Pub Date : 2024-04-01DOI: 10.12913/22998624/183949
Chaimae Haboubi, E. H. Barhdadi, K. Haboubi, Yahya El Hammoudani, Zouhair Sadoune, Aouatif El Abdouni, F. Dimane
In the present study, micromechanical modeling techniques were employed to examine the mechanical proper - ties of a hemp/clay composite material. This composite consists of hemp fibers incorporated into a clay matrix, a configuration chosen in response to environmental considerations and the natural advantages of hemp fibers, which include their lightweight nature and their considerable strength and stiffness relative to their weight. The approach adopted incorporates both localization and homogenization methodologies along with the three-phase model to provide an in-depth analysis of the composite’s behavior. The findings from this theoretical model show a promising correlation with empirical data, demonstrating the model’s efficacy in capturing the compos - ite’s mechanical response.
{"title":"Characterization of the Mechanical Behavior of Hemp-Clay Composites","authors":"Chaimae Haboubi, E. H. Barhdadi, K. Haboubi, Yahya El Hammoudani, Zouhair Sadoune, Aouatif El Abdouni, F. Dimane","doi":"10.12913/22998624/183949","DOIUrl":"https://doi.org/10.12913/22998624/183949","url":null,"abstract":"In the present study, micromechanical modeling techniques were employed to examine the mechanical proper - ties of a hemp/clay composite material. This composite consists of hemp fibers incorporated into a clay matrix, a configuration chosen in response to environmental considerations and the natural advantages of hemp fibers, which include their lightweight nature and their considerable strength and stiffness relative to their weight. The approach adopted incorporates both localization and homogenization methodologies along with the three-phase model to provide an in-depth analysis of the composite’s behavior. The findings from this theoretical model show a promising correlation with empirical data, demonstrating the model’s efficacy in capturing the compos - ite’s mechanical response.","PeriodicalId":517116,"journal":{"name":"Advances in Science and Technology Research Journal","volume":"3 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140354063","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 : 2024-04-01DOI: 10.12913/22998624/182932
Waldemar Małopolski, S. Skoczypiec
The progression of the industry, alongside the continuous enhancement of operational efficiency and the reduction of production costs, are paving the way for novel solutions in the realm of storage and transportation systems. The incorporation of new technologies and solutions, such as mobile robots, has culminated in the establishment of Smart Warehouses. It facilitates the reduction of non-value adding activities for companies. One of the methods of improving the efficiency of such systems is the more effective use of autonomous mobile robots. The article presented an inventive concept of an autonomous mobile robot capable of undertaking transport tasks both on the shop floor and within high-bay warehouses. The new concept of the drive mechanism enables it to navigate on surfaces and move along rail guides. By using an elevator, the robot can be lifted to higher levels within the warehouse. The well-conceived structural solution of the robot allows the elevator placement anywhere within the warehouse, eliminating the need for constructing a pit. The use of a mobile robot with the proposed structure will enable the execution of transport tasks without necessitating reloading. Such an approach has the potential to increase efficiency and reduce the costs of storage processes.
