Method for automatically solving elastic modulus of metal material under dynamic tension

Abstract

The present application relates to the technical field of materials, and relates to a method for automatically solving the elastic modulus of a metal material under dynamic tension. Engineering stress-engineering strain data of a target metal material under dynamic tension are obtained and preprocessed. Based on the mechanical properties of the material, an engineering strain analysis range is determined. According to the engineering strain analysis range, elastic modulus analysis data are determined from the engineering stress-engineering strain data. Based on the elastic modulus analysis data, linear fitting is performed to determine a first fitting curve. Based on the elastic modulus analysis data and the first fitting curve, the engineering strain analysis range of the target metal material is redetermined. Based on the redetermined engineering strain analysis range, linear fitting is performed to determine a second fitting curve. The slope error between the first fitting curve and the second fitting curve is determined, and in the case where the slope error meets a preset error value, the slope of the second fitting curve is taken as the elastic modulus of the target metal material.

Description

Technical Field

[0001] This specification relates to the field of materials technology, and in particular to an automated method for solving the elastic modulus of metallic materials under dynamic tension. Background Technology

[0002] With the increasing demands for accuracy in material data and reliability in automotive safety development, conducting dynamic tensile tests on automotive materials to obtain true and accurate mechanical property parameters has become a crucial development direction in the field of automotive materials testing. Automotive materials may withstand a wide range of strain rate loads during actual service, from quasi-static to high-speed collisions, and their dynamic strain rates typically cover… However, under dynamic loading conditions, due to the combined effects of stress wave propagation in the specimen, noise introduced by the testing system, and ultra-high-speed data acquisition, the engineering stress-strain curves directly measured in the experiment often exhibit non-ideal phenomena such as missing data points, local repetitions, and severe oscillations. Furthermore, to ensure the statistical reliability of the test results and fully reflect the strain rate effect of the material, it is usually necessary to repeat the experiment more than ten times, generating a large amount of raw engineering stress-strain data, which significantly burdens subsequent processing.

[0003] The elastic modulus is one of the most critical parameters in material constitutive models and structural simulations. Its value directly affects the magnitude of strain in the elastic stage of the material and the accuracy of the overall structural stiffness calculation. It is also the fundamental input for accurately obtaining the plastic rheological curve. Current national standards GB / T 228.1-2021 Appendix D and GB / T 22315-2008 provide methods for solving the elastic modulus under quasi-static tensile test conditions. These methods mainly rely on manual operations such as interactive methods, graphical methods, and fitting methods. During the calculation process, the operator needs to judge the start and end range of the linear portion of the elastic segment based on experience. These methods significantly increase labor costs. Furthermore, in complex situations where dynamic test data is missing, repetitive, or oscillating, the subjectivity of manual judgment further introduces uncertainty into the results, leading to significant differences in the elastic modulus values ​​obtained by different personnel and with different interpretation standards. Faced with massive amounts of noisy test data under dynamic conditions, relying solely on manual processing is not only inefficient but also makes it difficult to guarantee the accuracy and consistency of data processing.

[0004] Therefore, this specification provides an automated method for solving the elastic modulus of metallic materials under dynamic tension. Summary of the Invention

[0005] This specification provides an automated method for calculating the elastic modulus of metallic materials under dynamic tension, in order to partially solve the aforementioned problems existing in the prior art.

[0006] The following technical solution is adopted in this specification: This specification provides an automated method for calculating the elastic modulus of metallic materials under dynamic tension, including: S1. Obtain engineering stress-strain data of the target metallic material under dynamic tension; S2. Preprocess the engineering stress-engineering strain data; S3. Based on the mechanical properties of the target metallic material, determine the range of engineering strain analysis for the target metallic material; S4. Based on the engineering strain analysis range, determine the elastic modulus analysis data from the preprocessed engineering stress-engineering strain data; S5. Based on the elastic modulus analysis data, perform linear fitting to determine the first fitting curve; S6. Determine the intersection point of the stress-strain curve corresponding to the elastic modulus analysis data and the first fitted curve, and based on the engineering strain at the intersection point, redetermine the engineering strain analysis range of the target metallic material; S7. Based on the redefined engineering strain analysis range and the elastic modulus analysis data, perform linear fitting to determine the second fitting curve; S8. Determine the slope error between the first fitted curve and the second fitted curve. If the slope error meets the preset error value, use the slope of the second fitted curve as the elastic modulus of the target metal material.

