Solid waste ratio generation method and device, equipment and storage medium

Abstract

The invention belongs to the technical field of solid waste recycling, and discloses a solid waste ratio generation method, device and equipment and a storage medium. The method comprises the following steps: determining a plurality of particle size intervals based on the particle size characteristic of each solid waste, and determining the percentage content under sieve based on the median diameter of the plurality of particle size intervals; obtaining a porosity coefficient and an activity index coefficient according to the compressive strength, the porosity and the activity index of each solid waste component; performing coupling weighting according to the percentage content under the sieve, the porosity coefficient and the activity index coefficient to obtain the mixing percentage of each solid waste component under different particle sizes; optimizing the mixing amount percentage according to the actually measured undersize percentage content to obtain a solid waste ratio; by quantifying the physical, chemical and mechanical characteristics of the solid waste and performing multi-target coupling calculation, a matching scheme which can efficiently utilize the solid waste, ensure the high performance of the synthetic material and perform self-correction according to actual conditions is obtained, and the scientificity and reliability of solid waste resource utilization are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of solid waste recycling technology, and in particular to a method, apparatus, equipment and storage medium for generating solid waste proportioning. Background Technology

[0002] Addressing the environmental pollution and safety hazards caused by improper disposal and storage of industrial solid waste is of great significance for achieving industrial restructuring and energy conservation and emission reduction.

[0003] Geopolymers are cementing materials with SiO2 and Al2O3 as their main chemical components. They are prepared using an alkali-activated method, forming a three-dimensional network structure. They are commonly used in the building materials industry to optimize and replace high-CO2 emitting cement. With the continuous development of related technologies, the raw material system for geopolymers has become increasingly diverse, extending to industrial wastes such as slag, fly ash, desulfurization gypsum, and waste incineration fly ash. However, these raw materials are characterized by complex compositions and significant differences in particle size distribution. Currently, this field still requires extensive preliminary experiments to determine the optimal proportions of various solid waste raw materials. Most current multi-solid waste raw material proportioning design methods rely on blindly acquiring large amounts of data through experiments, followed by semi-empirical and semi-quantitative calculations and analyses. These methods require repeated verification and adjustments, lacking theoretical empirical formulas to plan experimental content and narrow the experimental scope. Summary of the Invention

[0004] In view of this, it is necessary to provide a method, apparatus, equipment and storage medium for generating solid waste proportions to solve the technical problem of low work efficiency caused by repeated testing and adjustment required for the proportioning of multiple solid waste raw materials.

[0005] To address the above problems, this invention provides a method for generating solid waste proportions, comprising: The total particle size range is determined based on the particle size characteristics of each solid waste, and the percentage of undersize particles in each particle size range is determined based on the median diameter of the largest particle size range in the total particle size range. The strength-porosity coefficient and strength-activity index coefficient of each solid waste are obtained based on the compressive strength, porosity and activity index of each solid waste. The strength-porosity coefficient is the correlation coefficient between the compressive strength and porosity of each solid waste, and the strength-activity index coefficient is the correlation coefficient between the compressive strength and activity index of each solid waste. The percentage content of each solid waste component in different particle size ranges is obtained by coupling and weighting the percentage content under sieve in each particle size range, the strength-porosity coefficient, and the strength-activity index coefficient. The percentage of each solid waste component in different particle size ranges is optimized based on the measured percentage content of each solid waste in each particle size range to obtain the solid waste ratio.

[0006] In one possible implementation, determining the total particle size range based on the particle size characteristics of each solid waste, and determining the undersize percentage of each particle size range based on the median diameter of the largest particle size range within the total particle size range, includes: Based on the particle size characteristics of each solid waste, the particle size range of each solid waste is obtained, and the particle size range of each solid waste is merged to obtain the total particle size range. Identify the largest particle size interval in the total particle size interval, and obtain the median diameter of the largest particle size interval based on the interval range of the largest particle size interval; The gradation correction index is obtained based on the median diameter of the maximum particle size range, and the undersize percentage content of each particle size range is obtained based on the gradation correction index and the maximum particle size range.

[0007] In one possible implementation, obtaining the gradation correction index based on the median diameter of the maximum particle size range, and obtaining the undersize percentage content of each particle size range based on the gradation correction index and the maximum particle size range, includes: The determination coefficient is obtained based on the median diameter of the maximum particle size range and the maximum particle size range. Determine the preset interval range in which the determination coefficient lies, and use the preset parameter corresponding to the preset interval range as the gradation correction index; The percentage of undersize particles in each particle size range is obtained based on the gradation correction index and the maximum particle size range.

[0008] In one possible implementation, obtaining the strength-porosity coefficient and strength-activity index coefficient of each solid waste based on its compressive strength, porosity, and activity index includes: The porosity of each solid waste is obtained based on its compact density and apparent density. The activity index of each solid waste is obtained based on the total amount of silicon and aluminum in the alkaline leachate and the total amount of silicon and aluminum in the raw material. The strength-porosity coefficient of each solid waste is obtained based on the compressive strength of each solid waste component and the porosity of each solid waste. The strength-activity index coefficient is obtained based on the compressive strength of each solid waste component and the activity index of each solid waste.

[0009] In one possible implementation, obtaining the strength-activity index coefficient based on the compressive strength of each solid waste component and the activity index of each solid waste includes: The total activity index is obtained by summing the activity indices of each solid waste. The initial coefficients are obtained based on the total activity index, the activity index, and the compressive strength. When the initial coefficient is less than or equal to a preset coefficient threshold, the preset coefficient threshold is used as the intensity-activity index coefficient; When the initial coefficient is greater than the preset coefficient threshold, the initial coefficient is used as the intensity-activity index coefficient.

