[0128] Furthermore, Jingyangcheng Specifically: 150 + 0.685 = 150.685, driving head =15.2m (calculated based on wellbore parameters), total foundation head for: 150.685+15.2=165.885≈166 m.

[0129] Furthermore, the effects of multiple factors on the submersible pump performance were calculated separately, including the efficiency reduction rate caused by air inclusion. The increase in head due to gas content is 0.212. The efficiency reduction rate due to sand content is 31.8m. The increase in head due to sand content is 0.065. The head increase due to corrosion is 16.6m. The efficiency reduction rate due to corrosion is 8.3m. The efficiency reduction rate due to organic matter is 0.032. The increase in head due to organic matter is 0. It is 0.

[0130] Furthermore, coupled calculations are performed to improve the overall efficiency. for: 0.82 - 0.212 - 0.065 - 0.032 + 0.008 (coupling term) = 0.519 Total head for: 166+31.8+16.6+8.3+8.2 (coupling term = 230.9 ≈ 231 m).

[0131] Furthermore, intelligent pump type matching is performed to determine the power requirements of the submersible pump. for: (8×231) / (367×0.519)×1.05 (safety factor)×0.95 (material factor) = 3549.6 / 190.5×1.25×0.95 = 18.63×1.25×0.95 = 18.4808 kW.

[0132] Obtained by matching a preset standard power sequence Equals 18.5kW (maximum power), then outputs the optimal flow range. Q opt = [7.2, 8.8] m³ / h, optimal head range H opt = [196, 254] m, recommended material is tungsten carbide coating (highest overall score).

[0133] The final selection result recommends an 18.5 kW submersible pump for ground immersion; the optimal operating parameters include a flow rate of 7.2-8.8 m³ / h and a head of 196-254 m; the material configuration includes a tungsten carbide coated impeller and a 316L stainless steel pump casing.

[0134] Calculation Example 2 is based on Calculation Example 1, but with the addition of an organic matter parameter, namely, the organic matter content. C org The concentration was 8.5 g / L, and the organic matter adhesion index was... SI The value is 0.65, indicating the degree of organic matter decomposition. DD The content of fibrous material is 0.3. FC The value is 0.3, and the particle size distribution is as follows: <0.1mm accounts for 40%, 0.1-0.5mm accounts for 30%, 0.5-1.0mm accounts for 20%, and 1.0-2.0mm accounts for 10%.

[0135] Calculations for the influence of organic matter, total solid volume fraction for: 15 / 2650 + 8.5 / 1200 = 0.00566 + 0.00708 = 0.01274 Viscosity increase factor for: 1 + 0.15 × 0.65 × 8.5^{0.8} × [1 + 0.3 × tanh(5 × 0.3)] = 1 + 0.15 × 0.65 × 5.278 × [1 + 0.3 × 0.917] = 1 + 0.515 × 1.275 = 1.656, Mixture viscosity for: 0.001 × 1.0368 × 1.656 = 0.001716 Pa·s, which is 71.6% higher than that of pure water.

[0136] Furthermore, a congestion risk assessment is conducted, including the particle aggregation coefficient. for: 0.4×0.4 + 0.3×0.3 + 0.2×0.2 + 0.1×0.1 = 0.16 + 0.09 + 0.04 + 0.01 = 0.30 The effect coefficient of temperature on organic matter for: 1 + 0.1 × tanh[0.2 × (25 - 20)] = 1 + 0.1 × tanh(1) = 1 + 0.1 × 0.7616 = 1.076, Congestion probability for: 0.65×0.30×(1+0.5×0.15)×e^{0.02×8.5}×1.076=0.65×0.30×1.075×1.185× 1.076 = 0.267, the risk level is medium risk (0.2 ≤ 0.267<0.5).

