Improved Approach to Determine the Material Parameters for a Combined Hardening Model

Seisenbacher, Benjamin; Winter, George; Grün, Florian

doi:10.4236/msa.2018.94024

Cited by 8 publications

(4 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the present study, the parameters of the combined hardening model, including the kinematic material parameters C i and γ i , as well as Q and b s of the isotropic part, are evaluated utilizing an optimization routine [31] which was developed at the Chair of Mechanical Engineering at the Montanuniversität Leoben. This routine was comprehensively validated for various materials under ambient and elevated temperatures [99][100][101][102][103].…”

Section: Parametrization Of Elastic-plastic Materials Modelmentioning

confidence: 99%

“…The approach presents a combined hardening model which considers isotropic as well as non-linear kinematic hardening and is therefore capable of describing the evolution of size and position of the yield surface in the space of stresses. The evaluation of the applicable constitutive model parameters is a well-researched topic and comprehensively published [31][32][33][34][35]. The application of combined hardening material models covers a broad variety of advanced research topics such as creep-fatigue analysis at elevated temperatures or uni-to multiaxial loading conditions in static and dynamic structural integrity analysis [36][37][38][39].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Numerically Efficient Method to Assess the Elastic–Plastic Strain Energy Density of Notched and Imperfective Cast Steel Components

2023

View full text Add to dashboard Cite

The fatigue strength of cast steel components is severely affected by manufacturing process-based bulk and surface imperfections. As these defect structures possess an arbitrary spatial shape, the utilization of local assessment methods is encouraged to design for service strength. This work applies the elastic–plastic strain energy density concept to study the fatigue strength properties of a high-strength cast steel alloy G12MnMo7-4+QT. A fatigue design limit curve is derived based on non-linear finite element analyses which merges experimental high-cycle fatigue results of unnotched and notched small-scale specimens tested at three different stress ratios into a unique narrow scatter band characterized by a scatter index of 1:TΔW¯(t)=2.43. A comparison to the linear–elastic assessment conducted in a preceding study reveals a significant improvement in prediction accuracy which is assigned to the consideration of the elastic–plastic material behaviour. In order to reduce computational effort, a novel approximation is presented which facilitates the calculation of the elastic–plastic strain energy density based on linear–elastic finite element results and Neuber’s concept. Validation of the assessment framework reveals a satisfying agreement to non-linear simulation results, showing an average root mean square deviation of only approximately eight percent in terms of total strain energy density. In order to study the effect of bulk and surface imperfections on the fatigue strength of cast steel components, defect-afflicted large-scale specimens are assessed by the presented elastic–plastic framework, yielding fatigue strength results which merge into the scatter band of the derived design limit curve. As the conducted fatigue assessment is based solely on linear–elastic two-dimensional simulations, the computational effort is substantially decreased. Within the present study, a reduction of approximately 400 times in computation time is observed. Hence, the established assessment framework presents an engineering-feasible method to evaluate the fatigue life of imperfective cast steel components based on rapid total strain energy density calculations.

show abstract

Section: Parametrization Of Elastic-plastic Materials Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Numerically Efficient Method to Assess the Elastic–Plastic Strain Energy Density of Notched and Imperfective Cast Steel Components

2023

View full text Add to dashboard Cite

show abstract

“…where c is the material constant, γ defines the rate of the kinematic hardening saturation, and d p is the equivalent plastic strain increment. The increment in isotropic hardening dr( p) is determined by Voce isotropic law [32] as:…”

Section: Combined Hardening: Problem Formulationmentioning

confidence: 99%

Fuzzy logic enhancement of material hardening parameters obtained from tension–compression test

Wójcik

Skrzat

2019

Continuum Mech. Thermodyn.

View full text Add to dashboard Cite

This paper presents the determination of material hardening parameters with the use of the fuzzy set theory. The hardening parameters were initially predicted from measurements taken in the cyclic tensioncompression test. The experimental hysteresis loop was compared to numerical one obtained by the integration of the plastic flow rule. The nonlinear combined hardening model-Voce isotropic hardening and Frederick-Armstrong kinematic hardening-was considered here. After the initial selection, the hardening parameters were adjusted in the optimization problem using the least-squares method. An approximation error of the hysteresis loop was minimized. Finally, nonlinear isotropic and kinematic hardening parameters were assumed to be fuzzy variables. Hardening parameters obtained in the optimization problem were randomly scattered up to 20%, and the membership functions associated with them were computed. The approximation error of the hysteresis loop was found for each selection of the hardening parameters providing the output membership function associated with this error. The α-level optimization method was used as the main numerical tool, while the extension principle was tested only as the reference solution. In the defuzzification process, the most reliable hardening parameters were found.

show abstract

“…The initial conditions are represented by the parameters

and

in Equation ( 6 ) and the value

describes the flow direction of the yield surface [ 79 ].

and

representing the kinematic part as well as Q and b for the isotropic part can be experimentally determined based on low-cycle fatigue (LCF) tests using an optimisation routine, proposed in [ 81 ].…”

Section: Introductionmentioning

confidence: 99%

Effect of Surface Finishing State on Fatigue Strength of Cast Aluminium and Steel Alloys

et al. 2023

View full text Add to dashboard Cite

The endurance limit of structural mechanical components is affected by the residual stress state, which depends strongly on the manufacturing process. In general, compressive residual stresses tend to result in an increased fatigue strength. Post-manufacturing processes such as shot peening or vibratory finishing may achieve such a compressive residual stress state. But within complex components, manufacturing-process-based imperfections severely limit the fatigue strength. Thus, the interactions of imperfections, residual stress state and material strength are key aspects in fatigue design. In this work, cast steel and aluminium alloys are investigated, each of them in vibratory finished and polished surface condition. A layer-based fatigue assessment concept is extended towards stable effective mean stress state considering the elastic–plastic material behaviour. Murakami’s concept was applied to incorporate the effect of hardness change and residual stress state. Residual stress relaxation is determined by elastic–plastic simulations invoking a combined hardening model. If the effective stress ratio within the local layer-based fatigue strength is evaluated as critical distance value, a sound calculation of fatigue strength can be achieved. Summing up, the layer-based fatigue strength design is extended and features an enhanced understanding of the effective stabilized mean stress state during cyclic loading.

show abstract

Improved Approach to Determine the Material Parameters for a Combined Hardening Model

Cited by 8 publications

References 12 publications

A Numerically Efficient Method to Assess the Elastic–Plastic Strain Energy Density of Notched and Imperfective Cast Steel Components

A Numerically Efficient Method to Assess the Elastic–Plastic Strain Energy Density of Notched and Imperfective Cast Steel Components

Fuzzy logic enhancement of material hardening parameters obtained from tension–compression test

Effect of Surface Finishing State on Fatigue Strength of Cast Aluminium and Steel Alloys

Contact Info

Product

Resources

About