Method and device for continuous prediction of strength of engineered dimension irradiated materials

Abstract

The present application relates to the technical field of strength prediction, in particular to a method and device for continuously predicting the strength of engineering size irradiated materials. The method comprises: obtaining first strength data of first tensile samples of different size points in different size spectra obtained through unirradiated tensile test; inputting the cross-sectional area of the gauge length section in the first tensile sample and the first strength data into an unirradiated strength prediction model to obtain a first parameter set; obtaining second strength data of second tensile samples of different size points obtained through tensile test after irradiation; inputting the cross-sectional area of the gauge length section in the second tensile sample, the first parameter set and the second strength data into an irradiated strength prediction model to obtain a second parameter set; and inputting the cross-sectional area of the engineering size irradiated material into the fitted irradiated strength prediction model to obtain predicted strength data of the engineering size irradiated material. The above technical solution can continuously predict the strength of the engineering size irradiated material.

Description

Technical Field

[0001] This invention relates to the field of intensity prediction technology, and in particular to a method and apparatus for continuous intensity prediction of irradiated materials of engineering size. Background Technology

[0002] Ion irradiation offers advantages such as short cycles and high controllability, but its damage layer depth is limited, and directly obtainable mechanical characterization often relies on small-scale sampling and corresponding mechanical testing. Meanwhile, metallic materials generally exhibit significant size effects at small scales; that is, strength is determined not only by the material's intrinsic properties and irradiation defects but also by factors such as geometric feature scale, dislocation source activation mode, and statistical volume. Therefore, the mechanical results of small-scale ion irradiation are not a simple proportional relationship with engineering-scale strength. Without a unified size variable and a cross-scale continuity model, small-scale data cannot be reliably extrapolated to engineering scales.

[0003] Common approaches in related technologies include indirectly converting strength using hardness or indentation indices, extrapolating strength increments based on hardening models with defect density, or fitting data at different scales separately and then performing empirical extrapolation. These methods often suffer from problems such as discontinuous extrapolation, insufficient characterization of size effect mechanisms, and limited parameter transferability, which in turn affect the stability of engineering predictions.

[0004] To address the aforementioned issues, there is an urgent need for a method that can explicitly consider size effects under a unified size variable and solve for irradiation state parameters through small-size irradiation calibration, thereby enabling continuous prediction of the intensity of irradiated materials of engineering size. Summary of the Invention

[0005] This invention provides a method and apparatus for continuous prediction of the intensity of irradiated materials of engineering size, which can continuously predict the intensity of irradiated materials of engineering size.

[0006] In a first aspect, embodiments of the present invention provide a method for continuous intensity prediction of irradiated materials of engineering size, comprising:

[0007] First strength data were obtained from unirradiated tensile tests on first tensile specimens at different size points under different size spectrums; wherein, different size spectrums include nano-tensile region, micro-tensile region and millimeter tensile region progressively from small to large;

[0008] The cross-sectional area of ​​the gauge length segment and the first strength data of the first tensile specimen are input into the unirradiated intensity prediction model to be fitted, and the first parameter set is obtained by fitting.

[0009] Second strength data were obtained from tensile tests of second tensile specimens at different size points in the nano-tensile region after irradiation; wherein the target displacement damage dose under irradiation conditions was 1 dpa.

[0010] The cross-sectional area of ​​the gauge length section of the second tensile specimen, the first parameter set, and the second strength data are input into the post-irradiation strength prediction model to be fitted, and the second parameter set is obtained by fitting.

[0011] The cross-sectional area of ​​the irradiated material of engineering size is input into the fitted post-irradiation strength prediction model to obtain the predicted strength data of the irradiated material of engineering size; where the engineering size is the size of the tensile zone in millimeters, and the types of the first strength data, the second strength data and the predicted strength data all include yield strength and tensile strength;

[0012] The prediction model for unirradiated intensity is as follows:

[0013]

[0014] In the formula, The cross-sectional area is Intensity of the unirradiated sample at that time d For the minimum feature size, The average grain size, For channel weighting functions, and These are the intensity functions for the dislocation source confined channel and the polycrystalline statistical channel, respectively. This is an optional weakening option;

[0015] The first set of parameters includes the inflection area parameter, kurtosis parameter, intensity parameter, first coefficient, second coefficient, lower bound parameter, macroscopic limit parameter, convergence parameter, third coefficient, valley depth parameter, valley center area parameter, and log-variance parameter. The second set of parameters includes the dislocation source term increment parameter and irradiation defect hardening term parameter to be fitted.

[0016] In the post-irradiation intensity prediction model, the minimum feature size is the sum of the minimum feature size in the unirradiated intensity prediction model and the incremental parameter of the dislocation source term, and the macroscopic limit parameter is the sum of the macroscopic limit parameter in the unirradiated intensity prediction model and the parameter of the irradiation defect hardening term.

[0017] Secondly, embodiments of the present invention also provide a device for continuous intensity prediction of engineering-sized irradiated materials, comprising:

[0018] The first acquisition module is used to acquire the first strength data of the first tensile specimens at different size points under different size series obtained by unirradiated tensile test; wherein, the different size series include the nano-tensile region, micron-tensile region and millimeter-tensile region progressively from small to large;

[0019] The first fitting module is used to input the cross-sectional area of ​​the gauge length segment and the first strength data of the first tensile specimen into the unirradiated intensity prediction model to be fitted, and to fit the first set of parameters.

[0020] The second acquisition module is used to acquire the second strength data of the second tensile specimens at different size points under the nano-tensile region after irradiation tensile test; wherein, the target displacement damage dose under irradiation condition is 1 dpa.

[0021] The second fitting module is used to input the cross-sectional area of ​​the gauge length segment in the second tensile specimen, the first parameter set, and the second strength data into the irradiated intensity prediction model to be fitted, and to fit the second parameter set.

