Einführung in die bruchmechanische Schadensbeurteilung

Edel, Karl-Otto

doi:10.1007/978-3-662-44264-7

Cited by 4 publications

(2 citation statements)

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“…As mentioned in Section 3.1, if the crack‐initiating defect emanates planar crack, then ridges appear not directly from the start but at some distance from the fisheye centre, forming a circular shaped ridges‐free SA. The average value of Δ K eff of SA measured within the analysed fracture surfaces (around 40 specimens) was already calculated in former work, 7 using empirical approximation by Murakami 1 ,p. 17 and the commonly accepted statement that the crack is closed during the negative part of cyclic stress 57 ,p. 160

Δ K_{eff SA} \equiv K_{Imax SA} = 0.5 σ_{a} \sqrt{π \sqrt{{italicarea}_{SA}}} = 6.4 italicMPa \sqrt m,

where area SA is the size of the SA, respectively 7 . Following the above‐mentioned assumption, the SA should be somehow related with the plastic zone size and martensitic structure.…”

Section: Discussionmentioning

confidence: 99%

On the formation of ridges and burnished debris along internal fatigue crack propagation in 42CrMo4 steel

Seleznev

Weidner

Biermann

2020

Fatigue Fract Eng Mat Struct

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A detailed microscopic analysis of fracture surfaces of 42CrMo4-hardened steel after ultrasonic fatigue testing revealed globular and cylindrical particles located in ridges along the crack propagation direction. Observed particles could be easily taken for non-metallic inclusions; however, chemical analysis showed that they are of the same composition as the steel matrix. The formation of such round-shaped debris was found to be a result of cutting out the matrix fragments by 'en passant' cracks interaction and their subsequent fretting burnishing. Possible correlation of the parameters of ridges and debris with cyclic plastic zone width and martensite structure is discussed.42CrMo4 steel, en passant cracks, fretting, high cycle fatigue, ultrasonic fatigue testing (USFT)

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Δ K_{eff SA} \equiv K_{Imax SA} = 0.5 σ_{a} \sqrt{π \sqrt{{italicarea}_{SA}}} = 6.4 italicMPa \sqrt m,

where area SA is the size of the SA, respectively 7 . Following the above‐mentioned assumption, the SA should be somehow related with the plastic zone size and martensitic structure.…”

Section: Discussionmentioning

confidence: 99%

On the formation of ridges and burnished debris along internal fatigue crack propagation in 42CrMo4 steel

Seleznev

Weidner

Biermann

2020

Fatigue Fract Eng Mat Struct

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“…There are different approaches in the fatigue life analysis which address these issues, for example the methods of the fracture mechanics [2] or nonlinear damage accumulation hypotheses [18]. But these methods are linked to a significantly higher effort and often need a lot of very precise K input data.…”

Section: -Area Of Limited Life)mentioning

confidence: 99%

Method for a cloud based remaining-service-life-prediction for vehicle-gearboxes based on big-data-analysis and machine learning

Vietze

Hein

Stahl

2020

Forsch Ingenieurwes

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Most vehicle-gearboxes operating today are designed for a limited service-life. On the one hand, this creates significant potential for decreasing cost and mass as well as reduction of the carbon-footprint. On the other hand, this causes a rising risk of failure with increasing operating time of the machine. Especially if a failure can result in a high economic loss, this fact creates a conflict of goals. On the one hand, the machine should only be maintained or replaced when necessary and, on the other hand, the probability of a failure increases with longer operating times. Therefore, a method is desirable, making it possible to predict the remaining service-life and state of health with as little effort as possible. Centerpiece of gearboxes are the gears. A failure of these components usually causes the whole gearbox to fail. The fatigue life analysis deals with the dimensioning of gears according to the expected loads and the required service-life. Unfortunately, there is very little possibility to validate the technical design during operation, today. Hence, the goal of this paper is to present a method, enabling the prediction of the remaining-service-life and state-of-health of gears during operation. Within this method big-data and machine-learning approaches are used. The method is designed in a way, enabling an easy transfer to other machine elements and kinds of machinery.

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Fracture Mechanics Based Approach to the Significance of Certain Loads on the Service Life of Rails

Pessel

Mensinger

2016

Transportation Research Procedia

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Einführung in die bruchmechanische Schadensbeurteilung

Cited by 4 publications

References 0 publications

On the formation of ridges and burnished debris along internal fatigue crack propagation in 42CrMo4 steel

On the formation of ridges and burnished debris along internal fatigue crack propagation in 42CrMo4 steel

Method for a cloud based remaining-service-life-prediction for vehicle-gearboxes based on big-data-analysis and machine learning

Fracture Mechanics Based Approach to the Significance of Certain Loads on the Service Life of Rails

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