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Wear performance analysis of B4C and graphene particles reinforced Al–Cu alloy based composites using Taguchi method

  • T. S. Sachit , Arunkumar Bongale EMAIL logo , Satish Kumar and Priya Jadhav
Published/Copyright: March 18, 2023
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Journal of the Mechanical Behavior of Materials
From the journal Journal of the Mechanical Behavior of Materials Volume 32 Issue 1

Abstract

In this study, the wear performance of boron carbide (B4C) and graphene (Gr) particles reinforced Al–Cu alloy composites was investigated. The composite samples were made using the solid-state manufacturing process. The wear performance was assessed using a pin-on-disc tribometer. The Taguchi optimization approach was used to determine the performance of each parameter. All experiments were carried out using the L27 array, which included three sets of parameters such as applied load, disc speed, and reinforcement percentage. The ANOVA approach was used to examine the impact of each parameter. According to the findings, the weight on the pin has the greatest influence on wear, followed by sliding speed and reinforcing percentage. The addition of B4C particles improves the wear resistance, and the Gr functions as a self-lubricating agent while in use. Scanning electron microscope analysis of worn-out samples revealed an abrasive type of wear process.

Keywords: dry sliding wear; metal matrix composite; boron carbide particles; graphene particles; Taguchi method

1 Introduction

Metal matrix composites (MMCs) are the new grade of composite materials reinforced with advanced hard ceramic particles. Generally, the properties of this class of composites were enhanced by different types of reinforcement particles. The properties like good strength, good wear resistance, high thermal strength, and good corrosion resistance can be enhanced by using different combinations of reinforcements [1]. MMCs reinforced with ceramic particles have high demand in automotive industries, space applications, defense field, electronic parts manufacturing, and so on [2]. The selection of matrix and reinforcement materials is purely based on the area of application and the property of the developed composite that depends on the method of manufacturing. In General, aluminum is highly used matrix material due to its lightweight and less cost. The different classes of aluminum are used for some specific applications. Apart from this, some special type of alloys like magnesium (Mg), copper (Cu), and titanium (Ti) are used for some specific property requirements. The hard reinforcement particles show acceptable remarks on the property enhancement in composites. Silicon carbide (SiC) and boron carbide (B4C) are commonly used hard ceramic particles because of low density and good wettability. TiC, TiO2, and Al2O3 are some of the particles which are used in specific requirements. The alloy Al–Cu combination matrix possess high strength during normal working conditions over other classes of Al alloys and thus gain the focus to perform as an excellent matrix material for the composites [3]. The uniform dispersion of the particles can be achieved in Al–Cu series alloys and they form a barrier to the movement of the dislocation in the overheat treatment. Therefore, Al–Cu alloy was preferred as a matrix material in this work and stir casting was the selected process. The reinforcement particles also increase the bonding strength thereby supporting in carrying the applied load so that they can help in preventing the quick failure. B4C is one of the hard ceramic particles with less density and high stiffness and good hardness property. Hence, Al–B4C composites possess improved hardness and good stiffness [4]. However, the high brittleness of the B4C particles leads to the inherent drawback in its use as a reinforcement in some applications. However, to overcome this drawback and to enhance the mechanical properties of the ceramics, filler materials can be used. Carbon nanotubes and graphene (Gr) powders are used as a protective material in composites. Gr is a lightweight material having 2.2 g/cc of density. Gr is having similar structure as carbon atoms, but it is flat or cylindrical in shape. Gr exhibits good mechanical and thermal properties due to its unique structure.

