Pub Date : 2024-06-07DOI: 10.1177/09544089241256747
Jenarthanan Mp, K. M., Ghousiya Begum K, P. S
The increase in population is also a factor that increases the vehicle strength. The biofuel derived from vegetation was found to be suitable and that can be used as biodiesel after chemical conversion. It can be utilized in an existing diesel engine without much modification that can reduce the usage of diesel. In this research, rice bran oil is used as biodiesel since it is available in plenty in south India. The main aim of this work is to create an uncertainty model and to optimize the parameter which gives improved performance by using Taguchi technique. Three factors, three level performance matrix, were considered in order to carry out the experimental investigation through uncertainty. “Design Expert 12.0” software was used for carrying out the uncertainty and graphical analysis of the data collected. The optimum values were obtained for the selected variables through analyzing the response surface contour plots and by solving the regression equation. The validity of the model was checked by analysis of variance (ANOVA) and for finding the significant parameters. Using such a model, the suitable blend which gives maximum performance was identified. Moreover, machine learning models were deployed to predict the brake specific fuel consumption (BSFC) and volumetric efficiency (VOL.E) of the engine tested based on the input features compression ratio (CR), blend (BLEND) and load (LOAD). Gradient boost repressor (GBR) has been found to be the superior model in predicting the multi-output parameters (BSFC and VOL) that decides the engine performance, with R2 of 0.987.
{"title":"Artificial intelligent-based analysis of VCR engine with biodiesel blends and modelling using uncertainty techniques","authors":"Jenarthanan Mp, K. M., Ghousiya Begum K, P. S","doi":"10.1177/09544089241256747","DOIUrl":"https://doi.org/10.1177/09544089241256747","url":null,"abstract":"The increase in population is also a factor that increases the vehicle strength. The biofuel derived from vegetation was found to be suitable and that can be used as biodiesel after chemical conversion. It can be utilized in an existing diesel engine without much modification that can reduce the usage of diesel. In this research, rice bran oil is used as biodiesel since it is available in plenty in south India. The main aim of this work is to create an uncertainty model and to optimize the parameter which gives improved performance by using Taguchi technique. Three factors, three level performance matrix, were considered in order to carry out the experimental investigation through uncertainty. “Design Expert 12.0” software was used for carrying out the uncertainty and graphical analysis of the data collected. The optimum values were obtained for the selected variables through analyzing the response surface contour plots and by solving the regression equation. The validity of the model was checked by analysis of variance (ANOVA) and for finding the significant parameters. Using such a model, the suitable blend which gives maximum performance was identified. Moreover, machine learning models were deployed to predict the brake specific fuel consumption (BSFC) and volumetric efficiency (VOL.E) of the engine tested based on the input features compression ratio (CR), blend (BLEND) and load (LOAD). Gradient boost repressor (GBR) has been found to be the superior model in predicting the multi-output parameters (BSFC and VOL) that decides the engine performance, with R2 of 0.987.","PeriodicalId":506108,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141373437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1177/09544089241259446
Thenmozhi Dhanraj, Manneri Eswara Rao, K. Vajravelu, P. Lakshminarayana
In this paper, a three-dimensional Darcy-Forchheimer flow model is considered to investigate the flow behavior of conducting paraffin oil with carbon nanotubes. The governing partial differential equations of the model are converted into a system of ordinary differential equations by using a similarity transformation. Then, a conversion numerical method along with a shooting technique is used to obtain the solutions to the governing ordinary differential equations. The study reveals significant effects of the porosity, radiation, thermophoresis and the Brownian motion on the flow and heat transfer characteristics. Also, the influences of the physical parameters on the bi-directional velocity, temperature and fluid concentration are discussed in detail. Since carbon nanotubes have high thermal conductivity, it has a high impact on the temperature profiles. Furthermore, as the paraffin oil has well-defined thermal properties, it can be used as a fluid to augment the heat transfer. The presence of carbon nanotubes in the fluid enhanced the thermal conductivity which in turn increased the temperature of the fluid. The magnetic field reduced the bi-directional velocity of the fluid but increased the temperature due to the stimulating effect of the Lorentz force. Hence, this heat transfer study of paraffin oil with carbon nanotubes has a wide range of industrial applications to steam generation, thermal management, heat-treated material and engine cooling.