[0137] Furthermore, adhesive wear calculations and adhesion efficiency factors are performed. for: 0.3×0.65+0.7×[1-e^{-2×0.3}]=0.195+0.7×[1-0.5488]=0.195+0.7×0.4512=0.195+0.3158 = 0.5108, Material adhesion coefficient It is 0.08. Adhesive abrasion coefficient. for: 0.08×0.5108×1.5^{1.5}×8.5^{0.7}×((25-20) / 30)^{0.3}=.08×0.5108×1.837×4.8 82×0.550^{0.3}=0.08×0.5108×1.837×4.882×0.861=0.315, Furthermore, the impact of organic matter on the performance of submersible pumps was determined, including the increase in head caused by organic matter. for: 0.03×8.5×(1+0.5×0.65)+0.008×0.315=0.03×8.5×1.325+0.00252=0.338+0.00252=0.3405m, Efficiency reduction due to organic matter for: 0.02×8.5×(1+0.65)+0.005×0.315=0.02×8.5×1.65+0.001575=0.2805+0.001575= 0.282, Power increment caused by organic matter for: (0.001716-0.001) / 0.001×18.63×(1+0.2×0.267)=0.716×18.63×1.0534=14.05kW.

[0138] Furthermore, the original submersible pump required 18.5 kW of power. Considering organic matter, the required power is 18.5 + 14.05 = 36.17 kW, which exceeds the maximum standard power of 22 kW. The solution is to reduce the design flow rate and the new flow rate... It equals 8.0 22 / 36.17=4.87≈4.9 m³ / h.

[0139] Furthermore, the recommended pump type is a 22 kW submersible pump specifically designed for ground immersion; the optimal operating parameters range from 4.5 to 5.3 m³ / h for flow rate and 210 to 270 m for head; special configuration requirements include a Teflon-coated impeller (anti-adhesion), a widened flow channel design (flow channel width ≥ 20 mm), a denser mineral layer filter (pore size 2 mm), and the addition of a reverse-flow flushing function for the submersible pump (once every 72 hours); material configuration includes a Teflon-coated impeller and a ceramic-coated pump casing.

[0140] Calculation Example 3 is a low-permeability deposit with high sand content, where the geological parameter is the ore layer permeability coefficient. k The permeability is 1.2 m / d (low permeability), and the thickness of the mineral-bearing aquifer is... b It is 18 m, and the water storage coefficient is... S The initial static water level depth is 0.00015. The diameter is 120m; among the wellbore parameters, the wellbore diameter is... D well The outer diameter of the pump body is 150mm. D pump The filter length is 102mm. L screen The design pumping capacity is 15m; the operating parameters include the designed pumping volume. Q The daily operating time is 6.0 m³ / h. t op The influence radius of the pumping well is 18 h / d. r The value is 20m; the gas content in the leachate parameters is... C g The sand concentration is 5%. C s The median particle size of the sand is 35 kg / m³ (high sand content). d 50 The thickness is 0.8mm (coarse sand), and the organic matter content is... C org The concentration was 2.0 g / L (for trace amounts of organic matter), and the organic matter adhesion index was... SI The value is 0.3, the pH value is 2.8, and the temperature is... T The temperature is 22°C.

[0141] In specific calculations, low permeability significantly increases the drawdown, and the permeability correction factor... for: 1.2 × e^{-0.05 × 1.2} + 0.8 × tanh(0.1 × 1.2) = 1.2 × 0.9418 + 0.8 × 0.1194 = 1.130 + 0.0955 = 1.2255, High sand content leads to severe wear, and the material's wear resistance coefficient is reduced. Equal to 0.15, a small amount of organic matter has a relatively small impact, and the probability of blockage is low. It equals 0.12 (low risk).

[0142] Furthermore, a 15 kW submersible pump specifically designed for ground immersion is recommended; the optimal operating parameter range includes... Flow rate 5.4-6.6 m³ / h, head 145-185 m; material configuration includes tungsten carbide coated impeller and pump casing; special configuration requirements include reinforced bearings and wear-resistant seals.