Many research works were carried out on Al-reinforced ceramics to understand the mechanical and wear resistance properties. Composites can be developed using different processing techniques by changing the percentage of reinforcements. Manivannan et al. [5] studied the Al6061–SiC–Gr hybrid nano composites. Addition of nano scale SiC and Gr particles improves the surface roughness and showed good wear resistance properties by addition of self-lubricating filler. Harichandran et al. [6] worked on the mechanical properties of the Al-reinforced with nano and micro B4C particles using ultrasonic cavitation method. Nano particles show better results than micro particles. Also, the wear resistance increased with the increase in particle percentage up to 8%. Qiu et al. [7] studied the SiC nano particles reinforced with Al–Cu particles using semisolid stirring and ball milling method. The particles distribution was analyzed using X-ray powder diffraction (XRD) and Scanning electron microscope (SEM). The nano particles were strongly reinforced. The mechanical properties of the composites are improved by adding nano SiC particles. The major improvement in tensile strength of the composite was due to the incorporation of SiC particles and good interfacial bonding between SiC and Al–Cu alloy. Pan et al. [8] prepared a high- performance copper-based composite using powder metallurgy by different techniques such as acid-mix treatment, molecular method, ball milling, and plasma sintering, and investigated their mechanical properties, microstructure, electrical conductivity, etc. It was concluded that adding aluminum oxide nanoparticles (NPs) to it worked as an effective mixing agent to distribute CNT in Cu powder and enhance adhesion between them improving the tensile strength, hardness, yield strength, elongation, etc. Similarly, Koga et al. [9] gave a different perspective for the application of quasi-crystalline composites forming a microstructure enclosing the quasi-crystalline, Al7Cu2Fe and Al phase by casting an alloy that was arc-melted, annealed, and characterized by XRD, SEM, TEM, etc. In a recent research, Kim et al. [10] fabricated the Al–Cu composites using spark plasma sintering and studied the effects of adding copper varying the weight percentage on physical and thermal properties. The findings reveal that the addition of copper improves the performance of the composites. Another research by Güler and Bağcı [11] included the investigation of effects of aluminum oxide addition and silver coating on the physical properties of copper matrix-based composites fabricated by electroless plating and hot pressing. Kumar et al. [12] adopted powder metallurgy for fabricating the composites and characterized the effects of normalizing and quenching medium i.e., water and oil on wear and friction of self- lubricating Al–Cu matrix composites. The powder metallurgy method makes sure that there is proper distribution of the reinforcement particles and proper bonding between the matrix and reinforcements. Mei et al. [13] investigated the mechanical properties of copper ions added to graphene oxide–Al powder to improve its distribution on aluminum by a simple electrostatic adsorption method. The addition of copper ions can improve the performance of the composite. Bhoi et al. [14] used copper–tin alloy reinforced by SiC particles and aluminum oxide as an abrasive material by varying its percentage of graphite powder as a friction modifier. The developed new brake material was tested using pin on disc machine to check its wear and friction. Results indicate that there is an improvement in wear resistance by the addition of SiC particles and aluminum oxide rubs over the disc material and minimizes the material removal rate. Castañeda-Vía et al. [15] developed an aluminum–iron–copper based composite and investigated their mechanical properties. XRD and SEM analysis were done using Fourier transform Raman spectroscopy. These experimental results indicate the addition of Gr to improve the wear resistance and help in lubrication. It is understood that the increase in the weight percentage of mono B4C particles by adding small amount of Gr powder can drastically improve the tribological properties of the developed composites. Also, the effect of particles size of the B4C can drastically improve the performance of the composites and the larger particle size reduces the problem of agglomeration and results in more homogeneous particle distribution. A recent work by Weng et al. [16] includes synthetization of copper NPs and their attachment to the surface of Al powder particles with the help of a polydopamine (PDA) coating which showed improved sintering behavior. The varying sintering temperature can affect the performance of the composites. The less sintering temperature can reduce the bonding between matrix and reinforcement and high sintering temperature can lead to the reduced solidification and thereby reduces the strength of the composites.

Based on the research studies, how the MMCs show their significant performance by enhancing the properties in different applications, current work focuses on development and experimentation of Al–Cu matrix reinforced with B4C and Gr particles with varying percentage of reinforcement using powder compaction method.

