A multi-objective optimization design and preparation method for neutron shielding composite materials

Abstract

The present invention provides a multi-objective optimization design and preparation method for neutron shielding composite materials, including: step 1, establishing an objective function, a fitness function and constraints; step 2, establishing an input file of a radiation shielding calculation program; step 3, calling the radiation shielding calculation program during the optimization process; step 4, using the obtained neutron transmittance and other results to calculate the objective function value of the population, and judging whether the constraint conditions are met, if not, calculating the penalty function value; step 5, generating a sub-generation population through population selection, mutation, and crossover operations; step 6, completing the set number of iterations to obtain a design scheme for the shielding material; step 7, configuring the powder according to the selected design ratio and mixing it evenly; step 8, and conducting microstructure observation and mechanical property testing on the prepared neutron shielding composite material. The method can directly form and prepare neutron shielding materials and parts with complex shapes and large sizes, reducing subsequent processing time and cost.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-objective optimization design and preparation of neutron shielding materials, and in particular to a neutron shielding material optimization design method and a neutron shielding material preparation method based on an additive manufacturing process. Background Art

[0002] In recent years, my country's nuclear industry has developed rapidly, with the scale of nuclear power units under construction ranking first in the world. By 2035, nuclear power generation will double that of 2022. The operation of nuclear reactors will produce a large amount of spent fuel. With the expansion of nuclear power, the amount of spent fuel will inevitably increase rapidly. It is urgent to pay attention to the safety and environmental protection issues caused by spent fuel. Spent fuel is a high-level radioactive waste, which will release a large number of neutrons with extremely strong penetrating power, causing serious radiation damage to electronic devices of nuclear industry equipment. In addition, the storage of a large amount of spent fuel must prevent criticality. Therefore, neutron shielding materials are needed to shield the radioactive sources that produce neutrons to protect the safety of nuclear industry equipment and workers.

[0003] The commonly used aluminum-based neutron shielding materials have poor mechanical properties and corrosion resistance. The design of neutron shielding materials needs to consider neutron shielding performance, secondary gamma photons generated after absorbing neutrons, formability, mechanical properties and corrosion resistance. Too many shielding elements will affect the mechanical properties and formability of the material. Adding a single neutron absorbing element cannot achieve multiple design goals. The design of neutron shielding materials constitutes a type of multi-objective optimization problem. In order to comprehensively consider multiple design goals, it is necessary to use different neutron absorbing elements as the shielding reinforcement of the matrix material for multi-objective optimization design.

[0004] Nuclear industry equipment generally has complex structures and is produced in small batches. Traditional manufacturing processes are not suitable for the preparation of neutron shielding structural parts for nuclear industry equipment. Aluminum-based boron carbide neutron shielding composite materials are usually only used as plates and are mainly prepared using traditional powder metallurgy processes. They cannot adapt to the current rapid growth in demand for complex nuclear industry special equipment. Therefore, in order to meet the demand for neutron shielding materials in the development of the nuclear industry, it is necessary to design and prepare neutron shielding materials with excellent comprehensive properties such as shielding properties and mechanical properties. Summary of the invention

[0005] The present invention aims to provide a multi-objective optimization design method for neutron shielding composite materials, which can be used for the optimization calculation of composite material components containing multiple neutron shielding enhancing elements, and provides an additive manufacturing method for neutron composite shielding materials.

[0006] The present invention provides a multi-objective optimization design and preparation method for a neutron shielding composite material, the multi-objective optimization design and preparation method for a neutron shielding composite material comprising the following steps:

[0007] Step 1, establishing the objective function, fitness function and constraints of the multi-objective optimization design problem of the content of each component of the neutron shielding composite material;

[0008] Step 2: Generate an initial population, encode the initial population in binary, and encode the B 4 The content range and variation step of C, Gd and 316L are coded to establish the input file of radiation shielding calculation program;

[0009] Step 3: During the optimization process, the radiation shielding calculation program is called to calculate the neutron transmittance, secondary γ photon generation rate, B 4 The sum of the volume percentages of C and Gd;