[0022] The strength prediction module is used to input the cross-sectional area of ​​the irradiated material of engineering size into the fitted post-irradiation strength prediction model to obtain the predicted strength data of the irradiated material of engineering size; wherein, the engineering size is the size of the tensile zone in millimeters, and the types of the first strength data, the second strength data and the predicted strength data all include yield strength and tensile strength;

[0023] The prediction model for unirradiated intensity is as follows:

[0024]

[0025] In the formula, The cross-sectional area is Intensity of the unirradiated sample at that time d For the minimum feature size, The average grain size, For channel weighting functions, and These are the intensity functions for the dislocation source confined channel and the polycrystalline statistical channel, respectively. This is an optional weakening option;

[0026] The first set of parameters includes the inflection area parameter, kurtosis parameter, intensity parameter, first coefficient, second coefficient, lower bound parameter, macroscopic limit parameter, convergence parameter, third coefficient, valley depth parameter, valley center area parameter, and log-variance parameter. The second set of parameters includes the dislocation source term increment parameter and irradiation defect hardening term parameter to be fitted.

[0027] In the post-irradiation intensity prediction model, the minimum feature size is the sum of the minimum feature size in the unirradiated intensity prediction model and the incremental parameter of the dislocation source term, and the macroscopic limit parameter is the sum of the macroscopic limit parameter in the unirradiated intensity prediction model and the parameter of the irradiation defect hardening term.

[0028] This invention provides a method and apparatus for continuous prediction of the strength of irradiated materials of engineering size. First, using the first strength data obtained from unirradiated tensile tests on first tensile specimens at different size points within different size spectrums, and the cross-sectional area of ​​the gauge length segment of the first tensile specimens at each size point, a first parameter set is obtained by fitting an unirradiated strength prediction model. Second, using the second strength data obtained from irradiated tensile tests on second tensile specimens at different size points within the nano-tensile region, and the cross-sectional area of ​​the gauge length segment of the second tensile specimens, along with the first parameter set, a second parameter set is obtained by fitting an irradiated strength prediction model. Finally, the cross-sectional area of ​​the irradiated material of engineering size is input into the fitted irradiated strength prediction model to obtain the predicted strength data of the irradiated material of engineering size. Therefore, the above technical solution can continuously predict the strength of irradiated materials of engineering size. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a flowchart of the method for continuous prediction of the intensity of irradiated materials of engineering dimensions provided in the embodiments of the present invention;

[0031] Figure 2 This is a hardware architecture diagram of the electronic device provided in an embodiment of the present invention;

[0032] Figure 3 This is a structural diagram of the continuous intensity prediction device for engineering-sized irradiated materials provided in an embodiment of the present invention;

[0033] Figure 4 These are actual processed morphology images of tensile specimens at different size points under different size spectrums;

[0034] Figure 5 This is a schematic diagram of grain orientation selection and sample taking;

[0035] Figure 6 This is a schematic diagram of the engineering stress-engineering strain curves of tensile specimens under different size spectrums.

[0036] Figure 7 This is a scatter plot of the actual intensity and cross-sectional area under unirradiated conditions;

[0037] Figure 8 It is a fitted curve of intensity and cross-sectional area under non-irradiated conditions;

[0038] Figure 9 It is a fitted curve of intensity and cross-sectional area under irradiation conditions;

[0039] Figure 10 This is a schematic diagram showing the dose-intensity comparison at the cross-sectional area of ​​the irradiated material of engineering size. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0041] like Figure 1 As shown, this embodiment of the invention provides a method for continuous intensity prediction of irradiated materials of engineering size, including:

[0042] Step 100: Obtain the first strength data of the first tensile specimens at different size points under different size spectrums through unirradiated tensile tests; wherein, the different size spectrums include the nano-tensile region, micron-tensile region and millimeter-tensile region progressively from small to large.

[0043] Step 102: Input the cross-sectional area of ​​the gauge length segment and the first strength data of the first tensile specimen into the unirradiated intensity prediction model to be fitted, and obtain the first parameter set.

[0044] Step 104: Obtain the second strength data of the second tensile specimens at different size points under the nano-tensile region after irradiation tensile test; wherein, the target displacement damage dose under irradiation condition is 1 dpa.

[0045] Step 106: Input the cross-sectional area of ​​the gauge length segment of the second tensile specimen, the first parameter set, and the second strength data into the irradiated intensity prediction model to be fitted, and obtain the second parameter set by fitting.

[0046] Step 108: Input the cross-sectional area of ​​the irradiated material of engineering size into the fitted post-irradiation strength prediction model to obtain the predicted strength data of the irradiated material of engineering size; wherein, the engineering size is the size of the tensile zone in millimeters, and the types of the first strength data, the second strength data and the predicted strength data all include yield strength and tensile strength.

[0047] In this embodiment, firstly, the first strength data obtained from unirradiated tensile tests on first tensile specimens at different size points under different size spectrums, along with the cross-sectional area of ​​the gauge length segment of the first tensile specimens at each size point, are used to fit the unirradiated strength prediction model to obtain a first parameter set. Secondly, the second strength data obtained from irradiated tensile tests on second tensile specimens at different size points under the nano-tensile region, along with the cross-sectional area of ​​the gauge length segment of the second tensile specimens and the first parameter set, are used to fit the irradiated strength prediction model to obtain a second parameter set. Finally, the cross-sectional area of ​​the irradiated material of engineering size is input into the fitted irradiated strength prediction model to obtain the predicted strength data of the irradiated material of engineering size. Therefore, the above technical solution can continuously predict the strength of irradiated materials of engineering size.

[0048] In one embodiment of the present invention, the unirradiated intensity prediction model is as follows:

[0049]

[0050] In the formula, The cross-sectional area is Intensity of the unirradiated sample at that time d For the minimum feature size, The average grain size, For channel weighting functions, and These are the intensity functions for the dislocation source confined channel and the polycrystalline statistical channel, respectively. This is an optional weakening option.

[0051] In one embodiment of the present invention, the channel weighting function is:

[0052]

[0053] In the formula, Let be the inflection area parameter to be fitted. Let be the kurtosis parameter to be fitted. exist A The value range within the domain is 0 to 1.

[0054] In one embodiment of the present invention, the intensity function of the confined channel of the dislocation source is:

[0055]

[0056] In the formula, The parameters to be fitted, the first coefficient, and the second coefficient are listed in order.

[0057] In one embodiment of the present invention, the intensity function of the polycrystalline statistical channel is:

[0058]

[0059] In the formula, Let be the lower bound parameter to be fitted. Let be the macroscopic limiting parameter to be fitted. Let be the convergence parameters to be fitted. The third coefficient to be fitted. This represents the average number of grains included in the gauge segment.