{"title":"The Concept of an Autonomous Mobile Robot for Automating Transport Tasks in High-Bay Warehouses","authors":"Waldemar Małopolski, S. Skoczypiec","doi":"10.12913/22998624/182932","DOIUrl":"https://doi.org/10.12913/22998624/182932","url":null,"abstract":"The progression of the industry, alongside the continuous enhancement of operational efficiency and the reduction of production costs, are paving the way for novel solutions in the realm of storage and transportation systems. The incorporation of new technologies and solutions, such as mobile robots, has culminated in the establishment of Smart Warehouses. It facilitates the reduction of non-value adding activities for companies. One of the methods of improving the efficiency of such systems is the more effective use of autonomous mobile robots. The article presented an inventive concept of an autonomous mobile robot capable of undertaking transport tasks both on the shop floor and within high-bay warehouses. The new concept of the drive mechanism enables it to navigate on surfaces and move along rail guides. By using an elevator, the robot can be lifted to higher levels within the warehouse. The well-conceived structural solution of the robot allows the elevator placement anywhere within the warehouse, eliminating the need for constructing a pit. The use of a mobile robot with the proposed structure will enable the execution of transport tasks without necessitating reloading. Such an approach has the potential to increase efficiency and reduce the costs of storage processes.","PeriodicalId":517116,"journal":{"name":"Advances in Science and Technology Research Journal","volume":"5 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140354804","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 : 2024-04-01DOI: 10.12913/22998624/184343
Diana Velychko, H. Osukhivska, Yuri Palaniza, Nadiia Lutsyk, Łukasz Sobaszek
The use of Artificial Intelligence is currently being observed in many areas of life. In addition to assisting in intel - lectual work, solving complex computational problems, or analyzing various types of data, the aforementioned techniques can also be applied in the process of providing security to people. The paper proposes an emergency identification system based on Artificial Intelligence that aims to provide timely detection and notification of dan - gerous situations. The proposed solution consider the position of a person “hands up” as an emergency situation that will indicate a potential danger for a person. Because people in the face of potential danger are mostly forced to raise their hands up and this pose attracts attention, emphasizes the emotional reaction to certain events and is usually used as a sign of risk or as a means of subjugation. The system should recognize the pose of a person, detect it, and consequently inform about the threat. In this paper, an AI based emergency identification system was proposed to detect the human pose “hands up” for emergency identification using the PoseNet Machine Learn - ing Model. The assumption consists that the utilization only of 6 key points made allows reducing the computing resources of the system since the conclusion is made taking into account a smaller amount of data. For the study, a dataset of 1510 images was created for training an Artificial Intelligence model, and the decisions were verified. Supervised Machine Learning methods are used to classify the definition of an emergency. Alternative methods: Support Vector Machine, Logistic Regression, Naïve Bayes Classifier, Discriminant Analysis Classifier, and K-nearest Neighbours Classifier based on the accuracy were evaluated. Overall, the paper presents a comprehensive and innovative approach to emergency identification for quick response to them using the proposed system.
{"title":"Artificial Intelligence Based Emergency Identification Computer System","authors":"Diana Velychko, H. Osukhivska, Yuri Palaniza, Nadiia Lutsyk, Łukasz Sobaszek","doi":"10.12913/22998624/184343","DOIUrl":"https://doi.org/10.12913/22998624/184343","url":null,"abstract":"The use of Artificial Intelligence is currently being observed in many areas of life. In addition to assisting in intel - lectual work, solving complex computational problems, or analyzing various types of data, the aforementioned techniques can also be applied in the process of providing security to people. The paper proposes an emergency identification system based on Artificial Intelligence that aims to provide timely detection and notification of dan - gerous situations. The proposed solution consider the position of a person “hands up” as an emergency situation that will indicate a potential danger for a person. Because people in the face of potential danger are mostly forced to raise their hands up and this pose attracts attention, emphasizes the emotional reaction to certain events and