{"title":"Analysis of carbon nanotubes-based nanofluid with paraffin oil in 3D MHD Darcy-Forchheimer flow through a bi-directional stretchable surface: Application to heat exchanger systems","authors":"Thenmozhi Dhanraj, Manneri Eswara Rao, K. Vajravelu, P. Lakshminarayana","doi":"10.1177/09544089241259446","DOIUrl":"https://doi.org/10.1177/09544089241259446","url":null,"abstract":"In this paper, a three-dimensional Darcy-Forchheimer flow model is considered to investigate the flow behavior of conducting paraffin oil with carbon nanotubes. The governing partial differential equations of the model are converted into a system of ordinary differential equations by using a similarity transformation. Then, a conversion numerical method along with a shooting technique is used to obtain the solutions to the governing ordinary differential equations. The study reveals significant effects of the porosity, radiation, thermophoresis and the Brownian motion on the flow and heat transfer characteristics. Also, the influences of the physical parameters on the bi-directional velocity, temperature and fluid concentration are discussed in detail. Since carbon nanotubes have high thermal conductivity, it has a high impact on the temperature profiles. Furthermore, as the paraffin oil has well-defined thermal properties, it can be used as a fluid to augment the heat transfer. The presence of carbon nanotubes in the fluid enhanced the thermal conductivity which in turn increased the temperature of the fluid. The magnetic field reduced the bi-directional velocity of the fluid but increased the temperature due to the stimulating effect of the Lorentz force. Hence, this heat transfer study of paraffin oil with carbon nanotubes has a wide range of industrial applications to steam generation, thermal management, heat-treated material and engine cooling.","PeriodicalId":506108,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":"84 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1177/09544089241259335
M. Ramesh, I. Jenish, Tamil Selvan M, A. Felix Sahayaraj
This study aimed to characterize Cryptostegia grandiflora stem fiber (CGSF) as a potential reinforcement material for lightweight polymer composites. Natural fiber-reinforced materials have gained attention as a promising alternative to synthetic fibers due to their comparable strength and modulus, and lack of harmful chemicals. The physical, chemical, and thermal properties of CGSF were investigated through fiber roughness, chemical measurement, physical measurement, Fourier transform infrared spectroscopy, XRD, water absorption, thermogravimetric analysis, and SEM conformation analysis. The results showed that CGSF has a high cellulose content (80.3 wt.%) and specific strength, making it suitable for use in polymer composites. Its flaky layered outer surface provides a high modulus, and its low microfibril angle observed through electron microscopy results in strong bonding qualities. The fiber also demonstrated improved heat stability up to 254–387 °C through thermogravimetric analysis, meeting the requirements for polymerization. These findings demonstrate the potential of CGSF as a natural reinforcement material for lightweight polymer composites.
{"title":"Characterizing Cryptostegia grandiflora stem fiber for reinforcing lightweight polymer composites: A comprehensive study of its physical, chemical, and thermal properties","authors":"M. Ramesh, I. Jenish, Tamil Selvan M, A. Felix Sahayaraj","doi":"10.1177/09544089241259335","DOIUrl":"https://doi.org/10.1177/09544089241259335","url":null,"abstract":"This study aimed to characterize Cryptostegia grandiflora stem fiber (CGSF) as a potential reinforcement material for lightweight polymer composites. Natural fiber-reinforced materials have gained attention as a promising alternative to synthetic fibers due to their comparable strength and modulus, and lack of harmful chemicals. The physical, chemical, and thermal properties of CGSF were investigated through fiber roughness, chemical measurement, physical measurement, Fourier transform infrared spectroscopy, XRD, water absorption, thermogravimetric analysis, and SEM conformation analysis. The results showed that CGSF has a high cellulose content (80.3 wt.%) and specific strength, making it suitable for use in polymer composites. Its flaky layered outer surface provides a high modulus, and its low microfibril angle observed through electron microscopy results in strong bonding qualities. The fiber also demonstrated improved heat stability up to 254–387 °C through thermogravimetric analysis, meeting the requirements for polymerization. These findings demonstrate the potential of CGSF as a natural reinforcement material for lightweight polymer composites.","PeriodicalId":506108,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":"329 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141386330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1177/09544089241258852
Ashutosh Pandey, M. K. Mishra
Entropy measures the disorderness or randomness of the systems. It may affect the effectiveness and performance of the thermal systems. That is why entropy analysis is one of the trending research topic in modern era of society. The motive of this article is to present a comprehensive analysis of entropy generation and thermal dispersion effect on mixed convective flow of (Cu-Al2O3)/(H2O) based hybrid nanofluid along a plate submerged in a non-Darcy porous medium. The mathematical model describing the flow problem encompasses a system of partial differential equation, resulting from the single-phase flow model of the nanofluid combined with the Darcy-Forchheimer expression for porous medium flow. The dimensional system of partial differential equation is transformed into a non-dimensional nonlinear ordinary differential system through a similarity transformations and subsequently, the system is solved using the BVP4C module in MATLAB. The study analyzes the flow variables and entropy generation with respect to the parameters inherent in the problem. The findings suggests that, the increasing thermal dispersion effects enhances the Heat transfer rate of the hybrid nanofluid. Further, it is reported that the entropy generation in hybrid nanofluid is lower than the mono nanofluid which makes the hybrid nanofluid a better choice for entropy management in the thermal systems. The outcome of the research has practical implications in various real-life applications, such as crude oil production, oil flow filtration, electronic cooling equipment, etc.