[0060] In one embodiment of the present invention, an optional reduction measure is:

[0061]

[0062] In the formula, The parameters to be fitted are, in order, valley depth, valley center area, and log-variance; when the experimental data do not have weakening features, let =0.

[0063] In one embodiment of the present invention, the first parameter set includes 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 log-variance parameter; the second parameter set includes the dislocation source term increment parameter and the irradiation defect hardening term parameter to be fitted.

[0064] In the post-irradiation intensity prediction model, the minimum feature size is the sum of the minimum feature size in the unirradiated intensity prediction model and the incremental parameter of the dislocation source term, and the macroscopic limit parameter is the sum of the macroscopic limit parameter in the unirradiated intensity prediction model and the parameter of the irradiation defect hardening term.

[0065] The process of building the above model is described below.

[0066] In micro-components, dislocation activity is strongly constrained by free surfaces and finite geometry; traditional dislocation sources require a certain length. L Only then can it be driven by stress. When the minimum feature size of the sample... d Less than or equal to the length of the dislocation source within the sample L At the microscopic level, the length of a dislocation source exhibits statistical fluctuations, so it is generally considered that for the same order of magnitude... d ≈ LThe source is truncated by the free surface, leaving only a single-arm dislocation source (SAS) with one end pinned and the other end near the surface. This significantly increases its activation critical stress, a phenomenon known as source truncation. Furthermore, the free surface of small samples is attractive to dislocations, causing them to slide towards the surface. Reduced access channels and the number of available sources make the material more "dislocation-deficient," further raising the yield threshold; this is known as starvation. With smaller samples, the number of independent sources / slip bands that can participate simultaneously decreases, meaning that even if the intensity distribution of each source remains unchanged, the weakest source overall will shift towards the stronger side.

[0067] Treating dislocations as having linear tension T A flexible line. For a length of... L Dislocations under external shear stress τ Under the influence of the force, it bends into an approximate circular arc, and when it reaches the "critical bending" state, it will emit dislocation loops (or push dislocations to the surface):

[0068]

[0069] In the formula b The Burgers vector is typically taken as the base vector for aluminum alloys. b =0.286nm. For isotropic elasticity,

[0070]

[0071] In the formula μ The shear modulus is taken as 26~30 GPa in Al-Mg alloys; ν The ratio is Poisson's ratio, taken as 0.33; r 0 is the dislocation scale, and R is the outer cutoff radius.

[0072] For a single-arm dislocation source, the length of the dislocation source is constrained by the geometric minimum scale, and the effective source length can be taken. L d At the same time, the outer cutoff radius R Also with L Since they are of the same order, therefore:

[0073]

[0074] In the formula, α is a dimensionless geometric / anisotropic correction. A * In order to put The dimensionless term resulting from merging the proportionality constant and the dislocation source radius ensures the correct dimensions within the logarithm.

[0075] Since the SAS model describes the dislocation shearing process, it needs to be transformed into a stretching process. Assume that the SAS occurs in a single crystal with a fixed orientation. , ( m s (for the Schmid factor); therefore

[0076]

[0077] In real materials, besides dislocation sources, there are also solid solution strengthening and precipitation strengthening. Since this experiment primarily focuses on size effects, other irrelevant dimensions or quantities minimally affected by size effects are combined into a single constant. σ 0. After merging constants:

[0078]

[0079] In the formula , .

[0080] In the field of materials preparation, the grain size of a sample significantly affects the yield strength of the material. According to the Hall-Petch relation, the yield strength of a material increases as the average grain diameter decreases. Assuming the grain diameter remains constant, when the cross-sectional area increases, the number of grains that can be supported in parallel within the cross-section... N Increase. When there are only a very few grains (or even just two) in the cross-section, the structural mechanics is more like a small number of parallel individuals, with the weakest link dominating failure. Two scenarios exist:

[0081] ① Including premature failure along grain / interface: If there is a grain boundary with high fault orientation or impurity segregation, this interface can locally crack or undergo severe slip discontinuity under low applied stress; the sample is "close to fracture" at this time, and the strength at this time is the lower limit of yield.

[0082] ② Unfavorable orientation / insufficient sampling: A small number of grains means fewer slip system combinations that can participate in load bearing, and there may be no favorable orientation with a "high Schmid factor"; the equivalent external stress required is lower to trigger local instability at a weak interface or unfavorable grain, which also pulls the overall stress down to the lower limit.

[0083] Suppose that in a certain slip system of a crystal (given the slip plane normal n and slip direction s), there is a shear stress threshold required to just initiate dislocation slip, denoted as τ CRSS Under uniaxial tension, the resolved shear stress on this slip system is:

[0084]

[0085] In the formula, θThe angle between the load direction and the normal to the slip surface. ξ The angle between the load direction and the slip direction. This "statistical isotropy" allows the material to exhibit a stable equivalent Taylor factor. M :

[0086]

[0087] in M Follow N Increase from low value M 1 (in the case of very few grains, corresponding to the effective Taylor factor of sample orientation / texture) towards the macroscopic limit M ∞ convergence.

[0088] along with N An increase will monotonically raise the macroscopic intensity and reduce the dispersion in two ways:

[0089] ① More comprehensive orientation statistics: More grains mean a more complete orientation / slip system. It is not one or two grains that determine success or failure, but many slip systems share the burden simultaneously.

[0090] ② "Multi-strain hardening": Polycrystalline parallel plasticity requires the geometric compatibility of adjacent grains. Geometrically necessary dislocations (GNDs) are generated near grain boundaries to coordinate mismatches, which increases the external stress required to maintain the same macroscopic strain. The more grains there are and the more diverse the orientations, the more obvious this network constraint becomes, and the equivalent macroscopic strength shifts upward accordingly.