[0007] Based on the aforementioned technical methods, compared to the traditional method of manually selecting linear segments of stress-strain curves based on experience, which is highly subjective and prone to introducing truncation bias, this scheme automatically determines the engineering strain analysis range and uses intersection point iterative feedback to dynamically correct the engineering strain analysis range, ensuring that the fitting interval strictly converges to the true elastic segment, significantly reducing the modulus calculation error caused by human factors. By comparing the slope error of two consecutive fitted curves as the convergence criterion, the final modulus is only output when the fitting result is stable within the preset accuracy range, ensuring the reliability and repeatability of the results. From the input of raw data (S1) to the output of elastic modulus (S8), the entire process is executed automatically by the algorithm, suitable for the rapid batch processing of large volumes of high-noise engineering stress-strain data generated by dynamic tensile tests.

[0008] Furthermore, S4 specifically includes: Within the scope of the engineering strain analysis, when the number of engineering stress-strain data pairs in the preprocessed engineering stress-strain data does not meet the preset number, interpolation is performed within the scope of the engineering strain analysis based on the preprocessed engineering stress-strain data to obtain the preset number of engineering stress-strain data pairs, which are then used as elastic modulus analysis data.

[0009] Based on the aforementioned techniques, linear fitting (especially the least squares method) requires the number of data points to reach the minimum threshold for statistical significance. In dynamic tensile tests, if the sampling frequency is set too low or too many noise points are removed during preprocessing, the number of effective data points within the elastic segment may be extremely small. Interpolation is forced to meet a preset number, avoiding fitting algorithm failure due to insufficient data (such as matrix singularity or insufficient degrees of freedom), ensuring the stable execution of steps S5 and S7. By interpolating to a preset number within the analysis range, an equally spaced (or approximately equally dense) data sequence is constructed, making the contribution of each strain interval to the slope more balanced during least squares fitting, thus improving the objectivity of the elastic modulus calculation.

[0010] Furthermore, S6 specifically includes: Based on the stress-strain curves corresponding to the elastic modulus analysis data and the first fitted curve, for each engineering strain, the absolute value of the difference between the engineering stresses corresponding to the engineering strain in the two curves is calculated, and the engineering strains are sorted from largest to smallest. According to the sorting of the engineering strains, the absolute values ​​of the differences are sorted. Based on the absolute values ​​of the sorted differences, determine the engineering strain corresponding to the minimum value among the first occurrences of the absolute values ​​of the differences, and use it as the extreme strain. Based on the extreme strain, the engineering strain analysis range of the target metallic material is redefined.

[0011] Based on the aforementioned technical methods, the strain is sorted from largest to smallest (searching from high strain to low strain). This aligns with the temporal pattern of material mechanics behavior—as loading progresses, strain increases, and the deviation from the elastic to the plastic segment inevitably first appears at the larger strain, with a critical point for the initial deviation existing along the direction of decreasing strain. By tracing back from the largest strain end, the starting point of the deviation can be accurately pinpointed, avoiding misjudging small fluctuations within the elastic segment as the elastic limit.

[0012] Furthermore, S2 specifically includes: The missing values ​​in the engineering stress-engineering strain data are supplemented. The expression for calculating missing values ​​is:

[0013] Among them, when When representing engineering stress, This indicates the missing first element in the aforementioned engineering stress-strain data. Individual engineering stress, Indicates the missing first The previous engineering stress that was not missing in the current engineering stress. Indicates the missing first The next non-missing engineering stress of an engineering stress.

