scholarly journals Implementation and Evaluation of the Virtual Fields Method: Determining Constitutive Model Parameters From Full-Field Deformation Data.

2014 ◽  
Author(s):  
Sharlotte Lorraine Bolyard Kramer ◽  
William M. Scherzinger
Keyword(s):  
Constitutive Model ◽  
Model Parameters ◽  
Virtual Fields Method ◽  
Full Field

scholarly journals On the optimisation efficiency for the inverse identification of constitutive model parameters

2021 ◽  
Author(s):  
Miguel Guimarães Oliveira ◽  
João Miguel Peixoto Martins ◽  
Bernardete Coelho ◽  
Sandrine Thuillier ◽  
António Andrade-Campos
Keyword(s):  
Constitutive Model ◽  
Mechanical Tests ◽  
Model Parameters ◽  
Inverse Identification ◽  
Full Field ◽  
Material Parameters ◽  
Gradient Based ◽  
Identification Techniques ◽  
Optimisation Algorithms ◽  
Optimisation Technique

The development of full-field measurement techniques paved the way for the design of new mechanical tests. However, because these mechanical tests provide heterogeneous strain fields, no closed-form solution exists between the measured deformation fields and the constitutive parameters. Therefore, inverse identification techniques should be used to calibrate constitutive models, such as the widely known finite element model updating (FEMU) and the virtual fields method (VFM). Although these inverse identification techniques follow distinct approaches to explore full-field measurements, they all require using an optimisation technique to find the optimum set of material parameters. Nonetheless, the choice of a suitable optimisation technique lacks attention and proper research. Most studies tend to use a least-squares gradient-based optimisation technique, such as the Levenberg-Marquardt algorithm. This work analyses optimisation algorithms, gradient-based and -free algorithms, for the inverse identification of constitutive model parameters. To avoid needless implementation and take advantage of highly developed programming languages, the optimisation algorithms available in optimisation libraries are used. A FEMU based approach is considered in the calibration of a thermoelastoviscoplastic model. The material parameters governing strain hardening, temperature and strain rate are identified. Results are discussed in terms of efficiency and the robustness of the optimisation processes.

scholarly journals A General Temperature-Dependent Stress–Strain Constitutive Model for Polymer-Bonded Composite Materials

Polymers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1393
Author(s):  
Xiaochang Duan ◽  
Hongwei Yuan ◽  
Wei Tang ◽  
Jingjing He ◽  
Xuefei Guan
Keyword(s):  
Composite Materials ◽  
Constitutive Model ◽  
Model Parameters ◽  
Temperature Dependent ◽  
Stress Strain ◽  
Proposed Model ◽  
Single Temperature ◽  
Testing Data ◽  
Bonded Composite ◽  
Tension And Compression

This study develops a general temperature-dependent stress–strain constitutive model for polymer-bonded composite materials, allowing for the prediction of deformation behaviors under tension and compression in the testing temperature range. Laboratory testing of the material specimens in uniaxial tension and compression at multiple temperatures ranging from −40 ∘C to 75 ∘C is performed. The testing data reveal that the stress–strain response can be divided into two general regimes, namely, a short elastic part followed by the plastic part; therefore, the Ramberg–Osgood relationship is proposed to build the stress–strain constitutive model at a single temperature. By correlating the model parameters with the corresponding temperature using a response surface, a general temperature-dependent stress–strain constitutive model is established. The effectiveness and accuracy of the proposed model are validated using several independent sets of testing data and third-party data. The performance of the proposed model is compared with an existing reference model. The validation and comparison results show that the proposed model has a lower number of parameters and yields smaller relative errors. The proposed constitutive model is further implemented as a user material routine in a finite element package. A simple structural example using the developed user material is presented and its accuracy is verified.

scholarly journals A Flow Stress Model of 300M Steel for Isothermal Tension

Materials ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 252
Author(s):  
Rongchuang Chen ◽  
Shiyang Zhang ◽  
Xianlong Liu ◽  
Fei Feng
Keyword(s):  
Flow Stress ◽  
Constitutive Model ◽  
Tensile Deformation ◽  
Flow Behavior ◽  
Tensile Tests ◽  
Uniaxial Tensile ◽  
Model Parameters ◽  
Average Deviation ◽  
Cross Sectional ◽  
300M Steel

