This research presents an approach to measuring the inherent randomness in properties of materials fabricated by the fused filament fabrication (FFF) method. Defects associated with the layer-by-layer process introduce significant variability in the elastic modulus field of materials printed. To describe the random distribution in Young’s modulus fields, statistical properties of mean, variance, and correlation length must be estimated for bulk regions (the printed filaments) and fusion regions (the thin regions connecting printed filaments). The goal is to estimate the random properties from the surface strain fields calculated by digital image correlation (DIC) analysis. A machine learning algorithm is developed that can estimate the spatial variations in the elastic modulus. The model is trained on a dataset of simulated two-dimensional strain fields with known random distributions in the corresponding elastic modulus fields generated by finite element (FE) simulations. On the test data, we achieved the R2 score of 0.93 and 0.95 for the mean in the bulk and fusion Young’s modulus fields, respectively. Also, for the variance in bulk and fusion areas, the R2 score of 0.74 and 0.83 are achieved, respectively. The results demonstrate the feasibility of the proposed approach in measuring the randomness in material properties of FFF-based printed materials.
{"title":"Uncertainty Quantification in Material Properties of Additively Manufactured Materials for Application in Topology Optimization","authors":"Zahra Kazemi, C. Steeves","doi":"10.1115/imece2022-95195","DOIUrl":"https://doi.org/10.1115/imece2022-95195","url":null,"abstract":"\u0000 This research presents an approach to measuring the inherent randomness in properties of materials fabricated by the fused filament fabrication (FFF) method. Defects associated with the layer-by-layer process introduce significant variability in the elastic modulus field of materials printed. To describe the random distribution in Young’s modulus fields, statistical properties of mean, variance, and correlation length must be estimated for bulk regions (the printed filaments) and fusion regions (the thin regions connecting printed filaments). The goal is to estimate the random properties from the surface strain fields calculated by digital image correlation (DIC) analysis. A machine learning algorithm is developed that can estimate the spatial variations in the elastic modulus. The model is trained on a dataset of simulated two-dimensional strain fields with known random distributions in the corresponding elastic modulus fields generated by finite element (FE) simulations. On the test data, we achieved the R2 score of 0.93 and 0.95 for the mean in the bulk and fusion Young’s modulus fields, respectively. Also, for the variance in bulk and fusion areas, the R2 score of 0.74 and 0.83 are achieved, respectively. The results demonstrate the feasibility of the proposed approach in measuring the randomness in material properties of FFF-based printed materials.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115978578","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}
Carbon fiber reinforced with carbon-based nano-fillers is becoming popular for many applications due to its exceptional properties, such as high strength and stiffness. The matrix toughening is another way to improve the interlaminar fracture resistance. Short, micro, and nano-fillers are used for enhancing matrix properties. One of the challenges of using nanomaterials is that they get agglomerated due to the high aspect ratio and strong intermolecular and dipole-dipole interactions. To overcome the agglomeration problem, researchers have used interleaving sheets typically inserted at various locations through the thickness of the laminate. The present work uses 48 layers, symmetrically arranged of Non-Crimp Carbon fibers prepregs which were oven-cured to fabricate the composite laminates, with and without buckypaper at the midplane. Multi-Walled Carbon Nanotubes (MWCNTs) buckypapers with 45 gsm were used to fabricate nanoengineered composite laminate. Double cantilever beam (GIC), short beam shear strength, and flexural strength were performed as per ASTM 5528-13, 2344-M16, and 790-15 standards to analyze static and dynamic properties. Buckypaper incorporated laminates showed degraded mechanical properties; to enhance these, the lattice structures formed on the buckypaper and composite laminates were analyzed. The results indicate that the composite laminates fabricated using lattice buckypaper structure had better interlaminar strength than those without lattice grid buckypaper.
