Evaluation of the Low‐Cycle Fatigue Life of Thin Dual‐Phase Steel Sheets for Automobiles Using Miniature Specimens

Ma, Zhenhua; Zhang, Bin; Song, Zhilong; Liu, Huasai; Guang-ping, Zhang

doi:10.1002/srin.201900186

Cited by 3 publications

(1 citation statement)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After controlling the variables, preparations were made for the next step of fatigue testing dominated by pores. Fatigue tests were carried out at room temperature using a self-developed, patented, small cantilever beam machine [20,33], which has been proven to be suitable for evaluating the fatigue properties of various cantilever beam specimens [27,[34][35][36]. The cantilever beam specimens were mainly subjected to symmetric bending fatigue loading under constant deflections of approximately ±0.8 mm and ±0.85 mm, respectively, corresponding to fixed strain amplitudes of about 0.274 and 0.295 [20,33,37].…”

Section: Specimen Preparation and Fatigue Testingmentioning

confidence: 99%

A Comparative Investigation of Machine Learning Algorithms for Pore-Influenced Fatigue Life Prediction of Additively Manufactured Inconel 718 Based on a Small Dataset

Hu,

Luo,

Zhang

et al. 2023

Materials

View full text Add to dashboard Cite

Fatigue life prediction of Inconel 718 fabricated by laser powder bed fusion was investigated using a miniature specimen tests method and machine learning algorithms. A small dataset-based machine learning framework integrating thirteen kinds of algorithms was constructed to predict the pore-influenced fatigue life. The method of selecting random seeds was employed to evaluate the performance of the algorithms, and then the ranking of various machine learning algorithms for predicting pore-influenced fatigue life on small datasets was obtained by verifying the prediction model twenty or thirty times. The results showed that among the thirteen popular machine learning algorithms investigated, the adaptive boosting algorithm from the boosting category exhibited the best fitting accuracy for fatigue life prediction of the additively manufactured Inconel 718 using the small dataset, followed by the decision tree algorithm in the nonlinear category. The investigation also found that DT, RF, GBDT, and XGBOOST algorithms could effectively predict the fatigue life of the additively manufactured Inconel 718 within the range of 1 × 105 cycles on a small dataset compared to others. These results not only demonstrate the capability of using small dataset-based machine learning techniques to predict fatigue life but also may guide the selection of algorithms that minimize performance evaluation costs when predicting fatigue life.

show abstract

Section: Specimen Preparation and Fatigue Testingmentioning

confidence: 99%

A Comparative Investigation of Machine Learning Algorithms for Pore-Influenced Fatigue Life Prediction of Additively Manufactured Inconel 718 Based on a Small Dataset

Hu,

Luo,

Zhang

et al. 2023

Materials

View full text Add to dashboard Cite

show abstract

A Fatigue Method in the Tension-Compression Axial Stress Control Test of Automotive Sheet Steel

Gao

et al. 2023

Journal of Testing and Evaluation

View full text Add to dashboard Cite

Focused on the common problem of easy buckling of specimens in the tension-compression axial stress control fatigue test of automobile sheet steel, a stress fatigue test method for thickness less than 2.5 mm was proposed. For two kinds of automobile sheet materials with different strength levels and thicknesses, fatigue specimens with different widths of test section, parallel lengths, and fillet radii are designed. Without the anti-buckling device, high-cycle fatigue tests with a stress ratio Rs = −1 at different stress levels were carried out, and the shape and size of the fatigue specimens of automobile sheet materials were determined by the number of fatigue life cycles of specimens with different sizes under the same stress cycle form. The results show that for automobile sheet steel with a thickness of 1.0–2.5 mm, the recommended sizes of the uniform-gauge fatigue specimens are width of test section w = (1–3) t, parallel length Lp = (1–3) w, and fillet radius r = (3–10) t. For automobile sheet steel with a thickness less than 1 mm, because the time-displacement curve jitters during the test, it is recommended to install an anti-buckling device, specifically the anti-buckling device with mortise and tenon structure by self-design and with a flattop structure recommended by ISO 1099-2017, Metallic Materials—Fatigue Testing—Axial Force-Controlled Method.

show abstract

The Effect of Buckling Restraint on Axial Strain Life Fatigue Data

Su,

Gao,

Liang

et al. 2024

Journal of Testing and Evaluation

View full text Add to dashboard Cite

Focused on the common problem of easy specimen buckling in the axial strain–controlled fatigue testing of thin automobile steel sheets, a strain fatigue test method for thicknesses less than 2.5 mm is proposed. Because of the unrestrained grip end of specimens between the anti-buckling device and the testing machine fixture, specimens were prone to buckling in this area. In addition, if the designed specimen sizes were unreasonable, buckling may have occurred in the width and thickness directions of the gauge length of the specimen. Both situations can lead to invalid tests. This paper adopted a testing machine fixture and an anti-buckling plate as a mortise-and-tenon structure for the anti-buckling method; the upper and lower fixtures of the testing machine were cut in straight grooves, and the left and right anti-buckling plates were designed to be connected with a mortise and tenon. This is equivalent to narrowing the width of the unrestrained part of the specimen’s grip end to avoid buckling failure due to plane strain. The factors affecting the stiffness of fatigue specimens are also discussed herein. In order to avoid common instability in the thickness and width directions of the gauge length and unconstrained part of the specimen’s grip end at a strain ratio of Re = −1 during testing, six recommended specimen sizes are given on the premise of ensuring maximum specimen stiffness. When using the anti-buckling device, the recommended specimen sizes and test points of this study (i.e., the lower limits for yield strength and thickness of strain control testing) are 110 MPa and 0.5 mm, respectively, with which continuous and smooth stress–strain curves that result in accurate and reliable experimental data can be obtained.

show abstract

Evaluation of the Low‐Cycle Fatigue Life of Thin Dual‐Phase Steel Sheets for Automobiles Using Miniature Specimens

Cited by 3 publications

References 36 publications

A Comparative Investigation of Machine Learning Algorithms for Pore-Influenced Fatigue Life Prediction of Additively Manufactured Inconel 718 Based on a Small Dataset

A Comparative Investigation of Machine Learning Algorithms for Pore-Influenced Fatigue Life Prediction of Additively Manufactured Inconel 718 Based on a Small Dataset

A Fatigue Method in the Tension-Compression Axial Stress Control Test of Automotive Sheet Steel

The Effect of Buckling Restraint on Axial Strain Life Fatigue Data

Contact Info

Product

Resources

About