To investigate the effect of hot working parameters on the flow behavior of 300M steel under tension, hot uniaxial tensile tests were implemented under different temperatures (950 °C, 1000 °C, 1050 °C, 1100 °C, 1150 °C) and strain rates (0.01 s−1, 0.1 s−1, 1 s−1, 10 s−1). Compared with uniaxial compression, the tensile flow stress was 29.1% higher because dynamic recrystallization softening was less sufficient in the tensile stress state. The ultimate elongation of 300M steel increased with the decrease of temperature and the increase of strain rate. To eliminate the influence of sample necking on stress-strain relationship, both the stress and the strain were calibrated using the cross-sectional area of the neck zone. A constitutive model for tensile deformation was established based on the modified Arrhenius model, in which the model parameters (n, α, Q, ln(A)) were described as a function of strain. The average deviation was 6.81 MPa (6.23%), showing good accuracy of the constitutive model.

Study on Multi-Axial Mechanical Properties of a Polyurethane Foam and Experimental Verification

2011 ◽  
Vol 311-313 ◽  
pp. 301-308
Author(s):  
Shou Hong Han ◽  
Zhen Hua Lu ◽  
Yong Jin Liu
Keyword(s):  
Mechanical Properties ◽  
Constitutive Model ◽  
Polyurethane Foam ◽  
Axial Compression ◽  
Axial Loading ◽  
Hydrostatic Compression ◽  
Model Parameters ◽  
Loading Conditions ◽  
Three Point Bending ◽  
Pu Foam

In order to investigate the multi-axial mechanical properties of a kind of PU (polyurethane) foam, some experiments in different loading conditions including uni-axial tension, uni-axial compression, hydrostatic compression and three-point bending were conducted. It is shown that the hydrostatic component influences yield behavior of PU foam, the yield strength and degree of strain hardening in hydrostatic compression exceed those for uni-axial compression. In terms of the differential hardening constitutive model, the evolution of PU foam yield surface and plastic hardening laws were fitted from experimental data. A finite element method was applied to analyze the quasi-static responses of the PU foam sandwich beam subjected to three-point bending, and good agreement was observed between experimental load-displacement responses and computational predictions, which validated the multi-axial loading methods and stress-strain constitutive model parameters. Moreover, effects of two foam models applied to uni-axial loading and multi-axial loading conditions were analyzed and compared with three-point bending tests and simulations. It is found that the multi-axial constitutive model can bring more accurate prediction whose parameters are obtained from the tests above mentioned.

Contrast Adaptation in a Nonadapting LGN Model

2007 ◽  
Vol 98 (3) ◽  
pp. 1287-1296 ◽  
Author(s):  
Kate S. Gaudry ◽  
Pamela Reinagel
Keyword(s):  
Information Transmission ◽  
Detailed Comparison ◽  
Spike Timing ◽  
Physiological Data ◽  
Model Parameters ◽  
Transient Effects ◽  
Full Field ◽  
Contrast Gain ◽  
Contrast Adaptation ◽  
Contrast Normalization

Sensory neurons appear to adapt their gain to match the variance of signals along the dimension they encode, a property we shall call “contrast normalization.” Contrast normalization has been the subject of extensive physiological and theoretical study. We previously found that neurons in the lateral geniculate nucleus (LGN) exhibit contrast normalization in their responses to full-field flickering white-noise stimuli, and that neurons with the strongest contrast normalization best preserved information transmission across a range of contrasts. We have also shown that both of these properties could be reproduced by nonadapting model cells. Here we present a detailed comparison of this nonadapting model to physiological data from the LGN. First, the model cells recapitulated other contrast dependencies of LGN responses: decreasing stimulus contrast resulted in an increase in spike-timing jitter and spike-number variability. Second, we find that the extent of contrast normalization in this model depends on model parameters related to refractoriness and to noise. Third, we show that the model cells exhibit rapid, transient changes in firing rate just after changes in contrast, and that this is sufficient to produce the transient changes in information transmission that have been reported in other neurons. It is known that intrinsic properties of neurons change during contrast adaptation. Nevertheless the model demonstrates that the spiking nonlinearity of neurons can produce many of the temporal aspects of contrast gain control, including normalization to input variance and transient effects of contrast change.

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