An Optimization Method and System for the Mix Ratio of a Solidifying Material for Dredged Silt with All Industrial Waste Residues

Abstract

The present invention discloses a method and system for optimizing the proportioning of a solidifying material for dredged sludge with all industrial waste residues, including: according to the synergistic solidification mechanism of volcanic ash, alkali and sulfate, conducting proportioning tests on dredged sludge using cement, mineral powder and desulfurized gypsum to determine the optimal dosage of each material, and giving the mass ratios of chemical components SO3 / Al2O3, CaO / Al2O3, (CaO + MgO) / SiO2; investigating the industrial waste residues within the preset range of the dredging project, classifying them into three types: active base materials, alkali-activated and sulfate-activated materials, and measuring their chemical components; establishing three objective functions for optimizing the proportioning of the solidifying material with all industrial waste residues according to the chemical components and the target mass ratios of chemical components determined by the proportioning tests; using an optimization algorithm to find the optimal solutions that satisfy the three objective functions. The present invention can solve the problem of proportioning changes caused by the differences in the chemical components of industrial waste residues in different regions, greatly improve the proportioning optimization efficiency, and has extremely high popularization value.

Description

Technical Field

[0001] The invention belongs to the technical field of river dredging sludge solidification, and particularly relates to a method and a system for optimizing the proportion of a solidification material of all industrial waste residues for dredging sludge. Background Art

[0002] In order to improve water quality and ensure the smoothness of water systems and waterways, large-scale river and lake dredging projects are carried out in China every year, inevitably generating a large amount of dredging sludge. At present, the dredging sludge of rivers and lakes is usually disposed of by throwing and filling, which not only forms a soft foundation and is difficult to utilize, but also occupies a large amount of land and causes secondary pollution. How to efficiently dispose of the increasing amount of waste dredging sludge is a global concern. Chemical solidification is one of the effective methods for large-scale disposal of dredging sludge. By adding solidifying agents such as cement and lime to the sludge, a series of physical and chemical reactions occur between the water, clay minerals in the sludge and the solidifying agents, so as to improve the engineering properties of the sludge, increase the soil strength and achieve the purpose of resource utilization. However, traditional solidifying materials such as cement and lime have problems such as high cost, high energy consumption, high CO2 emissions and serious environmental pollution in the production process. In addition, for dredging sludge with high water content and high organic matter, the solidifying effect of cement and lime is often poor, while different types of industrial waste residues (such as blast furnace slag, fly ash, carbide slag, desulfurized gypsum, etc.) can be effectively mixed to solidify the dredging sludge with high water content. Therefore, for a large number of river dredging projects, if solidifying materials can be developed by using the industrial waste residues in the project area and used for the efficient dehydration and solidification of high-water-content dredging sludge, a significant effect of "treating waste with waste" can be achieved.

[0003] However, for the same type of industrial waste residues from different regions and factories, there are great differences in their chemical components, and a large number of tests need to be carried out to find the optimal mixing ratio of different types of industrial waste residues, resulting in a huge test workload. Therefore, it is necessary to carry out proportioning tests of different types of materials for high-water-content dredging sludge based on the multi-component synergistic solidification mechanism of active substrates, alkaline activation and sulfate activation, determine the optimal dosage, and obtain the corresponding mass ratio of chemical components. On this basis, considering the differences in the chemical components of industrial waste residues in different regions and factories, a multi-objective function is established for proportioning optimization design, and a method and a system for optimizing the proportion of a solidification material of all industrial waste residues for dredging sludge are developed. This has important practical significance for improving the utilization efficiency of local industrial waste residues and the solidification effect of dredging sludge and realizing "treating waste with waste". Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the invention provides a method and a system for optimizing the proportion of a solidification material of all industrial waste residues for dredging sludge, so as to realize the rapid preparation of a solidification material for dredging sludge by using industrial waste residues from different regions and factories.

[0005] To achieve the above object, the invention provides the following solutions:

[0006] An optimization method for the mixing ratio of a solidifying material for dredged sludge with all industrial waste residues, comprising the following steps:

[0007] S1: According to the ternary synergistic solidification mechanism of active base materials, alkali activator materials and sulfate activator materials, carry out solidification mixing ratio tests on dredged sludge using cement, mineral powder and desulfurized gypsum to determine the optimal mixing ratio, and give the mass ratios of chemical components SO3 / Al2O3, CaO / Al2O3, (CaO + MgO) / SiO2;

[0008] S2: Investigate the industrial waste residues within the preset range of the dredging project, classify the industrial waste residues into three types: active base materials, alkali activator materials and sulfate activator materials, and measure the contents of the components to be measured in different industrial waste residues;

[0009] S3: According to the contents of the components to be measured of the three types of industrial waste residues and the mass ratios of the chemical components given by the optimization mixing ratio test, establish three objective functions for optimizing the mixing ratio of the solidifying material for dredged sludge with all industrial waste residues;

[0010] S4: Use an optimization algorithm to find the optimal solutions corresponding to the three objective functions, and determine the optimized mixing ratios of different types of industrial waste residues.

