CN-121877573-B - Continuous strength prediction method and device for engineering-size irradiation material

Abstract

The invention relates to the technical field of intensity prediction, in particular to a continuous intensity prediction method and device for engineering-size irradiation materials. The method comprises the steps of obtaining first strength data of first tensile samples of different size points under different size lineages through an unirradiation tensile test, inputting the cross-sectional area and the first strength data of a gauge length section in the first tensile samples into an unirradiation strength prediction model to obtain a first parameter set, obtaining second strength data of second tensile samples of different size points through an irradiation tensile test, inputting the cross-sectional area of the gauge length section in the second tensile samples, the first parameter set and the second strength data into an irradiation strength prediction model to obtain a second parameter set, and inputting the cross-sectional area of an engineering size irradiation material into a fitted irradiation strength prediction model to obtain predicted strength data of the engineering size irradiation material. The technical scheme can continuously predict the intensity of the engineering-size irradiation material.

Inventors

• RAN GUANG
• ZHU SHIKUN
• DING YIFAN
• WANG ZUOJIANG

Assignees

• 厦门大学

Dates

Publication Date

20260512

Application Date

20260318

Claims (2)

1. 1. A method for continuously predicting the intensity of an engineering-size irradiated material, comprising: Obtaining first strength data of first tensile samples of different size points under different size lineages through an unirradiation tensile test, wherein the different size lineages comprise a nanometer tensile region, a micrometer tensile region and a millimeter tensile region which are sequentially progressive from small to large; Inputting the cross section area and the first intensity data of the gauge length section in the first tensile sample into an unirradiated intensity prediction model to be fitted, and fitting to obtain a first parameter set; obtaining second strength data of a second tensile sample of different size points in the nanometer tensile region, wherein the second strength data is obtained by a tensile test after irradiation, and the target displacement injury dose under the irradiation working condition is 1dpa; inputting the cross section area of the gauge length section in the second tensile sample, the first parameter set and the second intensity data into a post-irradiation intensity prediction model to be fitted, and fitting to obtain a second parameter set; Inputting the cross-sectional area of the engineering-size irradiation material into a fitted post-irradiation intensity prediction model to obtain predicted intensity data of the engineering-size irradiation material, wherein the engineering size is the size of a millimeter stretching area, and the types of the first intensity data, the second intensity data and the predicted intensity data comprise yield intensity and tensile intensity; the non-irradiation intensity prediction model is: In the formula, Is of cross-sectional area of The intensity of the unirradiated sample at that time, d is the minimum feature size, In order for the average grain size to be the same, As a function of the channel weight, And Intensity functions of dislocation source limited channels and polycrystalline statistical channels respectively, Selectable weak items; The first parameter set comprises a turning area parameter, a kurtosis parameter, an intensity parameter, a first coefficient, a second coefficient, a lower bound parameter, a macroscopic limit parameter, a convergence parameter, a third coefficient, a valley depth parameter, a valley center area parameter and a logarithmic variance parameter, and the second parameter set comprises a dislocation source item increment parameter and an irradiation defect hardening item parameter to be fitted; In the post-irradiation intensity prediction model, the minimum feature size is the sum of the minimum feature size in the non-irradiation intensity prediction model and the dislocation source item increment parameter, and the macroscopic limit parameter is the sum of the macroscopic limit parameter in the non-irradiation intensity prediction model and the irradiation defect hardening item parameter; The channel weight function is: In the formula, As the turning area parameter to be fitted, As the kurtosis parameter to be fitted, The value range in the A domain is 0-1; The intensity function of the dislocation source limited passage is: In the formula, Sequentially obtaining an intensity parameter to be fitted, a first coefficient and a second coefficient; The intensity function of the polycrystalline statistical channel is: In the formula, As the lower bound parameter to be fitted, As a macroscopic limit parameter to be fitted, As the convergence parameter to be fitted, As a third coefficient to be fitted to, An average number of grains included in the gauge length segment; The optional weakening terms are: In the formula, Sequentially obtaining a valley depth parameter, a valley center area parameter and a logarithmic variance parameter to be fitted, and when the experimental data has no weakening characteristics, making =0。
2. 2. An apparatus for continuously predicting the intensity of an engineering-size irradiated material, comprising: The first acquisition module is used for acquiring first strength data obtained by unirradiation tensile test of first tensile samples of different size points under different size lineages, wherein the different size lineages comprise a nanometer tensile region, a micrometer tensile region and a millimeter tensile region which are sequentially progressive from small to large; the first fitting module is used for inputting the cross-sectional area and the first intensity data of the gauge length section in the first tensile sample into an unirradiated intensity prediction model to be fitted, and fitting to obtain a first parameter set; the second acquisition module is used for acquiring second strength data obtained by a tensile test of second tensile samples of different size points in the nanometer tensile region after irradiation, wherein the target displacement injury dose under the irradiation working condition is 1dpa; the second fitting module is used for inputting the cross sectional area of the gauge length section in the second tensile sample, the first parameter set and the second intensity data into a post-irradiation intensity prediction model to be fitted, and fitting to obtain a second parameter set; The system comprises an intensity prediction module, a radiation module and a radiation module, wherein the intensity prediction module is used for inputting the cross-sectional area of an engineering-size irradiation material into a fitted post-irradiation intensity prediction model to obtain predicted intensity data of the engineering-size irradiation material, wherein the engineering size is the size of a millimeter stretching area, and the types of the first intensity data, the second intensity data and the predicted intensity data comprise yield intensity and tensile intensity; the non-irradiation intensity prediction model is: In the formula, Is of cross-sectional area of The intensity of the unirradiated sample at that time, d is the minimum feature size, In order for the average grain size to be the same, As a function of the channel weight, And Intensity functions of dislocation source limited channels and polycrystalline statistical channels respectively, Selectable weak items; The first parameter set comprises a turning area parameter, a kurtosis parameter, an intensity parameter, a first coefficient, a second coefficient, a lower bound parameter, a macroscopic limit parameter, a convergence parameter, a third coefficient, a valley depth parameter, a valley center area parameter and a logarithmic variance parameter, and the second parameter set comprises a dislocation source item increment parameter and an irradiation defect hardening item parameter to be fitted; In the post-irradiation intensity prediction model, the minimum feature size is the sum of the minimum feature size in the non-irradiation intensity prediction model and the dislocation source item increment parameter, and the macroscopic limit parameter is the sum of the macroscopic limit parameter in the non-irradiation intensity prediction model and the irradiation defect hardening item parameter; The channel weight function is: In the formula, As the turning area parameter to be fitted, As the kurtosis parameter to be fitted, The value range in the A domain is 0-1; The intensity function of the dislocation source limited passage is: In the formula, Sequentially obtaining an intensity parameter to be fitted, a first coefficient and a second coefficient; The intensity function of the polycrystalline statistical channel is: In the formula, As the lower bound parameter to be fitted, As a macroscopic limit parameter to be fitted, As the convergence parameter to be fitted, As a third coefficient to be fitted to, An average number of grains included in the gauge length segment; The optional weakening terms are: In the formula, Sequentially obtaining a valley depth parameter, a valley center area parameter and a logarithmic variance parameter to be fitted, and when the experimental data has no weakening characteristics, making =0。