[0143] Compared to existing technologies, the accuracy rate of traditional pump selection methods is approximately 60-70%, while the accuracy rate of the pump selection embodiment of this invention can reach 90-95%. This improvement is due to factors such as dynamic calculation of drawdown, multi-factor coupled calculation, and consideration of the impact of organic matter on submersible pump performance. Simultaneously, the mean time between failures (MTBF) of pumps selected using traditional methods is 8-12 months, while the MTBF of pumps selected using this invention is 12-24 months, representing an extension of 100-200%. This can save a single well annually on pump purchase costs, labor and tool costs for pump retrieval, and additional costs affecting normal production. Furthermore, the power matching deviation of traditional methods reaches ±20-40%, while the power matching deviation of this invention is ±5-10%, reducing energy consumption by 15-25%. This results in annual electricity savings of 10,000-20,000 kWh per well, significantly reducing carbon emissions. Moreover, the failure rate of this invention embodiment is reduced from 0.5-1 times per month to once every 3-6 months, reducing maintenance costs by 40-60% and downtime by 50-70%. Furthermore, by establishing a complete calculation model of the impact of organic matter and providing targeted anti-clogging design schemes, this invention can reduce clogging failures by 80-90%. Furthermore, by establishing a standardized parameter system of 25 items and developing a reusable calculation model, this invention can provide a technical foundation for specifying industry standards. This invention is applicable to various high, medium, and low permeability sandstone-type in-situ leaching uranium deposits in northern China, and can adapt to different leaching solution characteristics such as acidic, neutral, and alkaline. It is also compatible with various pump types, including centrifugal, mixed-flow, and axial-flow pumps. Based on approximately 1000 pumping wells in in-situ leaching uranium mines nationwide, it can save several million yuan annually.

[0144] Furthermore, as Figure 1 , Figure 2 and Figure 8 The specific implementation of the method shown in this embodiment provides an intelligent selection device for submersible pumps under complex conditions in in-situ leaching uranium mining, such as... Figure 9 As shown, the device includes: an acquisition unit 101, a first calculation unit 102, a first determination unit 103, a second calculation unit 104, a third calculation unit 105, and a second determination unit 106.

[0145] The acquisition unit 101 can be used to acquire acquisition parameters during the in-situ leaching uranium mining process.

[0146] The first calculation unit 102 can be used to calculate the dynamic drawdown based on the collected parameters using the improved Theis formula, wherein the improved Theis formula introduces a permeability correction coefficient, a well structure correction coefficient, and an organic viscosity correction coefficient.

[0147] The first determining unit 103 can be used to determine the impact of multiple factors on the performance of the submersible pump based on the dynamic drawdown and the collected parameters.

[0148] The second calculation unit 104 can be used to construct a multi-factor coupling performance reduction matrix based on the influence of the multi-factors on the submersible pump performance, and calculate the submersible pump performance parameters under actual working conditions based on the multi-factor coupling performance reduction matrix.

[0149] The third calculation unit 105 can be used to calculate the submersible pump's required power under the actual operating conditions based on the submersible pump's performance parameters.

[0150] The second determining unit 106 can be used to determine the target pump type of the submersible pump based on the power requirement of the submersible pump.

[0151] In some embodiments, the collected parameters include geological parameters, wellbore parameters, operating condition parameters, and leachate parameters. The first calculation unit 102 can be specifically used to correct the basic permeability coefficient to obtain the permeability correction coefficient; calculate the wellbore structure correction coefficient based on the wellbore parameters; calculate the organic viscosity correction coefficient based on the leachate parameters; and substitute the operating condition parameters, the geological parameters, the permeability correction coefficient, the wellbore structure correction coefficient, and the organic viscosity correction coefficient into the improved Thys formula to calculate the dynamic drawdown.

[0152] In some embodiments, the multiple factors include gas content, sand content, corrosion, and organic matter. The first determining unit 103 includes a calculation module and a determining module.