[0010] Step 4: Use the obtained neutron transmittance, secondary γ photon generation rate, B 4 The volume proportion results of C and Gd are used to calculate the objective function value of the population and determine whether the constraint conditions are met. If not, the penalty function value is calculated;

[0011] Step 5: Generate a sub-population through population selection, mutation, and crossover operations, and determine whether the maximum number of iterations has been reached. If it has been reached, output the final sub-population; if not, use the sub-population to loop through steps 2 to 5;

[0012] Step 6: Complete the set number of iterations to obtain a design scheme for the shielding material, and select a suitable scheme from it for subsequent material preparation;

[0013] Step 7: According to the selected neutron shielding composite material design scheme, the B 4 C powder, Gd powder and 316L powder are mixed evenly;

[0014] Step 8: Use the uniformly mixed powder to prepare the neutron shielding composite material through directed energy deposition additive manufacturing technology, and perform microstructure observation and mechanical property testing on the prepared neutron shielding composite material.

[0015] Furthermore, in step 1: materials with high neutron absorption cross-sections such as B4C and Gd are used to generate secondary gamma photons when absorbing neutrons; the neutron transmittance, secondary gamma photon generation rate, and volume proportion of neutron shielding reinforcement materials are weighted by weight factors and then added together by multiplying them by their respective corresponding weight factors; and the constraints include the neutron transmittance, secondary gamma photon generation rate, and value range constraints of the B4C and Gd contents of the aluminum-based boron carbide composite material with a B4C mass fraction of 40%.

[0016] Further: in step 2, the content range and variation step of B4C, Gd and 316L are encoded in binary mode, and the genetic algorithm parameters are set, the population size is 32, the crossover probability is 0.6, and the total number of iterations is 110.

[0017] Further: in step 3, a Monte Carlo-based radiation shielding calculation program input file is compiled, and the radiation source parameters of the input file are set, including type, energy, and number of particles; material parameters, including composition, content, density, and structure.

[0018] Further: In step 4: the input file is calculated using a radiation shielding calculation program to obtain the neutron transmittance, secondary gamma photon production rate, and volume ratio of B4C and Gd. The objective function value of each population is calculated using the three target values, and the penalty function value is calculated if the constraints are not met.

[0019] Further: in step 5, a new offspring population is generated through selection, mutation, and crossover genetic operations, and the parent population is updated using the offspring population, and the cycle is repeated until the set number of iterations is reached; after completing the evolutionary algebra, the optimal design scheme of the composite material is obtained.

[0020] Further: in step 6, the mass fractions of B4C, Gd and 316L are selected to be 2%, 2.2% and 95.8% respectively, and the powders weighed according to the determined proportions are mixed using a powder mixing device to obtain a uniformly mixed powder.

[0021] Further: In step 7, the mixed powder is used as a raw material to prepare a neutron shielding material using a directed energy deposition additive manufacturing system.

[0022] The beneficial effects achieved by the present invention are:

[0023] The multi-objective optimization design method for neutron composite shielding materials described in this method can automatically optimize the design of materials under set constraints to obtain an optimization design scheme that comprehensively considers neutron shielding rate, secondary gamma photon generation rate, and formability. This design method deeply integrates the intelligent optimization algorithm with the shielding performance calculation of neutron shielding materials.

[0024] The additive manufacturing method of the neutron composite shielding material described in the present invention uses 316L with excellent mechanical properties and corrosion resistance as the base material, Gd and B with good neutron absorption ability 4 C is a reinforcement. 4 C produces fewer secondary gamma photons when absorbing neutrons, but requires a high content. Gd has better neutron absorption than B 4C but the secondary gamma photon generation rate is high. Using two neutron absorbing materials at the same time overcomes the disadvantages of using a single material. Directed energy deposition additive manufacturing technology can directly form and prepare neutron shielding materials and components with complex shapes and large sizes, reducing subsequent processing time and cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic diagram of the design and preparation process of a neutron shielding composite material based on a genetic algorithm provided by the present invention;