[0014] Furthermore, S2 specifically includes: The engineering stress-engineering strain data pairs contained in the engineering stress-engineering strain data are sorted in order of increasing engineering strain. Each engineering stress-engineering strain data pair includes an engineering strain and the engineering stress corresponding to that engineering strain. For each sorted pair of engineering stress-strain data, identify the remaining pairs of engineering stress-strain data that have the same engineering strain as that pair. Calculate the mean value of the engineering stress in the engineering stress-strain data pair and the remaining engineering stress-strain data pairs, and replace the engineering stress in the engineering stress-strain data pair with the mean value, and delete the remaining engineering stress-strain data pairs.

[0015] Furthermore, S2 specifically includes: In the engineering stress-engineering strain data, engineering strains less than zero and the engineering stresses corresponding to those engineering strains less than zero are deleted.

[0016] Furthermore, S3 specifically includes: In the preprocessed engineering stress-engineering strain data, determine the engineering strain corresponding to the maximum engineering stress of the target metallic material; The first strain upper limit is determined based on the preset ratio and the engineering strain corresponding to the maximum engineering stress. The upper limit of engineering strain analysis for the target metallic material is determined from the first upper limit of strain and the preset second upper limit of strain. Based on the upper limit of the engineering strain analysis, the range of engineering strain analysis for the target metallic material is determined.

[0017] Furthermore, step S8 also includes S81: If the slope error between the first fitting curve and the second fitting curve does not meet the preset error value, the engineering strain analysis range of the target metal material is re-determined based on the second fitting curve and the stress-strain curve corresponding to the elastic modulus analysis data. Based on the redefined engineering strain analysis range and the elastic modulus analysis data, linear fitting is performed to determine the third fitting curve. Determine the slope error between the second fitted curve and the third fitted curve; Determine whether the slope error between the second fitted curve and the third fitted curve meets the preset error value; If so, the slope of the third fitting curve is taken as the elastic modulus of the target metallic material; If not, continue with linear fitting until the slope error meets the preset error value.

[0018] This specification provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for automatically solving the elastic modulus of a metallic material under dynamic tension.

[0019] This specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements an automated method for solving the elastic modulus of a metallic material under dynamic tension.

[0020] The above-mentioned technical solutions adopted in this specification can achieve the following beneficial effects: Compared to traditional methods that rely on manual, experience-based selection of linear segments from stress-strain curves, which are highly subjective and prone to truncation bias, this method automatically determines the engineering strain analysis range and dynamically corrects it using intersection point iterative feedback. This ensures the fitted interval strictly converges to the true elastic segment, significantly reducing modulus calculation errors caused by human factors. By comparing the slope error of two fitted curves as a convergence criterion, the final modulus is only output when the fitting result is stable within a preset accuracy range, ensuring the reliability and repeatability of the results. From raw data input (S1) to elastic modulus output (S8), the entire process is executed automatically, making it suitable for rapid batch processing of large volumes of high-noise engineering stress-strain data generated by dynamic tensile tests. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of this specification and form part of this specification, illustrate exemplary embodiments and are used to explain this specification, but do not constitute an undue limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating an automated method for calculating the elastic modulus of metallic materials under dynamic tension, as provided in the embodiments of this specification. Figure 2 This specification provides a corresponding Figure 1 A schematic diagram of the structure of an electronic device. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this specification will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without creative effort are within the scope of protection of this application.

[0023] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0024] The technical solutions provided in the various embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0025] Figure 1 A flowchart illustrating an automated method for calculating the elastic modulus of metallic materials under dynamic tension, as provided in this specification, includes the following steps: S1: Obtain engineering stress-strain data of the target metallic material under dynamic tension.

[0026] This specification describes the process of automating the calculation of the elastic modulus of a metallic material under dynamic tension. In the embodiments described herein, this process can be executed by a server. However, this specification does not limit the type of device or platform used to perform this automated calculation; devices or platforms such as personal computers and mobile terminals can also be used. For ease of description, the following explanation uses a server as the executing entity.

[0027] In one or more embodiments of this specification, the server can acquire engineering stress-strain data of the target metallic material under dynamic tensile conditions. The engineering stress-strain data contains data in the form of engineering stress-strain data pairs, each pair including an engineering strain and the corresponding engineering stress.