{"title":"Entropy analysis of a non-Darcian mixed convective flow of Cu-Al2O3-based hybrid nanofluid with thermal dispersioneffect","authors":"Ashutosh Pandey, M. K. Mishra","doi":"10.1177/09544089241258852","DOIUrl":"https://doi.org/10.1177/09544089241258852","url":null,"abstract":"Entropy measures the disorderness or randomness of the systems. It may affect the effectiveness and performance of the thermal systems. That is why entropy analysis is one of the trending research topic in modern era of society. The motive of this article is to present a comprehensive analysis of entropy generation and thermal dispersion effect on mixed convective flow of (Cu-Al2O3)/(H2O) based hybrid nanofluid along a plate submerged in a non-Darcy porous medium. The mathematical model describing the flow problem encompasses a system of partial differential equation, resulting from the single-phase flow model of the nanofluid combined with the Darcy-Forchheimer expression for porous medium flow. The dimensional system of partial differential equation is transformed into a non-dimensional nonlinear ordinary differential system through a similarity transformations and subsequently, the system is solved using the BVP4C module in MATLAB. The study analyzes the flow variables and entropy generation with respect to the parameters inherent in the problem. The findings suggests that, the increasing thermal dispersion effects enhances the Heat transfer rate of the hybrid nanofluid. Further, it is reported that the entropy generation in hybrid nanofluid is lower than the mono nanofluid which makes the hybrid nanofluid a better choice for entropy management in the thermal systems. The outcome of the research has practical implications in various real-life applications, such as crude oil production, oil flow filtration, electronic cooling equipment, etc.","PeriodicalId":506108,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":"11 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141385221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-24DOI: 10.1177/09544089241257229
Sivasakthivel PS, Sudhakaran R
Increasing demand for high-performance materials has led to the exploration of composite materials for enhanced mechanical properties. In this study, a composite of silicon carbide particulate and rice husk ash (RHA) in varying proportions was utilized to reinforce an aluminum alloy (Al7075) hybrid composite fabricated through the stir casting technique. Microstructure examination via an optical microscope ensured the homogeneous distribution of reinforced particles. Wear was evaluated using a pin-on-disc apparatus, considering material factors (% of SiC and % of RHA) and mechanical wear factors (load applied, speed of rotation, and sliding distance). Experimental data were used to develop artificial neural network and adaptive neural fuzzy inference system models, which demonstrated high predictive accuracy. An objective function, formulated to minimize wear via regression analysis, guided the application of a genetic algorithm to determine optimal process parameters. The optimal combination, resulting in a minimum wear of 34.5 µm, comprised 12% SiC, 7% RHA, a sliding speed of 1.9 m/s, an applied load of 11.5 N, and a sliding distance of 715 mm. This study concludes with recommendations for further research and implications for composite material design and optimization.