[0026] Figure 2 It is a binary coding schematic diagram of a neutron composite shielding material provided by the present invention;

[0027] Figure 3 It is a genetic evolution operation based on binary tournament provided by the present invention;

[0028] Figure 4 This is an optical microscopic image of a neutron shielding composite material prepared based on a directed energy deposition additive process provided by the present invention;

[0029] Figure 5 The present invention provides a stress-strain curve of a neutron shielding composite material prepared based on a directed energy deposition additive process. DETAILED DESCRIPTION

[0030] The technical solution of the present invention is described in more detail below in conjunction with the accompanying drawings. The present invention includes but is not limited to the following embodiments.

[0031] As attached Figure 1 As shown, the present invention proposes a multi-objective optimization design and preparation method for a neutron shielding composite material, comprising the following steps:

[0032] Step 1, establishing the objective function, fitness function and constraints of the multi-objective optimization design problem of the content of each component of the neutron shielding composite material;

[0033] In this step, B 4 Materials with high neutron absorption cross-sections, such as C and Gd, will generate secondary γ photons when absorbing neutrons. In order to avoid secondary radiation damage caused by neutron absorbing materials, the neutron shielding rate, secondary γ photon generation rate and mechanical properties are comprehensively considered. The neutron transmittance, secondary γ photon generation rate, neutron shielding enhancement material (B) are weighted by weight factors. 4 The volume proportions of C and Gd are multiplied by their respective weight factors and then added together.

[0034] In this step, the constraints determined include B 4 Neutron transmittance, secondary γ photon generation rate and B 4C. Constraints on the value range of Gd content.

[0035] Among them: The multi-objective function is transformed into a mathematical model as shown below:

[0036]

[0037] Among them, F(X) is the objective function of the composite material design, f T (X), f γ (X) and f V (X) are the neutron transmittance, secondary γ photon generation rate and B of the composite material after dimensionless conversion. 4 The volume ratio of C and Gd is the objective function value; C T , C γ and C V are the weight coefficient values ​​corresponding to the above objective functions; T 0 and γ 0 Represents B 4 Neutron transmittance and secondary γ-photon generation rate of aluminum-based boron carbide composites with C mass fraction of 40%; V is B 4 Volume ratio of C and Gd.

[0038] According to the weight factor method and the above mathematical model, the multi-objective optimization problem of neutron composite shielding materials is transformed into a single-objective optimization problem as shown in formula (2):

[0039]

[0040] Among them, x j is the design variable corresponding to the optimal design of the composite material; L j and U j are the upper and lower boundaries of the corresponding design variable value range; X is the design parameter vector of the composite material; is the value space of X. 1 With x 2 B 4 Mass fraction of C and Gd; L 1 =0%≤x 1 ≤U 1 =7%, L 2 =1.2%≤x 2 ≤U 2 =2.7%.

[0041] Step 2: Generate an initial population, encode the initial population in binary, and encode the B 4 The content range and variation step of C, Gd and 316L are coded to establish the input file of radiation shielding calculation program;

[0042] In this step, B 4 The content range and variation step of C, Gd and 316L are as shown in the attached Figure 2 The genetic algorithm parameters are set as follows: population size is 32, crossover probability is 0.6, and total number of iterations is 110.

[0043] Step 3: During the optimization process, the radiation shielding calculation program is called to calculate the neutron transmittance, secondary γ photon generation rate, B 4 The sum of the volume proportions of C and Gd;

[0044] In this step, the input file of the Monte Carlo-based radiation shielding calculation program is compiled, and the radiation source parameters of the input file are set, such as type, energy, number of particles; material parameters, such as composition, content, density, structure, etc.

