Pub Date : 2022-09-01DOI: 10.37255/jme.v17i3pp091-097
Rolvin Barreto, Malagi R R, Chougula S R
The purpose of this comparative study is to improve the predictive accuracy of the cutting force during the turning of Ti-6Al-4V on a lathe machine. By optimizing the machining process parameters such as cutting speed, feed rate, and depth of cut, the cutting force in the machining process can be improved significantly. Cutting force is one of the crucial characteristics that must be monitored during the cutting process in order to enhance tool life and the surface finish of the workpiece. This paper is based on the experimental dataset of cutting forces collected during the turning of titanium alloy under the Minimum Quantity Lubrication (MQL) condition. To predict the cutting forces, two machine learning techniques are explored. Firstly, a black-box model called an Artificial Neural Network (ANN) is proposed to predict cutting force. Using the Levenberg-Marquardt algorithm, a two-layered feedforward neural network is built in MATLAB to predict cutting force. The second model to be implemented was the Genetic Algorithm (GA), a white-box model. GA is an optimization technique which is based on Darwinian theories. It is a probabilistic method of searching, unlike most other search algorithms, which require definite inputs. Using symbolic regression in HeuristicLab, a GA model is developed to estimate cutting force. The anticipated values of cutting forces for both models were compared. Since the ANN model had fewer errors, it was ascertained that the particular model is preferable for machining process optimization.
{"title":"A Comparative Study on Prediction of Cutting Force using Artificial Neural Network and Genetic Algorithm during Machining of Ti-6Al-4V","authors":"Rolvin Barreto, Malagi R R, Chougula S R","doi":"10.37255/jme.v17i3pp091-097","DOIUrl":"https://doi.org/10.37255/jme.v17i3pp091-097","url":null,"abstract":"The purpose of this comparative study is to improve the predictive accuracy of the cutting force during the turning of Ti-6Al-4V on a lathe machine. By optimizing the machining process parameters such as cutting speed, feed rate, and depth of cut, the cutting force in the machining process can be improved significantly. Cutting force is one of the crucial characteristics that must be monitored during the cutting process in order to enhance tool life and the surface finish of the workpiece. This paper is based on the experimental dataset of cutting forces collected during the turning of titanium alloy under the Minimum Quantity Lubrication (MQL) condition. To predict the cutting forces, two machine learning techniques are explored. Firstly, a black-box model called an Artificial Neural Network (ANN) is proposed to predict cutting force. Using the Levenberg-Marquardt algorithm, a two-layered feedforward neural network is built in MATLAB to predict cutting force. The second model to be implemented was the Genetic Algorithm (GA), a white-box model. GA is an optimization technique which is based on Darwinian theories. It is a probabilistic method of searching, unlike most other search algorithms, which require definite inputs. Using symbolic regression in HeuristicLab, a GA model is developed to estimate cutting force. The anticipated values of cutting forces for both models were compared. Since the ANN model had fewer errors, it was ascertained that the particular model is preferable for machining process optimization.","PeriodicalId":38895,"journal":{"name":"Academic Journal of Manufacturing Engineering","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90456956","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 : 2022-09-01DOI: 10.37255/jme.v17i3pp080-086
P. T, R. S, B. V
In the present investigation, the effect and role of plasma gas flow rate on the formation of microstructure during plasma arc welding of Ti6Al4V titanium alloy were studied using microscopic observation, energy dispersive spectroscopic analysis, tensile tests and microhardness measurements. Plasma gas flow rate influences the arc pressure, arc constriction, and stability. The transformation of plasma arc from conduction mode to keyhole mode causes severe changes to the microstructural characteristics of the titanium welds. This transformation takes place with slight variations of PGFR. Weld geometries increase with an increase in the PGFR. The microstructural examination shows that there are various phases formed during the variation in PGFR. Fusion zone had acicular α and widmanstätten α. Mechanical properties (i.e) strength and hardness of the joints increase with an increase in plasma gas flow rate. In the joint welded with 1 L/min, there is the formation of α-case which is an oxygen rich brittle subsurface structure and found detrimental to the ductility of the joints.
