Fuzzy Logic Application to Strain-Stress Analysis in Selected Elastic-Plastic Material Models

In order to describe the phenomenon for which the mathematical model or input data are unknown, the fuzzy logic is applied. The fuzzy theory enables to find the most reliable solution on the assumption that the input data are fuzzed. This paper presents the possibility of application of fuzzy theory in engineering problems. The theoretical basis of the fuzzy logic and mathematical calculations on fuzzy variables are presented. The comparison of two methods used in fuzzy logic-extension principle and α-level optimization are written and compared. Examples of the application of aforementioned methods for solving simple engineering problem were presented. Numerical calculations were done with the use of MATLAB program. The selection of the most reliable solution, based on finding the mass center or with the use of rank level method, was also shown.

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“…The normal Gaussian distribution is adequate for the most of real problem. But in practice, the linear distribution is most often used [17].…”

Section: Theoretical Basis Of Fuzzy Logic Theorymentioning

confidence: 99%

“…The extreme xαkl and xαkr values determine the subspace assigned to αk level. The xαk,l and xαk,r values for sufficiently high number of α-levels designate the shape of membership function [5,16,17].…”

Section: Theoretical Basis Of Fuzzy Logic Theorymentioning

confidence: 99%

The Application of Fuzzy Logic in Engineering Applications

Skrzat

Wójcik

2018

ZN PRz Mechanika

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“…The processed material is aluminum alloy at 450°C. The stress-plastic strain curve is obtained from [7] [8]. In numerical computations commercial ABAQUS program was used.…”

Section: Coupled Eulerian-lagrangian Simulation Of Backward Extrusionmentioning

confidence: 99%

Application of coupled Eulerian-Lagrangian approach in metal forming simulations

Skrzat¹

2012

ZN PRz Mechanika

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Numerical simulations of materials forming processes require both powerful computers and advanced software. Large displacements assumed in the analysis usually cause convergence problems. In the Lagrangian approach (typical for solid bodies) a remeshing is frequently necessary. This extends the computations and decreases the convergence. In such cases the application of Euler approach (typical for fluid flows) is an practical alternative. In the Euler approach the finite elements mesh remains fixed, while material flows through it. There is no need for remeshing, therefore. In this paper selected results of coupled Eulerian-Lagrangian analysis are presented. A bent beam as the benchmark test and backward extrusion as an example of metal forming process are considered. Some models parts (tools) are described by updated Lagrangian formulation, other parts (material) are described by Eulerian approach. Obtained results of CEL analyses were compared to ones of the pure Lagrangian approach.

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“…In [18], the application of the fuzzy logic for solving simple mechanical problems was presented. The response of the Bodner-Partom material to external loads with the use of fuzzy logic was investigated in [19]. The application of the fuzzy set theory for the determination of material strain hardening parameters in Hollomon equation based on the Heyer's test was described in [20].…”

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confidence: 99%

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

Wójcik

Skrzat

2019

Continuum Mech. Thermodyn.

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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.

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Fuzzy Logic Application to Strain-Stress Analysis in Selected Elastic-Plastic Material Models

Cited by 10 publications

References 5 publications

The Application of Fuzzy Logic in Engineering Applications

The Application of Fuzzy Logic in Engineering Applications

Application of coupled Eulerian-Lagrangian approach in metal forming simulations

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

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