[0153] The calculation module can be used to calculate the total head of the foundation based on the dynamic drawdown.

[0154] The calculation module can also be used to calculate the increase in head and efficiency reduction rate caused by gas inclusion based on the collected parameters and the basic total head, and to determine the power increment caused by gas inclusion.

[0155] The determining module can be used to determine the impact of gas on the performance of a submersible pump based on the increase in head, efficiency reduction rate, and power increment caused by the gas content.

[0156] The calculation module can also be used to calculate the increase in head and efficiency reduction rate caused by sand based on the collected parameters and the basic total head, and to determine the power increment caused by sand.

[0157] The determining module can also be used to determine the impact of sand on the performance of the submersible pump based on the increase in head, efficiency reduction rate, and power increment caused by the sand content.

[0158] The calculation module can also be used to calculate the increase in head and the efficiency reduction rate caused by corrosion based on the collected parameters, and to determine the power increment caused by corrosion.

[0159] The determining module can also be used to determine the impact of corrosion on the performance of the submersible pump based on the increase in head, efficiency reduction rate, and power increment caused by the corrosion.

[0160] The calculation module can also be used to calculate the increase in head, efficiency reduction rate and power increment caused by organic matter based on the collected parameters.

[0161] The determining module can also be used to determine the impact of organic matter on the performance of submersible pumps based on the increase in head, efficiency reduction rate, and power increment caused by the organic matter.

[0162] In some embodiments, the calculation module may be specifically used to calculate, based on the collected data, the critical gas content, the bubble size influence factor, and the gas composition influence index; to calculate the efficiency under gas-containing conditions based on the collected data, the critical gas content, the bubble size influence factor, and the gas composition influence index; to calculate the efficiency reduction rate caused by gas content based on the efficiency under gas-containing conditions and the efficiency under clear water conditions; and to calculate the head increase caused by gas content based on the collected data, the critical gas content, the bubble size influence factor, the gas composition influence index, and the basic total head.

[0163] In some embodiments, the calculation module may also be specifically used to calculate the particle impact velocity based on the collected data; calculate the wear coefficient based on the particle impact velocity and the collected parameters; calculate the efficiency under sand-containing conditions based on the wear coefficient; calculate the efficiency reduction rate caused by sand-containing conditions based on the efficiency under sand-containing conditions and the efficiency under clear water conditions; and calculate the head increase caused by sand-containing conditions based on the basic total head and the wear coefficient.

[0164] In some embodiments, the calculation module may also be specifically used to calculate the pH influence coefficient, the flow velocity influence index, and the organic corrosion promoting factor based on the collected parameters; calculate the corrosion rate based on the pH influence coefficient, the flow velocity influence index, and the organic corrosion promoting factor; and calculate the head increase and efficiency reduction rate caused by the corrosion based on the corrosion rate.

[0165] In some embodiments, the calculation module may further be used to: calculate the total solid volume fraction based on the collected parameters; calculate the viscosity increase factor based on the total solid volume fraction; calculate the viscosity of the mixture based on the viscosity increase factor and the total solid volume fraction; calculate the clogging probability based on the collected parameters, particle aggregation coefficient, and the influence coefficient of temperature on organic matter; calculate the adhesion efficiency factor based on the collected data; calculate the adhesion wear coefficient based on the adhesion efficiency factor, material adhesion coefficient, and the collected data; and calculate the head increase, efficiency reduction rate, and power increment caused by the organic matter based on the clogging probability, the viscosity of the mixture, and the adhesion wear coefficient.

[0166] In some embodiments, the second calculation unit 104 may be specifically used to calculate a secondary coupling effect correction term based on the influence of the multiple factors on the submersible pump performance; calculate the total efficiency, total head, total power demand, and blockage risk coefficient based on the multi-factor coupling performance reduction matrix and the secondary coupling effect correction term; and determine the submersible pump performance parameters under the actual operating conditions based on the total efficiency, total head, total power demand, and blockage risk coefficient.