[0011] Preferably, the chemical components to be measured in the industrial waste residues include: SiO2, Al2O3, CaO, MgO and SO3. According to the contents of the chemical components to be measured of the three types of industrial waste residues, the method for establishing the three objective functions for optimizing the mixing ratio of the solidifying material for dredged sludge with all industrial waste residues includes:

[0012]

[0013]

[0014] In the formula, i represents the type of industrial waste residue; m i represents the incorporated mass of the industrial waste residue of type i in the sludge solidifying agent; represents the percentage of SO3 in the industrial waste residue of type i; represents the total mass of SO3 in the three types of industrial waste residues of the base material, alkali activator and sulfate activator; represents the percentage of Al2O3 in the industrial waste residue of type i; represents the total mass of Al2O3 in the three types of industrial waste residues of the base material, alkali activator and sulfate activator; represents the percentage of CaO in the industrial waste residue of type i; represents the total mass of CaO in the three types of industrial waste residues of the base material, alkali activator and sulfate activator; represents the percentage of MgO in the industrial waste residue of type i; It represents the total mass of CaO and MgO in three types of industrial waste residues, namely the base material, alkali activator, and sulfate activator. It represents the percentage of SiO2 in the industrial waste residue of type i. It represents the total mass of SiO2 in three types of industrial waste residues, namely the base material, alkali activator, and sulfate activator. It is the target mass ratio of SO3 to Al2O3. It is the target mass ratio of CaO to Al2O3. It is the target mass ratio of CaO, MgO to SiO2.

[0015] Preferably, the target mass ratios include: and It is obtained by conducting a solidification ratio test on dredged sludge using cement, mineral powder, and desulfurized gypsum according to S1.

[0016] Preferably, the method for finding the optimal solutions corresponding to the three objective functions using an optimization algorithm includes:

[0017] S41: Input the number of types of industrial waste residue materials L, where L is a positive integer greater than or equal to 1, and the content of effective components Content(i,j) contained in each material, where i is the number of types of industrial waste residue materials, with a maximum of L, and j is the type data of effective components;

[0018] S42: Set m i The search range is [0, 1], set the number of particles to 2000, the maximum number of iterations to 100, and use a random function for particle swarm initialization;

[0019] S43: Calculate the fitness according to the two objective functions and assign values;

[0020] S44: Update the individual best value pbest of each particle;

[0021] S45: Calculate the density information;

[0022] S46: Calculate the global best value gbest in the set with rank = 1 according to the density information;

[0023] S47: Determine whether the convergence condition is satisfied. If it is satisfied, output m1, m2, m3;

[0024] S48: If not, update the particle positions and velocities of the next iteration step according to the core formula of the improved particle swarm algorithm, and repeat the calculation process of S41 - S47. The inertia weight and learning factor in the particle swarm algorithm adopt a linear decreasing function for dynamic improvement strategies.

[0025] The present invention also provides an optimization system for the proportioning of a solidifying material for dredged sludge with all industrial waste residues, comprising: a preliminary proportioning test module, an industrial waste residue classification module, an objective function construction module, and a solidifying material proportioning optimization analysis module;

[0026] The preliminary proportioning test module is used to carry out a solidifying proportioning test on dredged sludge using cement, mineral powder, and desulfurized gypsum according to the ternary synergistic solidifying mechanism of an active base material, an alkali activator, and a sulfate activator, determine the optimal proportion, and give the mass ratios of chemical components SO3 / Al2O3, CaO / Al2O3, and (CaO + MgO) / SiO2;

[0027] The industrial waste residue classification module is used to investigate the industrial waste residues within the preset range of a dredging project, classify the industrial waste residues into three types: active base material, alkali activator, and sulfate activator, and measure the contents of the components to be measured in different industrial waste residues;

[0028] The objective function construction module is used to establish three objective functions for optimizing the proportioning of the solidifying material for dredged sludge with all industrial waste residues according to the contents of the components to be measured of the three types of industrial waste residues and the mass ratios of the chemical components given by the optimization proportioning test;

[0029] The solidifying material proportioning determination module is used to find the optimal solutions corresponding to the three objective functions using an optimization algorithm and determine the optimized mixing ratios of different types of industrial waste residues.