[0028] S2: Preprocess the engineering stress-engineering strain data.

[0029] In one or more embodiments of this specification, the server may preprocess engineering stress-strain data to determine normalized engineering stress-strain data.

[0030] Specifically, data completion can be performed on each engineering stress-strain data pair in the acquired engineering stress-strain data to fill in missing values.

[0031] The expression for calculating missing values ​​is:

[0032] Among them, when When representing engineering stress, This indicates the missing first element in the engineering stress-strain data. Individual engineering stress, Indicates the missing first The previous engineering stress that was not missing in the current engineering stress. Indicates the missing first The next non-missing engineering stress for a given engineering stress. Similarly, when When representing engineering strain, This indicates the missing first element in the engineering stress-strain data. Each engineering response, Indicates the missing first The previous engineering strain that was not missing in the engineering strain. Indicates the missing first The next non-missing engineering strain of an engineering strain.

[0033] In this specification, when there are duplicate engineering strain data in the engineering stress-engineering strain data, only the first engineering stress-engineering strain data pair among each duplicate engineering strain data pair is retained. Simultaneously, the engineering stress value in this retained first engineering stress-engineering strain data pair is replaced by the average engineering stress of all its duplicate engineering stress-engineering strain data pairs.

[0034] Specifically, the server can sort the engineering stress-strain data pairs contained in the engineering stress-strain data set according to the engineering strain in ascending order. Each engineering stress-strain data pair includes an engineering strain and its corresponding engineering stress. Then, for each sorted engineering stress-strain data pair, the server can identify the remaining engineering stress-strain data pairs that have overlapping engineering strains with that data pair. Finally, the server calculates the mean of the engineering stresses in the original engineering stress-strain data pair and the remaining engineering stress-strain data pairs, replaces the engineering stress of the original engineering stress-strain data pair with the mean, and then deletes the remaining engineering stress-strain data pairs.

[0035] In this specification, the server can also delete engineering strains less than zero and the engineering stresses corresponding to engineering strains less than zero from the engineering stress-engineering strain data.

[0036] Therefore, the above-mentioned preprocessing methods can be used to determine standardized engineering stress-strain data.

[0037] S3: Based on the mechanical properties of the target metal material, determine the range of engineering strain analysis for the target metal material.

[0038] In one or more embodiments of this specification, the server can determine the engineering strain analysis range of the target metal material based on the material mechanical properties of the target metal material.

[0039] This mainly includes comprehensively determining the engineering strain analysis range of the target metal material based on the engineering strain range determined by the strength ratio of the target metal material and the empirical engineering strain range determined by the plasticity characteristics of the target metal material. Regarding the material strength ratio, the engineering strain corresponding to 0.8~0.95 times the preset tensile strength of the target metal is used as the maximum fitted strain. The engineering strain determined by the strength ratio of the target metal material can be determined from the engineering strain range corresponding to 0.8~0.95 times the tensile strength, denoted as eps1. Different types and strengths of metal materials have different elastic deformation ranges; the empirical engineering strain range is 0.01~0.02. The empirical engineering strain of the target metal can be determined from this empirical engineering strain range, denoted as eps2. Then, the minimum engineering strain between eps1 and eps2 is selected to determine the engineering strain analysis range of the target metal material, denoted as (0, min{eps1,eps2}).

[0040] Furthermore, in the preprocessed engineering stress-strain data, the server can determine the engineering strain corresponding to the maximum engineering stress of the target metallic material. Then, based on a preset ratio and the engineering strain corresponding to the maximum engineering stress, a first upper limit for strain is determined. This preset ratio can be referenced to 0.8~0.95 times the engineering strain corresponding to the tensile strength, with a randomly selected ratio value. For example, if a ratio of 0.85 is selected, then the first upper limit for strain is 0.85 times the engineering strain corresponding to the maximum engineering stress. Afterwards, the server can determine the upper limit for engineering strain analysis of the target metallic material from the first upper limit for strain and a preset second upper limit for strain. This second upper limit for strain is equivalent to the aforementioned empirical engineering strain. Finally, based on the upper limit for engineering strain analysis, the server determines the range of engineering strain analysis for the target metallic material. This upper limit for engineering strain analysis can be the minimum value between the first upper limit for strain and the preset second upper limit for strain; therefore, the range of engineering strain analysis is (0, upper limit for engineering strain analysis).