[0091] along with N As the number of grains increases, the statistically discrete probability of intergranular fracture is dispersed / passivated, and the macroscopic response changes from "weak chain control" to "collective yielding," with the intensity converging towards the macroscopic limit. When N When the yield strength is sufficiently large, the material exhibits a compatible flow of statistical isotropy and stability, and the yield / flow strength measured at this point is the limit obtained from conventional macroscopic tests. (i.e., macroscopic measurement results)

[0092] In statistics, coverage or extreme value statistics are typically described using an exponential saturation function:

[0093]

[0094] In the formula, N c The number of characteristic grains at which a statistical effect inflection point occurs; p Let be the convergence constant. M N Substitute return σ = Mτ CRSS :

[0095]

[0096] In the formula N Cross-sectional area A Functions: The yield strength regulated by the ST mechanism is:

[0097]

[0098] Based on the discussion in the previous two sections, at the ultrawide scale, the fracture behavior of the sample follows the mechanism as follows:

[0099] Small-sized end (near single crystal): There is only one or a very few grains on the cross-section. The free surface truncates the available dislocation sources into single-arm sources (SAS); the source "entry / turnover" threshold is high, and the nominal strength TS of the sample is close to the failure threshold. At this time, the SAS channel is the main load-bearing channel.

[0100] Large-size end (polycrystalline, isotropic): The cross-section contains many grains, and the free volume of each grain is approximately equal to the bulk volume of the grain, thus eliminating free surface constraints. A sufficient slip network can be used, and the material exhibits statistical isotropy, with strength converging towards the macroscopic limit. At this point, the SAS channel becomes "failed / marginalized" and is dominated by the ST channel.

[0101] Medium size (transition domain): The number of grains is still small, and the effective dislocation source length is... L Neither too short (not "passive") nor "infinitely long" (not macroscopic), the SAS channel is meaningful and participates in carrying. If a type of fragile grain boundary exists, a "shallow valley" may also appear in this range (premature weakening along the grain or at the interface).

[0102] To describe the proportion of physical mechanisms at the current size, channel openness is defined:

[0103]

[0104] In the formula, A w The boundary scale of the passage, that is, when A=A w At this time, the SAS and ST mechanisms have equal weight in intensity control; ω is the channel steepness, which represents how quickly the weight of the two mechanisms changes with area. A →0: Available dislocation sources are strongly constrained by the surface, and the SAS mechanism dominates entirely at this time. .when A As we approach infinity: the influence of free surfaces becomes negligible, and the ST mechanism dominates entirely. .

[0105] In summary, for the full-size effect, the relationship between yield strength and cross-sectional area is as follows:

[0106]

[0107] In the formula, ( A This refers to the valley weakening phase that describes a special case (such as a low-probability failure characteristic caused by N=2 and a particularly large grain boundary angle):

[0108]

[0109] This item can be deleted if the experimental results do not show obvious valleys or medium-sized (SEM size) intergranular fractures.

[0110] Example

[0111] In this embodiment, Al-Mg alloy sheet was selected as the sample material. The material was from the same batch and under the same processing and heat treatment conditions. Subsequent samples for all dimensions and irradiation were obtained from samples taken from this sheet. In this embodiment, a flat dog-bone tensile specimen with a rectangular cross-section was used uniformly throughout the entire dimensional spectrum, based on the original cross-sectional area of ​​the gauge length. A As a uniform dimensional variable across the entire size, the flat section is determined by the gauge length width. With thickness Determine, define A = w × t In this embodiment, the width-to-thickness ratio of the gauge length of the fixed sample is... w / t The ratio is 2:1±10% (i.e., 1.8:1~2.2:1), and the cross-sectional shape (width-to-thickness ratio) remains consistent across all scales.

[0112] In this embodiment, the sample cross-sectional shape is selected from either cylindrical or flat, and the cross-sectional shape remains consistent within the same size spectrum; the cross-sectional area of ​​the gauge length segment is used as the reference. A As a uniform dimensional variable, the cylindrical section is determined by its diameter, while the flat section is determined by its width and thickness.

[0113] In this embodiment, multiple size points are set in the nano-stretching region (i.e., the TEM region), the micro-stretching region (i.e., the SEM region and the DMA region), and the millimeter-stretching region (i.e., the EUTM region). For example, four nanometer-scale size points are set in the TEM region, and the gauge length thickness is... t The wavelengths are 200nm, 500nm, 800nm, and 1000nm, respectively; three micrometer-level points are set in the SEM area, and the gauge length thickness is... t The thicknesses are 3μm, 5μm, and 10μm, respectively; three large micrometer-level points are set in the DMA region, and the gauge length thickness is... tThe gauge lengths are 75 μm, 150 μm, and 300 μm, respectively; three millimeter-level points are set in the EUTM region, with gauge length thicknesses t of 1 mm, 3 mm, and 6 mm, respectively. Representative processing morphologies and geometric measurement results for specimens at each scale are as follows: Figure 4 As shown, the aspect ratio of all tensile samples (including parallel samples) involved in all dimensions ranges from 1.84:1 to 2.16:1, which meets the error range requirement of 2:1 ± 10%.

[0114] In this embodiment, "engineering size" refers to the millimeter-scale stretching region size relative to the nanometer and micrometer stretching regions, preferably referring to a range of millimeter-scale gauge length sizes that can be prepared and tested using conventional macroscopic stretching methods. In this embodiment, the engineering size corresponds to the EUTM region specimen, for example, including gauge length thicknesses of 1 mm, 3 mm, and 6 mm. In this embodiment, for each gauge length specimen, the key geometric parameters of the gauge length (width) are... w ,thickness t Gauge length L 0) Perform measurement recording; in this embodiment, the geometric measurement method is scale-matched: TEM-scale sample measurement is performed under TEM, and its thickness is... t Thickness data from the FIB-SEM sample preparation process is preferred, and the thickness is verified using the CBED method with a verification error of less than 9%. The dimensions of SEM-scale specimens are measured under SEM; the dimensions of DMA-scale specimens are measured using a metallographic microscope; and the dimensions of macroscopic EUTM-scale specimens are measured using vernier calipers.

[0115] In this embodiment, the corresponding grain orientation selection and sampling are illustrated as follows: Figure 5 As shown, the average grain size of the sample was measured using EBSD technology. For flat rectangular cross-section specimens, take This is used to characterize the statistical averaging of the lateral scale of gauge lengths at different sizes relative to the grain scale. Since this embodiment is fixed... w / t =2:1, therefore .