is usually used as a sign of risk or as a means of subjugation. The system should recognize the pose of a person, detect it, and consequently inform about the threat. In this paper, an AI based emergency identification system was proposed to detect the human pose “hands up” for emergency identification using the PoseNet Machine Learn - ing Model. The assumption consists that the utilization only of 6 key points made allows reducing the computing resources of the system since the conclusion is made taking into account a smaller amount of data. For the study, a dataset of 1510 images was created for training an Artificial Intelligence model, and the decisions were verified. Supervised Machine Learning methods are used to classify the definition of an emergency. Alternative methods: Support Vector Machine, Logistic Regression, Naïve Bayes Classifier, Discriminant Analysis Classifier, and K-nearest Neighbours Classifier based on the accuracy were evaluated. Overall, the paper presents a comprehensive and innovative approach to emergency identification for quick response to them using the proposed system.","PeriodicalId":517116,"journal":{"name":"Advances in Science and Technology Research Journal","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140356633","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 : 2024-04-01DOI: 10.12913/22998624/183528
H. Abdulridha, T. Abbas, A. Bedan
Fused deposition modeling (FDM) technology is one of the rapidly growing techniques used for producing various complicated configurations without the need for any tools or continuous human intervention. However, a low quality of surfaces results for the layered production used in FDM. It is essential to investigate a suitable method for enhancing the accuracy and quality associated with FDM parts. This study aims to investigate the impact of different parameters such as the percentage of infill density, the shell thickness, layer thickness, and the number of top/bottom layers, as well as the percentage of infill overlap on part quality and the improvement of surface finish for printed specimens achieved through post-processing. Polylactic acid (PLA) material is used in building test specimens through the FDM approach. The experiments are carried out based on the Taguchi design of experi - ment method using (L25) orthogonal array. Using an analysis-of-variance approach (ANOVA), it is possible to understand the significance of the FDM parameters in order to find optimal parameter combinations. The results indicate that the application of the vapour smoothing procedure (VSP) treatment enhances the surface quality of FDM components to a microstage with minimal dimensional variation. The dichloromethane chemical has been found to exhibit excellent surface finish at an infill density of 50%, a layer thickness of 0.1 mm, a shell thickness of 2.8 mm, five top/bottom layer numbers, and 0.25 infill overlap.
{"title":"Investigate the Effect of Chemical Post Processing on the Surface Roughness of Fused Deposition Modeling Printed Parts","authors":"H. Abdulridha, T. Abbas, A. Bedan","doi":"10.12913/22998624/183528","DOIUrl":"https://doi.org/10.12913/22998624/183528","url":null,"abstract":"Fused deposition modeling (FDM) technology is one of the rapidly growing techniques used for producing various complicated configurations without the need for any tools or continuous human intervention. However, a low quality of surfaces results for the layered production used in FDM. It is essential to investigate a suitable method for enhancing the accuracy and quality associated with FDM parts. This study aims to investigate the impact of different parameters such as the percentage of infill density, the shell thickness, layer thickness, and the number of top/bottom layers, as well as the percentage of infill overlap on part quality and the improvement of surface finish for printed specimens achieved through post-processing. Polylactic acid (PLA) material is used in building test specimens through the FDM approach. The experiments are carried out based on the Taguchi design of experi - ment method using (L25) orthogonal array. Using an analysis-of-variance approach (ANOVA), it is possible to understand the significance of the FDM parameters in order to find optimal parameter combinations. The results indicate that the application of the vapour smoothing procedure (VSP) treatment enhances the surface quality of FDM components to a microstage with minimal dimensional variation. The dichloromethane chemical has been found to exhibit excellent surface finish at an infill density of 50%, a layer thickness of 0.1 mm, a shell thickness of 2.8 mm, five top/bottom layer numbers, and 0.25 infill overlap.","PeriodicalId":517116,"journal":{"name":"Advances in Science and Technology Research Journal","volume":"52 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140357168","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 : 2024-04-01DOI: 10.12913/22998624/183611