[0041] S4: Based on the engineering strain analysis range, determine the elastic modulus analysis data from the preprocessed engineering stress-engineering strain data.

[0042] S5: Based on the elastic modulus analysis data, perform linear fitting to determine the first fitting curve.

[0043] In one or more embodiments of this specification, the server can determine the engineering stress-engineering strain data pairs within the engineering strain analysis range from the preprocessed engineering stress-engineering strain data, based on the engineering strain analysis range, and use them as elastic modulus analysis data.

[0044] Furthermore, to ensure the stable execution of the subsequent fitting process, the server can perform interpolation within the engineering strain analysis range based on the preprocessed engineering stress-strain data when the number of engineering stress-strain data pairs in the preprocessed engineering stress-strain data does not meet the preset number, to obtain the preset number of engineering stress-strain data pairs, such as ensuring that there are no less than 1000 engineering stress-strain data pairs, as elastic modulus analysis data.

[0045] Then, the server can perform linear fitting based on the elastic modulus analysis data to determine the first fitted curve.

[0046] Specifically, based on the elastic modulus analysis data, a first-order linear fit is performed according to the following fitting formula.

[0047] The fitting formula is expressed as: sigma = E × eps + b. Where sigma represents the engineering stress, E represents the fitting slope, eps represents the engineering strain, and b represents the fitting intercept.

[0048] Therefore, after determining the fitting slope and intercept of the fitting formula, and thus the specific fitting formula, the engineering strains in the interpolated preset number of engineering stress-engineering strain data pairs can be substituted into the fitting formula to calculate the preset number of fitted engineering stresses. Based on these preset number of engineering strains and the fitted engineering stresses corresponding to each engineering strain, the first fitting curve can be determined. Correspondingly, the server can easily determine the slope and intercept of the curve.

[0049] S6: Determine the intersection point of the stress-strain curve corresponding to the elastic modulus analysis data and the first fitted curve, and based on the engineering strain at the intersection point, redetermine the engineering strain analysis range of the target metallic material.

[0050] In one or more embodiments of this specification, the server can determine the stress-strain curve corresponding to the elastic modulus analysis data. Then, it determines the intersection point of the stress-strain curve corresponding to the elastic modulus analysis data and the first fitted curve, and based on the engineering strain at the intersection point, redetermines the engineering strain analysis range of the target metallic material.

[0051] It is worth noting that the intersection point here refers to the first intersection point in the coordinate system where the stress-strain curve corresponding to the elastic modulus analysis data and the first fitted curve are located, arranged in descending order of engineering strain. This is because if the engineering strain is arranged in ascending order, the two curves will initially have a nearly overlapping segment. Within this nearly overlapping segment, the intersection point cannot accurately characterize the starting point of the deviation from the elastic segment to the plastic segment under tension in metallic materials.

[0052] Therefore, more specifically, the server can, based on the stress-strain curves corresponding to the elastic modulus analysis data and the first fitted curve, calculate the absolute value of the difference between the engineering stresses corresponding to each engineering strain in the two curves. Then, it sorts the engineering strains from largest to smallest, and according to this sorting, it sorts the absolute values ​​of the differences. Based on the sorted absolute values ​​of the differences, it determines the engineering strain corresponding to the first occurrence of the minimum absolute value of the differences, which is taken as the extreme strain. Finally, based on this extreme strain, it redetermines the engineering strain analysis range of the target metallic material, i.e., (0, extreme strain).

[0053] S7: Based on the redefined engineering strain analysis range and the elastic modulus analysis data, perform linear fitting to determine the second fitting curve.