[0116] This embodiment introduces EBSD orientation screening and positioning during the sample preparation stage. For samples with a thickness of less than 5 μm, orientation constraints are implemented, meaning all relevant samples are taken from the

[001] oriented grains and the loading direction is ensured to be perpendicular to the target orientation. In this embodiment, the

[001] orientation deviation angle is controlled to be no more than 10°. Furthermore, this embodiment proposes a "same grain" constraint for key dimensions used in subsequent extrapolation of irradiation intensity: the irradiation calibration point used for extrapolation preferably ensures that the gauge length is located within the same grain; if it is unavoidable to cross two grains, the orientation angle between the two grains must be small, and the number of parallel tests must be increased.

[0117] In this embodiment, tensile tests were conducted on Al-Mg alloy specimens of various scales that were prepared and met the geometric quality control requirements, under pre-set loading and environmental conditions. Load-displacement data were obtained and converted into engineering stress-strain curves. Typical curves for specimens of different scales are shown below. Figure 6 As shown. Among them, tensile strength... σ t The maximum engineering stress peak value of the same engineering stress-engineering strain curve is taken, and the engineering strain corresponding to the peak point is recorded as the peak strain.

[0118] In this embodiment, three valid parallel samples are obtained for each dimension point for statistical analysis. If a parallel sample does not meet the validity criteria (including but not limited to the fracture not occurring within the gauge length or an abnormal curve), it is discarded and supplemented until the number of valid parallel samples for that dimension point is restored to three. The results are calculated separately for the three valid parallel samples at each dimension point. σ y and σ t And take the average value to obtain the average yield strength and average tensile strength of that dimension point; average the values ​​of each dimension point Compared with average Based on average cross-sectional area By summarizing, we obtain the dataset under the unirradiated conditions. ,like Figure 7 As shown.

[0119] This embodiment employs a non-irradiation intensity prediction model that combines SAS and ST channels, and uses a gating function χ(A) to smoothly transition between the two channels. This takes into account a rectangular cross-section and a typical width-to-thickness ratio. w / t ≈2:1, this embodiment uses ≈2:1 in the unified curve representation. Achieve the effect of cross-sectional area A To feature size d The mapping.

[0120] This embodiment uses the uniform curve calculation method... A (Unit: mm) 2 () is used as input and converted within the model; The output unit is MPa, where k = y Indicates yield strength, k = t Indicates tensile strength.

[0121] This embodiment is... Figure 7 As shown Weighted fitting of the scatter points yields the following uniform yield strength curve:

[0122]

[0123]

[0124]

[0125] because Therefore, the yield strength in this embodiment is

[0126]

[0127] This embodiment is... Figure 7 As shown Weighted fitting of the scatter points yields the following uniform tensile strength curve:

[0128]

[0129]

[0130]

[0131] Therefore, the tensile strength in this embodiment is:

[0132]

[0133] In this embodiment, the corresponding fitting result curve and the experimental scatter plot are compared as follows: Figure 8 As shown; the goodness of fit of the yield strength channel and the tensile strength channel are respectively R y =0.91 and R t =0.89.

[0134] In this embodiment, four micro / nano-scale points were selected from the determined size spectrum as irradiation calibration points, with thicknesses of [missing information]. t =200nm, 500nm, 800nm, 1000nm. In this embodiment, two target displacement damage doses are set, namely 1.0dpa and 10dpa; both doses use the same irradiation flux and irradiation temperature conditions, and the difference in target dose is achieved only by controlling the total flux (or irradiation time).

[0135] This embodiment uses single-energy descaling ion irradiation with incident ions of 1.35 MeV Si. 5+ The irradiation flux was set at 1.6 × 10⁻⁶. 12 ions·cm -2 ·s -1 The irradiation temperature was 298K. For the target dose... D tar Calculate the required total injection volume Φ (ions / cm) for 1.0 dpa and 10 dpa respectively. 2And based on this, the irradiation time is determined. t irr .

[0136] In this embodiment, the irradiation calibration points of the second tensile specimen are the same as those of the first tensile specimen, which are four thickness points. t =200nm, 500nm, 800nm, 1000nm. Yield strength after irradiation was obtained at four calibration points under two dose levels: 1.0dPa and 10dPa. Tensile strength after irradiation and the average cross-sectional area of ​​the gauge length segment As a unified size variable, intensity-size datasets are formed under two irradiation conditions. .

[0137] In this embodiment, for alloys irradiated with 1 dpa, according to the dataset Do not enable the weakening option, take The fitting result for its yield strength is:

[0138]

[0139]

[0140]

[0141] because Therefore, the yield strength of the alloy irradiated with 1 dpa in this embodiment is:

[0142]

[0143] In this embodiment, for alloys irradiated with 1 dpa, according to the dataset The fitting result for its tensile strength is:

[0144]

[0145]

[0146]

[0147]

[0148]

[0149] In this embodiment, for alloys irradiated with 10 dPa, based on the dataset... Do not enable the weakening option, take The fitting result for its yield strength is:

[0150]

[0151]

[0152]

[0153]

[0154]

[0155] In this embodiment, for alloys irradiated with 10 dPa, based on the dataset... The fitting result for its tensile strength is:

[0156]

[0157]

[0158]

[0159]

[0160]

[0161] The fitted curves of the alloy after two doses of irradiation were compared with the corresponding irradiation calibration points and extrapolated to obtain the following results: Figure 9 The results are shown; where the red dots and red curves correspond to 1.0 dPa, and the blue dots and blue curves correspond to 10 dPa. Figure 9 The millimeter-level reference points provided are used for external evaluation of the extrapolation results of the engineering dimension range in this embodiment. The Al-2.2Mg reference point is derived from the tensile property-feedback curve of Al-Mg alloy at 323 K in Farrell's work (K. Farrell, Microstructure and tensile properties of heavily irradiated 5052-O aluminum alloy, J. Nucl. Mater. 97(1981) 33–43), with a gauge length cross-sectional area of ​​approximately 8.04 mm² for the tensile specimen. 2The literature reference for Al-2.5Mg comes from the research by Li et al. (W. Li et al., Effect of neutronfluence on microstructure and mechanical properties of Al 5052 irradiated in the NRU reactor, J. Nucl. Mater. 522 (2019) 144–157), which published millimeter-scale tensile results, with a gauge length cross-sectional area of ​​approximately 12.57 mm for the tensile specimens. 2 The references mentioned above are all used to evaluate whether the strength magnitude of the extrapolation results in this embodiment is within a reasonable range for the engineering size range.