Łukasz Jedliński
This study investigates the problems of eccentricity and backlash using an analytical spur gear model with 26 degrees of freedom (DOF). Previous studies have only investigated the case of eccentricity with a parallel shift of the axis of rotation of the gear relative to its geometric axis of symmetry. This study presents a novel method for determining the radius of eccentricity and its angular position at any distance from the bearing support, in which the axis of rotation and the geometric axis of symmetry of the gear are non-parallel. The effect of gear motion in the line of action (LOA) and off-line of action (OLOA) directions on backlash is precisely determined, despite the fact that most studies usually ignore gear displacement along the OLOA direction. Numerical simulations are performed to determine the effect of eccentricity on backlash, and their results confirm that the proposed method for determining the radius of eccentricity for any eccentricity type is correct. A gear slice model is used for dynamic analysis. Results show that the type of eccentricity has a significant effect on the gear dynamics and that eccentric - ity analyses have to include other cases than merely eccentricity with parallel axes of gears
{"title":"Influence of Gear Eccentricity with Non-Parallel Axis on the Dynamic Behaviour of a Gear Unit Using a Gear Slice Model with 26 Degrees of Freedom","authors":"Łukasz Jedliński","doi":"10.12913/22998624/183611","DOIUrl":"https://doi.org/10.12913/22998624/183611","url":null,"abstract":"This study investigates the problems of eccentricity and backlash using an analytical spur gear model with 26 degrees of freedom (DOF). Previous studies have only investigated the case of eccentricity with a parallel shift of the axis of rotation of the gear relative to its geometric axis of symmetry. This study presents a novel method for determining the radius of eccentricity and its angular position at any distance from the bearing support, in which the axis of rotation and the geometric axis of symmetry of the gear are non-parallel. The effect of gear motion in the line of action (LOA) and off-line of action (OLOA) directions on backlash is precisely determined, despite the fact that most studies usually ignore gear displacement along the OLOA direction. Numerical simulations are performed to determine the effect of eccentricity on backlash, and their results confirm that the proposed method for determining the radius of eccentricity for any eccentricity type is correct. A gear slice model is used for dynamic analysis. Results show that the type of eccentricity has a significant effect on the gear dynamics and that eccentric - ity analyses have to include other cases than merely eccentricity with parallel axes of gears","PeriodicalId":517116,"journal":{"name":"Advances in Science and Technology Research Journal","volume":"46 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140357969","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}
This study leverages machine learning to analyze the cross-sectional profiles of materials subjected to wire-rolling processes, focusing on the specific stages of these processes and the characteristics of the resulting microstruc - tural profiles. The convolutional neural network (CNN), a potent tool for visual feature analysis and learning, is utilized to explore the properties and impacts of the cold plastic deformation technique. Specifically, CNNs are constructed and trained using 6400 image segments, each with a resolution of 120 × 90 pixels. The chosen ar - chitecture incorporates convolutional layers intercalated with polling layers and the “ReLu” activation function. The results, intriguingly, are derived from the observation of only a minuscule cropped fraction of the material’s cross-sectional profile. Following calibration two distinct neural networks, training and validation accuracies of 97.4%/97% and 79%/75% have been achieved. These accuracies correspond to identifying the cropped image’s location and the number of passes applied to the material. Further improvements in accuracy are reported upon integrating the two networks using a multiple-output setup, with the overall training and validation accuracies slightly increasing to 98.9%/79.4% and 94.6%/78.1%, respectively, for the two features. The study emphasizes the pivotal role of specific architectural elements, such as the rescaling parameter of the augmentation process, in attaining a satisfactory prediction rate. Lastly, we delve into the potential implications of our findings, which shed light on the potential of machine learning techniques in refining our understanding of wire-rolling processes and guiding the development of more efficient and sustainable manufacturing practices.