[0054] S8: Determine the slope error between the first fitting curve and the second fitting curve. If the slope error meets the preset error value, use the slope of the second fitting curve as the elastic modulus of the target metal material.

[0055] In one or more embodiments of this specification, the server can perform linear fitting on the engineering stress-engineering strain data pairs in the elastic modulus analysis data that belong to the newly determined engineering strain analysis range, based on the redefined engineering strain analysis range and elastic modulus analysis data, to determine the second fitting curve. The specific process can be referred to the specific content of S4 and S5 above, and will not be repeated here.

[0056] The server then determines the slope error between the first and second fitted curves, and can use the slope of the second fitted curve as the elastic modulus of the target metal material if the slope error meets the preset error value.

[0057] The expression for calculating the slope error is: Error i=( E i- E i-1) / E i-1. Wherein, Error i represents the slope error between the slope of the i-th fitted curve (i.e., the fitting slope) and the slope of the (i-1)-th fitted curve (i.e., the fitting slope). E i represents the slope of the i-th fitted curve. E i-1 represents the slope of the (i-1)th fitted curve.

[0058] Of course, in this specification, S8 also includes step S81: if the slope error between the first fitted curve and the second fitted curve does not meet the preset error value, the server can re-determine the engineering strain analysis range of the target metal material based on the stress-strain curve corresponding to the second fitted curve and the elastic modulus analysis data. Based on the re-determined engineering strain analysis range and the elastic modulus analysis data, linear fitting is performed to determine the third fitted curve. The slope error between the second fitted curve and the third fitted curve is determined. Then, it is determined whether the slope error between the second fitted curve and the third fitted curve meets the preset error value. If yes, the slope of the third fitted curve is used as the elastic modulus of the target metal material. If not, linear fitting continues until the slope error meets the preset error value.

[0059] based on Figure 1This paper presents an automated method for calculating the elastic modulus of metallic materials under dynamic tension. Compared to traditional methods that rely on manual, experience-based selection of linear segments from stress-strain curves, this approach is highly subjective and prone to introducing truncation bias. This method automatically determines the engineering strain analysis range and uses iterative feedback at intersection points to dynamically correct it, ensuring the fitted interval strictly converges to the true elastic segment, significantly reducing errors in modulus calculation caused by human factors. By comparing the slope error of two fitted curves as a convergence criterion, the final modulus is output only when the fitting result stabilizes within a preset accuracy range, ensuring the reliability and repeatability of the results. From raw data input (S1) to elastic modulus output (S8), the entire process is automated, making it suitable for rapid batch processing of large volumes of high-noise engineering stress-strain data generated from dynamic tensile tests.

[0060] This specification provides an embodiment for solving the elastic modulus of a target metallic material, ultra-high strength steel. The tensile strain rate of ultra-high strength steel is 500 / s, and under dynamic tensile conditions, the engineering stress-engineering strain curve of the material exhibits certain oscillating characteristics.

[0061] Engineering stress-strain data for ultra-high strength steel was obtained, including 899 pairs. No missing data was found. However, negative values, fluctuations, and duplicates were observed in the engineering strain data. The data were sorted in ascending order of engineering strain, with the corresponding engineering stress adjusted accordingly. Each stress-strain pair was checked individually, revealing 414 duplicate strain points. For these duplicates, only one strain data point was retained. The average engineering stress corresponding to the same strain was calculated. After deduplication, 485 valid data points remained. Four strain values ​​were found to be less than 0, and these pairs were removed.

[0062] Next, the engineering strain analysis range needs to be determined. This range is confirmed by comparing two strain data points. The first strain reference value ranges from 0.01 to 0.02. For materials with a lower elastic modulus, a larger reference value is used, and vice versa. In this case, the material is steel, so the reference strain value is 0.01. The second strain data point is the engineering strain corresponding to 0.8 to 0.95 times the tensile strength. This coefficient can be selected based on the material's work hardening capacity. For materials with a high work hardening index, a smaller coefficient is usually chosen, while for materials with a low work hardening index, a larger coefficient is chosen. In this case, the tensile strength of the material is 1365 MPa, so 0.9 times the tensile strength, i.e., 1228.5 MPa, is used as a reference, corresponding to an engineering strain of 0.0077. The upper limit of the engineering strain analysis range is eps = min{0.0077, 0.01} = 0.0077, and the engineering strain analysis range is (0, 0.0077).

