Use of a load non‐proportionality measure in fatigue under out‐of‐phase combined bending and torsion

Skibicki, Dariusz; Sempruch, J.

doi:10.1111/j.1460-2695.2004.00757.x

Cited by 16 publications

(8 citation statements)

References 16 publications

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“…Consequently, the fatigue life was successfully predicted for the four tested non-proportional loading paths (NPR1, NPR2, NPR3, NPR4) of different and complex shapes ( Figure 2 ) and for one proportional loading path (Prop). Furthermore, the common complex measures of the non-proportional loading effect on fatigue life, such as non-proportional factors [ 79 , 80 , 81 , 82 ], integral approaches [ 66 , 72 , 82 ] and enclosing surface methods [ 83 , 84 ], are not needed.…”

Section: Resultsmentioning

confidence: 99%

Gaussian Process for Machine Learning-Based Fatigue Life Prediction Model under Multiaxial Stress–Strain Conditions

2022

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In this paper, a new method for fatigue life prediction under multiaxial stress-strain conditions is developed. The method applies machine learning with the Gaussian process for regression to build a fatigue model. The fatigue failure mechanisms are reflected in the model by the application of the physics-based stress and strain invariants as input quantities. The application of the machine learning algorithm solved the problem of assigning an adequate parametric fatigue model to given material and loading conditions. The model was verified using the experimental data on the CuZn37 brass subjected to various cyclic loadings, including non-proportional multiaxial strain paths. The performance of the machine learning-based fatigue life prediction model is higher than the performance of the well-known parametric models.

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Section: Resultsmentioning

confidence: 99%

Gaussian Process for Machine Learning-Based Fatigue Life Prediction Model under Multiaxial Stress–Strain Conditions

2022

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“…The factors of loading nonproportionality can quantitatively assess the effect of nonproportional loading on fatigue life. At present, many factors have been proposed by researchers to calculate the degree of loading nonproportionality, and they are reviewed in detail by Luo et al…”

Section: Approach Of Critical Plane Of Notchmentioning

confidence: 99%

A notch critical plane approach of multiaxial fatigue life prediction for metallic notched specimens

Luo

Yao

2018

Fatigue Fract Eng Mat Struct

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An approach based on the local stress response is proposed to locate the fatigue critical point for metallic blunt notched specimens under multiaxial fatigue loading. According to the stress analysis, both stress gradient and gradient of loading nonproportionality exist at notch root. The plane in the vicinity of the notch that passes through the fatigue critical point and experiences the maximum shear stress amplitude is defined as the critical plane for notch specimens (CPN). Furthermore, the Susmel's fatigue damage parameter is modified to assess fatigue life of notched components by combining CPN and the theory of critical distance (TCD). The multiaxial fatigue test of the thin‐walled round tube specimens made of Ni‐base alloy GH4169 is carried out to verify the above approaches. In addition, test data of two kinds of materials are collected. The results show that the maximum absolute error of the fatigue critical point is 9.6° and the majority of the predicted life falls within the three‐time scatter band.

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“…the model by McDowell and Bennet 11 . The model for micro and short crack propagation presented below is developed on the basis of the model by McDowell and Bennet 5 and applied to our multiaxial tests for lifetime prediction.…”

Section: Modelling Of Microcrack Propagationmentioning

confidence: 99%

“…For this purpose, many multiaxial fatigue experiments have been performed in recent years. [1][2][3][4][5][6] The classification of the different kinds of multiaxial fatigue tests is shown in Fig. 2.…”

Section: Introductionmentioning

confidence: 99%

Modelling of fatigue lifetime under non‐proportional multiaxial alternating loading

Weick

Aktaa

2007

Fatigue Fract Eng Mat Struct

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A B S T R A C T This paper presents two approaches to lifetime prediction under non-proportional multiaxial alternating loading; a phenomenological approach using the Manson-Coffin relation and a microstructural approach. Both models have in common the use of a new multiaxiality factor. The data sets for the adaptation and validation of both models are taken from the authors' own experiments. In these tests, both the load paths and the phase shift are varied. The biaxial test apparatus allows for an application of fixed principal stress or strain directions even under non-proportional loading.A fairly good agreement with our multiaxial lifetime results is obtained with both models.For an advanced assessment of the quality of the approaches used, the models are compared with several other well-known models from the literature. An additive yardstick is used for the comparison of the different models.Keywords additional/reduced hardening; fixed principal stresses system; hydrostatic load; Manson-Coffin; microcrack propagation; multiaxial load. N O M E N C L A T U R Ea = crack length b μ = material parameter, microcrack regime C = material parameter C * = material parameter, uniaxially ascertained C j = microcrack propagation coefficient c μ = material parameter, microcrack regime d = mean grain size da/dN = crack growth rate E = Young's modulus f m = multiaxiality factor h = material parameter J = plastic deformation increasing function k = material parameter m j = crack propogation exponent m μ = crack propogation extra exponent for a < kd n = hardening exponent N f = number of cycles to failure q = material parameter s = mode factor t v = modulation factor u = material parameter z * = material parameter, uniaxially ascertained Correspondence: M. Weich.

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Use of a load non‐proportionality measure in fatigue under out‐of‐phase combined bending and torsion

Cited by 16 publications

References 16 publications

Gaussian Process for Machine Learning-Based Fatigue Life Prediction Model under Multiaxial Stress–Strain Conditions

Gaussian Process for Machine Learning-Based Fatigue Life Prediction Model under Multiaxial Stress–Strain Conditions

A notch critical plane approach of multiaxial fatigue life prediction for metallic notched specimens

Modelling of fatigue lifetime under non‐proportional multiaxial alternating loading

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