[0167] In some embodiments, the third calculation unit 105 may be specifically used to calculate the ground immersion condition safety factor and material matching factor based on the collected parameters; and to calculate the submersible pump power demand under the actual operating conditions based on the submersible pump performance parameters, the ground immersion condition safety factor and the material matching factor.

[0168] In some embodiments, the second determining unit 106 may be specifically used to determine the selection power from a preset standard power sequence based on the submersible pump's required power; and to determine the target pump type of the submersible pump based on the selection power.

[0169] In some embodiments, the second determining unit 106 can also be used to determine the optimal flow range corresponding to the target pump type based on the submersible pump's required power and the selected power.

[0170] The third calculation unit 105 can also be used to calculate the optimal head range corresponding to the target pump type based on the safety factor of the ground immersion condition and the total head in the performance parameters of the submersible pump.

[0171] The third calculation unit 105 can also be used to calculate the efficiency operating range corresponding to the target pump type based on the total efficiency in the performance parameters of the submersible pump.

[0172] The second determining unit 106 can also be used to determine the optimal operating parameter range corresponding to the target pump type based on the optimal flow range, the optimal head range, and the efficiency operating range.

[0173] In some embodiments, the apparatus further includes a scoring unit.

[0174] The scoring unit can be used to score each material from the dimensions of wear, corrosion, adhesion, cost, and versatility, respectively, to obtain the wear score, corrosion score, adhesion score, cost score, and versatility score corresponding to each material.

[0175] The second determining unit 106 can also be used to determine the comprehensive score corresponding to each material based on the wear score, the corrosion score, the adhesion score, the cost score and the versatility score.

[0176] The second determining unit 106 can also be used to determine the highest comprehensive score based on the comprehensive score corresponding to each material, and to use the material corresponding to the highest comprehensive score as the recommended material.

[0177] In some embodiments, the apparatus further includes a generation unit.

[0178] The generation unit can be used to generate a comprehensive selection report for the submersible pump based on the selected power, the target pump type, the optimal flow range, the optimal head range, the efficiency operating range, and the recommended materials.

[0179] It should be noted that other corresponding descriptions of the functional units involved in the intelligent selection device for submersible pumps under complex conditions in in-situ leaching uranium mining provided in this embodiment can be found in [reference needed]. Figure 1 , Figure 2 and Figure 8 The corresponding description in [the document] will not be repeated here.

[0180] Based on the above, Figure 1 , Figure 2 and Figure 8 Accordingly, this embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the above-described method. Figure 1 , Figure 2 and Figure 8 The method for intelligent selection of submersible pumps under complex conditions in in-situ leaching uranium mining is shown.

[0181] Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause an electronic device (such as personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of this application.

[0182] Based on the above, Figure 1 , Figure 2 and Figure 8 The method shown, and Figure 9 To achieve the above objectives, the present application also provides an electronic device, specifically a personal computer, tablet computer, server, or other network device, as shown in the virtual device embodiment. This device includes a storage medium and a processor; the storage medium stores a computer program; the processor executes the computer program to achieve the above-described objectives. Figure 1 , Figure 2 and Figure 8 The method for intelligent selection of submersible pumps under complex conditions in in-situ leaching uranium mining is shown.

[0183] Optionally, the aforementioned physical devices may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB interfaces, card reader interfaces, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Wi-Fi interfaces), etc.

[0184] Those skilled in the art will understand that the physical device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0185] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the aforementioned physical device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0186] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platform, or it can be implemented by hardware.

[0187] This invention employs an improved Theis formula to calculate dynamic drawdown in real time, avoiding the inaccurate selection problems caused by fixed water level values ​​in existing technologies. This improves the accuracy of submersible pump selection and ensures its rationality. Simultaneously, this invention analyzes the impact of multiple factors on submersible pump performance through dynamic drawdown and parameter acquisition, constructs a multi-factor coupled performance reduction matrix, and calculates submersible pump performance parameters under actual operating conditions. This considers the coupling effect of multiple factors, further improving the accuracy of submersible pump selection.