[0063] First-order linear fitting is performed. Based on the engineering strain analysis range confirmed in the previous step, preliminary fitting is carried out. The number of engineering strain data points within the engineering strain analysis range is 60, which is far lower than the expected data. Linear interpolation is used to ensure that the number of engineering strain data points within the engineering strain analysis range is 1000. Then, with engineering strain as the independent variable and engineering stress as the dependent variable, the first first-order linear fitting is performed based on the fitting formula. The obtained fitting parameters are: fitting slope E = 1.68117926e+05, fitting intercept b = 6.48952750e+01. The first fitting curve is generated based on the fitting parameters. By calculating the absolute value error of the difference between the first fitting curve and the stress-strain curve corresponding to the interpolated data under each engineering strain, the first minimum point is identified as the right intersection point in reverse order, and the corresponding engineering strain is 0.0061. A second first-order linear fit was performed, with the fitted data ranging from 0 to 0.0061 engineering strain. The fitted parameters obtained were E=1.82699731e+05 and b=3.14870724e+01.

[0064] Error Calculation. Based on the fitted parameters E from the two outputs, the error of the second fitting relative to the first is calculated: Error1 = (1.82699731e+05 - 1.68117926e+05) / 1.68117926e+05 = 8.7%. This error is greater than the preset error value of 5%. Multiple fitting and error calculation analyses are then performed, and the engineering strain analysis range is updated. After the third fitting, Error2 = 5.5%, still greater than 5%, requiring an update to the engineering strain analysis range. After the fourth fitting, Error3 = 0.1%, the error converges to within the 5% range, and fitting stops. The error after the fourth fitting converges to the preset error value, and the fitting slope E tends to flatten. The fitting slope E of the fourth fitting is taken as the elastic modulus.

[0065] This specification also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 This paper presents an automated method for calculating the elastic modulus of metallic materials under dynamic tension.

[0066] This instruction manual also provides Figure 2 The diagram shows a schematic structural representation of the electronic device. Figure 2 As shown, at the hardware level, this electronic device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to achieve the above. Figure 1 This paper presents an automated method for calculating the elastic modulus of metallic materials under dynamic tension.

[0067] Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of hardware and software. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0068] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must also be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0069] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0070] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0071] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0072] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0073] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0074] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0075] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0076] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0077] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0078] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic or disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0079] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0080] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0082] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0083] The above description is merely an embodiment of this specification and is not intended to limit this specification. Various modifications and variations can be made to this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims of this specification.

Claims

1. A method for automatically solving the elastic modulus of a metallic material under dynamic tension, characterized in that, include: S1. Obtain engineering stress-strain data of the target metallic material under dynamic tension; S2. Preprocess the engineering stress-engineering strain data; S3. Based on the mechanical properties of the target metallic material, determine the range of engineering strain analysis for the target metallic material; S4. Based on the engineering strain analysis range, determine the elastic modulus analysis data from the preprocessed engineering stress-engineering strain data; S5. Based on the elastic modulus analysis data, perform linear fitting to determine the first fitting curve; S6. Determine the intersection point of the stress-strain curve corresponding to the elastic modulus analysis data and the first fitted curve, and based on the engineering strain at the intersection point, redetermine the engineering strain analysis range of the target metallic material; S7. Based on the redefined engineering strain analysis range and the elastic modulus analysis data, perform linear fitting to determine the second fitting curve; S8. Determine the slope error between the first fitted curve and the second fitted curve. If the slope error meets the preset error value, use the slope of the second fitted curve as the elastic modulus of the target metal material.