[0010] In one possible implementation, the step of coupling and weighting the content of each solid waste component in different particle size ranges based on the percentage of undersize particles in each particle size range, the strength-porosity coefficient, and the strength-activity index coefficient includes: The proportioning parameters of each solid waste are calculated based on the strength-porosity coefficient and the strength-activity index coefficient of each solid waste. The total proportion of proportion parameters is obtained by summing the proportion parameters of each solid waste. The proportion parameter ratio is obtained by coupling calculation based on the proportion parameters of each solid waste and the total proportion parameters. The percentage of each solid waste component at different particle sizes is obtained by multiplying the ratio of the proportioning parameters and the percentage of undersize content in each particle size range.

[0011] In one possible implementation, optimizing the percentage of each solid waste component in different particle size ranges based on the measured percentage content of each solid waste in each particle size range to obtain the solid waste ratio includes: By comparing the measured percentage content of each solid waste under sieve and the percentage of each solid waste component at different particle sizes, the missing particle size range and missing content percentage of each solid waste are obtained. The vacant particle size range is merged into the adjacent particle size range to obtain a reference particle size range; the vacant doping percentage is merged into the percentage of the adjacent particle size range to obtain a reference percentage. Based on the reference particle size range and the reference percentage, the percentage of each solid waste component at different particle sizes is updated to obtain the solid waste ratio.

[0012] Furthermore, to achieve the above objectives, the present invention also proposes a solid waste proportioning and generation device, the solid waste proportioning and generation device comprising: The parameter calculation module is used to determine the total particle size range based on the particle size characteristics of each solid waste, and to determine the undersize percentage of each particle size range based on the median diameter of the largest particle size range in the total particle size range. The parameter calculation module is also used to obtain the strength-porosity coefficient and strength-activity index coefficient of each solid waste based on the compressive strength, porosity and activity index of each solid waste. The strength-porosity coefficient is the correlation coefficient between the compressive strength and porosity of each solid waste, and the strength-activity index coefficient is the correlation coefficient between the compressive strength and activity index of each solid waste. The parameter calculation module is also used to perform coupled weighting based on the percentage content under sieve of each particle size range, the strength-porosity coefficient and the strength-activity index coefficient to obtain the percentage of each solid waste component in different particle size ranges. The proportioning module is used to optimize the percentage of each solid waste component in different particle size ranges based on the measured percentage content of each solid waste in each particle size range, so as to obtain the solid waste proportion.

[0013] In addition, to achieve the above objectives, the present invention also proposes an electronic device, the electronic device comprising: a memory, a processor, a display, and a solid waste proportioning generation program stored in the memory and executable on the processor, the solid waste proportioning generation program being configured to implement the steps of the solid waste proportioning generation method as described above.

[0014] In addition, to achieve the above objectives, the present invention also proposes a storage medium storing a solid waste proportioning generation program, wherein when the solid waste proportioning generation program is executed by a processor, it implements the steps of the solid waste proportioning generation method described above.

[0015] The beneficial effects of adopting the above implementation method are as follows: By analyzing the particle size distribution of each solid waste and dividing it into intervals, the originally chaotic composition of solid waste particles is transformed into quantifiable and calculable mathematical parameters. By introducing compressive strength, porosity, and activity index, and converting them into porosity coefficient and activity index coefficient, it is ensured that the final formula not only has the optimal physical structure and chemical activity, but also guarantees mechanical properties. By coupling and weighting the percentage content under sieve, porosity coefficient, and activity index coefficient, multi-objective optimization is performed to obtain the preliminary dosage percentage, balancing the scientific results of the three major factors of particle filling, structural stability, and chemical activity. This avoids blind experiments, repeated verification and adjustment, and effectively improves work efficiency. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic flowchart of the first embodiment of the solid waste proportioning method of the present invention; Figure 2 This is a schematic flowchart of the second embodiment of the solid waste proportioning method of the present invention; Figure 3 This is a structural block diagram of the first embodiment of the solid waste proportioning and generation device of the present invention.

[0018] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention; Detailed Implementation The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0019] In the description of the embodiments of this application, unless otherwise stated, "a plurality of" means two or more.

[0020] In the embodiments of the present invention, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, apparatus, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such processes, methods, products or devices.

[0021] The naming or numbering of steps in the embodiments of the present invention does not mean that the steps in the method flow must be executed in the time / logical order indicated by the naming or numbering. The execution order of the named or numbered process steps can be changed according to the technical purpose to be achieved, as long as the same or similar technical effect can be achieved.

[0022] 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 the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] The executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or solid waste proportioning and generation device capable of performing the above functions. The following description uses a solid waste proportioning and generation device as an example to illustrate this embodiment and the subsequent embodiments.

[0024] This invention provides a method for generating solid waste proportions, referring to... Figure 1 , Figure 2 This is a schematic flowchart of the first embodiment of the solid waste proportioning method of the present invention.

[0025] In this embodiment, the solid waste proportioning method includes steps S10 to S40: Step S10: Determine the total particle size range based on the particle size characteristics of each solid waste, and determine the undersize percentage of each particle size range based on the median diameter of the largest particle size range in the total particle size range.

[0026] Understandably, particle size characteristics can refer to the particle size distribution of solid waste, which can be determined through sieving tests.

[0027] Understandably, the total particle size range is a redefined particle size region that includes the summation of the particle size ranges of various solid wastes.

[0028] It should be noted that the total particle size range of each solid waste is obtained by considering the particle size characteristics of each solid waste. For example, the particle size range of solid waste A is 1-20, and the particle size range of solid waste B is 5-40, so the total particle size range is 1-40. The total particle size range is then divided into multiple particle size intervals.

[0029] Understandably, the median diameter can be understood as the middle particle size value within a particle size range.

[0030] It is understood that the division method is not limited in this embodiment. It can be a uniform division or a division according to a preset ratio, and can be adjusted according to the actual situation.

[0031] It should be noted that the percentage of material passing through a sieve, also known as the pass rate or negative cumulative distribution, refers to the percentage of the total weight of material that passes through a standard sieve of a specific aperture in a sieving test.

