scholarly journals Fatigue assessment of cut edges in high strength steel - Influence of surface quality

2017 ◽  
Vol 48 (6) ◽  
pp. 556-569 ◽  
Author(s):  
T. Stenberg ◽  
E. Lindgren ◽  
Z. Barsoum ◽  
I. Barmicho
Keyword(s):  
Surface Quality ◽  
High Strength Steel ◽  
High Strength ◽  
Fatigue Assessment

scholarly journals Crack Initiation and Propagation Fatigue Life of Ultra High-Strength Steel Butt Joints

2019 ◽  
Vol 9 (21) ◽  
pp. 4590 ◽  
Author(s):  
Markus J. Ottersböck ◽  
Martin Leitner ◽  
Michael Stoschka ◽  
Wilhelm Maurer
Keyword(s):  
Fatigue Life ◽  
Crack Initiation ◽  
Welded Joints ◽  
High Strength Steel ◽  
High Strength ◽  
Crack Initiation And Propagation ◽  
Butt Joints ◽  
Fatigue Assessment ◽  
Initiation And Propagation ◽  
Ultra High Strength Steel

The division of the total fatigue life into different stages such as crack initiation and propagation is an important issue in regard to an improved fatigue assessment especially for high-strength welded joints. The transition between these stages is fluent, whereas the threshold between the two phases is referred to as technical crack initiation. This work presents a procedure to track crack initiation and propagation during fatigue tests of ultra high-strength steel welded joints. The method utilizes digital image correlation to calculate a distortion field of the specimens’ surface enabling the identification and measurement of cracks along the weld toe arising during the fatigue test. Hence, technical crack initiation of each specimen can be derived. An evaluation for ten ultra high-strength steel butt joints reveals, that for this superior strength steel grade more than 50% of fatigue life is spent up to a crack depth of 0.5 mm, which can be defined as initial crack. Furthermore, a notch-stress based fatigue assessment of these specimens considering the actual weld topography and crack initiation and propagation phase is performed. The results point out that two phase models considering both phases enable an increased accuracy of service life assessment.

An intelligent prediction model of the tool wear based on machine learning in turning high strength steel

2020 ◽  
Vol 234 (13) ◽  
pp. 1580-1597
Author(s):  
Minghui Cheng ◽  
Li Jiao ◽  
Xuechun Shi ◽  
Xibin Wang ◽  
Pei Yan ◽  
...  
Keyword(s):  
Tool Wear ◽  
Prediction Model ◽  
Cutting Force ◽  
Surface Quality ◽  
Surface Texture ◽  
High Strength Steel ◽  
Prediction Models ◽  
High Strength ◽  
Support Vector ◽  
Time Frequency

In the process of high strength steel turning, tool wear will reduce the surface quality of the workpiece and increase cutting force and cutting temperature. To obtain the fine surface quality and avoid unnecessary loss, it is necessary to monitor the state of tool wear in the dry turning. In this article, the cutting force, vibration signal and surface texture of the machined surface were collected by tool condition monitoring system and signal processing techniques are being used for extracting the time-domain, frequency-domain and time-frequency features of cutting force and vibration. The gray level processing technique is used to extract the features of the gray co-occurrence matrix of the surface texture and found that these features changed simultaneously when the cutting tool broke. After this, an intelligent prediction model of tool wear was built using the support vector regression (SVR) whose kernel function parameters were optimized by the grid search algorithm (GS), the genetic algorithm (GA) and the particle swarm optimization algorithm respectively. The features extracted from the signals and surface texture are used to train the prediction model in MATLAB. It was found that after the surface texture features were fused using the intelligent prediction model on the basis of the features of cutting force and vibration, prediction accuracy of the proposed method is found as 97.32% and 96.72% respectively under the two prediction models of GA-SVR and GS-SVR. Moreover, the intelligent prediction model can not only predict the tool wear under different cutting conditions, but also the different wear stages in a single wear cycle and the absolute error between the predicted value and the actual value is less than 10 μm, the confidence coefficient of prediction curve is around 0.99.

MQL machining of high strength steel: A case study on surface quality characteristic

2020 ◽  
Vol 26 ◽  
pp. 2616-2618 ◽  
Author(s):  
Rasmi Ranjan Mishra ◽  
Ashok Kumar Sahoo ◽  
Amlana Panda ◽  
Ramanuj Kumar ◽  
Diptikanta Das ◽  
...  
Keyword(s):  
Surface Quality ◽  
High Strength Steel ◽  
High Strength ◽  
Quality Characteristic

COMPARATIVE CHARACTERISTICS OF PHYSICAL AND MECHANICAL PROPERTIES OF COMPOSITE MATERIALS AND HIGH-STRENGTH STEEL 30FGSN2A

2020 ◽  
Author(s):  
I.R. Antypes ◽  
◽  
V.V. Zaitsev ◽  
Keyword(s):  
Composite Materials ◽  
High Strength Steel ◽  
Critical Stress ◽  
Physical And Mechanical Properties ◽  
High Strength ◽  
Aviation Industry ◽  
Specific Strength ◽  
Aircraft Landing ◽  
Carbon Plastics ◽  
Aircraft Landing Gear

Currently, the use of composite materials is increasingly used in various areas of the national economy, including the aviation industry. The materials of this article are devoted to the study of the use of composite materials for the manufacture of aircraft landing gear in comparison with the traditionally used brand of steel. As a result of the work carried out, it was found that the slope made of carbon fiber showed a critical stress twice as high as its design made of 30xgsn2a steel. In addition, carbon plastics are superior to high-strength steel in terms of specific strength, stiffness, and tensile strength.

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