Dry-sliding wear analysis and prediction using response surface method and fuzzy logic for Kota stone dust–fly ash–epoxy hybrid composites

Agrawal, Alok; Gupta, Gaurav; Pati, Pravat Ranjan; Nayak, Sandip K.

doi:10.1177/09544089231158902

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…To mitigate these issues, micro-or nano-scale filler materials are added to fiber-reinforced composites. 7 In recent years, many studies [8][9][10][11][12][13] have aimed to improve the mechanical properties as well as impact resistance, wear resistance, electrical, and thermal properties of fiber-reinforced polymers by incorporating different types of fillers. 14 Wear is typically defined as damage involving material loss due to relative motion between two contacting surfaces.…”

Section: Introductionmentioning

confidence: 99%

Tribological and mechanical properties of nanofilled glass fiber reinforced composites and analyzing the tribological behavior using artificial neural networks

Demir,

Cetkin,

Ergün

et al. 2024

Polymer Composites

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This study investigates the effects of filler content and type on the mechanical (tensile strength and impact resistance) and tribological properties of woven glass fiber‐reinforced composites (WGFC) produced using three different nanofillers (MgO, CuO, and Al2O3) at various loading levels (0.7, 1.4, and 2.8 wt%). Additionally, analyses of the artificial neural network algorithm were reported for the predictions of wear rate, mass loss, and coefficient of friction (COF) by given applied load, sliding distance, filler ratio, and filler type. The composites were fabricated using the hand lay‐up method. The filled composites were characterized using Fourier Transform Infrared (FTIR) spectroscopy, and the worn surfaces of the samples after the wear test were analyzed using Scanning Electron Microscopy (SEM). The wear resistance of the composite samples improved at 0.7 wt% CuO and 1.4 wt% MgO filler contents. At 200 m sliding distance and 1.4 wt% filler ratio, the highest wear ratio was determined as 55 mm3/m × 10−3 in the Al2O3‐filled composite, and the lowest was determined as 31 mm3/m × 10−3 in the MgO‐filled composite. At 1.4% filler ratio and 15 N load, the lowest friction coefficient was determined as 0.45 μ in MgO‐filled composite, and the highest was 0.56 μ in Al2O3‐filled composite. Al2O3 filler increased the mass loss and wear rate of the composite material. In Charpy impact tests, the maximum impact energy of 13.9 J/m2 was obtained with a 2.8 wt% Al2O3 filler content. Tensile tests showed an increase in tensile strength for all filler contents compared to unfilled composites. The highest tensile strength of 242.1 MPa was achieved with 0.7 wt% CuO reinforcement.Highlights In all applied wear parameters and filler ratios, the Al2O3 filler adversely affected the wear resistance of the composite, while the MgO filler showed the best performance in terms of wear resistance. All types and ratios of fillers increased the tensile strength compared to the unfilled composite. Contrary to its negative effect on wear, the Al2O3‐filled composites exhibited the highest impact resistance. The prediction analysis of the tribological behavior of composite material using ANN reveals that the Levenberg–Marquardt algorithm fits very well.

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Section: Introductionmentioning

confidence: 99%

Tribological and mechanical properties of nanofilled glass fiber reinforced composites and analyzing the tribological behavior using artificial neural networks

Demir,

Cetkin,

Ergün

et al. 2024

Polymer Composites

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Experimental study of physical, mechanical and tribological behaviour of polyester/kota stone dust composite

Awasthi,

Bharti,

Agrawal

et al. 2024

Eng. Res. Express

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In the industry of Kota stone, a significant amount of waste material is produced at the time of manufacturing. This waste is typically discarded on the local site, which is then carried away by rainwater and air, leading to environmental deterioration. The current study focuses on utilizing the waste i.e. Kota stone dust (KSD) as the filler in the polyester resin for the development of a polymeric composite. Various composite sets with different micro-particulate contents through open moulding technique are prepared and its characterization is reported. The density and void percentage of polyester increase with KSD loading. The hardness and compressive strength increased to 83.7 Shore-D number and 102.7 MPa respectively, at 40 wt. % KSD. A tensile and flexural modulus also increases with KSD loading showing an improvement of 72.8 % and 64.1 % respectively. Contrary to that, the highest tensile and flexural strength was recorded at 25 wt. % and 30 wt. % KSD loading respectively, which is 29.2 % and 28.8 % higher than unfilled polyester. Sliding wear tests were conducted following Taguchi's experimental design. The experiments revealed that the filler content had the most significant impact on the specific rate. The study of surface morphology of the worn surfaces provided an insight into the wear mechanisms of the composites such as craters, cracks, wear debris, and wear track formation at different sliding conditions. The composites' wear response prediction for various test conditions within and beyond the experimental boundary was conducted by successfully implementing a model based on artificial neural networks.

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Parametric analysis of erosion wear of sponge iron slag-filled ramie–epoxy composites using Taguchi and preference selection index methods

Mahapatra,

Satapathy

2023

Proceedings of the Institution of Mechanical Engineers, Part E:

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The present work reports on the development of a novel set of ramie–epoxy composites filled with sponge iron (SI) slag (0–30 wt.%) and on their response to solid particle erosion wear under different test conditions. SI slag is a by-product generated during the processing of SI to steel in arc or induction furnace. While these composites are fabricated using the conventional hand layup technique, the erosion tests are carried out using an air jet erosion tester following ASTM G76 test standard as per Taguchi's L27 orthogonal array. Mechanical characterization of ramie–epoxy composites suggests that the incorporation of SI slag improves their tensile strength by about 52%, flexural strength by 10% and micro-hardness by about 30%. A parametric appraisal of the erosion response carried out using Taguchi method reveals that the filler content, impact velocity and impingement angle are the most significant control factors influencing the erosion rate of these composites. The individual effects of different factors in wider ranges (impact velocity 25–125 m/s, filler content 0–30 wt.% and impingement angle 30–90°) are ascertained by conducting steady-state erosion experiments in controlled conditions. Preference selection index method, which is an effective multi-criteria decision-making tool is used to select the best candidate among all composites based on different physical, mechanical and wear test results. It is found that the composite with 30 wt.% SI slag content displays the optimal combination of properties. The worn morphologies of the eroded surfaces of the composites are studied and analyzed using electron microscopy to identify possible mechanisms causing the wear loss.

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Dry-sliding wear analysis and prediction using response surface method and fuzzy logic for Kota stone dust–fly ash–epoxy hybrid composites

Cited by 3 publications

References 28 publications

Tribological and mechanical properties of nanofilled glass fiber reinforced composites and analyzing the tribological behavior using artificial neural networks

Tribological and mechanical properties of nanofilled glass fiber reinforced composites and analyzing the tribological behavior using artificial neural networks

Experimental study of physical, mechanical and tribological behaviour of polyester/kota stone dust composite

Parametric analysis of erosion wear of sponge iron slag-filled ramie–epoxy composites using Taguchi and preference selection index methods

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