2. The method for automatically solving the elastic modulus of metallic materials under dynamic tension as described in claim 1, characterized in that, S4 specifically includes: Within the scope of the engineering strain analysis, when the number of engineering stress-strain data pairs in the preprocessed engineering stress-strain data does not meet the preset number, interpolation is performed within the scope of the engineering strain analysis based on the preprocessed engineering stress-strain data to obtain the preset number of engineering stress-strain data pairs, which are then used as elastic modulus analysis data.

3. The method for automatically solving the elastic modulus of metallic materials under dynamic tension as described in claim 1, characterized in that, S6 specifically includes: Based on the stress-strain curves corresponding to the elastic modulus analysis data and the first fitted curve, for each engineering strain, the absolute value of the difference between the engineering stresses corresponding to the engineering strain in the two curves is calculated, and the engineering strains are sorted from largest to smallest. According to the sorting of the engineering strains, the absolute values ​​of the differences are sorted. Based on the absolute values ​​of the sorted differences, determine the engineering strain corresponding to the minimum value among the first occurrences of the absolute values ​​of the differences, and use it as the extreme strain. Based on the extreme strain, the engineering strain analysis range of the target metallic material is redefined.

4. The method for automatically solving the elastic modulus of metallic materials under dynamic tension as described in claim 1, characterized in that, S2 specifically includes: The missing values ​​in the engineering stress-engineering strain data are supplemented. The expression for calculating missing values ​​is: Among them, when When representing engineering stress, This indicates the missing first element in the aforementioned engineering stress-strain data. Individual engineering stress, Indicates the missing first The previous engineering stress that was not missing in the current engineering stress. Indicates the missing first The next non-missing engineering stress of an engineering stress.

5. The method for automatically solving the elastic modulus of metallic materials under dynamic tension as described in claim 1, characterized in that, S2 specifically includes: The engineering stress-engineering strain data pairs contained in the engineering stress-engineering strain data are sorted in order of increasing engineering strain. Each engineering stress-engineering strain data pair includes an engineering strain and the engineering stress corresponding to that engineering strain. For each sorted pair of engineering stress-strain data, identify the remaining pairs of engineering stress-strain data that have the same engineering strain as that pair. Calculate the mean value of the engineering stress in the engineering stress-strain data pair and the remaining engineering stress-strain data pairs, and replace the engineering stress in the engineering stress-strain data pair with the mean value, and delete the remaining engineering stress-strain data pairs.

6. The method for automatically solving the elastic modulus of metallic materials under dynamic tension as described in claim 1, characterized in that, S2 specifically includes: In the engineering stress-engineering strain data, engineering strains less than zero and the engineering stresses corresponding to those engineering strains less than zero are deleted.

7. The method for automatically solving the elastic modulus of metallic materials under dynamic tension as described in claim 1, characterized in that, S3 specifically includes: In the preprocessed engineering stress-engineering strain data, determine the engineering strain corresponding to the maximum engineering stress of the target metallic material; The first strain upper limit is determined based on the preset ratio and the engineering strain corresponding to the maximum engineering stress. The upper limit of engineering strain analysis for the target metallic material is determined from the first upper limit of strain and the preset second upper limit of strain. Based on the upper limit of the engineering strain analysis, the range of engineering strain analysis for the target metallic material is determined.

8. The method for automatically solving the elastic modulus of metallic materials under dynamic tension as described in claim 1, characterized in that, Step S8 also includes S81: If the slope error between the first fitting curve and the second fitting curve does not meet the preset error value, the engineering strain analysis range of the target metal material is re-determined based on the second fitting curve and the stress-strain curve corresponding to the elastic modulus analysis data. Based on the redefined engineering strain analysis range and the elastic modulus analysis data, linear fitting is performed to determine the third fitting curve. Determine the slope error between the second fitted curve and the third fitted curve; Determine whether the slope error between the second fitted curve and the third fitted curve meets the preset error value; If so, the slope of the third fitting curve is taken as the elastic modulus of the target metallic material; If not, continue with linear fitting until the slope error meets the preset error value.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method described in any one of claims 1 to 8.

10. An electronic device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in any one of claims 1 to 8.

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