[0162] In other words, to evaluate the rationality of the extrapolation results of the new cross-sectional area input value of the model established in this embodiment within the engineering size range, based on the extrapolation results of 72 mm² engineering size, an external reference point formed by millimeter-level Al-Mg alloy tensile data is further disclosed to evaluate whether the strength magnitude of the extrapolation results in this embodiment is within a reasonable range within the engineering size range.

[0163] In this embodiment, the preferred engineering size is a millimeter tensile specimen; samples with gauge length thicknesses of 1 mm, 3 mm, and 6 mm constitute representative size points within the engineering size range. This embodiment selects a macroscopic engineering size tensile specimen with a gauge length thickness of 6 mm as the extrapolation prediction target, with a cross-sectional area of ​​72 mm². 2 .

[0164] In this embodiment, a macroscopic engineering tensile sample with a gauge length thickness of 6 mm is selected as the extrapolation prediction target, and its cross-sectional area is 72 mm². 2 .

[0165] This embodiment outputs macroscopic engineering dimensions under different irradiation doses. D The predicted values ​​of yield strength and tensile strength are denoted as follows:

[0166]

[0167] Extrapolate the above engineering dimensions to the cross-sectional area of ​​the target sample. A eng Substituting the strength fitting formulas corresponding to three working conditions—0 dPa (unirradiated baseline), 1.0 dPa, and 10 dPa—into the macroscopic engineering dimensions... A eng The extrapolated predicted values ​​of yield strength and tensile strength are as follows (unit: MPa):

[0168]

[0169]

[0170]

[0171] Therefore, Figure 9 Based on the original irradiation fitting curve, additional data points from publicly available literature on millimeter-scale Al-Mg alloys were added to externally evaluate the extrapolation results for the engineering size range of this embodiment. The supplemented literature points in the figure are located within the millimeter-scale cross-sectional area range and can be used to evaluate whether the strength magnitude of the extrapolation results for this embodiment is within a reasonable range for the engineering size range. Figure 9 As can be seen, in the low-dose region, the literature points at similar irradiation exposure levels are on a similar order of magnitude to the extrapolation results of this embodiment, indicating that the model in this embodiment has a certain degree of extrapolation rationality within the engineering size range. For the high-dose region, the published neutron irradiation literature points are generally higher than the 10 dpa extrapolation curve of this embodiment; combined with the discussion in the published literature on the additional enhancement mechanism under high heat flux, this part of the results is mainly used to illustrate the applicable boundaries of the model in this embodiment, rather than to make a strict quantitative consistency judgment.

[0172] The applicable boundary of the extrapolation prediction in this embodiment is: the extrapolation results should be combined with external literature reference points supplemented by the engineering size range and evidence of local hardening trends under the same material system to determine whether they correspond or are similar to the strength levels obtained by similar materials and under similar service / irradiation conditions in engineering practice in terms of magnitude and trend, and then used for engineering evaluation and screening decisions.

[0173] Figure 10 A comparison is provided between the extrapolated results of this embodiment and publicly available neutron irradiation data. The comparison points for 5052-O and 5154-O in the figure are derived from the tensile curves of irradiated Al alloys summarized in the Kolluri review (Murthy Kolluri, Neutron Irradiation Effects in 5xxx and 6xxx Series Aluminum Alloys: A Literature Review). The black boxes and red data points in the figure represent the neutron irradiation intensity data obtained under corresponding conditions for 5052-O and 5154-O aluminum alloys in the published literature, respectively. The temperatures within parentheses represent the service temperatures corresponding to the data. The extrapolated results of this embodiment correspond to the T-state aluminum alloy. It should be noted that... Figure 10 The publicly available data differs from this embodiment in terms of alloy composition, heat treatment state, aging history, and service temperature. Furthermore, the irradiation dose shown on the horizontal axis is a similar irradiation exposure level calculated based on the material correspondence in this embodiment, used for reference and comparison between different data points, and does not imply a strict one-to-one correspondence between the publicly available data and this embodiment in terms of dpa. Therefore, Figure 10 This method is primarily used to compare the intensity variation magnitude and trend between the extrapolation results of this embodiment and publicly available neutron irradiation data within similar exposure ranges. Overall, the extrapolation results of this embodiment are comparable to publicly available neutron irradiation data in terms of intensity variation trend and magnitude, and can be used as a reference for engineering evaluation and screening.

[0174] It should be noted that, Figure 9 The supplementary publicly available literature data is only used for external evaluation under similar service temperatures and similar irradiation exposure levels. Its purpose is to assess whether the strength magnitude of the extrapolation results of this embodiment is reasonable within the engineering size range, rather than to prove that different material systems have quantitative consistency under strictly identical dpa conditions.

[0175] Therefore, this invention establishes an extrapolation method for calculating the yield strength and tensile strength of irradiated materials at engineering sizes by combining a standardized multi-scale specimen system, a non-irradiated baseline model, and small-size irradiation calibration. Furthermore, by incorporating external literature evaluation data supplemented within the engineering size range and evidence of auxiliary hardening trends under the same material system, the strength magnitude, variation trend, and applicable boundaries of the extrapolated results can be evaluated, providing a reference for strength assessment, material selection, and service trend judgment of irradiated materials at engineering sizes.

[0176] Therefore, this invention combines a standardized multi-scale sample system, an unirradiated baseline model, and small-size irradiation calibration to achieve extrapolation prediction of yield strength and tensile strength of engineering-sized samples after irradiation without the need for large-volume neutron irradiation mechanical tests. This invention can be used for rapid material screening and engineering evaluation decisions.