{"title":"Estimation of optimal process parameters for minimum wear in the application of SiC/RHA reinforced Al7075 hybrid composites using ANN, ANFIS, and GA","authors":"Sivasakthivel PS, Sudhakaran R","doi":"10.1177/09544089241257229","DOIUrl":"https://doi.org/10.1177/09544089241257229","url":null,"abstract":"Increasing demand for high-performance materials has led to the exploration of composite materials for enhanced mechanical properties. In this study, a composite of silicon carbide particulate and rice husk ash (RHA) in varying proportions was utilized to reinforce an aluminum alloy (Al7075) hybrid composite fabricated through the stir casting technique. Microstructure examination via an optical microscope ensured the homogeneous distribution of reinforced particles. Wear was evaluated using a pin-on-disc apparatus, considering material factors (% of SiC and % of RHA) and mechanical wear factors (load applied, speed of rotation, and sliding distance). Experimental data were used to develop artificial neural network and adaptive neural fuzzy inference system models, which demonstrated high predictive accuracy. An objective function, formulated to minimize wear via regression analysis, guided the application of a genetic algorithm to determine optimal process parameters. The optimal combination, resulting in a minimum wear of 34.5 µm, comprised 12% SiC, 7% RHA, a sliding speed of 1.9 m/s, an applied load of 11.5 N, and a sliding distance of 715 mm. This study concludes with recommendations for further research and implications for composite material design and optimization.","PeriodicalId":506108,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":"91 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141101288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-23DOI: 10.1177/09544089241253533
Peyman Maghsoudi, Hassan Lakzayi, Yahya Pourgholy Digeh Sara, Mehdi Bidabadi
In this study, by proposing a comprehensive multi-step model, the combustion of magnesium particles in O2-He, O2-Ar, and O2-N2 is scrutinized. In the current model, both the heterogeneous and homogeneous combustions are considered and the process is divided into four stages solid, liquid, and gas combustion and melting. Moreover, the diffusions of oxygen and unreacted magnesium to droplet and infinity together with surface exothermic reaction are considered. The governing equations are analytically solved and then, the formulas are extracted for combustion time and temperature, flame standoff distance, and evaporation rate as the functions of particle diameter, ambient temperature and pressure, oxygen mass fraction, type of inert gas, and Lewis numbers. For 120 µm particle and oxygen content of 0.05, time contributions of homogeneous and heterogeneous combustions are 85.8% and 14.2%, respectively. The burning time has drastic changes at ambient pressures below l atm, so that the burning time variations relative to the pressure in the environments less than 1 atm and greater than it are equal to 1200–1550 and 70–90 ms/atm, respectively. When the oxygen mass fraction is less than 0.29, combustion in helium-oxygen ends earlier than that in O2-Ar and O2-N2, but for the mass fraction greater than 0.35, it has the longest burning time.
{"title":"Analytical assessment of hetero-/homogeneous combustion of magnesium particle: Fully explicit formulas for flame characteristics","authors":"Peyman Maghsoudi, Hassan Lakzayi, Yahya Pourgholy Digeh Sara, Mehdi Bidabadi","doi":"10.1177/09544089241253533","DOIUrl":"https://doi.org/10.1177/09544089241253533","url":null,"abstract":"In this study, by proposing a comprehensive multi-step model, the combustion of magnesium particles in O2-He, O2-Ar, and O2-N2 is scrutinized. In the current model, both the heterogeneous and homogeneous combustions are considered and the process is divided into four stages solid, liquid, and gas combustion and melting. Moreover, the diffusions of oxygen and unreacted magnesium to droplet and infinity together with surface exothermic reaction are considered. The governing equations are analytically solved and then, the formulas are extracted for combustion time and temperature, flame standoff distance, and evaporation rate as the functions of particle diameter, ambient temperature and pressure, oxygen mass fraction, type of inert gas, and Lewis numbers. For 120 µm particle and oxygen content of 0.05, time contributions of homogeneous and heterogeneous combustions are 85.8% and 14.2%, respectively. The burning time has drastic changes at ambient pressures below l atm, so that the burning time variations relative to the pressure in the environments less than 1 atm and greater than it are equal to 1200–1550 and 70–90 ms/atm, respectively. When the oxygen mass fraction is less than 0.29, combustion in helium-oxygen ends earlier than that in O2-Ar and O2-N2, but for the mass fraction greater than 0.35, it has the longest burning time.","PeriodicalId":506108,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":"29 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141106467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-23DOI: 10.1177/09544089241255927
A. Duggirala, B. Acherjee, Souren Mitra
Multi-physics computational models based on finite element analysis, offer detailed insights into the dynamics and metrics in the weld pool formed by laser welding. Conversely, data-driven surrogate models provide a cost-effective means to predict desired responses. These models establish statistical or mathematical correlations with input–output data, eliminating the need for additional simulations during design optimization. This study proposes a data-driven surrogate model, employing the Gaussian process regression network (GPRN), to predict weld pool metrics, such as weld width and depth of penetration in laser welding of aluminum alloy. A 3D computational fluid dynamics-based numerical model is initially constructed and experimentally validated to predict weld pool metrics. Subsequent experimental runs, guided by the design of experiments, include various configurations of process parameter settings. The developed numerical model computes weld pool metrics for each experimental run, forming a dataset for training and testing the GPRN model. The GPRN model is evaluated against simulated data, showing adequacy with a mean square error of 1.7 µm and mean absolute percentage error of 10−7, with experimental validation further confirming its accuracy, revealing a minimum error of 1.7%, a maximum error of 8%, and an average error of 3%. The key contribution and novelty of this study lie in the development of the hybrid data-driven model, which accurately predicts weld pool metrics while minimizing experimental and computational efforts.