[0032] For example, undersize refers to the smaller portion of material that can pass through the sieve, and percentage content refers to the weight percentage of this portion of material. For instance, for a sieve with an aperture of 2.36 mm, if the undersize percentage is 40%, it means that 40% of the particles in the solid waste sample have a particle size smaller than 2.36 mm.

[0033] It should be noted that each solid waste refers to a single solid waste that participates in the formulation; for example, a building material formula may contain "fly ash", "slag powder", "steel slag", "recycled aggregate from construction waste", etc., each of which is called a "solid waste".

[0034] Step S20: Obtain the strength-porosity coefficient and strength-activity index coefficient of each solid waste based on its compressive strength, porosity, and activity index. The strength-porosity coefficient is the correlation coefficient between the compressive strength and porosity of each solid waste, and the strength-activity index coefficient is the correlation coefficient between the compressive strength and activity index of each solid waste.

[0035] It should be noted that compressive strength refers to the maximum ability of a material to resist failure under pressure load. It is a core indicator for measuring the mechanical properties (load-bearing capacity) of a material, and the unit is usually megapascal (MPa). Compressive strength directly determines the mechanical strength and durability of the final composite material (such as concrete and roadbed materials). High-strength solid waste components can contribute more mechanical properties.

[0036] Furthermore, porosity refers to the percentage of pore volume in a material to the total volume, describing the density of the material. Materials with high porosity usually have lower strength and higher water absorption, but may have better water retention or thermal insulation. In the formulation, it is necessary to balance porosity, ensuring both strength (requiring low porosity) and sometimes other properties (such as thermal insulation and water permeability).

[0037] Furthermore, the activity index is a quantitative indicator specifically referring to the ability of industrial waste residues (such as fly ash and slag) to undergo chemical reactions and generate cementitious strength under alkaline or sulfate-induced activation. It is usually determined by the ratio to the strength of a benchmark cement mortar. Active solid waste (referred to as "auxiliary cementitious materials") can not only serve as fillers but also participate in hydration reactions to generate cementitious products, significantly improving the strength of the final product. This is key to the high-value utilization of solid waste.

[0038] It should be emphasized that the strength-porosity coefficient is an index that integrates two interrelated attributes: "compressive strength" and "porosity". It quantifies the contribution efficiency of the solid waste component to the material density while providing strength. The higher the value, the higher the strength that the material can provide per unit porosity and the better the efficiency.

[0039] It should be emphasized that the strength-activity index coefficient is an indicator that combines the two attributes of "compressive strength" and "activity index". It quantifies the "dual contribution" of the solid waste component in terms of both mechanical strength and chemical activity. The higher the value, the better the material is as both a good aggregate and a good cementitious material.

[0040] In one feasible implementation, step S20 may include steps A21 to A24: Step A21: Obtain the porosity of each solid waste based on its compact density and apparent density.

[0041] It should be understood that compaction density refers to the mass per unit volume of powdered or granular materials after they have been packed tightly according to a specified method (such as by vibration or the application of a certain pressure). The unit is usually kilograms per cubic meter (kg / m³) or grams per cubic centimeter (g / cm³). It represents the densest state that granular materials can achieve when large air pores between particles are eliminated as much as possible. It is close to the sum of the volume of the granular material itself (including the closed pores inside the particles) and the volume of the smallest void between the particles.

[0042] It should be understood that apparent density refers to the mass per unit volume of a material in its natural state (including the internal pores of the material). For particulate materials, this "natural state" usually refers to a loosely packed state that has not been strongly compacted, reflecting the density of the material itself. It also includes the volume of open and closed pores that can be filled with water, and is an inherent physical property of the material.

[0043] It should be noted that the porosity described here refers to the porosity between particles, not the porosity inside the particles.

[0044] Furthermore, apparent density is obtained through a liquid displacement method (such as the specific gravity bottle method), where the volume of liquid displaced is equal to the actual volume of the particles (including internal pores); compacted density is usually obtained by filling powder or granular material into a container of known volume, using standardized vibration or tamping methods to achieve the densest state, and then weighing and calculating the density.

[0045] It should be noted that the porosity of each solid waste can be obtained by referring to the following formula based on its compact density and apparent density:

[0046] in, These represent compact density and apparent density, respectively, with P representing porosity.

[0047] Step A22: Obtain the activity index of each solid waste based on the total amount of silicon and aluminum in the alkaline leaching solution and the total amount of silicon and aluminum in the raw material.

[0048] It should be noted that the alkali leaching solution in the total amount of silicon and aluminum in the alkali leaching solution refers to the solution obtained by soaking solid waste samples under specific conditions (such as specified temperature, time, and alkali concentration, commonly NaOH or KOH solution), in order to simulate the dissolution behavior of solid waste in an alkaline environment (such as the pore solution produced by cement hydration).

[0049] The total amount of silicon and aluminum refers to the total molar concentration or total mass concentration of silicon (Si) and aluminum (Al) elements dissolved in the above-mentioned alkaline leaching solution. It is the core reactant for the formation of cementitious products such as calcium silicate hydrate (CSH) and calcium aluminate hydrate.

[0050] Ultimately, it should be understood that the total amount of silicon and aluminum in the alkaline leachate represents the amount of effective silicon and aluminum components that can be released and participate in the gelation reaction in an alkaline environment, and measures the reaction potential of the solid waste.

[0051] It should be emphasized that the raw material in the total amount of silicon and aluminum in the raw material can refer to the original solid waste that has not been soaked in alkaline solution; the total amount of silicon and aluminum in the raw material refers to the total molar amount or total mass of all silicon (Si) and aluminum (Al) elements in the solid waste, which can be measured by composition analysis techniques such as X-ray fluorescence (XRF).

[0052] The total amount of silicon and aluminum in the raw materials represents the total amount of silicon and aluminum components in the solid waste that can theoretically be reacted, and is a benchmark value.