[0045] Step 4: Use the obtained neutron transmittance, secondary γ photon generation rate, B 4 The volume proportion results of C and Gd are used to calculate the objective function value of the population and determine whether the constraint conditions are met. If not, the penalty function value is calculated;

[0046] In this step, the radiation shielding calculation program is used to calculate the input file to obtain the neutron transmittance, secondary gamma photon production rate, B 4 The volume ratio of C and Gd. The objective function value of each population is calculated through these three target values, and the penalty function value is calculated if the constraint conditions are not met. The fitness function G(X) and penalty function used in multi-objective optimization As shown below:

[0047]

[0048]

[0049] Step 5: Generate a sub-population through population selection, mutation, and crossover operations, and determine whether the maximum number of iterations has been reached. If it has been reached, output the final sub-population; if not, use the sub-population to loop through steps 2 to 5;

[0050] In this step, new offspring populations are generated through selection, mutation, and crossover genetic operations. The selection of populations is carried out as shown in the attached Figure 3 The binary tournament method shown in FIG. 1 is used to enable the best individuals to enter the offspring population. The offspring population is used to update the parent population, and the cycle is repeated until the set number of iterations is reached. After completing the evolutionary algebra, the optimal design of the composite material is obtained.

[0051] Step 6: Complete the set number of iterations to obtain a design scheme for the shielding material, and select a suitable scheme from it for subsequent material preparation;

[0052] In this step, select B from the design solutions obtained according to the above steps. 4 The mass fractions of C, Gd and 316L are 2%, 2.2% and 95.8% respectively, which can meet the neutron shielding performance requirements. The powders weighed according to the above proportions are mixed using a powder mixing device to obtain a uniformly mixed powder.

[0053] Step 7: According to the selected neutron shielding composite material design scheme, the B 4 C powder, Gd powder and 316L powder are mixed evenly;

[0054] In this step, the mixed powder is used as the raw material, and the neutron shielding material is prepared using the directed energy deposition additive manufacturing system. Turn on the cooling device, put the mixed powder into the cleaned DPSF-2 powder conveying device, and install an electric stirrer on the upper end of the device. Use a high-pressure air gun to inflate the powder delivery tube to remove the original powder in the powder delivery tube. Place a 10mm thick stainless steel substrate with a sandpaper-polished surface on the workbench, adjust the distance between the laser cladding head and the stainless steel substrate, set the process parameters, turn on the protective atmosphere equipment and the powder conveying equipment, and press the laser start switch after the output of the cladding head is stable to prepare the shielding material. The laser beam melts the powder, and the deposited material cools and forms after the laser is removed. The main process parameters set are: laser power 710W, scanning speed 470mm / min, powder conveying speed 11g / min.

[0055] Step 8: Use the uniformly mixed powder to prepare the neutron shielding composite material through directed energy deposition additive manufacturing technology, and perform microstructure observation and mechanical property testing on the prepared neutron shielding composite material.

[0056] In this step, after the deposited material and the stainless steel substrate are cooled, the deposited material installation model size is cut and sampled using a wire cutting device. The taken samples are water-grinded with sandpaper of 120, 400, 600, 800, 1000, 1500, and 2000 meshes in turn, and then mechanically polished with diamond abrasives and silica abrasives.

[0057] The hardness of the neutron shielding material was measured using a HVS-1000B microhardness tester with a test force of 0.98N. The diagonal length of the diamond indentation was measured using an optical microscope, as shown in the attached figure. Figure 4 As shown, the microhardness of the sample is obtained by calculation. The microhardness of the neutron shielding composite material is 328HV. Compared with 316L stainless steel, the microhardness of the composite material is increased by 49.1%.

[0058] The tensile properties of the samples were tested using the SEM-SERVO PULSER in-situ fatigue test system. The tensile stress-strain curve is shown in the attached figure. Figure 5 As shown in Figure 1, the tensile strength of the neutron shielding composite material is increased by 62.3% compared with 316L stainless steel. The neutron shielding performance of the composite material was simulated and calculated using a Monte Carlo particle transport calculation program. When the neutron energy was 0.025ev and the thickness was 1mm, the neutron shielding rate of the composite material was 8.8 times that of 316L stainless steel.

[0059] The present invention is not limited to the above-mentioned specific implementation modes. A person skilled in the art may implement the present invention in various other specific implementation modes according to the embodiments and the disclosure of the drawings. Therefore, any design that adopts the design structure and concept of the present invention and makes some simple transformations or changes shall fall within the scope of protection of the present invention.