2 Materials and method

In the present research work, Al–Cu powders are used as a matrix material. Al with 6wt% copper weight percentage was maintained in the matrix mixture. B4C particles with varying percentage of reinforcement was used as a reinforcement material and Gr particle is used as binder material [17]. The composites are fabricated using solid state fabrication method. The powder compaction method is one of the techniques which is used to fabricate the composites. As compared with other fabrication methods, the powder compaction method has significant effect in gaining the fine grain structures and maintains the chemically homogeneousness of the powders. The properties of the powder compacted composites enhance owing to the proper distribution of the nano B4C particles with Al–Cu alloy powders [1]. The powder compaction method has significant effect in gaining the fine grain structures and maintains the chemical homogeneity of powders. The properties of the powder compacted composites enhance owing to the proper distribution of the nano B4C particles in the Al–Cu alloy powders [1]. The die which is used to compact the powder has a cylinder and top and bottom plungers. Hydraulic pressing machine of capacity 5 ton is used to compact the powder particles. The weighed amount of Al–Cu powder and B4C particles are mixed well using a planetary ball mill and poured into the die. To avoid material contamination on the inner wall of the cylinder, zinc stearate solution is applied on the walls of plunger and cylinder [18]. Figure 1 shows the powder compaction method. The PVA is added to the mixtures to enable proper bonding between the Al–Cu and B4C.

Figure 1 Powder compaction method.
Figure 1

Powder compaction method.

The percentage of reinforcement was maintained at 2, 4, and 6 wt% for B4C particles and a constant 3 wt% of Gr was maintained for all the samples. Table 1 shows the % reinforcement B4C and Gr used to develop the composite. After compaction of the samples, sintering was carried out under controlled environment to avoid further oxidation of the samples [19]. A vacuum chamber temperature was gradually increased up to 500°C for time duration of 90  min. The phases present in the powder particles were found using the XRD and the element confirmation was done by using EDS analysis. The average particle size was analyzed using SEM analysis.

Table 1

Labeling of composite samples

Sample label B 4 C (wt%) Gr (wt%)
A23 2 3
A43 4 3
A63 6 3

Figure 2a–d shows the EDS analysis of the matrix and reinforcement powders. From Figure 2a, the spectra of Al were detected and there were no other elements present in the powder so that there were no other impurities present in the powder. Similar results can be seen in spectra of Cu.

Figure 2 (a) EDS analysis of the Al powder and its SEM image. (b) EDS analysis of the Cu powder and its weight percentage. (c) EDS analysis of B4C particles and its weight percentage. (d) EDS analysis of Gr powder and its phases.
Figure 2

(a) EDS analysis of the Al powder and its SEM image. (b) EDS analysis of the Cu powder and its weight percentage. (c) EDS analysis of B4C particles and its weight percentage. (d) EDS analysis of Gr powder and its phases.

Figure 2b depicts the EDS analysis and its elemental mapping of Cu can be seen. Figure 2c shows the elemental mapping for B4C particles and it was observed that the boron and carbide phases were present in the powder. No other elements were observed in the powder. Figure 2d shows the elemental mapping for Gr powder. It was observed that 99 % of carbon element was present in the Gr and less than <1% of associated elements can be observed in the powder.

Figure 3a and b depicts the SEM images of the Al powder with different magnifications. It was observed from the SEM result that the uniform particle size was maintained throughout the volume. Figure 4a and b shows the SEM images of Cu powder with different magnifications. Figure 5a and b shows the SEM images of B4C particles with different magnifications. Figure 6a and b shows the SEM images of Gr particles with different magnifications.

Figure 3 (a) and (b) SEM images of Al particles with different magnifications.
Figure 3

(a) and (b) SEM images of Al particles with different magnifications.

Figure 4 (a) and (b) SEM images of Cu powder at different magnifications.
Figure 4

(a) and (b) SEM images of Cu powder at different magnifications.

Figure 5 (a) and (b) SEM images of B4C particles at different magnifications.
Figure 5

(a) and (b) SEM images of B4C particles at different magnifications.

Figure 6 (a) and (b) SEM images of Gr powder at different magnifications.
Figure 6

(a) and (b) SEM images of Gr powder at different magnifications.

The XRD was recorded for all the compositions room temperature. Strong and intense peaks corresponding to Al, Cu, and Gr were identified from the diffractogram, as shown in Figure 7. It was seen that the peaks resembled that of Al and Cu which formed the base matrix. The trace of B4C was less than the detectable limit. The CIF files obtained from the materials studio for Al and Cu matched perfectly with the data obtained. Both Al and Cu was present in the cubic closed packing structure with a space group of “Fm3m". The average crystal size for all the compositions was calculated using the Debye Scherrer equation.