[0053] It should be understood that the total silica and aluminum content in the alkaline leaching solution and the total silica and aluminum content in the raw material specifically refer to the potential activity that can be rapidly assessed through this chemical leaching method. This allows for the prediction of the material's chemical contribution capacity before its use. The activity index can be calculated using the following formula:

[0054] Where ω represents the activity index; These represent the total amount of silicon and aluminum in the alkaline leachate and solid waste raw materials, respectively.

[0055] Step A23: Obtain the strength-porosity coefficient of each solid waste based on the compressive strength of each solid waste component and the porosity of each solid waste.

[0056] It should be noted that the strength-porosity coefficient can be calculated using the following formula:

[0057] in, Indicates the strength-porosity coefficient. This represents compressive strength, and m represents m specific solid waste components. This represents the porosity of the m-th type of solid waste; It represents the total porosity of various solid wastes.

[0058] Step A24: Obtain the strength-activity index coefficient based on the compressive strength of each solid waste component and the activity index of each solid waste.

[0059] It should be noted that the strength-activity index coefficient can be calculated using the following formula:

[0060] in, Indicates the strength-activity index coefficient. This represents the activity index of the m-th type of solid waste. It represents the total activity index of various solid wastes.

[0061] It should be noted that the step of obtaining the strength-activity index coefficient based on the compressive strength of each solid waste component and the activity index of each solid waste includes: summing the activity indices of each solid waste to obtain a total activity index; obtaining an initial coefficient based on the total activity index, the activity index, and the compressive strength; when the initial coefficient is less than or equal to a preset coefficient threshold, using the preset coefficient threshold as the strength-activity index coefficient; and when the initial coefficient is greater than the preset coefficient threshold, using the initial coefficient as the strength-activity index coefficient.

[0062] It should be noted that, considering that inactive solid waste can also play a certain role in supporting the skeleton and thus enhancing strength, the strength-activity index coefficient needs to be limited.

[0063] Furthermore, among them When the value is less than a preset coefficient threshold, the preset coefficient threshold will be used as the new threshold. ;exist When the value is greater than or equal to the preset coefficient threshold, The preset coefficient threshold can be set to 0.0005 or other data. This embodiment does not limit this and can be adjusted according to the actual situation.

[0064] In this embodiment, the porosity between particles is indirectly and accurately calculated using readily available density parameters. Chemical activity indicators are obtained by combining the total amount of silica and aluminum in the alkaline leaching solution with the original total amount of silica and aluminum. This "reduces" and "quantifies" the complex and multidimensional physical and chemical properties of solid waste into a set of standardized and comparable coefficients, thereby providing accurate and reliable input parameters for subsequent multi-objective optimization ratio models. It can simultaneously weigh the different capabilities of materials in terms of packing density, mechanical contribution, and chemical contribution, thus calculating the optimal ratio scientifically rather than empirically.

[0065] The above are merely feasible implementations of step S20 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S20.

[0066] Step S30: Based on the percentage content under sieve in each particle size range, the strength-porosity coefficient, and the strength-activity index coefficient, a coupled weighted sum is performed to obtain the percentage of each solid waste component in different particle size ranges.

[0067] It should be noted that a component-particle size coupling model can be constructed based on the percentage of undersize content in each particle size range, the strength-porosity coefficient, and the strength-activity index coefficient. Based on the component-particle size coupling model, the percentage of undersize content of each solid waste can be directly calculated.

[0068] This can also be understood as follows: a calculation formula is constructed based on the percentage of undersize particles in each particle size range, the strength-porosity coefficient, and the strength-activity index coefficient. Based on this calculation formula, the percentage of undersize particles at different particle sizes of various solid wastes can be obtained.

[0069] It should be noted that the coupling weighting can be understood as assigning different dosing percentages to different particle sizes of solid waste based on the percentage content undersize in each particle size range.

[0070] In one feasible implementation, step S30 may include steps A31 to A33: Step A31: Calculate the proportioning parameters of each solid waste based on the strength-porosity coefficient and the strength-activity index coefficient of each solid waste.

[0071] It should be noted that the following formulas can be used to calculate the proportioning parameters of each solid waste based on its strength-porosity coefficient and strength-activity index coefficient:

[0072] Step A32: Summing the proportioning parameters of each solid waste to obtain the total proportioning parameters, and performing coupled calculations based on the proportioning parameters of each solid waste and the total proportioning parameters to obtain the proportioning parameter ratio.

[0073] It should be noted that the summation of the proportioning parameters for each solid waste can be done using the following formula:

[0074] Where M represents the number of solid waste types.

[0075] Furthermore, the ratio of the proportioning parameters obtained by coupling calculation based on the proportioning parameters of each solid waste and the sum of the proportioning parameters can be expressed as:

[0076] Step A33: Multiply the ratio of the proportioning parameters and the percentage of undersize content in each particle size range to obtain the percentage of each solid waste component at different particle sizes.

[0077] It should be noted that the percentage of admixture can be calculated using the following formula:

[0078] It should be noted that the particle sizes d1, d2, ..., d of the m-th type of solid waste are... n-1 and d n The percentage content of the sieve was F m-d1 F m-d2 ..., F m-d（n-1） and Fm-dn The percentage of the m-th type of solid waste with a particle size smaller than d1 is then determined. For F m-d1 The percentage of the m-th type of solid waste in particle sizes d1 to d2 for ..., the mth type of solid waste d n ~d n-1 Particle size percentage for .

[0079] In this embodiment, the percentage of solid waste passing through the sieve at different particle sizes is combined with the strength-porosity coefficient and strength-activity index coefficient of each solid waste to achieve a refined ratio. This precisely indicates which solid waste, in which particle size range, and how much percentage should be added, thus generating a refined formula that ensures both high product performance and processability while maximizing the utilization of solid waste.

[0080] The above are merely feasible implementations of step S30 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S30.

[0081] Step S40: Optimize the percentage of each solid waste component in different particle size ranges based on the measured percentage content under the sieve in each particle size range to obtain the solid waste ratio.