Claims

1. A multi-objective optimization design and preparation method for a neutron shielding composite material, characterized in that: Step 1, establishing the objective function, fitness function and constraints of the multi-objective optimization design problem of the content of each component of the neutron shielding composite material; In step 1: 316L is used as the matrix material, and materials with high neutron absorption cross sections such as B4C and Gd are used to generate secondary γ photons when absorbing neutrons; the neutron transmittance, secondary γ photon generation rate, and volume proportion of neutron shielding reinforcement materials are weighted by weight factors and then added together by multiplying them by their respective corresponding weight factors; the constraints include the neutron transmittance, secondary γ photon generation rate, and value range constraints of the B4C and Gd contents of aluminum-based boron carbide composite materials with a B4C mass fraction of 40%; Step 2, generating an initial population, binary-coding the initial population, encoding the content range and variation step of B4C, Gd and 316L in the neutron shielding composite material by a binary coding method, and establishing an input file for a radiation shielding calculation program; Step 3: During the optimization process, the radiation shielding calculation program is called to calculate the neutron transmittance, secondary γ photon generation rate, and the sum of the volume proportions of B4C and Gd of the neutron shielding composite material according to the input file parameters; Step 4: Calculate the objective function value of the population using the obtained neutron transmittance, secondary gamma photon generation rate, and volume ratio of B4C and Gd to determine whether the constraint conditions are met. If not, calculate the penalty function value; Step 5: Generate a sub-population through population selection, mutation, and crossover operations, and determine whether the maximum number of iterations has been reached; if it has been reached, output the final sub-population; if not, use the sub-population to loop through steps 2 to 5; Step 6: Complete the set number of iterations to obtain a design scheme for the shielding material, and select a suitable scheme from it for subsequent material preparation; Step 7, according to the selected neutron shielding composite material design scheme, the B4C powder, Gd powder and 316L powder configured according to the selected design ratio are mixed evenly; Step 8: Use the uniformly mixed powder to prepare the neutron shielding composite material through directed energy deposition additive manufacturing technology, and perform microstructure observation and mechanical property testing on the prepared neutron shielding composite material.

2. The multi-objective optimization design and preparation method of neutron shielding composite material according to claim 1, characterized in that: In step 2, the content range and change step of B4C, Gd and 316L are encoded in binary mode, and the genetic algorithm parameters are set, the population size is 32, the crossover probability is 0.6, and the total number of iterations is 110.

3. The multi-objective optimization design and preparation method of neutron shielding composite material according to claim 1, characterized in that: In step 3, write the input file of the Monte Carlo-based radiation shielding calculation program, set the radiation source parameters of the input file, including type, energy, and number of particles; material parameters, including composition, content, density, and structure.

4. The multi-objective optimization design and preparation method of neutron shielding composite material according to claim 1, characterized in that: In step 4: use the radiation shielding calculation program to calculate the input file to obtain the neutron transmittance, secondary gamma photon production rate, and the volume ratio of B4C and Gd. The objective function value of each population is calculated using the three target values. If the constraints are not met, the penalty function value is calculated.

5. The multi-objective optimization design and preparation method of neutron shielding composite material according to claim 1, characterized in that: In step 5, a new offspring population is generated through selection, mutation, and crossover genetic operations, and the parent population is updated using the offspring population, and the cycle is repeated until the set number of iterations is reached; after completing the evolutionary algebra, the optimal design scheme of the composite material is obtained.

6. The multi-objective optimization design and preparation method of neutron shielding composite material according to claim 5, characterized in that: In step 6, the mass fractions of B4C, Gd, and 316L are selected to be 2%, 2.2%, and 95.8%, respectively, and the powders weighed according to the determined ratio are mixed using a powder mixing device to obtain a uniformly mixed powder.

7. The multi-objective optimization design and preparation method of neutron shielding composite material according to claim 5, characterized in that: In step 7, the mixed powder is used as a raw material to prepare a neutron shielding material using a directed energy deposition additive manufacturing system.

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