{"title":"Predicting weld pool metrics in laser welding of aluminum alloys using data-driven surrogate modeling: A FEA-DoE-GPRN hybrid approach","authors":"A. Duggirala, B. Acherjee, Souren Mitra","doi":"10.1177/09544089241255927","DOIUrl":"https://doi.org/10.1177/09544089241255927","url":null,"abstract":"Multi-physics computational models based on finite element analysis, offer detailed insights into the dynamics and metrics in the weld pool formed by laser welding. Conversely, data-driven surrogate models provide a cost-effective means to predict desired responses. These models establish statistical or mathematical correlations with input–output data, eliminating the need for additional simulations during design optimization. This study proposes a data-driven surrogate model, employing the Gaussian process regression network (GPRN), to predict weld pool metrics, such as weld width and depth of penetration in laser welding of aluminum alloy. A 3D computational fluid dynamics-based numerical model is initially constructed and experimentally validated to predict weld pool metrics. Subsequent experimental runs, guided by the design of experiments, include various configurations of process parameter settings. The developed numerical model computes weld pool metrics for each experimental run, forming a dataset for training and testing the GPRN model. The GPRN model is evaluated against simulated data, showing adequacy with a mean square error of 1.7 µm and mean absolute percentage error of 10−7, with experimental validation further confirming its accuracy, revealing a minimum error of 1.7%, a maximum error of 8%, and an average error of 3%. The key contribution and novelty of this study lie in the development of the hybrid data-driven model, which accurately predicts weld pool metrics while minimizing experimental and computational efforts.","PeriodicalId":506108,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":"35 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141107647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-23DOI: 10.1177/09544089241255942
K. Veera Venkata Nagaraju, M. Joseph Davidson, G. Venkatesh, M. Manjaiah, K. Harikrishna
The goal of the present work is to produce the efficient cutting of Ti-16Al-14Nb (α/β) alloy through wire-electric discharge machining and contemplate the terminologies such as machining ability, surface integrity and material removing capability. For this, the experimentation has been designed by considering three process parameters, pulse-on time ( Ton), pulse-off time ( Toff) and peak current ( Ip) at three significant levels (low, high, intermediate) in L27 order designed from design of experiments. The effect of these process variables on pulse characteristics, surface roughness ( Ra), kerfwidth ( Kw) and material removal rate ( MRR) is analyzed and mathematically modeled with analysis of variance. The results state that the highest MRR (0.521, 0.51, 0.506 mm3/sec) and low surface roughness (8.91, 8.89, 8.68 µm) values are observed at the highest level (110 µs, 15 µs, 8 A). If the pulse duration is kept at low ( Ton = 40µs, Toff = 3µs), the increase in peak current from 3 A to 8 A leads to a 64.54% increase in MRR and a 52.9% increase in Ra values. ANOVA results stated that Ton has contributed 20.4%, 35.8% and 19.3%, and Ip has contributed 43.1%, 30.5% and 46.6% influence on MRR, Kw and Ra respectively. The voltage–current characteristics studies confirmed that the strong intense pulses at a higher peak current (8 A) resulted in the increased MRR (0.521 mm3/sec) and Ra (8.43 µm) leading to the formation of swages and ridges. The surface integrity analysis derived from Abbott–Firestone curve agreed that the lowest level has shown better skewness ( Rsk = −0.274) and at highest level showed a larger deviation in skewness ( Rsk = +2.672) signifies that higher asymmetry (poor) of the surface.