[0082] It should be understood that the percentage of each solid waste component at different particle sizes is based on the optimal percentage of each solid waste component at different particle sizes that can be achieved by considering the strength-porosity coefficient, strength-activity index coefficient, and compressive strength of each solid waste. However, the percentage of some solid wastes under the sieve at different particle sizes may not meet the percentage required for optimal performance and needs to be optimized.

[0083] It should be noted that optimizing the percentage of each solid waste component at different particle sizes can be understood as optimizing the particle size distribution based on the particle size characteristics of different solid wastes, specifically d1, d2, ..., d... n-1 and d n The measured percentage content of Q under sieve m-d1 Q m-d2 ... Q m-d（n-1） and Q m-dn ;If there is Q m-d1 Or Q m-di+1 -Q m-diIf (1≤i<n)≤1%, then according to the principle that the activity index of the performance of the all-solid waste cementitious material has a higher priority than the particle size distribution effect, the actual content of this particle size and the theoretically required content are replaced by the higher content of the adjacent particle size of the raw material to achieve reasonable consumption of solid waste raw materials. Similarly, if the demand for a certain particle size is much greater than the particle size of the current raw material in the actual batching process, the insufficient part can also be replaced by the higher content of the adjacent particle size. Thus, the design of the solid waste content of the all-solid waste-based cementitious material that meets the actual production application can be obtained.

[0084] In one feasible implementation, step S40 may include steps A41 to A43: Step A41: Compare the measured percentage content of each solid waste under sieve with the percentage of each solid waste component at different particle sizes to obtain the missing particle size range and missing content percentage of each solid waste.

[0085] It is understandable that the measured percentage content under the sieve of each solid waste can be interpreted as the actual percentage content of the solid waste in each particle size range; the percentage of each solid waste component at different particle sizes can be interpreted as the percentage content required by the theoretically optimal formula for that solid waste at that particle size.

[0086] In practice, the theoretical formulation requires a certain amount of solid waste in a specific particle size range (e.g., 0.3mm-0.6mm) (e.g., 10%), which is then compared with the actual content of that solid waste in the same particle size range (e.g., only 2% as measured). If the theoretical demand exceeds the actual content, creating a demand gap, this gap (0.3mm-0.6mm) is marked as the "vacant particle size range," and the size of the gap (10%-2%=8%) is the "vacant dosage percentage."

[0087] It should be emphasized that if the percentage content under the screen of a certain particle size of solid waste differs from the percentage content under the screen of adjacent particle size range by less than or equal to 1%, that particle size will also be regarded as a missing particle size range, and the percentage content of the missing particle size range will be merged.

[0088] Step A42: Merge the vacant particle size range into the adjacent particle size range to obtain a reference particle size range, and merge the vacant doping percentage into the percentage of the adjacent particle size range to obtain a reference percentage.

[0089] Understandably, the adjacent particle size range can be the particle size range that is closest to the particle size of the vacant particle size range.

[0090] It should be noted that the logic for filling missing particle size intervals is that since there is not enough material in this particle size interval (the missing particle size), the material in the adjacent coarser interval (the adjacent particle size interval) is used to replace it, because coarse and fine particles have a certain substitution and complementary effect in filling gaps.

[0091] In practice, the "adjacent particle size range" usually refers to an adjacent range that is coarser than the "gap particle size range". For example, if the gap is 0.3mm-0.6mm, the adjacent particle size range may be 0.6mm-1.18mm.

[0092] Furthermore, the reference particle size range is the new particle size range formed after merging (for example, merging 0.3mm-0.6mm into 0.6mm-1.18mm, the new reference particle size may be 0.3mm-1.18mm); the reference percentage is the new doping requirement after merging (for example, the original 0.6mm-1.18mm range required an increase of 15%, and now the 8% gap in 0.3mm-0.6mm is added, the new reference percentage is 23%).

[0093] Step A43: Update the percentage of each solid waste component at different particle sizes based on the reference particle size range and the reference percentage to obtain the solid waste ratio.

[0094] It should be noted that the original percentages of parameters for each solid waste have been revised based on the reference particle size range and the reference percentages to better reflect the actual raw material composition in industrial production.

[0095] In this embodiment, by automatically identifying the specific particle size range and gap magnitude that do not match the theoretical formula of solid waste raw materials, adaptive adjustment is achieved by using adjacent substitution to merge particle size ranges and redistribute dosage. An executable ratio based on actual material characteristics is output, realizing the precise transformation from theoretical ratio to production practice. This solves the core contradiction between raw material volatility and product stability in the process of solid waste resource utilization, and provides key technical support for large-scale industrial application.

[0096] The above are merely feasible implementations of step S40 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S40.

[0097] For example, Example 1 illustrates a component-particle size coupling efficient integrated model design method for fly ash, red mud, and granite powder, which determines the maximum particle size d based on the characteristics of the above solid wastes. max =130.36μm and minimum particle size d min =0.8μm, and based on application requirements, it is divided into 6 particle size ranges: d1=0.8μm, d2=2μm, d3=10μm, d4=35μm, d5=50μm, and d6=130.36μm. The particle size characteristics of the measured percentage content under sieves of the three raw materials are shown in Table 1 below: Table 1

[0098] According to the determination coefficient f = 15.32 / 130.36 - 0.2 = -0.08 .

[0099] Among them, the acceptable .

[0100] Percentage content after screening We can then obtain: , , , , , 100.00%.

[0101] Based on the compacted density, apparent density, and alkaline leaching silica-alumina content of the above three types of solid waste, the porosity and activity index were further calculated: P 粉煤灰 = (1 - 1834 / 2273) × 100% = 0.193 P 赤泥 = (1 - 1982 / 2463) × 100% = 0.195 P 花岗岩石粉 = (1 - 1566 / 2572) × 100% = 0.391

[0102]

[0103]

[0104] Further, based on the 28-day compressive strength of the cementitious materials prepared separately by each solid waste under the same process: Y fly ash = 37.8 MPa, Y red mud = 17.8 MPa, Y granite powder = 6.9 MPa.