{"title":"Influence of Plasma Gas Flow Rate on the Mechanical and Microstructural Aspects of Plasma Arc Welded Titanium Alloy Joints","authors":"P. T, R. S, B. V","doi":"10.37255/jme.v17i3pp080-086","DOIUrl":"https://doi.org/10.37255/jme.v17i3pp080-086","url":null,"abstract":"In the present investigation, the effect and role of plasma gas flow rate on the formation of microstructure during plasma arc welding of Ti6Al4V titanium alloy were studied using microscopic observation, energy dispersive spectroscopic analysis, tensile tests and microhardness measurements. Plasma gas flow rate influences the arc pressure, arc constriction, and stability. The transformation of plasma arc from conduction mode to keyhole mode causes severe changes to the microstructural characteristics of the titanium welds. This transformation takes place with slight variations of PGFR. Weld geometries increase with an increase in the PGFR. The microstructural examination shows that there are various phases formed during the variation in PGFR. Fusion zone had acicular α and widmanstätten α. Mechanical properties (i.e) strength and hardness of the joints increase with an increase in plasma gas flow rate. In the joint welded with 1 L/min, there is the formation of α-case which is an oxygen rich brittle subsurface structure and found detrimental to the ductility of the joints.","PeriodicalId":38895,"journal":{"name":"Academic Journal of Manufacturing Engineering","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79525717","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 : 2022-09-01DOI: 10.37255/jme.v17i3pp104-110
Sanjay Kumar Dubey, Shashank sharma
Host Ba2MgSi2O7 phosphor was successfully prepared via low temperature combustion synthesis route. The phase identification of the prepared phosphor was done with the help of powder XRD technique. The XRD pattern of the phosphor revealed its monoclinic crystal symmetry with a space group C2/c. The XRD pattern have well clarified with JCPDS PDF card no. #23-0842. The average crystallite size was calculated as 42nm and crystal lattice strain size calculated as 0.24, respectively. It is acquired that the sample UV exposed for 15min gives optimum TL intensity at 112.190C temperature and displays single TL glow peak. On the basis of TL glow curve, it can be suggested that the Ba2MgSi2O7 (BMS) phosphor is an efficient host lattice but not a better TL phosphor. In our present study, we have discussed on the XRD, FESEM and thermo-luminescence (TL) characteristics as well as different kinetic parameters of this phosphor.
{"title":"Structural and Thermal Properties of a Selected Host Crystal Lattice: Exploration of Inherent Possibilities","authors":"Sanjay Kumar Dubey, Shashank sharma","doi":"10.37255/jme.v17i3pp104-110","DOIUrl":"https://doi.org/10.37255/jme.v17i3pp104-110","url":null,"abstract":"Host Ba2MgSi2O7 phosphor was successfully prepared via low temperature combustion synthesis route. The phase identification of the prepared phosphor was done with the help of powder XRD technique. The XRD pattern of the phosphor revealed its monoclinic crystal symmetry with a space group C2/c. The XRD pattern have well clarified with JCPDS PDF card no. #23-0842. The average crystallite size was calculated as 42nm and crystal lattice strain size calculated as 0.24, respectively. It is acquired that the sample UV exposed for 15min gives optimum TL intensity at 112.190C temperature and displays single TL glow peak. On the basis of TL glow curve, it can be suggested that the Ba2MgSi2O7 (BMS) phosphor is an efficient host lattice but not a better TL phosphor. In our present study, we have discussed on the XRD, FESEM and thermo-luminescence (TL) characteristics as well as different kinetic parameters of this phosphor. ","PeriodicalId":38895,"journal":{"name":"Academic Journal of Manufacturing Engineering","volume":"100 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72855408","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 : 2022-09-01DOI: 10.37255/jme.v17i3pp087-090
Subravel V, Chandrasekar V
Different techniques have been used to achieve a high heat transfer rate. Among them, one of the advanced techniques is a suspension of nanoparticles in the base fluids as water and coated with aluminum and titanium. The present work has been carried out on a double pipe heat exchanger with twisted tape insert with twist ratio (y/w = 4 and 6) and thickness (0.8mm) for heat transfer investigation of water to water and nanofluid to water with counter flow arrangement under turbulent flow conditions. The computational fluid dynamic code simulates different concentrations of nanofluid (0.01% to 0.19%) in ANSYS FLUENT R 18.1 software. The overall heat transfer coefficients for all concentrations are measured as a function of the hot and cold stream's mass flow rates. The thermal performance parameter overall heat transfer coefficient is compared for nanofluids with water. The work concludes that there is a good enhancement in heat transfer rate using nanofluid.