{"title":"Analysis of Wire Rolling Processes Using Convolutional Neural Networks","authors":"Matheus Capelin, Gustavo Aristides Santana Martínez, Yutao Xing, Adriano Francisco Siqueira, Wei-Liang Qian","doi":"10.12913/22998624/183699","DOIUrl":"https://doi.org/10.12913/22998624/183699","url":null,"abstract":"This study leverages machine learning to analyze the cross-sectional profiles of materials subjected to wire-rolling processes, focusing on the specific stages of these processes and the characteristics of the resulting microstruc - tural profiles. The convolutional neural network (CNN), a potent tool for visual feature analysis and learning, is utilized to explore the properties and impacts of the cold plastic deformation technique. Specifically, CNNs are constructed and trained using 6400 image segments, each with a resolution of 120 × 90 pixels. The chosen ar - chitecture incorporates convolutional layers intercalated with polling layers and the “ReLu” activation function. The results, intriguingly, are derived from the observation of only a minuscule cropped fraction of the material’s cross-sectional profile. Following calibration two distinct neural networks, training and validation accuracies of 97.4%/97% and 79%/75% have been achieved. These accuracies correspond to identifying the cropped image’s location and the number of passes applied to the material. Further improvements in accuracy are reported upon integrating the two networks using a multiple-output setup, with the overall training and validation accuracies slightly increasing to 98.9%/79.4% and 94.6%/78.1%, respectively, for the two features. The study emphasizes the pivotal role of specific architectural elements, such as the rescaling parameter of the augmentation process, in attaining a satisfactory prediction rate. Lastly, we delve into the potential implications of our findings, which shed light on the potential of machine learning techniques in refining our understanding of wire-rolling processes and guiding the development of more efficient and sustainable manufacturing practices.","PeriodicalId":517116,"journal":{"name":"Advances in Science and Technology Research Journal","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353523","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 : 2024-04-01DOI: 10.12913/22998624/184115
J. Kowalska, M. Witkowska
Austenitic stainless steels are widely used in industry, from heavy industry and power generation to precision me - chanics and electronics, accounting for about 2/3 of the stainless steels produced. The stability of austenite influ - ences the properties and behaviour of these steels during deformation and annealing. This paper presents the results of research into austenitic metastable phase X5CrNi1810 steel, which was subjected to cold rolling (in the range of 5 to 80%) and then annealing (at temperatures of 500–900 °C). The research focused mainly on changes in crystal - lographic texture parameters occurring during the analysed processes. It was found that the observed development of the deformation texture is complex due to the fact that several processes take place simultaneously. Namely, the deformation of austenite, the transformation of austenite into martensite, and the deformation of the resulting mar - tensite. The texture of the deformed austenite was similar to the texture of the alloy type {112}<110>. After 80% deformation, the Goss-type {110}<001> texture component showed the highest intensity. The lack of {112}<111> orientation in the texture was due to the fact that this orientation changes to the {112}<110> martensite orientation as a result of the γ → α’ phase transition. Annealing of the deformed steel at 500 °C led to an increase in the degree of texturing (sharpening of the texture), which was related to the improvement of the texture in this temperature range. Above 600 °C, the degree of texturing decreased, which is directly related to the α ’ → γ reverse transformation and the subsequent recrystallization process. Magnetic studies indicate an increasing proportion of the magnetic phase α’ (martensite) together with an increasing degree of deformation. For deformation of 80%, the amount of magnetic phase reached a value of more than 33%. After annealing at a temperature of 800 °C, there is no martensite in the structure, which indicates that, in these heat treatment conditions, the complete reverse transformation of martensite into austenite has already taken place.
{"title":"The Influence of Cold Deformation and Annealing on Texture Changes in Austenitic Stainless Steel","authors":"J. Kowalska, M. Witkowska","doi":"10.12913/22998624/184115","DOIUrl":"https://doi.org/10.12913/22998624/184115","url":null,"abstract":"Austenitic stainless steels are widely used in industry, from heavy industry and power generation to precision me - chanics and electronics, accounting for about 2/3 of the stainless steels produced. The stability of austenite influ - ences the properties and behaviour of these steels during deformation and annealing. This paper presents the results of research into austenitic metastable phase X5CrNi1810 steel, which was subjected to cold rolling (in the range of 5 to 80%) and then annealing (at temperatures of 500–900 °C). The research focused mainly on changes in crystal - lographic texture parameters occurring during the analysed processes. It was found that the observed development of the deformation texture is complex due to the fact that several processes take place simultaneously. Namely, the deformation of austenite, the transformation of austenite into martensite, and the deformation of the resulting mar - tensite. The texture of the deformed austenite was similar to the texture of the alloy type {112}<110>. After 80% deformation, the Goss-type {110}<001> texture component showed the highest intensity. The lack of {112}<111> orientation in the texture was due to the fact that this orientation changes to the {112}<110> martensite orientation as a result of the γ → α’ phase transition. Annealing of the deformed steel at 500 °C led to an increase in the degree of texturing (sharpening of the texture), which was related to the improvement of the texture in this temperature range. Above 600 °C, the degree of texturing decreased, which is directly related to the α ’ → γ reverse transformation and the subsequent recrystallization process. Magnetic studies indicate an increasing proportion of the magnetic phase α’ (martensite) together with an increasing degree of deformation. For deformation of 80%, the amount of magnetic phase reached a value of more than 33%. After annealing at a temperature of 800 °C, there is no martensite in the structure, which indicates that, in these heat treatment conditions, the complete reverse transformation of martensite into austenite has already taken place.","PeriodicalId":517116,"journal":{"name":"Advances in Science and Technology Research Journal","volume":"18 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140356873","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 : 2024-04-01DOI: 10.12913/22998624/184100
