Determination of reliable fatigue life predictors for magnetorheological elastomers under dynamic equi-biaxial loading

Zhou, Yanfen; Jiang, Liang; Chen, Shaojuan; Ma, Jing; Betts, Anthony; Jerrams, Stephen

doi:10.1016/j.polymertesting.2017.05.021

Cited by 25 publications

(26 citation statements)

References 22 publications

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“…7. Based on the results from cyclic testing, an equation for fatigue life prediction using maximum engineering stress (σ) can be postulated as follows [42].…”

Section: Crack Tip Evolutionmentioning

confidence: 99%

Enhanced fatigue and durability of carbon black/natural rubber composites reinforced with graphene oxide and carbon nanotubes

Guo

Jerrams

et al. 2020

Engineering Fracture Mechanics

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Graphene oxide (GO) sheets and carbon nanotubes (CNTs) are of nanometer size and offer large shape factors which are beneficial in reducing crack propagation rates of composites when used in carbon black (CB) reinforced natural rubber (NR), thereby prolonging the service lives of rubber composites. In this research, CNT-CB/NR and GO-CB/NR composites were prepared by partially replacing CB with one-dimensional CNTs and two-dimensional flaky graphene oxide GO, respectively. The results showed that the complex filler dispersion in NR matrices was improved due to the isolation effect between the different fillers. The strain-induced crystallization (SIC) ability of CB/NR was effectively enhanced by the addition of both GO and CNT. The modulus at 100% strain and tear strength of the composites were also improved. More branching and deflections were observed at the crack tips of the composites and both effectively hindered crack propagation in the materials. Under uniaxial and multi-axial cyclic loading, the fatigue lives of CNT-CB/NR and GO-CB/NR composites greatly increased when compared with the fatigue lives of CB/NR composites. The GO-CB/NR composites exhibited evident advantages in respect of fatigue resistance and durability among the three composites.

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“…7. Based on the results from cyclic testing, an equation for fatigue life prediction using maximum engineering stress (σ) can be postulated as follows [42].…”

Section: Crack Tip Evolutionmentioning

confidence: 99%

Enhanced fatigue and durability of carbon black/natural rubber composites reinforced with graphene oxide and carbon nanotubes

Guo

Jerrams

et al. 2020

Engineering Fracture Mechanics

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“…MR effect can also be affected by the particle distribution in the MRE element. Reported from the previous work by Zhou et al [24], the anisotropic arrangement provides a better performance than the isotropic arrangement. Anisotropic can be considered as a pre-structured MRE and possess strictly directed particle orientation.…”

Section: A Chemical Compositionsmentioning

confidence: 87%

“…According to the literature surveyed on the durability of MRE, circular disk design was the highest employed geometry for the MRE durability test. The radius of ranged between 13 mm [34] to 60 mm [36] was used, however 50 mm [14], [16], [17], [19], [24], [31] was the commonly been practiced. This may due to the requirement of the sample mounting devices from the test machine itself, such as the Modular Compact Rheometer (MCR) and the bi-axial test device.…”

Section: Durability Test Specimenmentioning

confidence: 99%

An Overview of Durability Evaluations of Elastomer-Based Magnetorheological Materials

et al. 2020

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Most parts of the failures in structural elements in use were consequences of mechanical durability. Therefore, durability had been one of the critical factors to be considered in designing durable mechanical elements. In magnetorheological elastomer (MRE) materials, the durability process involves different damage mechanisms that result in the degradation of the materials. Increasingly used of outstanding performance of MRE was susceptible to failure under durability performance for various applications. In response to these problems, with limited sources of published articles on MRE durability, an overview of the durability of elastomer based MRE is presented. The study focuses on collecting and analyzing the works including experimental and modeling approaches that have been conducted on MRE durability up to date. Two bibliographic searched databases, Scopus and Web of Science were consulted to collect the final set of articles with the aims to identify current and future trends of MRE durability. Prominence works conducted on MRE durability were also encapsulated in this paper to provide a visual perspective and subsequently motivate researchers to heighten the need for MRE durability investigation.

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“…Numerous factors affect the fatigue performance of rubber, such as load history, ambient temperature, ozone concentration, and compound formula (such as filler volume fraction and rubber type). Multi‐factor rubber material fatigue test is difficult because of the small test data sample points and large dispersion . To establish a quantitative analysis model of rubber material fatigue life, finding a mathematical model that can maximize scarce sample data is necessary.…”

Section: Introductionmentioning

confidence: 99%

“…Multi-factor rubber material fatigue test is difficult because of the small test data sample points and large dispersion. [6][7][8][9][10][11] To establish a quantitative analysis model of rubber material fatigue life, finding a mathematical model that can maximize scarce sample data is necessary.…”

Section: Introductionmentioning

confidence: 99%

Fatigue life prediction for vibration isolation rubber based on parameter‐optimized support vector machine model

Liu

Shi

Chen

2018

Fatigue Fract Eng Mat Struct

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Given the small sample size, nonlinearity, and large dispersion of the measured data of fatigue performance for vibration isolation rubbers, the fatigue life prediction model for vibration isolation rubber materials was established using a support vector machine (SVM). A modified gravity search algorithm (MGSA) is proposed to optimize the parameters of the SVM. Using environmental temperature, the Rockwell hardness of the rubber compound, and the engineering strain peak as the input variables, the model was trained based on the experimental fatigue data of vibration isolation rubber materials. For comparison, the standard genetic algorithm, the standard particle swarm algorithm, and the standard simulated annealing algorithm are also implemented. Moreover, a back propagation neural network regression model is applied to the life prediction, with the conclusion that the prediction accuracy and the efficiency of MGSA are better than those of extant methods. This work can provide reference for further fatigue life prediction and structural improvement of rubber parts.

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Determination of reliable fatigue life predictors for magnetorheological elastomers under dynamic equi-biaxial loading

Cited by 25 publications

References 22 publications

Enhanced fatigue and durability of carbon black/natural rubber composites reinforced with graphene oxide and carbon nanotubes

Enhanced fatigue and durability of carbon black/natural rubber composites reinforced with graphene oxide and carbon nanotubes

An Overview of Durability Evaluations of Elastomer-Based Magnetorheological Materials

Fatigue life prediction for vibration isolation rubber based on parameter‐optimized support vector machine model

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