[0177] In summary, this invention discloses a strength extrapolation prediction method based on multi-scale mechanical size effects and small-scale irradiation calibration. This method converts mechanical data obtained from small-scale samples under ion irradiation conditions into post-irradiation strength prediction results for engineering-sized components. The method normalizes the strength response of samples at different scales using a unified size variable, establishes a strength-size continuity model that considers both the confinement effect of small-scale dislocation sources and the statistical effect of larger sizes, and achieves smooth transitions between different mechanism channels through gating functions. Based on this, the irradiation state model parameters are solved using small-scale irradiation calibration points to obtain the irradiation state strength-size relationship and achieve extrapolation prediction of engineering dimensions. Compared to traditional methods relying on large-volume neutron irradiation mechanical experiments or single-scale empirical extrapolation, this invention can achieve rapid prediction of post-irradiation yield strength and tensile strength while ensuring the interpretability of size effects and the continuity of extrapolation. It can be used for rapid screening of irradiated materials, engineering evaluation, and service performance inference.

[0178] like Figure 2 , Figure 3As shown, this invention provides a device for continuous intensity prediction of irradiated materials at engineering dimensions. The device can be implemented via software, hardware, or a combination of both. From a hardware perspective, such as... Figure 2 The diagram shown is a hardware architecture diagram of an electronic device for continuously predicting the intensity of irradiated materials of engineering dimensions, provided in an embodiment of the present invention. Except for... Figure 2 In addition to the processor, memory, network interface, and non-volatile memory shown, the electronic device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing packets. Taking software implementation as an example, such as... Figure 3 As shown, a device in a logical sense is formed by the CPU of the electronic device in which it is located reading the corresponding computer program from the non-volatile memory into the memory for execution.

[0179] This embodiment provides a continuous intensity prediction device for engineering-sized irradiated materials, comprising:

[0180] The first acquisition module 300 is used to acquire the first strength data of the first tensile specimens at different size points under different size series obtained by unirradiated tensile test; wherein, the different size series includes the nano-tensile region, micro-tensile region and millimeter tensile region progressively from small to large.

[0181] The first fitting module 302 is used to input the cross-sectional area of ​​the gauge length segment and the first strength data of the first tensile specimen into the unirradiated intensity prediction model to be fitted, and to fit the first parameter set.

[0182] The second acquisition module 304 is used to acquire the second strength data of the second tensile specimens at different size points under the nano-tensile region after irradiation tensile test; wherein, the target displacement damage dose under irradiation condition is 1 dpa.

[0183] The second fitting module 306 is used to input the cross-sectional area of ​​the irradiated material of engineering size into the irradiated intensity prediction model to be fitted, and to obtain the second parameter set.

[0184] The strength prediction module 308 is used to input the cross-sectional area of ​​the irradiated material of engineering size into the fitted post-irradiation strength prediction model to obtain the predicted strength data of the irradiated material of engineering size; wherein, the engineering size is the size of the tensile zone in millimeters, and the types of the first strength data, the second strength data and the predicted strength data all include yield strength and tensile strength;

[0185] The prediction model for unirradiated intensity is as follows:

[0186]

[0187] In the formula, The cross-sectional area is Intensity of the unirradiated sample at that time d For the minimum feature size, The average grain size, For channel weighting functions, and These are the intensity functions for the dislocation source confined channel and the polycrystalline statistical channel, respectively. This is an optional weakening option;

[0188] The first set of parameters includes the inflection area parameter, kurtosis parameter, intensity parameter, first coefficient, second coefficient, lower bound parameter, macroscopic limit parameter, convergence parameter, third coefficient, valley depth parameter, valley center area parameter, and log-variance parameter. The second set of parameters includes the dislocation source term increment parameter and irradiation defect hardening term parameter to be fitted.

[0189] In the post-irradiation intensity prediction model, the minimum feature size is the sum of the minimum feature size in the unirradiated intensity prediction model and the incremental parameter of the dislocation source term, and the macroscopic limit parameter is the sum of the macroscopic limit parameter in the unirradiated intensity prediction model and the parameter of the irradiation defect hardening term.

[0190] In this embodiment of the invention, the first acquisition module 300 can be used to execute step 100 in the above method embodiment, the first fitting module 302 can be used to execute step 102 in the above method embodiment, the second acquisition module 304 can be used to execute step 104 in the above method embodiment, the second fitting module 306 can be used to execute step 106 in the above method embodiment, and the intensity prediction module 308 can be used to execute step 108 in the above method embodiment.

[0191] In one embodiment of the present invention, the channel weighting function is:

[0192]

[0193] In the formula, Let be the inflection area parameter to be fitted. Let be the kurtosis parameter to be fitted. exist A The value range within the domain is 0 to 1.

[0194] In one embodiment of the present invention, the intensity function of the confined channel of the dislocation source is:

[0195]

[0196] In the formula, The parameters to be fitted, the first coefficient, and the second coefficient are listed in order.

[0197] In one embodiment of the present invention, the intensity function of the polycrystalline statistical channel is:

[0198]

[0199] In the formula, Let be the lower bound parameter to be fitted. Let be the macroscopic limiting parameter to be fitted. Let be the convergence parameters to be fitted. The third coefficient to be fitted. This represents the average number of grains included in the gauge segment.

[0200] In one embodiment of the present invention, an optional reduction measure is:

[0201]

[0202] In the formula, The parameters to be fitted are, in order, valley depth, valley center area, and log-variance; when the experimental data do not have weakening features, let =0.

[0203] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on an intensity continuous prediction device for engineering-size irradiated materials. In other embodiments of the present invention, an intensity continuous prediction device for engineering-size irradiated materials may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0204] The information interaction and execution process between the modules in the above-mentioned device are based on the same concept as the method embodiment of the present invention, and the specific details can be found in the description of the method embodiment of the present invention, and will not be repeated here.

[0205] This invention also provides an electronic device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements a method for continuous intensity prediction of engineering-sized irradiated materials according to any embodiment of this invention.

[0206] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform a method for continuous intensity prediction of an engineering-sized irradiated material according to any embodiment of this invention.

[0207] Specifically, a system or apparatus equipped with a storage medium may be provided, on which software program code implementing the functions of any of the embodiments described above is stored, and the computer (or CPU or MPU) of the system or apparatus may read and execute the program code stored in the storage medium.

[0208] In this case, the program code read from the storage medium can itself implement the function of any of the above embodiments, and therefore the program code and the storage medium storing the program code constitute part of the present invention.

[0209] Storage media embodiments for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, program code can be downloaded from a server computer via a communication network.