Dunya Adnan Ghulam, A. Ibrahim
Inconel 718 super alloy is suitable for components exposed to high temperatures and demanding high strength; it is one of the hardest alloys to machine by conventional processes due to its properties. Nano Powder mixed electrical discharge machining is one of the most sophisticated processes to produce precise three dimensional complicated forms of hard metals through a thermo-physical process, so it is suitable for machining Inconel 718. This study reports an experimental investigation to improve the machining performance of Inconel 718 super alloy by adding nano chromium oxide powder particles to biodegradable and renewable soybean oil, which is used as a dielectric fluid to preserve the environment, with a magnetic field to assist in improving the process performance. The effects of machining parameters, namely peak current, pulse on time, powder concentration, and magnetic field on the re - sponses in terms of white layer thickness, heat affected zone, surface roughness, material removal rate, and surface crack density were investigated. The observed results manifested that the addition of nano chromium oxide particles to dielectric fluid enhances the process performance. The white layer thickness and heat affected zone improved by 43.93% and 48.82%, respectively. The enhancements in measured surface roughness and material removal rate were 51.76% and 20.62%, respectively. Micrographs of scanning electron microscope verifies that the number of cracks on the machined surface with 4 g/l of nano Cr 2 O 3 powder addition was reduced by half, and surface crack density improved by 10.31%, in comparison to machining without powder addition. It is observed that the current had the largest effect on the responses, followed by powder concentration, pulse on time, and magnetic field.
{"title":"Enhancing Electrical Discharge Machining Performance by Mixing Nano Chromium Trioxide Powder with Soybean Dielectric to Machine Inconel 718 Alloy","authors":"Dunya Adnan Ghulam, A. Ibrahim","doi":"10.12913/22998624/184100","DOIUrl":"https://doi.org/10.12913/22998624/184100","url":null,"abstract":"Inconel 718 super alloy is suitable for components exposed to high temperatures and demanding high strength; it is one of the hardest alloys to machine by conventional processes due to its properties. Nano Powder mixed electrical discharge machining is one of the most sophisticated processes to produce precise three dimensional complicated forms of hard metals through a thermo-physical process, so it is suitable for machining Inconel 718. This study reports an experimental investigation to improve the machining performance of Inconel 718 super alloy by adding nano chromium oxide powder particles to biodegradable and renewable soybean oil, which is used as a dielectric fluid to preserve the environment, with a magnetic field to assist in improving the process performance. The effects of machining parameters, namely peak current, pulse on time, powder concentration, and magnetic field on the re - sponses in terms of white layer thickness, heat affected zone, surface roughness, material removal rate, and surface crack density were investigated. The observed results manifested that the addition of nano chromium oxide particles to dielectric fluid enhances the process performance. The white layer thickness and heat affected zone improved by 43.93% and 48.82%, respectively. The enhancements in measured surface roughness and material removal rate were 51.76% and 20.62%, respectively. Micrographs of scanning electron microscope verifies that the number of cracks on the machined surface with 4 g/l of nano Cr 2 O 3 powder addition was reduced by half, and surface crack density improved by 10.31%, in comparison to machining without powder addition. It is observed that the current had the largest effect on the responses, followed by powder concentration, pulse on time, and magnetic field.","PeriodicalId":517116,"journal":{"name":"Advances in Science and Technology Research Journal","volume":"6 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353227","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 : 2024-04-01DOI: 10.12913/22998624/184194
P. Wysmulski, G. Mieczkowski
This manuscript concerns the investigation of the influence of the open hole on stability of the compression plate made of carbon-epoxy composite. Experimental tests carried out on the real plate resulted in a postcritical path from which the critical load value was determined using appropriate approximation method. In parallel, an independent study was carried out based on a numerical analysis using the finite element method (FEM). Investiga - tions were conducted in terms of a linear eigenproblem analysis, from which the value of the bifurcation load was determined for the FEM model of the plate. Its values resulting from the numerical analyses were validated against the experimental results, thus confirming the adequacy of the designed FEM model of the plate. The paper shows that the incremental increase of the hole in the plate monotonically influences the decrease in the critical load of the plate. The largest decrease was observed for the specimen with the largest hole analysed and was 13.5% compared to a plate without a hole. The newness of the paper is the application of interdisciplinary investigation methods to describe the influence of the open hole compression (OHC) on the stability of composite plates. ABAQUS® was used as the tool with which the numerical analyses were realised.