[0105] Calculate their respective strength-porosity coefficients and strength-activity index coefficients, then we have:

[0106]

[0107]

[0108]

[0109]

[0110]

[0111] The specific calculations for the percentage content under the sieve of each particle size of each solid waste, based on the component-particle size coupling model, are not detailed here. For the percentage dosage of each solid waste at different particle sizes, please refer to Table 2. Table 2

[0112] Based on the measured particle size characteristics in Table 1 of the raw materials, the optimal dosage of fly ash for each particle size can be determined: + , , .

[0113] Optimal dosage of red mud of each particle size: =1.10%

[0114] Optimal Dosage of Granite Powder in Each Particle Size =0.23%, .

[0115] Based on the above ratio, the polymer compressive strength of the multi-solid waste base can reach over 52.7 MPa, which is more than 39% higher than the highest mechanical properties of a single solid waste.

[0116] For example, Example 2 illustrates a component-particle size coupling efficient integrated model design method for coal slag and activated granite powder (activated stone powder). The particle size characteristics of the raw materials are shown in Table 3. The maximum particle size d is determined based on the characteristics of the solid waste. max =115.10 Reference particle size range (μm) and minimum particle size (d) min =0.8 reference particle size interval μm. According to application requirements, it is divided into 6 particle size intervals: d1=0.8 reference particle size interval μm, d2=2 reference particle size interval μm, d3=10 reference particle size interval μm, d4=35 reference particle size interval μm, d5=50 reference particle size interval μm, and d6=115.10 reference particle size interval μm.

[0117] The specific calculation steps are not detailed here. Table 3 shows the particle size characteristics of the measured percentage content under the sieve for the two raw materials, and Table 4 shows the theoretical parameter percentage content calculated by the model for the two raw materials. Table 3

[0118] Table 4

[0119] Based on the measured particle size characteristics in Table 1, the optimal dosage of each particle size of coal slag can be determined: .

[0120] Optimal Dosage of Activated Stone Powder in Each Particle Size =2.14% However, considering the actual situation of living fossil powder Therefore, in order to conform to actual production applications, it was adjusted to .

[0121] The polymer compressive strength of the multi-solid waste substrate prepared under these parameters can reach over 34.7 MPa, which is more than 35% higher than the highest mechanical properties of a single solid waste.

[0122] This embodiment provides a method for generating solid waste formulations. By analyzing the particle size distribution of various solid wastes and dividing them into intervals, the originally chaotic composition of solid waste particles is transformed into quantifiable and calculable mathematical parameters. By introducing compressive strength, porosity, and activity index, and converting them into porosity coefficient and activity index coefficient, it is ensured that the final formulation not only has the optimal physical structure and chemical activity, but also guarantees mechanical properties. The percentage content under sieve, porosity coefficient, and activity index coefficient are coupled and weighted for multi-objective optimization. This results in a preliminary dosage percentage that balances the scientific results of particle filling, structural stability, and chemical activity. The measured percentage content under sieve is introduced to verify and optimize the theoretical value, taking into account the deviation caused by the fluctuation of actual materials. This gives the formulation scheme an adaptive adjustment capability, ensuring the reliability and stability of the formulation results.

[0123] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 Step S10, the solid waste proportioning method further includes steps S11 to S13: Step S11: Based on the particle size characteristics of each solid waste, obtain the particle size range of each solid waste, and merge the particle size ranges of each solid waste to obtain the total particle size range.

[0124] Understandably, the starting point of the total particle size range is the smallest particle size of all solid wastes, and the ending point is the largest particle size of all solid wastes.

[0125] Understandably, the particle size range is different for each type of solid waste.

[0126] In practical implementation, based on the particle size characteristics of each solid waste, according to the maximum particle size d max To the minimum particle size d min Divided into n granular intervals, denoted by d i (1≤i≤n) represents the particle size of each grade as the independent variable.

[0127] Step S12: Identify the largest particle size interval in the total particle size interval, and obtain the median diameter of the largest particle size interval based on the interval range of the largest particle size interval.

[0128] It should be understood that the maximum particle size range refers to the particle size range with the largest value among all particle size ranges. For example, if 1-40 is divided into two ranges, 0-5, 5-15, 15-30, and 30-35, where 30-35 is the maximum particle size range, then the range is 5, and the median diameter of the maximum particle size range is 32.5.

[0129] Step S13: Obtain the gradation correction index based on the median diameter of the maximum particle size range, and obtain the undersize percentage content of each particle size range based on the gradation correction index and the maximum particle size range.

[0130] It should be noted that the calculation of the percentage content under sieve is based on the closest packing theory and is derived from an empirical formula.

[0131] In one feasible implementation, step S13 may include steps A131 to A133: Step A131: Obtain the determination coefficient based on the median diameter of the maximum particle size range and the maximum particle size range.

[0132] It should be noted that the judgment coefficient can be understood as a value used to determine the range of values ​​for the gradation correction index.

[0133] Furthermore, the coefficient of determination can be calculated using the following formula:

[0134] Where D50 is the median diameter of the largest particle size solid waste, and f represents the determination coefficient.

[0135] Step A132: Determine the preset interval range in which the determination coefficient is located, and use the preset parameter corresponding to the preset interval range as the gradation correction index.

[0136] Understandably, the preset range includes three ranges: less than or equal to -0.14, greater than -0.14 and less than or equal to 0.24, and greater than 0.24.

[0137] It should be noted that the preset range can be based on experience or experimental data, or it can be adjusted according to the actual situation. This embodiment is used as an example for illustration and is not limited thereto.

[0138] Furthermore, when the determination coefficient is less than or equal to -0.14, the corresponding preset parameter is 0; when the determination coefficient is greater than -0.14 and less than or equal to 0.24, the corresponding preset parameter is 0.12; and when the determination coefficient is greater than 0.24, the corresponding preset parameter is 0.24. The corresponding preset parameter is used as the gradation correction index.