D = 0.9 λ β cos θ ,

where, D, 0.9, λ, β, and θ are the crystallite size, size constant, wavelength, full width half maximum (FWHM), and the angle of diffraction, respectively. The average crystal size was calculated using all reflections across the 2θ range of 20–85°.

It was seen that there was a shift in the peaks corresponding to Al and Cu, which confirms the variation in lattice cell parameters. Such a change is a signature of distortion of the lattice cell parameters due to the incorporation of guest element into its structure. However, it was interesting to notice that, at high % of Gr, the intensity corresponding to Al and Cu reflections fell to almost half which is an indication of loss of crystallinity due to lattice cell distortion. Figure 8a and b shows the SEM images of the developed samples took under different magnifications. The SEM images confirm the presence of B4C particles in the composites.

Figure 7 XRD data of pristine and composite materials recorded at room temperature.
Figure 7

XRD data of pristine and composite materials recorded at room temperature.

Figure 8 (a) and (b) SEM images of A43 and A63 samples under different magnifications.
Figure 8

(a) and (b) SEM images of A43 and A63 samples under different magnifications.

3 Experimental method

3.1 Hardness test

Hardness of the developed samples were assessed by using Vickers micro hardness test. The test specimens were polished using polishing machine with different grade sand papers and finally the mirror finished surface was obtained by polishing using diamond abrasive [20]. Hardness test was performed under ASTM E 384-10 standards [21]. Totally five indentations were made on the surface of the sample to avoid the impression of indention on the reinforcement particle. All the samples were tested with an average load of 300 g with a time duration of 10 s [22]. The average of the all the five readings were reported.

3.2 Dry sliding wear

Dry sliding wear tests were performed using pin-on-disc tribometer as per ASTM G99 standard [23]. All the samples were tested under room temperature and no lubricants were used during testing. The three different test parameters were chosen to identify the optimum wear rate among the developed composites. Table 2 shows the chosen test factors and levels.

Table 2

Wear test parameters and levels

Applied load (N) Disc speed (rpm) B 4 C (wt%) Gr (wt%)
15 200 2 3
20 300 4 3
25 400 6 3

The wear test was done by holding the pin stationary over the rotating disc. The steel disc En-35 with a surface roughness of less than 0.5 μm was used [24]. The rotating diameter of 100 mm was kept for all the experiments. The wear rate was calculated by taking the initial and final weight of the pin before and after the test. The wear rate was measured by means of weight loss per minute. All the tests were conducted for 10 min of time, so that the final wear rate value was measured in terms of g/min.

3.3 Taguchi optimization technique

Taguchi approach was incorporated to understand the effect of parameters and to identify the optimum wear value [25]. From the selected parameters and their levels in Table 2, A3 level 3 factor was designed using Minitab 16 software. L27 design was chosen to perform the experiments with the obtained orthogonal array. A total of 27 experiments were carried out with interactions between each parameter. The level of significance was identified by the signal to noise (S/N) ratio obtained from the results. The “smaller is the better” characteristic was chosen to detect the rank of the factor [26]. Table 4 depicts the L27 orthogonal array, and the wear rate values obtained.

4 Results and discussion

4.1 Microhardness

The results of microhardness test conducted on A23, A43, and A63 samples are shown in Table 3. The results reveled that the addition of hard B4C particles increases the hardness of the composites. It was observed that the hardness values significantly improved with the addition of B4C particles and the addition of Gr also showed some influence on the hardness value. Pure Al–Cu alloy sample was developed without adding B4C and Gr. The results were compared long with reinforced samples.

Table 3

Microhardness results of with and without adding B4C and Gr particles

Sample label B 4 C (wt%) Gr (wt%) Vickers Microhardness
A00 — — 49
A23 2 3 63
A43 4 3 78
A63 6 3 90

4.2 Wear rate analysis

Wear rate analysis was carried out by conducting the experiments as per Taguchi design of experiments and the results are shown in Table 4.