{"title":"Influence of Size of Open Hole on Stability of Compressed Plate Made of Carbon Fiber Reinforced Polymer","authors":"P. Wysmulski, G. Mieczkowski","doi":"10.12913/22998624/184194","DOIUrl":"https://doi.org/10.12913/22998624/184194","url":null,"abstract":"This manuscript concerns the investigation of the influence of the open hole on stability of the compression plate made of carbon-epoxy composite. Experimental tests carried out on the real plate resulted in a postcritical path from which the critical load value was determined using appropriate approximation method. In parallel, an independent study was carried out based on a numerical analysis using the finite element method (FEM). Investiga - tions were conducted in terms of a linear eigenproblem analysis, from which the value of the bifurcation load was determined for the FEM model of the plate. Its values resulting from the numerical analyses were validated against the experimental results, thus confirming the adequacy of the designed FEM model of the plate. The paper shows that the incremental increase of the hole in the plate monotonically influences the decrease in the critical load of the plate. The largest decrease was observed for the specimen with the largest hole analysed and was 13.5% compared to a plate without a hole. The newness of the paper is the application of interdisciplinary investigation methods to describe the influence of the open hole compression (OHC) on the stability of composite plates. ABAQUS® was used as the tool with which the numerical analyses were realised.","PeriodicalId":517116,"journal":{"name":"Advances in Science and Technology Research Journal","volume":"18 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140356878","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 : 2024-04-01DOI: 10.12913/22998624/185298
Elżbieta Gawrońska, M. Zych, R. Dyja, Michal Kowalkowski
The research shows a novel approach leveraging swarm algorithms, the artificial bee colony (ABC) and ant colony optimization (ACO), to rebuild the heat transfer coefficient, especially for the continuous border condition. The authors utilized their application software to do numerical computations, employing classical variants of swarm algorithms. The numerical calculations employed a functional determining error to assess the accuracy of the esti - mated result. The coefficient of the thermally conductive layer was recalibrated utilizing swarm methods within the range of 900–1500 W/m 2 K and subsequently compared to a predetermined reference value. A finite element mesh consisting of 576 nodes was used for the calculations. The study involved simulations with populations of 5, 10, 15, and 20 individuals. Furthermore, each scenario also considered noise of 0%, 2%, and 5% of the reference values. The results make it evident that the reconstructed values of the kappa coefficient, cooling curves, and temperatures for the ABC and ACO algorithms are physically correct. The consequences indicate a notable level of satisfaction and strong concurrence with the anticipated κ parameter values. The results from the numerical simulations demon - strate considerable promise for applying artificial intelligence algorithms to optimize production processes, analyze data, and facilitate data-driven decision-making. This contribution not only underscores the effectiveness of swarm intelligence in engineering applications but also opens new avenues for research in thermal process optimization.
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