Characterization, wear surface roughness and tensile failure analysis of Al7075-TiC-MoS<sub>2</sub> hybrid composites using online acoustic emission

Ramanan, G.; Suresh, S.; Prabha, N. Rajesh; Dhas, J. Edwin Raja

doi:10.1088/2053-1591/ab0d7a

Cited by 19 publications

(3 citation statements)

References 32 publications

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“…Table 1 shows the amplitude variation for the hits distribution at each interval. The breakage between the particle and the matrix and the particle breakages may also occur as the stress points on the area of reinforcing SiCp but an excellent source of AE signal was obtain on both the methods [18]. Nowadays rise angle data's are procured as the ration of rise time to amplitude to find the new part of wave form measured in ms/v [19].…”

Section: Resultsmentioning

confidence: 99%

Analysis of failure mode and fracture behavior by using acoustic emission parameter and artificial neural network

Christopher

Sasikumar²,

Suresh³

2019

Eng. Res. Express

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Acoustic emission (AE) provide snumerous statistics regarding the fracture attitude of distinct materials. In this research AE investigation was handled on 14 numbers of tensile specimens built of aluminum 6061 strengthened by silicon carbide particles at which 100 KN. Universal testing machine is used for tensile testing. The AE parameters are refined from the specimens and only 60% of actual tensile strength parameters are considered for further analysis. Parameters like count, energy, duration, rise time and amplitude are used to characterize the fractures occurred on metal matrix composites due to the low matrix cavitations, particle cracking, interfacial debonding and the transition of mode from tensile to shear. The two individual artificial neural networks generated with the parameters rise angle and by theshear mode of rise angle. The ultimate strength is considered as the anticipated output by training it properly. The structure has the capable to predict the absolute fault up to 2.74% and 1.31%. The shear mode values which occurred at few cycles before the failure of the specimen as inputs are found to be better than the rise angle(RA) data entered, however the prediction exercise proved by the two trained artificial neural network(ANN) has proved its significances.

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Section: Resultsmentioning

confidence: 99%

Analysis of failure mode and fracture behavior by using acoustic emission parameter and artificial neural network

Christopher

Sasikumar²,

Suresh³

2019

Eng. Res. Express

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“…The wire of crossing is invariably sustained from wire feed spool and collected on take up spool moving. But, the work piece is upheld with the pressure among two wire aides placed at work piece's inverse side [12]. Table 1 Shows the input process parameters with their levels.…”

Section: Methodsmentioning

confidence: 99%

Optimization of Wire Electrical Discharge Machining Parameters of Activated Carbon Reinforced Aluminium Composite

Ramanan¹,

Reddy²,

Manishankar³

2020

MSF

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The quality of machining through process parameters on the responses in wire electrical discharge machining (WEDM) is studied. This paper discusses the optimization of parameters of a process in WEDM machining with the application of the desirability approach on the basis of response surface methodology (RSM). Pulse on time, servo speed rate, discharge current, and pulse off time have been considered as influential factors. The established experimental data of AA7075 aluminium reinforced with 9% of activated carbon composite to analyze the process parameter effects on responses, like material removal rate (MRR) and surface roughness (SR). After machining multiple regression analysis is used to find the interaction among the process parameters is obtained. The optimal parameters were found using the desirability optimization methodologies as 10.43mm3/min and 3.32μm respectively. The performance of the optimization test confirmed that the proposed method in this study effectively improves the performance of the WEDM process.

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“…The Al7075/titanium carbide/ molybdenum disulfide hybrid composite was prepared and determined, properties like strength, and toughness. Results revealed that resistance of wear was improved because of hard titanium carbide and soft molybdenum disulfide particle dispersion [27]. The mechanical as well as wear properties of AA7075/silicon nitride composites were also studied with the addition of molybdenum disulfide and revealed decreased mechanical strength of composites however, tribological properties were improved [18].…”

Section: Introductionmentioning

confidence: 99%

Synthesis and wear characterization of Al7075/molybdenum disulfide/zirconium diboride hybrid composites

Dubey,

Kumar,

Mohan

2024

Materialwissenschaft Werkst

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The manuscript presents the synthesis and dry sliding wear performance of Al7075 alloy‐based composites. Five compositions namely Al7075 alloy, Al7075+3 vol % molybdenum disulfide, Al7075+3 vol % molybdenum disulfide+3 vol % zirconium diboride, Al7075+3 vol % molybdenum disulfide+6 vol % zirconium diboride and Al7075+3 vol % molybdenum disulfide+9 vol % zirconium diboride were stir cast and characterized for hardness, x‐ray diffraction, microstructure, and tribological properties. In‐situ formed zirconium diboride particles increase the hardness of Al7075 alloy whereas molybdenum disulfide shows the opposite trend due to its self‐lubricating nature. X‐ray diffraction analysis identifies subsequent phase particles in the matrix while microstructural images exhibit the dispersion and morphology of reinforcement particles. The wear tests and friction coefficient were analyzed with variations of sliding velocity, normal load, sliding distance, and compositions. Further, the obtained wear results were also correlated with microstructure and wear surface topography. Al7075+3 vol % molybdenum disulfide composite shows the lowest coefficient of friction because of its self‐lubricating nature. Al7075+3 vol % molybdenum disulfide+9 vol % zirconium diboride hybrid composite exhibits the lowest wear rate at high velocity as well as at high load and can be potentially used in manufacturing and tribological applications. Moreover, the use of this material may lead to the minimum requirement of external toxic lubricants that make it cost‐effective and environmentally sustainable.

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Characterization, wear surface roughness and tensile failure analysis of Al7075-TiC-MoS₂ hybrid composites using online acoustic emission

Cited by 19 publications

References 32 publications

Analysis of failure mode and fracture behavior by using acoustic emission parameter and artificial neural network

Analysis of failure mode and fracture behavior by using acoustic emission parameter and artificial neural network

Optimization of Wire Electrical Discharge Machining Parameters of Activated Carbon Reinforced Aluminium Composite

Synthesis and wear characterization of Al7075/molybdenum disulfide/zirconium diboride hybrid composites

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Characterization, wear surface roughness and tensile failure analysis of Al7075-TiC-MoS2 hybrid composites using online acoustic emission

Cited by 19 publications

References 32 publications

Analysis of failure mode and fracture behavior by using acoustic emission parameter and artificial neural network

Analysis of failure mode and fracture behavior by using acoustic emission parameter and artificial neural network

Optimization of Wire Electrical Discharge Machining Parameters of Activated Carbon Reinforced Aluminium Composite

Synthesis and wear characterization of Al7075/molybdenum disulfide/zirconium diboride hybrid composites

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Characterization, wear surface roughness and tensile failure analysis of Al7075-TiC-MoS₂ hybrid composites using online acoustic emission