Table 4

Taguchi L27 with wear and response data

S. No. Load (N) Speed (rpm) B4C (wt%) Wear (g/min × 10–3) S/N ratio
1 15 200 2 0.2674 11.456
2 15 200 4 0.2526 11.951
3 15 200 6 0.2189 13.195
4 15 300 2 0.2737 11.254
5 15 300 4 0.2674 11.456
6 15 300 6 0.2256 12.933
7 15 400 2 0.2918 10.698
8 15 400 4 0.2746 11.225
9 15 400 6 0.2623 11.624
10 20 200 2 0.3274 9.698
11 20 200 4 0.2837 10.942
12 20 200 6 0.2692 11.398
13 20 300 2 0.3592 8.893
14 20 300 4 0.3325 9.564
15 20 300 6 0.3083 10.220
16 20 400 2 0.3673 8.699
17 20 400 4 0.3416 9.329
18 20 400 6 0.3179 9.954
19 25 200 2 0.4385 7.160
20 25 200 4 0.4263 7.405
21 25 200 6 0.3896 8.187
22 25 300 2 0.4659 6.634
23 25 300 4 0.4025 7.904
24 25 300 6 0.3936 8.098
25 25 400 2 0.5262 5.576
26 25 400 4 0.5037 5.956
27 25 400 6 0.4772 6.425

The wear results show that the maximum wear rate was found under high applied load condition. When the load applied on the pin increases, the amount of metal removal rate increases. From the wear table, it was observed that the minimum wear rate was obtained at high load condition. The disc speed also shows some influence on wear rate, as the speed increases, the wear rate increases. But the B4C reinforcement shows better resistance on wear rate. When B4C percentage increases, the wear rate decreases. The maximum wear rate occurred for the specimen of 2wt% B4C particles and disc speed of 400 rpm when the specimen load was 25 N. Similarly, the minimum wear rate was obtained at 6wt% B4C, 200 rpm disc speed with 15 N of applied load.

4.3 S/N response and ANOVA

The response of individual parameter on the wear rate of the developed samples can be evaluated using S/N response table by means of rank. Table 5 shows the S/N ratio response of each parameter. The most inducing parameter on the wear rate was the applied load and that has been ranked as 1, followed by disc speed having nominal influence on wear rate that has been ranked as 2. Even the B4C reinforcement percentage a shows some nominal influence on the wear rate and that has been ranked as 3. The main effect plot of means of applied load, disc speed, and weight percentage of B4C are was shown in Figure 9. The smaller is the better model was chosen for the analysis. It was observed that the applied load of 15 N shows the minimum response on wear rate, similarly 200 rpm of disc speed and 6wt% of B4C shows the minimum response on wear rate of the composites.

Table 5

S/N response table

Level Applied load (N) Disc speed (rpm) B 4 C (wt%)
1 0.2594 0.3193 0.3686
2 0.323 0.3365 0.3428
3 0.4471 0.3736 0.3181
Delta 0.1877 0.0543 0.0505
Rank 1 2 3
Figure 9 Main effect plot of means of applied load, disc speed, and B4C wt%.
Figure 9

Main effect plot of means of applied load, disc speed, and B4C wt%.

Table 6 reveals the ANOVA results obtained from the available wear rate data. The influence of each parameter on the wear rate was analyzed using ANOVA data.

Table 6

Wear rate analysis using ANOVA

Factors DF Seq SS Adj SS Adj MS F P P (%)
Load in N 2 0.164 0.164 0.082 238.56 0 83.57
Speed in rpm 2 0.014 0.014 0.00694 20.19 0 7.072
B4C wt% 2 0.011 0.011 0.00575 16.72 0 5.857
Error 20 0.007 0.007 0.00034 3.503
Total 26 0.196

S = 0.0185398, R-Sq = 96.50%, R-Sq(adj) = 95.45%.

The applied load on the pin shows 83.57% influence on the wear rate, and load was the most influencing parameter which causes the increase in wear rate, followed by disc speed, which shows some influence of 7.07% on wear rate. The B4C reinforcement shows some negligible impact on the wear rate. The interaction between the parameters shows to be insignificant on the wear values so their effect on the wear rate was not considered. The analysis was carried out with the confidence level of 95% and level of significance of 0.05. The R 2 calculated was 96.50% and was well fitted with in the adjusted limit. Similar observations were made in our previous work [20], where applied load shows significant influence on the wear rate.

