Performance prediction of a specific wear rate in epoxy nanocomposites with various composition content of polytetrafluoroethylen (PTFE), graphite, short carbon fibers (CF) and nano-TiO2 using adaptive neuro-fuzzy inference system (ANFIS)

Mesbahi, Ali Haghighat; Semnani, Dariush; Khorasani, Saied Nouri

doi:10.1016/j.compositesb.2011.11.026

Cited by 30 publications

(7 citation statements)

References 18 publications

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“…Due to its unique molecular and morphological structure, PTFE has one of the lowest coefficients of friction against any solid. In addition, PTFE could form a third-body transfer film when it is sliding over a hard surface [38]. PTFE has been widely used as an engineering plastic due to its relatively chemically inert nature, low friction coefficient, and outstanding thermal stability.…”

Section: Polytetrafluoroethylene (Ptfe) As Coatingsmentioning

confidence: 99%

Fatigue Analysis of Actuators with Teflon Impregnated Coating—Challenges in Numerical Simulation

Kang

Ouyang

2021

Actuators

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Actuators are essential components for motion in machines, and warranty service lives are basic specifications of actuators. However, fatigue damage or wear of actuators are very complex and related to many design factors, such as materials properties, surface conditions, loads, and operating temperature. Actuator manufacturers still rely heavily on physical experiments to determine the fatigue lives of actuators. This paper investigates the state-of-the-art of using numerical simulations for fatigue analysis of mechanical actuators. Failure criteria of machine elements are discussed extensively; existing works on using finite element methods for machine element designs are examined to (1) explore the feasibility of using a numerical simulation for fatigue analysis and (2) discuss the technical challenges in practice. Moreover, a systematic procedure is suggested to predict fatigue lives of mechanical actuators with Teflon impregnated hard coatings. A virtual fatigue analysis allows for optimizing a mechanical structure, reducing design verification costs, and shortening the development time of actuators.

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Section: Polytetrafluoroethylene (Ptfe) As Coatingsmentioning

confidence: 99%

Fatigue Analysis of Actuators with Teflon Impregnated Coating—Challenges in Numerical Simulation

Kang

Ouyang

2021

Actuators

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“…ANFIS and ANN were compared in the prediction of K s PTFE and its composites. It was found that ANN performed better than ANFIS 32 . Prediction of abrasive wear of industrial waste and glass filled polyester composites was done using ANN and linear regression model.…”

Section: Introductionmentioning

confidence: 99%

Optimization and prediction of tribological behaviour of filled polytetrafluoroethylene composites using Taguchi Deng and hybrid support vector regression models

Ibrahim

Çamur²,

Savas³

et al. 2022

Sci Rep

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This study presents optimization and prediction of tribological behaviour of filled polytetrafluoroethylene (PTFE) composites using hybrid Taguchi and support vector regression (SVR) models. To achieve the optimization, Taguchi Deng was employed considering multiple responses and process parameters relevant to the tribological behaviour. Coefficient of friction (µ) and specific wear rate (Ks) were measured using pin-on-disc tribometer. In this study, load, grit size, distance and speed were the process parameters. An L27 orthogonal array was applied for the Taguchi experimental design. A set of optimal parameters were obtained using the Deng approach for multiple responses of µ and KS. Analysis of variance was performed to study the effect of individual parameters on the multiple responses. To predict µ and Ks, SVR was coupled with novel Harris Hawks’ optimization (HHO) and swarm particle optimization (PSO) forming SVR-HHO and SVR-PSO models respectively, were employed. Four model evaluation metrics were used to appraise the prediction accuracy of the models. Validation results revealed enhancement under optimal test conditions. Hybrid SVR models indicated superior prediction accuracy to single SVR model. Furthermore, SVR-HHO outperformed SVR-PSO model. It was found that Taguchi Deng, SVR-PSO and SVR-HHO models led to optimization and prediction with low cost and superior accuracy.

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“…Amongst various lubricant additives the advantages of PTFE is well documented [19][20][21][22] where in most cases a reduction in friction coefficient is experienced. Zuo et al [23] reported the excellent friction and wear behaviors of the PES/PTFE composite under the dry sliding conditions.…”

Section: Introductionmentioning

confidence: 98%

Eco-friendly mono-layered PTFE blended polymer composites for dry sliding tribo - systems

Karthikeyan

Rajini

Baets

et al. 2016

Tribology International

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Performance prediction of a specific wear rate in epoxy nanocomposites with various composition content of polytetrafluoroethylen (PTFE), graphite, short carbon fibers (CF) and nano-TiO2 using adaptive neuro-fuzzy inference system (ANFIS)

Cited by 30 publications

References 18 publications

Fatigue Analysis of Actuators with Teflon Impregnated Coating—Challenges in Numerical Simulation

Fatigue Analysis of Actuators with Teflon Impregnated Coating—Challenges in Numerical Simulation

Optimization and prediction of tribological behaviour of filled polytetrafluoroethylene composites using Taguchi Deng and hybrid support vector regression models

Eco-friendly mono-layered PTFE blended polymer composites for dry sliding tribo - systems

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