[0030] Preferably, the components to be measured in the industrial waste residues include: SiO2, Al2O3, CaO, MgO, and SO3. The process of establishing three objective functions for optimizing the proportioning of the solidifying material for dredged sludge with all industrial waste residues according to the contents of the components to be measured of the three types of industrial waste residues and the target mass ratios obtained by the preliminary proportioning test module includes:

[0031]

[0032] In the formula, i represents the type of industrial waste residue; m i represents the incorporated mass of the industrial waste residue of type i in the sludge solidifying agent; represents the percentage of SO3 in the industrial waste residue of type i; represents the total mass of SO3 in the three types of industrial waste residues: active base material, alkali activator, and sulfate activator; represents the percentage of Al2O3 in the industrial waste residue of type i; represents the total mass of Al2O3 in the three types of industrial waste residues: active base material, alkali activator, and sulfate activator; represents the percentage of CaO in the industrial waste residue of type i; represents the total mass of CaO in the three types of industrial waste residues: active base material, alkali activator, and sulfate activator; Represents the percentage of MgO in industrial waste residue of type i; Represents the total mass of CaO and MgO in three types of industrial waste residues, namely the base material, alkali activator, and sulfate activator; Represents the percentage of SiO2 in industrial waste residue of type i; Represents the total mass of SiO2 in three types of industrial waste residues, namely the base material, alkali activator, and sulfate activator; Is the target mass ratio of SO3 to Al2O3; Is the target mass ratio of CaO to Al2O3; Is the target mass ratio of CaO, MgO to SiO2.

[0033] Preferably, the target mass ratios include: and Obtained from the solidification ratio test on dredged sludge using cement, mineral powder, and desulfurized gypsum according to the previous ratio test module;

[0034] Preferably, the solidification material ratio determination module includes: an input unit, an initialization unit, a first calculation unit, an update unit, a second calculation unit, a third calculation unit, a judgment unit, and a dynamic improvement unit;

[0035] The input unit is used to input the number of types of industrial waste residue materials L, where L is a positive integer greater than or equal to 1, and the content of effective components Content(i, j) contained in each material, where i is the number of types of industrial waste residue materials, with a maximum of L, and j is the data of the types of effective components;

[0036] The initialization unit is used to set the search range of m i to [0, 1], set the number of particles to 2000, set the maximum number of iterations to 100, and perform particle swarm initialization using a random function;

[0037] The first calculation unit is used to calculate the fitness according to two objective functions and assign values;

[0038] The update unit is used to update the individual optimal value pbest of each particle;

[0039] The second calculation unit is used to calculate density information;

[0040] The third calculation unit is used to calculate the global optimal value gbest in the set where rank = 1 according to the density information;

[0041] The judgment unit is used to judge whether the convergence condition is satisfied. If satisfied, it outputs m1, m2, m3;

[0042] The dynamic improvement unit is used to update the particle positions and velocities in the next iteration step according to the core formula of the improved particle swarm optimization algorithm if the conditions are not met, and repeat the calculation process of the input unit - judgment unit. The inertia weight and learning factor in the particle swarm optimization algorithm adopt a linear decreasing function for the dynamic improvement strategy.

[0043] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0044] (1) Aiming at the problems that there are differences in the chemical components of the same type of industrial waste residues in different regions and factories, the workload of preparing the curing material ratio test for dredged silt with high water content is large, and the material ratio needs to be dynamically adjusted. The present invention proposes an optimization method and system for the curing material ratio of dredged silt with all industrial waste residues. First, according to the ternary synergistic curing mechanism of active base materials, alkali activation, and sulfate activation, cement, mineral powder, and desulfurized gypsum are used to carry out curing ratio tests on dredged silt to obtain the target mass ratios of the chemical components SO3 / Al2O3, CaO / Al2O3, and (CaO + MgO) / SiO2 of the curing material. Synchronously, the industrial waste residues within 50 km around the local dredging factory are investigated and statistically analyzed, and they are divided into three types according to the hydration reaction mechanism: active base materials, alkali activators, and sulfate activators. The contents of SiO2, Al2O3, CaO, MgO, and SO3 in each type of industrial waste residue are measured. According to the chemical components of different types of industrial waste residues and the target mass ratios of the chemical components in the optimal ratio curing material, three objective functions for optimizing the curing material ratio of dredged silt with all industrial waste residues are established. Then, the multi-objective particle swarm optimization algorithm is used to find the optimal solutions corresponding to the three objective functions to determine the dosages of different types of industrial waste residues. This method can quickly design an optimized ratio scheme for the curing material aiming at the differences in the chemical components of industrial waste residues in different regions and factories, greatly reducing the workload of conventional ratio tests and improving the design efficiency of the curing material ratio.