Description

Continuous strength prediction method and device for engineering-size irradiation material Technical Field The invention relates to the technical field of intensity prediction, in particular to a continuous intensity prediction method and device for engineering-size irradiation materials. Background The ion irradiation has the advantages of short period, strong controllability and the like, but the depth of a damaged layer is limited, and the mechanical characterization which can be directly obtained often depends on small-size sampling and corresponding mechanical testing. Meanwhile, the metal material has remarkable size effect in small size, namely the strength is not only determined by intrinsic and irradiation defects of the material, but also influenced by factors such as geometrical characteristic dimensions, dislocation source activation modes, statistical volume and the like. Therefore, the mechanical result of small-size ion irradiation and the engineering size strength are not in a simple proportional relationship, and if a unified size variable and a trans-scale continuous model are lacked, the small-size data are difficult to reliably extrapolate to the engineering scale. In the related art, common schemes include indirect conversion of strength by using hardness or indentation index, calculation of strength increment by using a hardening model based on defect density, or empirical extrapolation after fitting different scale data respectively. The methods often have the problems of discontinuous extrapolation, insufficient characterization of a size effect mechanism, limited parameter mobility and the like, thereby influencing the stability of engineering prediction. In order to solve the above problems, a method is needed to realize irradiation state parameter solution through small-size irradiation calibration by explicitly considering the size effect under the condition of uniform size variable, so as to continuously predict the intensity of engineering-size irradiation materials. Disclosure of Invention The embodiment of the invention provides a continuous prediction method and a continuous prediction device for the strength of an engineering-size irradiation material, which can continuously predict the strength of the engineering-size irradiation material. In a first aspect, an embodiment of the present invention provides a method for continuously predicting an intensity of an engineering-size irradiated material, including: Obtaining first strength data of first tensile samples of different size points under different size lineages through an unirradiation tensile test, wherein the different size lineages comprise a nanometer tensile region, a micrometer tensile region and a millimeter tensile region which are sequentially progressive from small to large; Inputting the cross section area and the first intensity data of the gauge length section in the first tensile sample into an unirradiated intensity prediction model to be fitted, and fitting to obtain a first parameter set; obtaining second strength data of a second tensile sample of different size points in the nanometer tensile region, wherein the second strength data is obtained by a tensile test after irradiation, and the target displacement injury dose under the irradiation working condition is 1dpa; inputting the cross section area of the gauge length section in the second tensile sample, the first parameter set and the second intensity data into a post-irradiation intensity prediction model to be fitted, and fitting to obtain a second parameter set; Inputting the cross-sectional area of the engineering-size irradiation material into a fitted post-irradiation intensity prediction model to obtain predicted intensity data of the engineering-size irradiation material, wherein the engineering size is the size of a millimeter stretching area, and the types of the first intensity data, the second intensity data and the predicted intensity data comprise yield intensity and tensile intensity; the non-irradiation intensity prediction model is: In the formula, Is of cross-sectional area ofThe intensity of the unirradiated sample at that time, d is the minimum feature size,In order for the average grain size to be the same,As a function of the channel weight,AndIntensity functions of dislocation source limited channels and polycrystalline statistical channels respectively,Selectable weak items; The first parameter set comprises a turning area parameter, a kurtosis parameter, an intensity parameter, a first coefficient, a second coefficient, a lower bound parameter, a macroscopic limit parameter, a convergence parameter, a third coefficient, a valley depth parameter, a valley center area parameter and a logarithmic variance parameter, and the second parameter set comprises a dislocation source item increment parameter and an irradiation defect hardening item parameter to be fitted; In the post-irradiation intensity prediction model, the minim