{"title":"Machinability and pulse characteristics of Ti-16Al-14Nb (α/β) alloy in wire-electric discharge machining process: A surface integrity study","authors":"K. Veera Venkata Nagaraju, M. Joseph Davidson, G. Venkatesh, M. Manjaiah, K. Harikrishna","doi":"10.1177/09544089241255942","DOIUrl":"https://doi.org/10.1177/09544089241255942","url":null,"abstract":"The goal of the present work is to produce the efficient cutting of Ti-16Al-14Nb (α/β) alloy through wire-electric discharge machining and contemplate the terminologies such as machining ability, surface integrity and material removing capability. For this, the experimentation has been designed by considering three process parameters, pulse-on time ( Ton), pulse-off time ( Toff) and peak current ( Ip) at three significant levels (low, high, intermediate) in L27 order designed from design of experiments. The effect of these process variables on pulse characteristics, surface roughness ( Ra), kerfwidth ( Kw) and material removal rate ( MRR) is analyzed and mathematically modeled with analysis of variance. The results state that the highest MRR (0.521, 0.51, 0.506 mm3/sec) and low surface roughness (8.91, 8.89, 8.68 µm) values are observed at the highest level (110 µs, 15 µs, 8 A). If the pulse duration is kept at low ( Ton = 40µs, Toff = 3µs), the increase in peak current from 3 A to 8 A leads to a 64.54% increase in MRR and a 52.9% increase in Ra values. ANOVA results stated that Ton has contributed 20.4%, 35.8% and 19.3%, and Ip has contributed 43.1%, 30.5% and 46.6% influence on MRR, Kw and Ra respectively. The voltage–current characteristics studies confirmed that the strong intense pulses at a higher peak current (8 A) resulted in the increased MRR (0.521 mm3/sec) and Ra (8.43 µm) leading to the formation of swages and ridges. The surface integrity analysis derived from Abbott–Firestone curve agreed that the lowest level has shown better skewness ( Rsk = −0.274) and at highest level showed a larger deviation in skewness ( Rsk = +2.672) signifies that higher asymmetry (poor) of the surface.","PeriodicalId":506108,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":"33 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141104257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-23DOI: 10.1177/09544089241255943
YP Deepthi, Santosh Kumar Sahu, D. Anitha, Nakul Gupta, Niranjan dude, Srinivasu Gangi Setti, CD Sandeep
The friction and wear resistance of polytetrafluoroethylene (PTFE) composites can be enhanced by incorporating nickel-coated graphite. An electroless coating method employing Gin plates (418A, 418B) is utilized to produce nickel-coated graphite. X-ray diffractometer analysis reveals the presence of nickel and graphite peaks in the coated graphite powders at 44° and 26.4°, respectively. Scanning electron microscopy images confirm the presence of nickel coating on graphite particles. Tribological tests using a pin-on-disc tribometer (L9) demonstrate that composites filled with 20 wt.% Nickel-coated graphite exhibits the lowest wear rate of 220 µm, compared to 1166 µm for pure PTFE specimens. The notable improvement in wear resistance is attributed to enhanced bonding strength between the filler and matrix material. Pure PTFE exhibits varying coefficient of friction (CoF) at different parameters, with the highest and lowest CoF observed at 200 rpm, 20N and 180 rpm, 10 N, respectively. Optimal parameters for minimizing wear rate and CoF, determined through analysis of means, include a 20 wt.% filler concentration, disc speed of 180 rpm, and 10N load. Analysis of variance identifies composition and speed as primary factors affecting wear and CoF.