[0188] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing this application. Those skilled in the art will understand that the modules in the apparatus of the embodiment can be distributed within the apparatus of the embodiment as described, or can be modified to be located in one or more apparatuses different from this embodiment. The modules of the above-described embodiment can be combined into one module, or further divided into multiple sub-modules.

[0189] The serial numbers in this application are for descriptive purposes only and do not represent the superiority or inferiority of any particular implementation scenario. The above disclosures are merely a few specific implementation scenarios of this application; however, this application is not limited thereto, and any variations conceived by those skilled in the art should fall within the protection scope of this application.

Claims

1. An intelligent selection method for a submersible pump for complex in-situ leaching of uranium, characterized in that, include: To obtain the acquisition parameters during the in-situ leaching uranium extraction process; Based on the collected parameters, the dynamic drawdown is calculated using the improved Theis formula, which incorporates a permeability correction factor, a well structure correction factor, and an organic viscosity correction factor. Based on the dynamic drawdown and the collected parameters, the influence of multiple factors on the performance of the submersible pump is determined. Based on the influence of the multiple factors on the performance of the submersible pump, a multi-factor coupling performance reduction matrix is ​​constructed, and the performance parameters of the submersible pump under actual working conditions are calculated based on the multi-factor coupling performance reduction matrix. Based on the submersible pump performance parameters, calculate the submersible pump power requirement under the actual operating conditions; Based on the power requirements of the submersible pump, the target pump type of the submersible pump is determined; The multiple factors include gas content, sand content, corrosion, and organic matter. The determination of the impact of these multiple factors on the submersible pump performance based on the dynamic drawdown and the collected parameters includes: Calculate the total head of the foundation based on the dynamic drawdown. Based on the collected parameters and the basic total head, the increase in head and efficiency reduction rate caused by gas inclusion are calculated respectively, and the power increment caused by gas inclusion is determined. Based on the increase in head, efficiency reduction rate, and power increment caused by the gas content, the impact of gas content on the performance of the submersible pump is determined. Based on the collected parameters and the basic total head, the increase in head and efficiency reduction rate caused by sand are calculated respectively, and the power increment caused by sand is determined. Based on the increase in head, efficiency reduction rate, and power increment caused by sand content, the impact of sand content on the performance of submersible pumps is determined. Based on the collected parameters, the increase in head and efficiency reduction rate caused by corrosion are calculated respectively, and the power increment caused by corrosion is determined. Based on the increase in head, efficiency reduction rate, and power increment caused by corrosion, the impact of corrosion on the performance of the submersible pump is determined. Based on the collected parameters, the increase in head, efficiency reduction rate, and power increment caused by organic matter are calculated respectively. The impact of organic matter on the performance of submersible pumps is determined based on the increase in head, efficiency reduction rate, and power increment caused by the organic matter. The calculation of submersible pump performance parameters under actual operating conditions based on the multi-factor coupling performance reduction matrix includes: Based on the influence of the aforementioned multiple factors on the performance of the submersible pump, a secondary coupling effect correction term is calculated. Based on the multi-factor coupling performance reduction matrix and the secondary coupling effect correction term, the total efficiency, total head, total power demand and blockage risk coefficient are calculated respectively. The submersible pump performance parameters under the actual operating conditions are determined based on the total efficiency, total head, total power requirement, and blockage risk coefficient. The step of calculating the submersible pump's required power under actual operating conditions based on the submersible pump's performance parameters includes: Based on the collected parameters, the safety factor and material matching factor for the ground immersion condition are calculated; Based on the submersible pump performance parameters, the ground immersion condition safety factor, and the material matching coefficient, the submersible pump power requirement under the actual operating conditions is calculated.