[0045] (2) The present invention uses industrial waste residues to quickly prepare high-water-content silt curing materials and applies them to the improvement of river-lake-reservoir dredged silt, enabling it to be applied to filling projects such as dikes and roadbeds, realizing "treating waste with waste" and having significant economic and environmental benefits. Description of the Drawings

[0046] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0047] Figure 1 It is a flowchart of an optimization method for the curing material ratio of dredged silt with all industrial waste residues according to an embodiment of the present invention;

[0048] Figure 2 Schematic diagram of the curing effect of the curing material designed for the embodiments of the present invention. Detailed implementation manners

[0049] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0050] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0051] Embodiment 1

[0052] The present invention proposes a method and system for optimizing the proportion of a high-water-content dredged sludge full-industrial waste curing material. According to the ternary synergistic curing mechanism of active base materials, alkali activation, and sulfate activation, cement, mineral powder, and desulfurized gypsum are used to conduct curing proportion tests on dredged sludge, and the target mass ratios of the chemical components SO3 / Al2O3, CaO / Al2O3, and (CaO + MgO) / SiO2 of the curing material are obtained; the industrial waste residues within 50 km of the dredging project are investigated and statistically analyzed, and they are divided into three types: active base materials, alkali activation materials, and sulfate activation materials. The chemical components of various types of industrial waste residues are tested using an X-ray fluorescence spectrometer (XRF); according to the measured chemical component contents and target mass ratios, three objective functions for optimizing the proportion of the high-water-content dredged sludge full-industrial waste curing material are established; an optimization algorithm is used to find the optimal solutions corresponding to the three objective functions (i.e., the optimal admixture ratios of different types of industrial waste residues). Refer to Figure 1 , a method and system for optimizing the proportion of a high-water-content dredged sludge full-industrial waste curing material includes the following steps:

[0053] S1. According to the ternary synergistic curing mechanism of active base materials, alkali activation, and sulfate activation, use Conch P42.5 cement, S95 mineral powder, and desulfurized gypsum to conduct curing proportion tests on dredged sludge with a water content of 80%. Use the response surface method for proportion design, prepare specimens with a diameter of 50 mm and a height of 100 mm, and conduct unconfined compressive strength tests at different curing ages. The test results are shown in Table 1. According to the chemical components of cement, mineral powder, and desulfurized gypsum, the target mass ratios of the chemical components of the corresponding optimal proportion curing material are as follows: When, this component can effectively promote the formation of ettringite (AFt) and C-S-H gel, and the curing effect is significant.

[0054] Table 1 Results of the preliminary proportion test

[0055]

[0056]

[0057] S2. Investigate the industrial waste residues within 50 km around the dredging project, classify them into active base materials (such as blast furnace slag, fly ash, steel slag, etc.), alkali-activated materials (such as carbide slag, alkali residue, aluminum sludge, etc.), and sulfate-activated materials (such as desulfurized gypsum, phosphogypsum, titanium gypsum, etc.), and detect the contents of SiO2, Al2O3, CaO, MgO, and SO3 components in each industrial waste residue.

[0058] S3. Select one industrial waste residue from each of the active base materials, alkali-activated materials, and sulfate-activated materials, and establish an optimization objective function for the proportion of the dredged sludge solidification material based on all industrial waste residues according to the contents of SiO2, Al2O3, CaO, MgO, and SO3 in them:

[0059]

[0060] In the formula, i represents the type of industrial waste residue; m i represents the incorporated mass of the industrial waste residue of type i in the sludge solidifying agent; represents the percentage of SO3 in the industrial waste residue of type i; represents the total mass of SO3 in the three types of industrial waste residues of the base material, alkali activator, and sulfate activator; represents the percentage of Al2O3 in the industrial waste residue of type i; represents the total mass of Al2O3 in the three types of industrial waste residues of the active base material, alkali activator, and sulfate activator; represents the percentage of CaO in the industrial waste residue of type i; represents the total mass of CaO in the three types of industrial waste residues of the base material, alkali activator, and sulfate activator; represents the percentage of CaO and MgO in the industrial waste residue of type i; represents the total mass of CaO and MgO in the three types of industrial waste residues of the active base material, alkali activator, and sulfate activator; represents the percentage of SiO2 in the industrial waste residue of type i; represents the total mass of SiO2 in the three types of industrial waste residues of the active base material, alkali activator, and sulfate activator; is the target mass ratio of SO3 to Al2O3; is the target mass ratio of CaO to Al2O3; is the target mass ratio of CaO, MgO to SiO2.

[0061] S4. Use the optimization algorithm to find the optimal solutions m1, m2, and m3 corresponding to the three objective functions, which respectively correspond to the dosages of three types of industrial waste residues, namely active base materials, alkali activators, and sulfate activators.

[0062] For example, conduct investigations and sampling tests on industrial waste residues within 50 km of a certain dredging project, measure the contents of components such as SiO2, Al2O3, CaO, MgO, and SO3 in each type of industrial waste residue, and classify the industrial waste residues into active base materials, alkali-activated materials, and sulfate-activated materials according to the hydration reaction mechanism.