[0139] Step A133: Obtain the percentage content under sieve for each particle size range based on the gradation correction index and the maximum particle size range.

[0140] Understandably, the gradation correction index and the maximum particle size range are substituted into the following empirical formula:

[0141] in, This represents the i-th particle size range. This represents the maximum particle size range, and q represents the gradation correction index. This indicates the percentage of particles passing through the sieve in each particle size range.

[0142] In this embodiment, the determination coefficient is obtained by using the median diameter of the maximum particle size range and the maximum particle size range. Then, the corresponding gradation correction index is obtained by taking the value of the determination coefficient to calculate the percentage content of undersize in each particle size range. By combining the theoretical formula with the median diameter of the actual maximum particle size solid waste, the "personalization" and "precision" of the percentage ratio of each particle size range are realized.

[0143] The above are merely feasible implementations of step S13 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S13.

[0144] This embodiment provides a solid waste ratio generation method that accurately captures the distribution characteristics of coarse particles by using the median diameter of the maximum particle size range, fully reflecting the particle size characteristics of each solid waste. It can take into account both the complexity of the raw material composition and the diversity of particle size distribution, providing precise guidance for the reasonable ratio of different solid wastes. This is beneficial for the subsequent coupling of the effects of both components and particle size, fully exploring the potential gelling properties of solid waste raw materials, and achieving their efficient utilization and precise ratio.

[0145] To better implement the solid waste proportioning method in this embodiment of the invention, based on the solid waste proportioning method, correspondingly, as follows: Figure 3 As shown, this embodiment of the invention also provides a solid waste proportioning and generation device, the solid waste proportioning and generation device 300 comprising: The parameter calculation module 301 is used to determine the total particle size range based on the particle size characteristics of each solid waste, and to determine the undersize percentage of each particle size range based on the median diameter of the largest particle size range in the total particle size range. The parameter calculation module 301 is also used to obtain the strength-porosity coefficient and strength-activity index coefficient of each solid waste based on the compressive strength, porosity and activity index of each solid waste. The parameter calculation module 301 is also used to perform coupled weighting based on the percentage content under sieve of each particle size range, the strength-porosity coefficient and the strength-activity index coefficient to obtain the percentage of each solid waste component in different particle size ranges. The proportioning module 302 is used to optimize the percentage of each solid waste component in different particle size ranges based on the measured percentage content of each solid waste in each particle size range, so as to obtain the solid waste proportion.

[0146] The solid waste proportioning generation device 300 provided in the above embodiments can realize the technical solutions described in the above solid waste proportioning generation method embodiments. The specific implementation principles of each module or unit can be found in the corresponding content in the above solid waste proportioning generation method embodiments, and will not be repeated here.

[0147] like Figure 4 As shown, the present invention also provides an electronic device 400. The electronic device 400 includes a processor 401, a memory 402, and a display 403. Figure 4 Only some components of the electronic device 400 are shown, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead.

[0148] In some embodiments, memory 402 may be an internal storage unit of electronic device 400, such as a hard disk or memory of electronic device 400. In other embodiments, memory 402 may also be an external storage device of electronic device 400, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on electronic device 400.

[0149] Furthermore, the memory 402 may include both internal storage units of the electronic device 400 and external storage devices. The memory 402 is used to store application software and various types of data installed on the electronic device 400.

[0150] In some embodiments, processor 401 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 402 or process data, such as the solid waste ratio generation method of the present invention.

[0151] In some embodiments, display 403 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 403 is used to display information from electronic device 400 and to display a visual user interface. Components 401-403 of electronic device 400 communicate with each other via a system bus.

[0152] In some embodiments of the present invention, when the processor 401 executes the solid waste proportioning generation program in the memory 402, the following steps can be implemented: The total particle size range is determined based on the particle size characteristics of each solid waste, and the percentage of undersize particles in each particle size range is determined based on the median diameter of the largest particle size range in the total particle size range. The strength-porosity coefficient and strength-activity index coefficient of each solid waste are obtained based on the compressive strength, porosity, and activity index of each solid waste. The percentage content of each solid waste component in different particle size ranges is obtained by coupling and weighting the percentage content under sieve in each particle size range, the strength-porosity coefficient, and the strength-activity index coefficient. The percentage of each solid waste component in different particle size ranges is optimized based on the measured percentage content of each solid waste in each particle size range to obtain the solid waste ratio.

[0153] It should be understood that when the processor 401 executes the solid waste ratio generation program in the memory 402, in addition to the functions mentioned above, it can also perform other functions, as can be found in the description of the corresponding method embodiments above.

[0154] Furthermore, the embodiments of the present invention do not specifically limit the type of electronic device 400 mentioned. Electronic device 400 can be a mobile phone, tablet computer, personal digital assistant (PDA), wearable device, laptop computer, or other portable electronic device. Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices running iOS, Android, Microsoft, or other operating systems. The aforementioned portable electronic device can also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, electronic device 400 may not be a portable electronic device, but rather a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0155] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the solid waste proportioning generation method provided by the methods described above, the method comprising: The total particle size range is determined based on the particle size characteristics of each solid waste, and the percentage of undersize particles in each particle size range is determined based on the median diameter of the largest particle size range in the total particle size range. The strength-porosity coefficient and strength-activity index coefficient of each solid waste are obtained based on the compressive strength, porosity, and activity index of each solid waste. The percentage content of each solid waste component in different particle size ranges is obtained by coupling and weighting the percentage content under sieve in each particle size range, the strength-porosity coefficient, and the strength-activity index coefficient. The percentage of each solid waste component in different particle size ranges is optimized based on the measured percentage content of each solid waste in each particle size range to obtain the solid waste ratio.