[0210] Furthermore, it should be clear that not only can the program code read by the computer be executed, but also the operating system or other components operating on the computer can be instructed based on the program code to perform some or all of the actual operations, thereby realizing the function of any of the embodiments described above.

[0211] Furthermore, it is understood that the program code read from the storage medium is written to the memory set in the expansion board inserted into the computer or to the memory set in the expansion module connected to the computer. Then, based on the instructions of the program code, the CPU or other components installed on the expansion board or expansion module execute some and all of the actual operations, thereby realizing the function of any of the above embodiments.

[0212] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or electronic device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or electronic device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or electronic device that includes said element.

[0213] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various storage media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0214] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for continuous prediction of the intensity of irradiated materials of engineering dimensions, characterized in that, include: First strength data were obtained from unirradiated tensile tests on first tensile specimens at different size points under different size spectrums; wherein, different size spectrums include nano-tensile region, micro-tensile region and millimeter tensile region progressively from small to large; The cross-sectional area of ​​the gauge length segment and the first strength data of the first tensile specimen are input into the unirradiated intensity prediction model to be fitted, and the first parameter set is obtained by fitting. Second strength data were obtained from tensile tests of second tensile specimens at different size points in the nano-tensile region after irradiation; wherein the target displacement damage dose under irradiation conditions was 1 dpa. The cross-sectional area of ​​the gauge length section of the second tensile specimen, the first parameter set, and the second strength data are input into the post-irradiation strength prediction model to be fitted, and the second parameter set is obtained by fitting. The cross-sectional area of ​​the irradiated material of engineering size is input into the fitted post-irradiation strength prediction model to obtain the predicted strength data of the irradiated material of engineering size; where the engineering size is the size of the tensile zone in millimeters, and the types of the first strength data, the second strength data and the predicted strength data all include yield strength and tensile strength; The prediction model for unirradiated intensity is as follows: In the formula, The cross-sectional area is Intensity of the unirradiated sample at that time d For the minimum feature size, The average grain size, For channel weighting functions, and These are the intensity functions for the dislocation source confined channel and the polycrystalline statistical channel, respectively. This is an optional weakening option; The first set of parameters includes the inflection area parameter, kurtosis parameter, intensity parameter, first coefficient, second coefficient, lower bound parameter, macroscopic limit parameter, convergence parameter, third coefficient, valley depth parameter, valley center area parameter, and log-variance parameter. The second set of parameters includes the dislocation source term increment parameter and irradiation defect hardening term 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 unirradiated intensity prediction model and the incremental parameter of the dislocation source term, and the macroscopic limit parameter is the sum of the macroscopic limit parameter in the unirradiated intensity prediction model and the parameter of the irradiation defect hardening term. The channel weighting function is: In the formula, Let be the inflection area parameter to be fitted. Let be the kurtosis parameter to be fitted. exist A The value range within the domain is 0 to 1; The intensity function of the confined channel of the dislocation source is: In the formula, The parameters to be fitted, the first coefficient, and the second coefficient are, in order. The intensity function of the polycrystalline statistical channel is: In the formula, Let be the lower bound parameter to be fitted. Let be the macroscopic limiting parameter to be fitted. Let be the convergence parameters to be fitted. The third coefficient to be fitted. This represents the average number of grains included in the gauge length segment. Optional weakening measures are: In the formula, The parameters to be fitted are, in order, valley depth, valley center area, and log-variance; when the experimental data do not have weakening features, let =0.

2. A device for continuous intensity prediction of irradiated materials of engineering dimensions, characterized in that, include: The first acquisition module is used to acquire the first strength data of the first tensile specimens at different size points under different size series obtained by unirradiated tensile test; wherein, the different size series include the nano-tensile region, micron-tensile region and millimeter-tensile region progressively from small to large; The first fitting module is used to input the cross-sectional area of ​​the gauge length segment and the first strength data of the first tensile specimen into the unirradiated intensity prediction model to be fitted, and to fit the first set of parameters. The second acquisition module is used to acquire the second strength data of the second tensile specimens at different size points under the nano-tensile region after irradiation tensile test; wherein, the target displacement damage dose under irradiation condition is 1 dpa. The second fitting module is used to input the cross-sectional area of ​​the gauge length segment in the second tensile specimen, the first parameter set, and the second strength data into the irradiated intensity prediction model to be fitted, and to fit the second parameter set. The strength prediction module is used to input the cross-sectional area of ​​the irradiated material of engineering size into the fitted post-irradiation strength prediction model to obtain the predicted strength data of the irradiated material of engineering size; wherein, the engineering size is the size of the tensile zone in millimeters, and the types of the first strength data, the second strength data and the predicted strength data all include yield strength and tensile strength; The prediction model for unirradiated intensity is as follows: In the formula, The cross-sectional area is Intensity of the unirradiated sample at that time d For the minimum feature size, The average grain size, For channel weighting functions, and These are the intensity functions for the dislocation source confined channel and the polycrystalline statistical channel, respectively. This is an optional weakening option; The first set of parameters includes the inflection area parameter, kurtosis parameter, intensity parameter, first coefficient, second coefficient, lower bound parameter, macroscopic limit parameter, convergence parameter, third coefficient, valley depth parameter, valley center area parameter, and log-variance parameter. The second set of parameters includes the dislocation source term increment parameter and irradiation defect hardening term 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 unirradiated intensity prediction model and the incremental parameter of the dislocation source term, and the macroscopic limit parameter is the sum of the macroscopic limit parameter in the unirradiated intensity prediction model and the parameter of the irradiation defect hardening term. The channel weighting function is: In the formula, Let be the inflection area parameter to be fitted. Let be the kurtosis parameter to be fitted. exist A The value range within the domain is 0 to 1; The intensity function of the confined channel of the dislocation source is: In the formula, The parameters to be fitted, the first coefficient, and the second coefficient are, in order. The intensity function of the polycrystalline statistical channel is: In the formula, Let be the lower bound parameter to be fitted. Let be the macroscopic limiting parameter to be fitted. Let be the convergence parameters to be fitted. The third coefficient to be fitted. This represents the average number of grains included in the gauge length segment. Optional weakening measures are: In the formula, The parameters to be fitted are, in order, valley depth, valley center area, and log-variance; when the experimental data do not have weakening features, let =0.

Images