[0063] Take blast furnace slag (GGBS) as the active base material, carbide slag (CS) as the alkali activator, and phosphogypsum (PG) as the sulfate activator, and establish three objective functions based on the optimization of the mixture ratio of all-industrial-waste-residue dredged sludge solidification materials:

[0064]

[0065] In the formula, i represents the type of industrial waste residue; m i represents the dosage of the industrial waste residue of type i in the sludge solidifying agent; represents the percentage of SO3 in the industrial waste residue of type i; represents the total mass of SO3 in the three types of industrial waste residues, namely the active base material, alkali activator, and sulfate activator; represents the percentage of Al2O3 in the industrial waste residue of type i; represents the total mass of Al2O3 in the three types of industrial waste residues, namely the active base material, alkali activator, and sulfate activator; represents the percentage of CaO in the industrial waste residue of type i; represents the total mass of CaO in the three types of industrial waste residues, namely the active base material, alkali activator, and sulfate activator; represents the percentage of CaO and MgO in the industrial waste residue of type i; represents the total mass of CaO and MgO in the three types of industrial waste residues, namely the active base material, alkali activator, and sulfate activator; represents the percentage of SiO2 in the industrial waste residue of type i; represents the total mass of SiO2 in the three types of industrial waste residues, namely the active base material, alkali activator, and sulfate activator; is the target mass ratio of SO3 to Al2O3; is the target mass ratio of CaO to Al2O3; is the target mass ratio of CaO, MgO to SiO2.

[0066] According to the target mass ratio distribution range of the optimal solidification material chemical components obtained from the S1 solidification mixture ratio test, input The multi-objective particle swarm optimization algorithm is used to optimize the proportion of industrial waste residues, and the optimal proportion results of the solidification material are as follows: the ratio of blast furnace slag to carbide slag is 2.04, and the mass percentage of phosphogypsum is 10.4%. Figure 2 This invention presents the solidification effect of the optimized proportion solidification material on highly water-containing silt. The initial water content of the dredged silt is 100%, and the solidifying agent dosage is 100 kg / m 3 , and the results prove that the optimized proportion given by this invention has the best solidification effect.

[0067] When this invention uses the improved particle algorithm for objective optimization, the specific steps are as follows:

[0068] 1) Input the number of types L (a positive integer greater than or equal to 1) of industrial waste residue materials, and the content of effective components Content(i,j) contained in each material - "i" is the number of types of industrial waste residue materials (the maximum is L), and "j" is the data of the types of effective components;

[0069] 2) Set the search range of the blast furnace slag dosage m1, carbide slag dosage m2, and phosphogypsum dosage m3 to [0, 1], set the number of particles to 2000, the maximum number of iterations to 100 times, and the coordinate of each particle is a three-dimensional vector x i (m1, m2, m3), and use the random function Rand() to randomly generate the initial position coordinates x of each particle i and the initial velocity v i Use the random function to initialize the particle swarm;

[0070] 3) Substitute the coordinate vector x of each particle i into the above objective functions f1, f2, and f3 respectively, calculate the distances between the three objective functions and the target values respectively and sum them as the individual fitness of each particle at the current coordinate; calculate the fitness according to the two objective functions and assign values;

[0071] 4) Compare the fitness of each particle at the current coordinate with the optimal fitness of the particle during the iteration process. If the fitness at the current coordinate is smaller, update the optimal value pbest of the individual fitness of each particle, and update the particle coordinate x corresponding to the optimal value i ;

[0072] 5) Calculate the global optimal value gbest in the set with rank = 1 according to the density information; compare the optimal values of the individual fitness of all particles, save the minimum value as the global fitness optimal value gbest, and update the particle coordinate corresponding to the optimal value;

[0073] 6) Judge whether the global fitness optimal value gbest meets the convergence condition. If it meets, output the particle coordinate (m1, m2, m3) corresponding to this optimal value;

[0074] 7) If not satisfied, update the particle positions and velocities at the next iteration step according to the core formula of the improved particle swarm algorithm, and repeat the above calculation process;

[0075] v i (t + 1) = v i (t) + c1r1[pbest i (t) - x i (t)] + c2r2[gbest i (t) - x i (t)]

[0076] x i (t + 1) = x i (t) + v i (t + 1)

[0077] Among them, c1, c2 and r1, r2 are the inertia weight and learning factors in the particle swarm algorithm respectively. They decrease with the increase of the number of iterations to improve the local search ability of the particle swarm algorithm, where k is the parameter controlling the decreasing rate.

[0078]

[0079] The present invention effectively overcomes the problem of large workload of curing material proportioning tests caused by inconsistent types of industrial waste residues and differences in component contents in different regions and factories. By classifying industrial waste residues, determining the contents of SiO2, Al2O3, CaO, MgO and SO3 in each industrial waste residue, and using an optimization algorithm to quickly determine the optimized proportion of all-industrial-waste-residue-based curing materials, the effective utilization rate of industrial waste residues is improved, and it is applied to the improvement of river dredging silt to achieve "treating waste with waste".