{"title":"Tribological investigation into nickel-coated graphite polytetrafluoroethylene composites","authors":"YP Deepthi, Santosh Kumar Sahu, D. Anitha, Nakul Gupta, Niranjan dude, Srinivasu Gangi Setti, CD Sandeep","doi":"10.1177/09544089241255943","DOIUrl":"https://doi.org/10.1177/09544089241255943","url":null,"abstract":"The friction and wear resistance of polytetrafluoroethylene (PTFE) composites can be enhanced by incorporating nickel-coated graphite. An electroless coating method employing Gin plates (418A, 418B) is utilized to produce nickel-coated graphite. X-ray diffractometer analysis reveals the presence of nickel and graphite peaks in the coated graphite powders at 44° and 26.4°, respectively. Scanning electron microscopy images confirm the presence of nickel coating on graphite particles. Tribological tests using a pin-on-disc tribometer (L9) demonstrate that composites filled with 20 wt.% Nickel-coated graphite exhibits the lowest wear rate of 220 µm, compared to 1166 µm for pure PTFE specimens. The notable improvement in wear resistance is attributed to enhanced bonding strength between the filler and matrix material. Pure PTFE exhibits varying coefficient of friction (CoF) at different parameters, with the highest and lowest CoF observed at 200 rpm, 20N and 180 rpm, 10 N, respectively. Optimal parameters for minimizing wear rate and CoF, determined through analysis of means, include a 20 wt.% filler concentration, disc speed of 180 rpm, and 10N load. Analysis of variance identifies composition and speed as primary factors affecting wear and CoF.","PeriodicalId":506108,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":"18 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141104596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Comprehending the behaviour of ternary hybrid nanofluids with the influence of couple stress effects on a flat plate will provide vital insights for the development of more effective heat exchangers and cooling systems. In this investigation, we analyzed the impact of various factors, including couple stress and cross-diffusion parameters (Dufour and Soret), on a ternary hybrid nanofluid flow [Formula: see text] across a convectively heated flat plate. The analysis takes into account non-Fourier heat flux and irreversibility. The governing equations are converted into a set of ordinary differential equations using appropriate similarity transformations, and then the bvp4c solver is used to find solutions. Outcomes are provided for two instances, that is, nanofluid ([Formula: see text]) and ternary hybrid nanofluid [Formula: see text] The fluid velocity is found to be negatively correlated with the couple stress parameter rises ([Formula: see text]) which is one of the major findings in this study. Within the range of [Formula: see text] it is seen that the friction factor exhibits a gradual increase with a rate of 0.02878 (in the case of nanofluid flow) and 0.038083 (in the case of ternary hybrid nanofluid flow). Additionally, when the Dufour number is between 0 and 0.6, the Nusselt number exhibits a discernible decrease of 0.27678 (in the case of nanofluid flow) and 0.26428 (in the case of ternary hybrid nanofluid flow). Furthermore, at [Formula: see text] (the Sherwood number), the Sherwood number drops at a rate of 0.0786 (in the case of nanofluid flow) and 0.05592 (in the case of ternary hybrid nanofluid flow). It has been observed that an increase in the chemical reaction parameter [Formula: see text] lowers the fluid concentration. It is observed that the Sherwood number increases at a rate of 0.037654 (in the case of nanofluid flow) and 0.037661 (in the case of ternary hybrid nanofluid flow) when [Formula: see text].
{"title":"Irreversibility analysis of EMHD ternary nanofluid flow: Unveiling the combined effects of thermal radiation, chemical reactions and cross-diffusion","authors":"Gandrakota Kathyayani, Satuluri Satya Nagendra Rao","doi":"10.1177/09544089241253938","DOIUrl":"https://doi.org/10.1177/09544089241253938","url":null,"abstract":"Comprehending the behaviour of ternary hybrid nanofluids with the influence of couple stress effects on a flat plate will provide vital insights for the development of more effective heat exchangers and cooling systems. In this investigation, we analyzed the impact of various factors, including couple stress and cross-diffusion parameters (Dufour and Soret), on a ternary hybrid nanofluid flow [Formula: see text] across a convectively heated flat plate. The analysis takes into account non-Fourier heat flux and irreversibility. The governing equations are converted into a set of ordinary differential equations using appropriate similarity transformations, and then the bvp4c solver is used to find solutions. Outcomes are provided for two instances, that is, nanofluid ([Formula: see text]) and ternary hybrid nanofluid [Formula: see text] The fluid velocity is found to be negatively correlated with the couple stress parameter rises ([Formula: see text]) which is one of the major findings in this study. Within the range of [Formula: see text] it is seen that the friction factor exhibits a gradual increase with a rate of 0.02878 (in the case of nanofluid flow) and 0.038083 (in the case of ternary hybrid nanofluid flow). Additionally, when the Dufour number is between 0 and 0.6, the Nusselt number exhibits a discernible decrease of 0.27678 (in the case of nanofluid flow) and 0.26428 (in the case of ternary hybrid nanofluid flow). Furthermore, at [Formula: see text] (the Sherwood number), the Sherwood number drops at a rate of 0.0786 (in the case of nanofluid flow) and 0.05592 (in the case of ternary hybrid nanofluid flow). It has been observed that an increase in the chemical reaction parameter [Formula: see text] lowers the fluid concentration. It is observed that the Sherwood number increases at a rate of 0.037654 (in the case of nanofluid flow) and 0.037661 (in the case of ternary hybrid nanofluid flow) when [Formula: see text].","PeriodicalId":506108,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":"48 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141107311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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