不同的技术已被用于实现高传热率。其中，一种先进的技术是将纳米颗粒悬浮在以水为基础的流体中，并涂上铝和钛。本文在双管换热器上进行了紊流条件下水与水、纳米流体与水逆流布置的换热研究，双管换热器的捻比分别为(y/w = 4和6)和厚度为(0.8mm)。计算流体动力学代码在ANSYS FLUENT R 18.1软件中模拟了不同浓度的纳米流体(0.01%至0.19%)。所有浓度的总传热系数作为冷热流质量流率的函数来测量。对含水纳米流体的热性能参数——总传热系数进行了比较。研究结果表明，纳米流体可以有效地提高传热速率。
{"title":"Design and Analysis for Heat Transfer Through Twisted Tape with Nanoparticles","authors":"Subravel V, Chandrasekar V","doi":"10.37255/jme.v17i3pp087-090","DOIUrl":"https://doi.org/10.37255/jme.v17i3pp087-090","url":null,"abstract":"Different techniques have been used to achieve a high heat transfer rate. Among them, one of the advanced techniques is a suspension of nanoparticles in the base fluids as water and coated with aluminum and titanium. The present work has been carried out on a double pipe heat exchanger with twisted tape insert with twist ratio (y/w = 4 and 6) and thickness (0.8mm) for heat transfer investigation of water to water and nanofluid to water with counter flow arrangement under turbulent flow conditions. The computational fluid dynamic code simulates different concentrations of nanofluid (0.01% to 0.19%) in ANSYS FLUENT R 18.1 software. The overall heat transfer coefficients for all concentrations are measured as a function of the hot and cold stream's mass flow rates. The thermal performance parameter overall heat transfer coefficient is compared for nanofluids with water. The work concludes that there is a good enhancement in heat transfer rate using nanofluid.","PeriodicalId":38895,"journal":{"name":"Academic Journal of Manufacturing Engineering","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90878897","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 : 2022-07-04DOI: 10.37255/jme.v17i4pp119-126
Ziad Al Sarraf
In this presented work, an Artificial Neural Network (ANN) connected with the backpropagation method was employed to predict the strength of joining materials that were carried out by using an ultrasonic spot welding process. The models created in this study were investigated, and their process parameters were analyzed. These parameters were classified and set as input variables like applying pressure, time of duration weld and trigger of vibrating amplitude. In contrast, the weld strength of joining dissimilar materials (Al-Cu) is set as output parameters. The identification from the process parameters is obtained using several experiments and finite element analyses based on prediction. The results of actual and numerical are accurate and reliable; however, their complexity has a significant effect due to being sensitivity to the condition variation of welding processes. Therefore, an efficient technique like an artificial neural network coupled with the backpropagation method is required to use the experiments as input data in the simulation of the ultrasonic welding process, finding the adequacy of the modeling process in the prediction of weld strength and to confirm the performance of using mathematical methods. The results of the selecting non-linear models show a noticeable potency when using ANN with a backpropagation method in providing high accuracy compared with other results obtained by conventional models.