2. The method of claim 1, wherein, The collected parameters include geological parameters, wellbore parameters, operating condition parameters, and leachate parameters. The calculation of dynamic drawdown based on these collected parameters using the improved Theis formula includes: The basic permeability coefficient is corrected to obtain the permeability correction coefficient; Based on the wellbore parameters, calculate the wellbore structure correction coefficient; Based on the leachate parameters, calculate the viscosity correction factor for the organic matter; The dynamic drawdown is obtained by substituting the operating parameters, geological parameters, permeability correction coefficient, wellbore structure correction coefficient, and organic matter viscosity correction coefficient into the improved Thys formula.

3. The method of claim 1, wherein, Based on the collected parameters and the basic total head, the increase in head and efficiency reduction rate caused by gas inclusion are calculated respectively, and the power increment caused by gas inclusion is determined, including: Based on the collected parameters, the critical gas content, bubble size influence factor, and gas composition influence index were calculated respectively. Based on the collected parameters, the critical gas content, the bubble size influence factor, and the gas composition influence index, the efficiency under gas-containing conditions is calculated. Based on the efficiency under the gas-containing condition and the efficiency under the clear water condition, calculate the efficiency reduction rate caused by the gas content; Based on the collected parameters, the critical gas content, the bubble size influence factor, the gas composition influence index, and the basic total head, the increase in head caused by the gas content is calculated.

4. The method of claim 1, wherein, The calculation of the head increase and efficiency reduction rate caused by sand content, based on the collected parameters and the basic total head, includes: Based on the collected parameters, the particle impact velocity is calculated; The wear coefficient is calculated based on the particle impact velocity and the collected parameters; Based on the wear coefficient, the efficiency under sand-containing conditions is calculated; Calculate the efficiency reduction rate caused by sand content based on the efficiency under the sand-containing condition and the efficiency under the clear water condition. Based on the total head and the wear coefficient, the increase in head caused by sand content is calculated.

5. The method of claim 1, wherein, The calculation of the increase in head and efficiency reduction rate caused by corrosion based on the collected parameters includes: Based on the collected parameters, the acid-base influence coefficient, the flow velocity influence index, and the organic matter corrosion promotion factor were calculated respectively. The corrosion rate is calculated based on the pH influence coefficient, the flow rate influence index, and the organic corrosion promoting factor. Based on the corrosion rate, the increase in head and the efficiency reduction rate caused by the corrosion are calculated respectively.

6. The method of claim 1, wherein, The calculation of the head increase, efficiency reduction rate, and power increment caused by organic matter based on the collected parameters includes: Based on the collected parameters, the total solid volume fraction is calculated; Calculate the viscosity increase factor based on the total solid volume fraction; The viscosity of the mixture is calculated based on the viscosity increase factor and the total solid volume fraction. Based on the collected parameters, particle aggregation coefficient, and the influence coefficient of temperature on organic matter, the blockage probability is calculated. Based on the collected parameters, the adhesion efficiency factor is calculated; The adhesion wear coefficient is calculated based on the adhesion efficiency factor, the material adhesion coefficient, and the collected parameters. Based on the blockage probability, the viscosity of the mixture, and the adhesion and abrasion coefficient, the increase in head, efficiency reduction rate, and power increment caused by the organic matter are calculated respectively.

7. The method of claim 1, wherein, The step of determining the target pump type for the submersible pump based on its power requirements includes: Based on the submersible pump's required power, the selected power is determined from a preset standard power sequence; Based on the selected power, the target pump type of the submersible pump is determined.

8. The method of claim 7, wherein, The method further includes: Based on the submersible pump's required power and the selected power, determine the optimal flow range corresponding to the target pump type; Based on the safety factor for the ground immersion condition and the total head in the performance parameters of the submersible pump, the optimal head range corresponding to the target pump type is calculated. Based on the overall efficiency in the submersible pump performance parameters, calculate the efficiency operating range corresponding to the target pump type; Based on the optimal flow range, the optimal head range, and the efficiency operating range, the optimal operating parameter range corresponding to the target pump type is determined.