4.4 Regression model

Linear regression model was developed from the wear data using Minitab 16 software and it was presented by Eq. (1).

(1) Wear rate = − 0.0632 + 0.0188 ( L ) + 0.000272 ( S ) − 0.0126 ( R ) ,

where, L is the load on the pin in N, S is the disc speed in rpm, R is the % of reinforcement.

The confirmation test was carried out using different sets of parameters to match the expected values of the wear and the significance of the developed regression model. Table 7 shows the results of regression model wear value for the same set of parameters and experimental wear value. The error obtained between the predicted wear value using regression model and experimental wear value was within the acceptable limit of 0.05.

Table 7

Confirmation experiment results

Response Selected parameters Regression model value (g/min) Confirmation experiment value (g/min) Difference in value
Wear rate 15 N, 200 rpm, 6wt% 0.1772 0.2189 0.04

4.5 Evaluation of wear mechanism

Figure 10 indicates the SEM images of the worn surfaces for different samples. The wear mechanism of the worn surfaces was influenced by different factors. The experimental results showed that the applied load had major contribution on wear. When the load increases, the material removal rate increases and the friction between the pin and the steel disc surface increases.

Figure 10 SEM images of the wear samples: (a) 25 N load, 300 rpm speed, and 4 wt% of B4C and (b) 15 N load, 200 rpm speed, and 2 wt% B4C.
Figure 10

SEM images of the wear samples: (a) 25 N load, 300 rpm speed, and 4 wt% of B4C and (b) 15 N load, 200 rpm speed, and 2 wt% B4C.

The effect of disc speed reveals a sensible increase in the wear loss. It indicates that during low load, increase in disc speed shows an increase in loss due to higher interface temperature and molecular smoothening due to heat. The metal wear rate was severe in high load condition, mean after the metal removed from the surface of the pin and the oxide surface was developed when the gap created during metal removal. During that condition, the filler plays an important role in friction behavior of the composite. At low load condition, the oxide layer forms a low coefficient of friction (COF) and makes less the shear strength and less ductility. At high load, high COF leads to protective oxide layer that reduces the chances of further metal removal. Basavarajappa et al. [27] revealed that the Gr particles act as a self-lubricating and strain at the interface and reduce the COF. The hard Cu particles present in the composite decreases the high friction force between the pin and disc material. During high load condition, the shear load was carried by this hard Cu particles and reduces further the metal removal rate and reduces the high frictional heat during sliding.

Due to dry sliding between the pin and disc, higher shear forces will generate and cause the soft metal to abrade. That develops the small debris to wear out from the sample and settle on the wear tracks. During low load condition, grooves will be developed on the surface of the pin. The small debris will be formed, and they get trapped between the pin and the disc and form a protective layer. Addition of Gr in the composite acts as a self-lubricating agent and minimizes further the wear rate of the samples. The abrasive wear type of mechanism can be seen in the present investigation.

5 Conclusion

Based on the results obtained, the final conclusions are listed below.

Powder compaction method is one of the effective methods of fabrication of Al-based composites. The hard reinforcement particles can be easily incorporated into the alloy powders using powder compaction method. Results clearly shows that the wear performance of the composites are mainly based on different parameters like applied load and sliding speed. But the reinforcement percentage also shows some influence on the wear performance of the composites. The wear performance of the composites can be improved by incorporating different reinforcement particles and by changing the percentage of reinforcement. From the obtained results, it has been observed that the Gr NPs act as a self-lubrication agent by minimizing the wear. The following final conclusions were made from the current research study.

  1. The Al–Cu alloys were successfully reinforced with B4C hard particles and Gr using powder compaction method.

  2. Powder particles were uniformly distributed in Al–Cu alloy powder, which ensures that powder metallurgy is one of the successful fabrication methods to manufacture the composites.

  3. The wear analysis results indicate that applied load shows major influence on wear rate as compared to the other two parameters.