{"title":"Prediction of Weld Strength in Power Ultrasonic Spot Welding Process Using Artificial Neural Network (ANN) and Back Propagation method","authors":"Ziad Al Sarraf","doi":"10.37255/jme.v17i4pp119-126","DOIUrl":"https://doi.org/10.37255/jme.v17i4pp119-126","url":null,"abstract":"In this presented work, an Artificial Neural Network (ANN) connected with the backpropagation method was employed to predict the strength of joining materials that were carried out by using an ultrasonic spot welding process. The models created in this study were investigated, and their process parameters were analyzed. These parameters were classified and set as input variables like applying pressure, time of duration weld and trigger of vibrating amplitude. In contrast, the weld strength of joining dissimilar materials (Al-Cu) is set as output parameters. The identification from the process parameters is obtained using several experiments and finite element analyses based on prediction. The results of actual and numerical are accurate and reliable; however, their complexity has a significant effect due to being sensitivity to the condition variation of welding processes. Therefore, an efficient technique like an artificial neural network coupled with the backpropagation method is required to use the experiments as input data in the simulation of the ultrasonic welding process, finding the adequacy of the modeling process in the prediction of weld strength and to confirm the performance of using mathematical methods. The results of the selecting non-linear models show a noticeable potency when using ANN with a backpropagation method in providing high accuracy compared with other results obtained by conventional models.","PeriodicalId":38895,"journal":{"name":"Academic Journal of Manufacturing Engineering","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90304679","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 : 2022-06-01DOI: 10.37255/jme.v17i2pp051-063
E. Ekpruke, C. Ossia, A. Big-Alabo
Asbestos has been a significant reinforcement material in the production of automobile friction components due to its physical and mechanical properties. However, the replacement of asbestos and other toxic metals employed in producing conventional friction components has been called for due to health and environmental concerns. Research in this area has led to the development of more efficient non-asbestos based organic friction materials for automobiles. In this study, recent progress in the manufacture of non-asbestos based, eco-friendly automotive brake pads is reviewed. A complete classification of conventional and non-conventional friction materials used in the development of brake pads is presented, and the production method and the roles of friction materials in the mechanical and tribological properties of the manufactured pads are discussed. The study shows that the performance of brake pads manufactured from plants, animals, or plants and animal materials (hybrid) varies depending on the physical, chemical and mechanical properties of the plants and/or animals.
{"title":"Recent Progress and Evolution in the Development of Non-Asbestos Based Automotive Brake Pad- A Review","authors":"E. Ekpruke, C. Ossia, A. Big-Alabo","doi":"10.37255/jme.v17i2pp051-063","DOIUrl":"https://doi.org/10.37255/jme.v17i2pp051-063","url":null,"abstract":"Asbestos has been a significant reinforcement material in the production of automobile friction components due to its physical and mechanical properties. However, the replacement of asbestos and other toxic metals employed in producing conventional friction components has been called for due to health and environmental concerns. Research in this area has led to the development of more efficient non-asbestos based organic friction materials for automobiles. In this study, recent progress in the manufacture of non-asbestos based, eco-friendly automotive brake pads is reviewed. A complete classification of conventional and non-conventional friction materials used in the development of brake pads is presented, and the production method and the roles of friction materials in the mechanical and tribological properties of the manufactured pads are discussed. The study shows that the performance of brake pads manufactured from plants, animals, or plants and animal materials (hybrid) varies depending on the physical, chemical and mechanical properties of the plants and/or animals.","PeriodicalId":38895,"journal":{"name":"Academic Journal of Manufacturing Engineering","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84753969","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 : 2022-06-01DOI: 10.37255/jme.v17i2pp044-050
Chinmay V. Sutar, Adish A. Mandavkar, Sairaj B Patil, Tejas U. Mohite, Tushar A. Patole, Sunil J. Raykar
A current manufacturing scenario focuses on processes which can manufacture products at the highest quality with minimum wastage of material. Additive manufacturing is one such technology which can fulfil the demands of today’s manufacturing organisation. Fused Deposition Modelling is a 3D printing process from the additive manufacturing family to build polymer components accurately with almost negligible wastage of material. In the current investigation, analysis and prediction of the operating range of process parameters for surface roughness of 3D printed parts are presented. During the investigation, orientation is an essential aspect of the surface of fused deposition modelling printed parts. From contour plots, it is concluded that orientations 0⁰ to 15⁰ and 85⁰ to 90⁰ with a layer thickness range of 0.12 mm to 0.16 mm and Infill density within 80% to 90% are found to be suitable working range for better surface roughness below 6 µm.