9. The method of claim 8, wherein, The method further includes: Each material is scored from the dimensions of wear, corrosion, adhesion, cost, and versatility, respectively, to obtain the wear score, corrosion score, adhesion score, cost score, and versatility score for each material. Based on the wear score, corrosion score, adhesion score, cost score, and versatility score, a comprehensive score is determined for each material. Based on the comprehensive scores of each material, the highest comprehensive score is determined, and the material corresponding to the highest comprehensive score is selected as the recommended material.

10. The method of claim 9, wherein, The method further includes: A comprehensive selection report for the submersible pump is generated based on the selected power, the target pump type, the optimal flow range, the optimal head range, the efficiency operating range, and the recommended materials.

11. An intelligent selection device for a submersible pump for in-situ leaching of uranium under complex conditions, characterized in that include: Acquisition unit, used to acquire acquisition parameters during the in-situ leaching uranium mining process; The first calculation unit is used to calculate the dynamic drawdown based on the collected parameters using the improved Theis formula, wherein the improved Theis formula introduces a permeability correction coefficient, a well structure correction coefficient, and an organic viscosity correction coefficient. The first determining unit is used to determine the influence of multiple factors on the performance of the submersible pump based on the dynamic drawdown and the collected parameters, wherein the multiple factors include gas content, sand content, corrosion and organic matter. The second calculation unit is used to construct a multi-factor coupling performance reduction matrix based on the influence of the multi-factors on the submersible pump performance, and to calculate the submersible pump performance parameters under actual working conditions based on the multi-factor coupling performance reduction matrix. The third calculation unit is used to calculate the submersible pump power requirement under the actual operating conditions based on the submersible pump performance parameters. The second determining unit is used to determine the target pump type of the submersible pump based on the power requirement of the submersible pump. The first determining unit is specifically used to calculate the total foundation head based on the dynamic drawdown; calculate the head increase and efficiency reduction rate caused by aeration based on the collected parameters and the total foundation head, and determine the power increment caused by aeration; determine the impact of aeration on the submersible pump performance based on the head increase, efficiency reduction rate, and power increment caused by aeration; calculate the head increase and efficiency reduction rate caused by sand based on the collected parameters and the total foundation head, and determine the power increment caused by sand; and determine the head increase and efficiency reduction rate caused by sand. The impact of sand content on submersible pump performance is determined by measuring the amount of sand, efficiency descent rate, and power increment. Based on the collected parameters, the increase in head and efficiency descent rate caused by corrosion are calculated, and the power increment caused by corrosion is determined. Based on the increase in head, efficiency descent rate, and power increment caused by corrosion, the impact of corrosion on submersible pump performance is determined. Based on the collected parameters, the increase in head, efficiency descent rate, and power increment caused by organic matter are calculated, and the impact of organic matter on submersible pump performance is determined. The second calculation unit is specifically used to calculate the secondary coupling effect correction term based on the influence of the multiple factors on the submersible pump performance; calculate the total efficiency, total head, total power demand and blockage risk coefficient based on the multi-factor coupling performance reduction matrix and the secondary coupling effect correction term; and determine the submersible pump performance parameters under the actual operating conditions based on the total efficiency, total head, total power demand and blockage risk coefficient. The third calculation unit is specifically used to calculate the safety factor and material matching coefficient for ground immersion conditions based on the collected parameters; and to calculate the submersible pump power requirement under the actual operating conditions based on the submersible pump performance parameters, the safety factor for ground immersion conditions, and the material matching coefficient.

12. A storage medium having stored thereon a computer program, characterized in that When the computer program is executed by a processor, it implements the method of any one of claims 1 to 10.

13. An electronic device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 10.

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