  4. Applied load has 83.57% impact on the wear rate followed by disc speed of 7.07% and B4C wt% of 5.85%.

  1. Funding information: The authors state no funding involved.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Conflict of interest: The authors reported no potential conflict of interest.

  4. Data availability statement: The data that are used in findings of this study are available on request basis from the corresponding author. However, the data are available due to privacy/ethical restrictions.

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Received: 2022-06-10
Revised: 2022-11-28
Accepted: 2022-11-29
Published Online: 2023-03-18

© 2023 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  2. The mechanical properties of lightweight (volcanic pumice) concrete containing fibers with exposure to high temperatures
  3. Experimental investigation on the influence of partially stabilised nano-ZrO2 on the properties of prepared clay-based refractory mortar
  4. Investigation of cycloaliphatic amine-cured bisphenol-A epoxy resin under quenching treatment and the effect on its carbon fiber composite lamination strength
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  7. Effect of calcined diatomaceous earth, polypropylene fiber, and glass fiber on the mechanical properties of ultra-high-performance fiber-reinforced concrete
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  9. Performance analysis of subgrade in asphaltic rail track design and Indonesia’s existing ballasted track
  10. Utilization of hybrid fibers in different types of concrete and their activity
  11. Validated three-dimensional finite element modeling for static behavior of RC tapered columns
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  14. Microstructural characteristics and mechanical properties of rotary friction-welded dissimilar AISI 431 steel/AISI 1018 steel joints
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  16. Connective and magnetic effects in a curved wavy channel with nanoparticles under different waveforms
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  64. Dynamic response of a two-story steel structure subjected to earthquake excitation by using deterministic and nondeterministic approaches
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https://doi.org/10.1515/jmbm-2022-0274
Keywords for this article
dry sliding wear; metal matrix composite; boron carbide particles; graphene particles; Taguchi method
Creative Commons
BY 4.0