{"title":"Analysis and Prediction of Working Range of Process Parameters for Surface Roughness of 3D Printed Parts with Fused Deposition Modelling","authors":"Chinmay V. Sutar, Adish A. Mandavkar, Sairaj B Patil, Tejas U. Mohite, Tushar A. Patole, Sunil J. Raykar","doi":"10.37255/jme.v17i2pp044-050","DOIUrl":"https://doi.org/10.37255/jme.v17i2pp044-050","url":null,"abstract":"A current manufacturing scenario focuses on processes which can manufacture products at the highest quality with minimum wastage of material. Additive manufacturing is one such technology which can fulfil the demands of today’s manufacturing organisation. Fused Deposition Modelling is a 3D printing process from the additive manufacturing family to build polymer components accurately with almost negligible wastage of material. In the current investigation, analysis and prediction of the operating range of process parameters for surface roughness of 3D printed parts are presented. During the investigation, orientation is an essential aspect of the surface of fused deposition modelling printed parts. From contour plots, it is concluded that orientations 0⁰ to 15⁰ and 85⁰ to 90⁰ with a layer thickness range of 0.12 mm to 0.16 mm and Infill density within 80% to 90% are found to be suitable working range for better surface roughness below 6 µm.","PeriodicalId":38895,"journal":{"name":"Academic Journal of Manufacturing Engineering","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88026354","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 : 2022-06-01DOI: 10.37255/jme.v17i2pp064-067
A. Md
Friction stir processing (FSP), derived from the friction stir welding (FSW) process, is an emerging novel, green and energy-efficient processing technique to fabricate surface composite. The FSP technique has been used in the present investigation to fabricate surface composites, using Aluminium Alloy 7075 as parent metal and Titanium Dioxide and Silicon Carbide powder particles as reinforcement. Aluminium Alloy 7075 has been selected as the matrix phase, as being widely used by the automotive and aerospace application and has the highest strength among all commercial Al alloys. The present work details the fabrication of surface composites using various reinforcement combinations like AA7075- TiO2, AA7075- and AA7075- SiC, TiO2+SiC at constant tool rotation, tool travel speed and the number of passes have been discussed. The same being intended to improve hardness and thereby wear resistance. The fabricated surface composites are examined for microstructure using an image analyzer and found friction stir processed zone with fine microstructure than the base material. It is also observed that the average hardness of friction stir processed surface composite was higher than that of parent metal. Wear Resistance is found to be improved compared to the parent metal. It is found that Tensile strength is also enhanced than the base material.
{"title":"Fabrication of Surface Metal Matrix Composite of AA7075 using Friction Stir Processing","authors":"A. Md","doi":"10.37255/jme.v17i2pp064-067","DOIUrl":"https://doi.org/10.37255/jme.v17i2pp064-067","url":null,"abstract":"Friction stir processing (FSP), derived from the friction stir welding (FSW) process, is an emerging novel, green and energy-efficient processing technique to fabricate surface composite. The FSP technique has been used in the present investigation to fabricate surface composites, using Aluminium Alloy 7075 as parent metal and Titanium Dioxide and Silicon Carbide powder particles as reinforcement. Aluminium Alloy 7075 has been selected as the matrix phase, as being widely used by the automotive and aerospace application and has the highest strength among all commercial Al alloys. The present work details the fabrication of surface composites using various reinforcement combinations like AA7075- TiO2, AA7075- and AA7075- SiC, TiO2+SiC at constant tool rotation, tool travel speed and the number of passes have been discussed. The same being intended to improve hardness and thereby wear resistance. The fabricated surface composites are examined for microstructure using an image analyzer and found friction stir processed zone with fine microstructure than the base material. It is also observed that the average hardness of friction stir processed surface composite was higher than that of parent metal. Wear Resistance is found to be improved compared to the parent metal. It is found that Tensile strength is also enhanced than the base material.","PeriodicalId":38895,"journal":{"name":"Academic Journal of Manufacturing Engineering","volume":"21 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72412242","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 : 2022-06-01DOI: 10.37255/jme.v17i2pp068-072
A. V., S. K
Fossil fuels are being gradually exhausted and need to go to new energy options. The vegetable oils are significant resources for biodiesel production and the best alternative for diesel from crude oil. This research aims to study the physical characteristics of diesel in combination with linseed oil, waste cooking oil and rubber seed oil as ternary blend biodiesels. Ternary blends mean a combination of diesel, biodiesel-1 and biodiesel-2. Four ternary blends have been prepared in various proportions from linseed and rubber seed oil, and another four ternary blends have been prepared from linseed and waste cooking oil. These three oils have relatively similar physical characteristics, non-edible. Physical characteristics tests were carried out using ternary biodiesel mixtures. The experimental study has shown the physical characteristics of the ternary blend by comparing the blends' kinematic viscosity, density, flash point and fire point. The blend of 95% diesel, 2.5% linseed and 2.5% rubber seed biodiesel gives better physical characteristics. By analysing the graph, the particular blends give similar physical characteristics to diesel. So the blend of linseed and rubber seed oil gives the best physical characteristics compared to other blends. It has lower viscosity values, nearly the same as diesel. So it does not affect the performance of an engine.