[0080] Example Two

[0081] The present invention also provides a system for optimizing the proportion of all-industrial-waste-residue curing materials for dredging silt, including: a preliminary proportioning test module, an industrial waste residue classification module, an objective function construction module and a curing material proportion optimization analysis module;

[0082] The preliminary proportioning test module is used to carry out curing proportioning tests on dredging silt using cement, mineral powder and desulfurized gypsum according to the ternary synergistic curing mechanism of active base materials, alkali-activated materials and sulfate-activated materials, determine the optimal proportion, and give the mass ratios of chemical components SO3 / Al2O3, CaO / Al2O3, (CaO + MgO) / SiO2;

[0083] The industrial waste residue classification module is used to investigate the industrial waste residues within the preset range of the dredging project, classify the industrial waste residues into three types: active base materials, alkali-activated materials, and sulfate-activated materials, and measure the contents of the components to be measured in different industrial waste residues;

[0084] The objective function construction module is used to establish three objective functions for optimizing the ratio of the solidification material of the entire industrial waste residue in the dredged silt according to the contents of the components to be measured in the three types of industrial waste residues and the mass ratios of the chemical components given by the optimization ratio test;

[0085] The solidification material ratio determination module is used to use the optimization algorithm to find the optimal solutions corresponding to the three objective functions and determine the optimized mixing ratios of different types of industrial waste residues.

[0086] In this embodiment, the components to be measured in the industrial waste residue include: SiO2, Al2O3, CaO, MgO, and SO3. According to the contents of the components to be measured in the three types of industrial waste residues and the target mass ratios obtained by the previous ratio test module, the process of establishing three objective functions for optimizing the ratio of the solidification material of the entire industrial waste residue in the dredged silt includes:

[0087]

[0088] where i represents the type of industrial waste residue; m i represents the incorporated mass of the industrial waste residue of type i in the silt solidifying agent; represents the percentage of SO3 in the industrial waste residue of type i; represents the total mass of SO3 in the three types of industrial waste residues of the base material, alkali activator, and sulfate activator; represents the percentage of Al2O3 in the industrial waste residue of type i; represents the total mass of Al2O3 in the three types of industrial waste residues of the base material, alkali activator, and sulfate activator; represents the percentage of CaO in the industrial waste residue of type i; represents the total mass of CaO in the three types of industrial waste residues of the base material, alkali activator, and sulfate activator; represents the percentage of MgO in the industrial waste residue of type i; represents the total mass of CaO and MgO in the three types of industrial waste residues of the base material, alkali activator, and sulfate activator; represents the percentage of SiO2 in the industrial waste residue of type i; represents the total mass of SiO2 in the three types of industrial waste residues of the base material, alkali activator, and sulfate activator; is the target mass ratio of SO3 to Al2O3; is the target mass ratio of CaO to Al2O3; is the target mass ratio of CaO, MgO to SiO2.

[0089] In this embodiment, the target mass ratio includes: and obtained from the solidification ratio test on dredged silt using cement, mineral powder, and desulfurized gypsum by the preliminary ratio test module. When it can effectively promote the formation of ettringite (AFt) and C-S-H gel, and the solidification effect is remarkable.

[0090] In this embodiment, the solidification material ratio determination module includes: an input unit, an initialization unit, a first calculation unit, an update unit, a second calculation unit, a third calculation unit, a judgment unit, and a dynamic improvement unit;

[0091] The input unit is used to input the number of types of industrial waste residue materials L, where L is a positive integer greater than or equal to 1, and the content of the effective components Content(i,j) contained in each material, where i is the number of types of industrial waste residue materials, with a maximum of L, and j is the data of the types of effective components;

[0092] The initialization unit is used to set the search range of m i to [0, 1], set the number of particles to 2000, set the maximum number of iterations to 100, and use a random function for particle swarm initialization;

[0093] The first calculation unit is used to calculate the fitness according to two objective functions and assign values;

[0094] The update unit is used to update the individual best value pbest of each particle;

[0095] The second calculation unit is used to calculate density information;

[0096] The third calculation unit is used to calculate the global best value gbest in the set where rank = 1 according to the density information;

[0097] The judgment unit is used to judge whether the convergence condition is satisfied. If satisfied, it outputs m1, m2, m3;

[0098] The dynamic improvement unit is used, if not satisfied, to update the particle positions and velocities of the next iteration step according to the core formula of the improved particle swarm algorithm, and repeat the calculation process of the input unit - judgment unit. The inertia weight and learning factor in the particle swarm algorithm adopt a linear decreasing function for the dynamic improvement strategy.

[0099] Embodiment III

[0100] The present invention also provides a computer device, including:

[0101] One or more processors;

[0102] A memory; and

[0103] One or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processor, the steps of the method for optimizing the ratio of high-moisture sludge solidification materials based on all industrial waste residues as described above are implemented.

[0104] The present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method for optimizing the ratio of high-moisture sludge solidification materials based on all industrial waste residues as described above are implemented.

[0105] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, a computer device, or a computer program product. Therefore, the software of the present invention is developed based on Matlab, which can quickly determine the optimal ratio for different types of industrial waste residues, and the pictures and ratio optimization results support being saved locally or uploaded to the cloud.