Articles in the same Issue

  1. Research Articles
  2. The mechanical properties of lightweight (volcanic pumice) concrete containing fibers with exposure to high temperatures
  3. Experimental investigation on the influence of partially stabilised nano-ZrO2 on the properties of prepared clay-based refractory mortar
  4. Investigation of cycloaliphatic amine-cured bisphenol-A epoxy resin under quenching treatment and the effect on its carbon fiber composite lamination strength
  5. Influence on compressive and tensile strength properties of fiber-reinforced concrete using polypropylene, jute, and coir fiber
  6. Estimation of uniaxial compressive and indirect tensile strengths of intact rock from Schmidt hammer rebound number
  7. Effect of calcined diatomaceous earth, polypropylene fiber, and glass fiber on the mechanical properties of ultra-high-performance fiber-reinforced concrete
  8. Analysis of the tensile and bending strengths of the joints of “Gigantochloa apus” bamboo composite laminated boards with epoxy resin matrix
  9. Performance analysis of subgrade in asphaltic rail track design and Indonesia’s existing ballasted track
  10. Utilization of hybrid fibers in different types of concrete and their activity
  11. Validated three-dimensional finite element modeling for static behavior of RC tapered columns
  12. Mechanical properties and durability of ultra-high-performance concrete with calcined diatomaceous earth as cement replacement
  13. Characterization of rutting resistance of warm-modified asphalt mixtures tested in a dynamic shear rheometer
  14. Microstructural characteristics and mechanical properties of rotary friction-welded dissimilar AISI 431 steel/AISI 1018 steel joints
  15. Wear performance analysis of B4C and graphene particles reinforced Al–Cu alloy based composites using Taguchi method
  16. Connective and magnetic effects in a curved wavy channel with nanoparticles under different waveforms
  17. Development of AHP-embedded Deng’s hybrid MCDM model in micro-EDM using carbon-coated electrode
  18. Characterization of wear and fatigue behavior of aluminum piston alloy using alumina nanoparticles
  19. Evaluation of mechanical properties of fiber-reinforced syntactic foam thermoset composites: A robust artificial intelligence modeling approach for improved accuracy with little datasets
  20. Assessment of the beam configuration effects on designed beam–column connection structures using FE methodology based on experimental benchmarking
  21. Influence of graphene coating in electrical discharge machining with an aluminum electrode
  22. A novel fiberglass-reinforced polyurethane elastomer as the core sandwich material of the ship–plate system
  23. Seismic monitoring of strength in stabilized foundations by P-wave reflection and downhole geophysical logging for drill borehole core
  24. Blood flow analysis in narrow channel with activation energy and nonlinear thermal radiation
  25. Investigation of machining characterization of solar material on WEDM process through response surface methodology
  26. High-temperature oxidation and hot corrosion behavior of the Inconel 738LC coating with and without Al2O3-CNTs
  27. Influence of flexoelectric effect on the bending rigidity of a Timoshenko graphene-reinforced nanorod
  28. An analysis of longitudinal residual stresses in EN AW-5083 alloy strips as a function of cold-rolling process parameters
  29. Assessment of the OTEC cold water pipe design under bending loading: A benchmarking and parametric study using finite element approach
  30. A theoretical study of mechanical source in a hygrothermoelastic medium with an overlying non-viscous fluid
  31. An atomistic study on the strain rate and temperature dependences of the plastic deformation Cu–Au core–shell nanowires: On the role of dislocations
  32. Effect of lightweight expanded clay aggregate as partial replacement of coarse aggregate on the mechanical properties of fire-exposed concrete
  33. Utilization of nanoparticles and waste materials in cement mortars
  34. Investigation of the ability of steel plate shear walls against designed cyclic loadings: Benchmarking and parametric study
  35. Effect of truck and train loading on permanent deformation and fatigue cracking behavior of asphalt concrete in flexible pavement highway and asphaltic overlayment track
  36. The impact of zirconia nanoparticles on the mechanical characteristics of 7075 aluminum alloy
  37. Investigation of the performance of integrated intelligent models to predict the roughness of Ti6Al4V end-milled surface with uncoated cutting tool
  38. Low-temperature relaxation of various samarium phosphate glasses
  39. Disposal of demolished waste as partial fine aggregate replacement in roller-compacted concrete
  40. Review Articles
  41. Assessment of eggshell-based material as a green-composite filler: Project milestones and future potential as an engineering material
  42. Effect of post-processing treatments on mechanical performance of cold spray coating – an overview
  43. Internal curing of ultra-high-performance concrete: A comprehensive overview
  44. Special Issue: Sustainability and Development in Civil Engineering - Part II
  45. Behavior of circular skirted footing on gypseous soil subjected to water infiltration
  46. Numerical analysis of slopes treated by nano-materials
  47. Soil–water characteristic curve of unsaturated collapsible soils
  48. A new sand raining technique to reconstitute large sand specimens
  49. Groundwater flow modeling and hydraulic assessment of Al-Ruhbah region, Iraq
  50. Proposing an inflatable rubber dam on the Tidal Shatt Al-Arab River, Southern Iraq
  51. Sustainable high-strength lightweight concrete with pumice stone and sugar molasses
  52. Transient response and performance of prestressed concrete deep T-beams with large web openings under impact loading
  53. Shear transfer strength estimation of concrete elements using generalized artificial neural network models
  54. Simulation and assessment of water supply network for specified districts at Najaf Governorate
  55. Comparison between cement and chemically improved sandy soil by column models using low-pressure injection laboratory setup
  56. Alteration of physicochemical properties of tap water passing through different intensities of magnetic field
  57. Numerical analysis of reinforced concrete beams subjected to impact loads
  58. The peristaltic flow for Carreau fluid through an elastic channel
  59. Efficiency of CFRP torsional strengthening technique for L-shaped spandrel reinforced concrete beams
  60. Numerical modeling of connected piled raft foundation under seismic loading in layered soils
  61. Predicting the performance of retaining structure under seismic loads by PLAXIS software
  62. Effect of surcharge load location on the behavior of cantilever retaining wall
  63. Shear strength behavior of organic soils treated with fly ash and fly ash-based geopolymer
  64. Dynamic response of a two-story steel structure subjected to earthquake excitation by using deterministic and nondeterministic approaches
  65. Nonlinear-finite-element analysis of reactive powder concrete columns subjected to eccentric compressive load
  66. An experimental study of the effect of lateral static load on cyclic response of pile group in sandy soil
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