{"title":"Physical Characteristics of Ternary Blends of Biodiesel","authors":"A. V., S. K","doi":"10.37255/jme.v17i2pp068-072","DOIUrl":"https://doi.org/10.37255/jme.v17i2pp068-072","url":null,"abstract":"Fossil fuels are being gradually exhausted and need to go to new energy options. The vegetable oils are significant resources for biodiesel production and the best alternative for diesel from crude oil. This research aims to study the physical characteristics of diesel in combination with linseed oil, waste cooking oil and rubber seed oil as ternary blend biodiesels. Ternary blends mean a combination of diesel, biodiesel-1 and biodiesel-2. Four ternary blends have been prepared in various proportions from linseed and rubber seed oil, and another four ternary blends have been prepared from linseed and waste cooking oil. These three oils have relatively similar physical characteristics, non-edible. Physical characteristics tests were carried out using ternary biodiesel mixtures. The experimental study has shown the physical characteristics of the ternary blend by comparing the blends' kinematic viscosity, density, flash point and fire point. The blend of 95% diesel, 2.5% linseed and 2.5% rubber seed biodiesel gives better physical characteristics. By analysing the graph, the particular blends give similar physical characteristics to diesel. So the blend of linseed and rubber seed oil gives the best physical characteristics compared to other blends. It has lower viscosity values, nearly the same as diesel. So it does not affect the performance of an engine.","PeriodicalId":38895,"journal":{"name":"Academic Journal of Manufacturing Engineering","volume":"79 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72704319","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 : 2022-06-01DOI: 10.37255/jme.v17i2pp073-078
A. Negemiya, Tushar Sonar, Rajakumar Selvarajan
In this investigation, the effect of holding time on the microstructure of joint interface and bonding strength of vacuum diffusion bonded dissimilar austenitic stainless (ASS) – titanium (Ti) alloy joints were investigated. The dissimilar joints of ASS - Ti alloy were developed using the holding time of 30, 45, 60, 75 and 90 minutes in a vacuum chamber at a temperature of 900⁰C and pressure of 14 MPa. The bonding strength of ASS – Ti alloy joints was evaluated using the ram tensile test. The microhardness survey was done perpendicular to the joint interface. The microstructure of the joint interface was analyzed using optical microscopy (OM). The evolution of intermetallic compounds at the joint interface was analyzed using X-ray diffraction (XRD). The microstructure of the joint interface was correlated to the bonding strength of joints.
{"title":"Effect of Holding Time on Bonding Strength and Joint Interface Microstructure of Vacuum Diffusion Bonded Dissimilar Austenitic Stainless Steel - Titanium Alloy Joints","authors":"A. Negemiya, Tushar Sonar, Rajakumar Selvarajan","doi":"10.37255/jme.v17i2pp073-078","DOIUrl":"https://doi.org/10.37255/jme.v17i2pp073-078","url":null,"abstract":"In this investigation, the effect of holding time on the microstructure of joint interface and bonding strength of vacuum diffusion bonded dissimilar austenitic stainless (ASS) – titanium (Ti) alloy joints were investigated. The dissimilar joints of ASS - Ti alloy were developed using the holding time of 30, 45, 60, 75 and 90 minutes in a vacuum chamber at a temperature of 900⁰C and pressure of 14 MPa. The bonding strength of ASS – Ti alloy joints was evaluated using the ram tensile test. The microhardness survey was done perpendicular to the joint interface. The microstructure of the joint interface was analyzed using optical microscopy (OM). The evolution of intermetallic compounds at the joint interface was analyzed using X-ray diffraction (XRD). The microstructure of the joint interface was correlated to the bonding strength of joints.","PeriodicalId":38895,"journal":{"name":"Academic Journal of Manufacturing Engineering","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81355019","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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