[0106] The present invention is described with reference to the flowchart of the method according to the embodiments of the present invention. It should be understood that each process in the flowchart and the combination of processes in the flowchart can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a system for implementing the functions specified in one Figure 1 process or multiple processes.

[0107] Technical features of the software: The first is easy maintenance: designed with Matlab code, during the progress of the entire project, the code is simple and clear, and the annotations are clear; the second advantage is high efficiency: only the content of the effective components in each type of industrial waste residue needs to be input to obtain the optimized ratio, which is easy for beginners to master and improves the usage efficiency; the third is easy expansion: it can be coupled into other large-scale integrated calculation codes, making the system more flexible and easier to expand, and applicable to a wider range of fields.

[0108] Main functions of the software developed by the present invention: (1) Open the stored mixture_design.m and the file of the content of the effective components of each type of industrial waste residue required, and perform the optimal mix ratio optimization design of the solidification materials according to the user's command; (2) The operation interface is clear and intuitive, and users can clearly understand the required operations through the annotations of each line in the code interface. Save the given optimization results and pictures and clear the calculation results, and quickly enter the calculation of the next group of industrial waste residue materials; (3) It has good maintenance, modification, and expansion functions. Both the system hardware and software meet the requirements of the open standard, and meet the requirements for the increase of hardware nodes, the expansion of the database capacity, and the enhancement of the system software functions in the future.

[0109] The embodiments described above are only descriptions of the preferred embodiments of the present invention, and do not limit the scope of the present invention. Without departing from the spirit of the present invention's design, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. An optimization method for the proportioning of a solidification material for dredged silt and all industrial waste residues, characterized in that, It includes the following steps: S1: According to the ternary synergistic curing mechanism of the active substrate, alkali-activated material and sulfate-activated material, carry out a curing ratio test on dredged sludge using cement, mineral powder and desulfurized gypsum, determine the optimal ratio, and give the mass ratios of chemical components SO3 / Al2O3, CaO / Al2O3, and (CaO+MgO) / SiO2; S2: Investigate the industrial waste residues within the preset scope of the dredging project, classify the industrial waste residues into three types: active substrate, alkali-activated material and sulfate-activated material, and measure the contents of the components to be measured in different industrial waste residues; S3: According to the contents of the components to be measured in the three types of industrial waste residues and the mass ratios of the chemical components given by the optimized ratio test, establish three objective functions for optimizing the ratio of the all-industrial waste residue curing material for dredged sludge; S4: Use an optimization algorithm to find the optimal solutions corresponding to the three objective functions and determine the optimized mixing ratios of different types of industrial waste residues; The chemical components to be measured in the industrial waste residue include: SiO2, Al2O3, CaO, MgO and SO3. According to the contents of the chemical components to be measured in the three types of industrial waste residues, the method for establishing the three objective functions for optimizing the ratio of the all-industrial waste residue curing material for dredged sludge includes: Wherein, i represents the type of industrial waste residue; m i represents the incorporated mass of the industrial waste residue of type i in the sludge solidifying agent; represents the percentage of SO3 in the industrial waste residue of type i; represents the total mass of SO3 in the industrial waste residues of the three types of base materials, alkali activators and sulfate activators; represents the percentage of Al2O3 in the industrial waste residue of type i; represents the total mass of Al2O3 in the industrial waste residues of the three types of base materials, alkali activators and sulfate activators; represents the percentage of CaO in the industrial waste residue of type i; represents the total mass of CaO in the industrial waste residues of the three types of base materials, alkali activators and sulfate activators; represents the percentage of MgO in the industrial waste residue of type i; represents the total mass of CaO and MgO in the industrial waste residues of the three types of base materials, alkali activators and sulfate activators; represents the percentage of SiO2 in the industrial waste residue of type i; represents the total mass of SiO2 in the industrial waste residues of the three types of base materials, alkali activators and sulfate activators; is the target mass ratio of SO3 to Al2O3; is the target mass ratio of CaO to Al2O3; is the target mass ratio of CaO, MgO to SiO2.

2. The optimization method of the dredging sludge full industrial waste residue solidification material ratio according to claim 1, characterized in that The target mass ratio includes: and Obtained from the solidification ratio test of dredged silt using cement, mineral powder, and desulfurized gypsum according to S1 3. The optimization method of the dredged sludge full industrial waste residue solidification material ratio according to claim 1, characterized in that The method for using an optimization algorithm to find the optimal solutions corresponding to the three objective functions includes: S41: Input the number of types L of industrial waste residue materials, where L is a positive integer greater than or equal to 1, and the content Content(i,j) of the effective components contained in each material, where i is the number of types of industrial waste residue materials, with a maximum of L, and j is the data of the types of effective components; S42: Set m i The search range is [0, 1]. Set the number of particles to 2000 and the maximum number of iterations to 100. Use a random function to initialize the particle swarm; S43: Calculate the fitness according to the two objective functions and assign values; S44: Update the individual optimal value pbest of each particle; S45: Calculate the density information; S46: Calculate the overall optimal value gbest in the set where rank = 1 according to the density information; S47: Judge whether the convergence condition is satisfied. If it is satisfied, output m1, m2, m3; S48: If not, update the particle positions and velocities of the next iteration step according to the core formula of the improved particle swarm algorithm, and repeat the calculation process of S41 - S47. The inertia weight and learning factor in the particle swarm algorithm adopt a dynamic improvement strategy using a linearly decreasing function.

