Titanium alloy stress corrosion critical stress intensity factor prediction method
A critical stress and intensity factor technology, applied in machine learning, instrumentation, design optimization/simulation, etc., can solve problems such as accurately predicting the critical stress intensity of stress corrosion
Pending Publication Date: 2022-06-03
UNIV OF SCI & TECH BEIJING
View PDF0 Cites 1 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0005] However, in the existing technology, it is impossible to accurately predict the critical stress intensity factor of stress corrosion based on the existing corrosion data
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0030] In order to make the objectives, technical solutions and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.
[0031] like figure 1 As shown, an embodiment of the present invention provides a method for predicting a critical stress intensity factor for stress corrosion of titanium alloys, including:
[0032] S101: Obtain a training sample set and a test sample set, wherein each sample in the training sample set and the test sample set includes: tissue structure, loading direction, pressure, temperature, dissolved oxygen concentration, and K ISCC , K ISCC is the stress corrosion critical stress intensity factor;
[0033] In this embodiment, the obtaining of the training set and the test set includes:
[0034]A1, according to the five parameters of the structure, loading direction, pressure, temperature and dissolved oxygen concentration of the titan...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention provides a titanium alloy stress corrosion critical stress intensity factor prediction method, and belongs to the technical field of titanium alloy corrosion detection. The method comprises the following steps: acquiring a training sample set and a test sample set; inputting the training sample set into a plurality of different regression models for training, inputting the test sample set into the trained regression model for testing after the training is completed, and obtaining the prediction accuracy of the KISCC prediction value of each regression model according to the test result; and inputting the organization structure, the loading direction, the pressure, the temperature and the dissolved oxygen concentration of the to-be-predicted titanium alloy under the condition into the regression model with the highest prediction accuracy, and outputting a KISCC prediction value. With the adoption of the method, the stress corrosion critical stress intensity factor KISCC can be accurately predicted by utilizing five parameters, namely the organization structure, the loading direction, the pressure, the temperature and the dissolved oxygen concentration, of the to-be-predicted titanium alloy under the condition of the to-be-predicted titanium alloy.
Description
technical field [0001] The invention relates to the technical field of titanium alloy corrosion detection, in particular to a method for predicting the critical stress intensity factor of titanium alloy stress corrosion. Background technique [0002] The corrosion evaluation of titanium alloys in the deep sea environment is a systematic project, which involves complex scientific and technological issues such as the evolution behavior of materials in a multi-factor coupled environment under service conditions, and the scale correlation from microscopic to real structures. Material corrosion data is the basis for studying the corrosion failure law of materials and the evolution of material properties. In recent years, with the rapid development of data-driven modeling ideas, the development of a new generation of artificial intelligence technology represented by machine learning has provided new ideas for material failure law mining, material corrosion rate prediction and fail...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More IPC IPC(8): G06F30/27G06N20/00G06F119/14
CPCG06F30/27G06N20/00G06F2119/14Y02P90/30
Inventor 张卫冬张琬滢艾轶博
Owner UNIV OF SCI & TECH BEIJING