Viscoplastic analysis of structural polymer composites using stress relaxation and creep data

Al-Haik, Marwan; Vaghar, M. R.; Garmestani, Hamid; Shahawy, Mohsen

doi:10.1016/s1359-8368(00)00042-1

Cited by 28 publications

(16 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The neural networks-based creep model is more cost efficient compared to the explicit viscoplastic model (Al-Haik et al [3]); only one type of data is required, i.e., creep data at different thermomechanical histories, while the explicit viscoplastic model required both tensile tests data along with load relaxation data, and of course creep data is still required to verify the performance of the model. While the duration of tensile and load relaxation tests are short compared to the creep tests, the outcome of using tensile load relaxation based viscoplastic model produced considerable errors when predicting the creep strain [2,3].…”

Section: Resultsmentioning

confidence: 99%

“…A detailed investigation about this model can be found in earlier investigation by Gates and Sun [15,16] and recently in the work of Al-Haik et al [1,2,3,12]. The model describes the rate dependant stress/strain behavior in graphite reinforced polymeric composite.…”

Section: Analytical Model Descriptionmentioning

confidence: 99%

“…All these parameters were obtained from load relaxation and tensile data at in previous published investigations [1,2,3,12] and they are presented in Table1.…”

Section: Analytical Model Descriptionmentioning

confidence: 99%

“…Viscoplastic constitutive equations presented earlier by the authors [1,3], were written explicitly and they involve many parameters, which significantly influence the behavior of the constitutive equations. Appropriate parameters must be determined accordingly, such that the accurate behaviors of the material can be expressed.…”

mentioning

confidence: 99%

“…Some of the problems involved with the explicit constitutive models, from our earlier investigation [3], include:…”

mentioning

confidence: 99%

See 4 more Smart Citations

Truncated-Newton training algorithm for neurocomputational viscoplastic model

Al-Haik

Garmestani

Navon

2003

Computer Methods in Applied Mechanics and Engineering

View full text Add to dashboard Cite

We present an estimate approach to compute the viscoplastic behavior of a polymer matrix composite (PMC) under different thermomechanical environments. This investigation incorporates computational neural network as the tool for deter-mining the creep behavior of the composite. We propose a new second-order learning algorithm for training the multilayer networks. Training in the neural network is generally specified as the minimization of an appropriate error function with respect to parameters of the network (weights and learning rates) corresponding to excitory and inhibitory connections. We propose here a technique for error minimization based on the use of the truncated Newton (TN) large-scale unconstrained minimization technique with quadratic convergence rate. This technique offers a more sophisticated use of the gradient information compared to simple steepest descent or conjugate gradient methods. In this work we briefly specify the necessary details for implementing the truncated Newton method for training the neural networks that predicts the viscoplastic behavior of the polymeric composite. We provide comparative experimental results and explicit model results to verify the effectiveness of the neural networks-based model. These results verify the 1 Corresponding author, Tel: 850-644-6560. E-mail address: navon@csit.fsu.edu. 2 superiority of the present approach compared to the explicit modeling scheme. Moreover, the present study demonstrates for the first time the feasibility of introducing the truncated Newton method, with quadratic convergence rate, to the field of neural networks.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Analytical Model Descriptionmentioning

confidence: 99%

“…All these parameters were obtained from load relaxation and tensile data at in previous published investigations [1,2,3,12] and they are presented in Table1.…”

Section: Analytical Model Descriptionmentioning

confidence: 99%

mentioning

confidence: 99%

“…Some of the problems involved with the explicit constitutive models, from our earlier investigation [3], include:…”

mentioning

confidence: 99%

See 3 more Smart Citations

Truncated-Newton training algorithm for neurocomputational viscoplastic model

Al-Haik

Garmestani

Navon

2003

Computer Methods in Applied Mechanics and Engineering

View full text Add to dashboard Cite

show abstract

Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites

2008

View full text Add to dashboard Cite

The viscoplastic behavior of a carbon fiber/polymer matrix composite is investigated via different modeling schemes. The first model is phenomenological in nature based on the overstress-viscoplasticity. The second model utilizes neural networks paradigms. Genetic algorithm-based strategies are used to prune the proposed neural network. Several optimization algorithms are implemented for training the network. In comparison, the neurocomputational model is found to outperform the phenomenological model.

show abstract

Evaluation of fundamental viscoelastic functions by a nonlinear viscoelastic model

Spathis

Katsourinis

Kontou

2017

Polymer Engineering & Sci

View full text Add to dashboard Cite

In this work, a new constitutive equation for the description of the nonlinear viscoelastic response of polymeric materials is presented, by proposing modifications on a model developed in previous works. This time-dependent equation has been derived on the basis of transient model, and a new assumption regarding the kinetics of active molecular chains due to the imposed deformation. The present treatment was proved to be more flexible, given that it contains a relaxation function that has been derived by considering, instead of first-order kinetics, a fractional derivative that controls the rate of molecular chain detachment from their junctions. It has been further explored that the potential of this equation to be employed for the evaluation of the dynamic modulus master curve, once the experimental data of the compliance modulus of a polymeric structure have been matched.

show abstract

Viscoplastic analysis of structural polymer composites using stress relaxation and creep data

Cited by 28 publications

References 9 publications

Truncated-Newton training algorithm for neurocomputational viscoplastic model

Truncated-Newton training algorithm for neurocomputational viscoplastic model

Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites

Evaluation of fundamental viscoelastic functions by a nonlinear viscoelastic model

Contact Info

Product

Resources

About