4. A system for optimizing the proportioning of a solidifying material for dredged sludge and all industrial waste residues, characterized in that, It includes: The preliminary ratio test module, the industrial waste residue classification module, the objective function construction module and the curing material ratio optimization analysis module; The preliminary ratio test module is used to carry out a curing ratio test on dredged sludge using cement, mineral powder and desulfurized gypsum according to the ternary synergistic curing mechanism of the active substrate, alkali-activated material and sulfate-activated material, determine the optimal ratio, and give the mass ratios of chemical components SO3 / Al2O3, CaO / Al2O3, and (CaO+MgO) / SiO2; The industrial waste residue classification module is used to investigate the industrial waste residues within the preset scope of the dredging project, classify the industrial waste residues into three types: active substrate, alkali-activated material and sulfate-activated material, and measure the contents of the components to be measured in different industrial waste residues; The target function construction module is used to establish three target functions for optimizing the ratio of the all-industrial waste solidification material for dredged silt according to the content of the components to be measured of the three types of industrial waste residues and the mass ratio of chemical components given by the optimization ratio test; The solidification material ratio determination module is used to find the optimal solutions corresponding to the three target functions by using an optimization algorithm and determine the optimized mixing ratios of different types of industrial waste residues; The components to be measured of the industrial waste residues include: SiO2, Al2O3, CaO, MgO, and SO3. The process of establishing the three target functions for optimizing the ratio of the all-industrial waste solidification material for dredged silt according to the content of the components to be measured of the three types of industrial waste residues and the target mass ratio obtained by the previous ratio test module includes: In the formula, i represents the type of industrial waste residue; m i represents the incorporated mass of industrial waste residue of type i in the sludge solidifying agent; represents the percentage of SO3 in industrial waste residue of type i; represents the total mass of SO3 in the three types of industrial waste residues of base material, alkali activator and sulfate activator; represents the percentage of Al2O3 in industrial waste residue of type i; represents the total mass of Al2O3 in the three types of industrial waste residues of base material, alkali activator and sulfate activator; represents the percentage of CaO in industrial waste residue of type i; represents the total mass of CaO in the three types of industrial waste residues of base material, alkali activator and sulfate activator; represents the percentage of MgO in industrial waste residue of type i; represents the total mass of CaO and MgO in the three types of industrial waste residues of base material, alkali activator and sulfate activator; represents the percentage of SiO2 in industrial waste residue of type i; represents the total mass of SiO2 in the three types of industrial waste residues of base material, alkali activator and sulfate activator; is the target mass ratio of SO3 to Al2O3; is the target mass ratio of CaO to Al2O3; is the target mass ratio of CaO, MgO to SiO2.

5. The dredging sludge full industrial waste residue solidification material ratio optimization system according to claim 4, characterized in that The target mass ratio includes: and obtained from the solidification ratio test on dredged silt using cement, slag powder and desulfurized gypsum according to the previous ratio test module 6. The dredging sludge full industrial waste residue solidification material ratio optimization system according to claim 4, characterized in that The solidification material ratio determination module includes: an input unit, an initialization unit, a first calculation unit, an update unit, a second calculation unit, a third calculation unit, a judgment unit, and a dynamic improvement unit; The input unit is used to input the number of types of industrial waste residue materials L, where L is a positive integer greater than or equal to 1, and the content of the effective components Content(i,j) contained in each material, where i is the number of types of industrial waste residue materials, with a maximum of L, and j is the data of the types of effective components; The initialization unit is used to set m i The search range is [0, 1], the number of particles is set to 2000, the maximum number of iterations is 100, and a random function is used for particle swarm initialization; The first calculation unit is used to calculate and assign the fitness according to two target functions; The update unit is used to update the individual optimal value pbest of each particle; The second calculation unit is used to calculate the density information; The third calculation unit is used to calculate the global optimal value gbest in the set where rank = 1 according to the density information; The judgment unit is used to judge whether the convergence condition is satisfied. If it is satisfied, m1, m2, and m3 are output; The dynamic improvement unit is used to, if not satisfied, update the positions and velocities of the particles in the next iteration step according to the core formula of the improved particle swarm algorithm, and repeat the calculation process of the input unit - judgment unit. The inertia weight and learning factor in the particle swarm algorithm adopt a linear decreasing function for the dynamic improvement strategy.

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