[0156] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0157] The solid waste proportioning method provided by the present invention has been described in detail above. Specific examples have been used to illustrate the principle and implementation of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation and application scope based on the idea of ​​the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for generating solid waste by proportioning, characterized in that, include: The total particle size range is determined based on the particle size characteristics of each solid waste, and the percentage of undersize particles in each particle size range is determined based on the median diameter of the largest particle size range in the total particle size range. The strength-porosity coefficient and strength-activity index coefficient of each solid waste are obtained based on the compressive strength, porosity and activity index of each solid waste. The strength-porosity coefficient is the correlation coefficient between the compressive strength and porosity of each solid waste, and the strength-activity index coefficient is the correlation coefficient between the compressive strength and activity index of each solid waste. The percentage content of each solid waste component in different particle size ranges is obtained by coupling and weighting the percentage content under sieve in each particle size range, the strength-porosity coefficient, and the strength-activity index coefficient. The percentage of each solid waste component in different particle size ranges is optimized based on the measured percentage content of each solid waste in each particle size range to obtain the solid waste ratio.

2. The solid waste proportioning method as described in claim 1, characterized in that, The determination of the total particle size range based on the particle size characteristics of each solid waste, and the determination of the undersize percentage content of each particle size range based on the median diameter of the largest particle size range within the total particle size range, include: Based on the particle size characteristics of each solid waste, the particle size range of each solid waste is obtained, and the particle size range of each solid waste is merged to obtain the total particle size range. Identify the largest particle size interval in the total particle size interval, and obtain the median diameter of the largest particle size interval based on the interval range of the largest particle size interval; The gradation correction index is obtained based on the median diameter of the maximum particle size range, and the undersize percentage content of each particle size range is obtained based on the gradation correction index and the maximum particle size range.

3. The solid waste proportioning method as described in claim 2, characterized in that, The step of obtaining the gradation correction index based on the median diameter of the maximum particle size range, and obtaining the undersize percentage content of each particle size range based on the gradation correction index and the maximum particle size range, includes: The determination coefficient is obtained based on the median diameter of the maximum particle size range and the maximum particle size range. Determine the preset interval range in which the determination coefficient lies, and use the preset parameter corresponding to the preset interval range as the gradation correction index; The percentage of undersize particles in each particle size range is obtained based on the gradation correction index and the maximum particle size range.

4. The solid waste proportioning method as described in claim 1, characterized in that, The process of obtaining the strength-porosity coefficient and strength-activity index coefficient for each solid waste based on its compressive strength, porosity, and activity index includes: The porosity of each solid waste is obtained based on its compact density and apparent density. The activity index of each solid waste is obtained based on the total amount of silicon and aluminum in the alkaline leachate and the total amount of silicon and aluminum in the raw material. The strength-porosity coefficient of each solid waste is obtained based on the compressive strength of each solid waste component and the porosity of each solid waste. The strength-activity index coefficient is obtained based on the compressive strength of each solid waste component and the activity index of each solid waste.

5. The solid waste proportioning method as described in claim 4, characterized in that, The process of obtaining the strength-activity index coefficient based on the compressive strength of each solid waste component and the activity index of each solid waste includes: The total activity index is obtained by summing the activity indices of each solid waste. The initial coefficients are obtained based on the total activity index, the activity index, and the compressive strength. When the initial coefficient is less than or equal to a preset coefficient threshold, the preset coefficient threshold is used as the intensity-activity index coefficient; When the initial coefficient is greater than the preset coefficient threshold, the initial coefficient is used as the intensity-activity index coefficient.

6. The solid waste proportioning method as described in claim 1, characterized in that, The percentage of solid waste components in different particle size ranges is obtained by coupling and weighting the content of undersize particles in each particle size range, the strength-porosity coefficient, and the strength-activity index coefficient, including: The proportioning parameters of each solid waste are calculated based on the strength-porosity coefficient and the strength-activity index coefficient of each solid waste. The total proportion of proportion parameters is obtained by summing the proportion parameters of each solid waste. The proportion parameter ratio is obtained by coupling calculation based on the proportion parameters of each solid waste and the total proportion parameters. The percentage of each solid waste component at different particle sizes is obtained by multiplying the ratio of the proportioning parameters and the percentage of undersize content in each particle size range.

7. The solid waste proportioning method as described in claim 1, characterized in that, The optimization of the dosage percentage of each solid waste component in different particle size ranges based on the measured percentage content of each solid waste in each particle size range, to obtain the solid waste ratio, includes: By comparing the measured percentage content of each solid waste under sieve and the percentage of each solid waste component at different particle sizes, the missing particle size range and missing content percentage of each solid waste are obtained. The vacant particle size range is merged into the adjacent particle size range to obtain a reference particle size range; the vacant doping percentage is merged into the percentage of the adjacent particle size range to obtain a reference percentage. Based on the reference particle size range and the reference percentage, the percentage of each solid waste component at different particle sizes is updated to obtain the solid waste ratio.

8. A solid waste proportioning and generation device, characterized in that, The solid waste formulation includes: The parameter calculation module is used to determine the total particle size range based on the particle size characteristics of each solid waste, and to determine the undersize percentage of each particle size range based on the median diameter of the largest particle size range in the total particle size range. The parameter calculation module is also used to obtain the strength-porosity coefficient and strength-activity index coefficient of each solid waste based on the compressive strength, porosity and activity index of each solid waste. The strength-porosity coefficient is the correlation coefficient between the compressive strength and porosity of each solid waste, and the strength-activity index coefficient is the correlation coefficient between the compressive strength and activity index of each solid waste. The parameter calculation module is also used to perform coupled weighting based on the percentage content under sieve of each particle size range, the strength-porosity coefficient and the strength-activity index coefficient to obtain the percentage of each solid waste component in different particle size ranges. The proportioning module is used to optimize the percentage of each solid waste component in different particle size ranges based on the measured percentage content of each solid waste in each particle size range, so as to obtain the solid waste proportion.

9. An electronic device, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps of the solid waste proportioning generation method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the solid waste proportioning generation method as described in any one of claims 1 to 7.

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