{"title":"Effect of Interleaved MWCNTs Buckypaper on the Mechanical Properties of Non-Crimp Carbon Fiber Composites","authors":"V. Jadhav, A. Kelkar","doi":"10.1115/imece2022-94193","DOIUrl":"https://doi.org/10.1115/imece2022-94193","url":null,"abstract":"\u0000 Carbon fiber reinforced with carbon-based nano-fillers is becoming popular for many applications due to its exceptional properties, such as high strength and stiffness. The matrix toughening is another way to improve the interlaminar fracture resistance. Short, micro, and nano-fillers are used for enhancing matrix properties. One of the challenges of using nanomaterials is that they get agglomerated due to the high aspect ratio and strong intermolecular and dipole-dipole interactions. To overcome the agglomeration problem, researchers have used interleaving sheets typically inserted at various locations through the thickness of the laminate. The present work uses 48 layers, symmetrically arranged of Non-Crimp Carbon fibers prepregs which were oven-cured to fabricate the composite laminates, with and without buckypaper at the midplane. Multi-Walled Carbon Nanotubes (MWCNTs) buckypapers with 45 gsm were used to fabricate nanoengineered composite laminate. Double cantilever beam (GIC), short beam shear strength, and flexural strength were performed as per ASTM 5528-13, 2344-M16, and 790-15 standards to analyze static and dynamic properties. Buckypaper incorporated laminates showed degraded mechanical properties; to enhance these, the lattice structures formed on the buckypaper and composite laminates were analyzed. The results indicate that the composite laminates fabricated using lattice buckypaper structure had better interlaminar strength than those without lattice grid buckypaper.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126650486","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}
Carbon steel corrosion in hydrochloric acid media is a huge challenge in the chemical industry; hence, creating green and more efficient inhibitors is an urgent task. Furthermore, the increasing amount of solid wastes arising from the municipality and other sources and its disposal consequence has been a major economic and environmental problem. Hence, in this research, the effect of agricultural waste as a natural inhibitor on the carbon steel dissolution in one molar hydrochloric acid solution was studied using electrochemical and surface techniques. The obtained results showed that the corrosion protection potential of the agricultural waste increases with the agricultural waste concentration and an optimum value of 95.92% was achieved at 500 ppm concentration. The waste adsorption on the metallic surface followed the Langmuir adsorption isotherm. The electrochemical impedance spectroscopy test shows that the inhibitor inhibits the metal against corrosion by getting adhered to the carbon steel surface. The scanning electron microscopy analysis proves that in the presence of the inhibitor, the surface of the carbon steel becomes smooth owing to the inhibitive films formed on the metal surface. The results demonstrated that the agricultural waste extract is an excellent green and eco-friendly corrosion inhibitor.
{"title":"A Green and Sustainable Approach for Carbon Steel Acidic Corrosion Inhibition Using Agricultural Waste: Experimental and Theoretical Studies","authors":"O. Sanni, J. Ren, T. Jen","doi":"10.1115/imece2022-95031","DOIUrl":"https://doi.org/10.1115/imece2022-95031","url":null,"abstract":"\u0000 Carbon steel corrosion in hydrochloric acid media is a huge challenge in the chemical industry; hence, creating green and more efficient inhibitors is an urgent task. Furthermore, the increasing amount of solid wastes arising from the municipality and other sources and its disposal consequence has been a major economic and environmental problem. Hence, in this research, the effect of agricultural waste as a natural inhibitor on the carbon steel dissolution in one molar hydrochloric acid solution was studied using electrochemical and surface techniques. The obtained results showed that the corrosion protection potential of the agricultural waste increases with the agricultural waste concentration and an optimum value of 95.92% was achieved at 500 ppm concentration. The waste adsorption on the metallic surface followed the Langmuir adsorption isotherm. The electrochemical impedance spectroscopy test shows that the inhibitor inhibits the metal against corrosion by getting adhered to the carbon steel surface. The scanning electron microscopy analysis proves that in the presence of the inhibitor, the surface of the carbon steel becomes smooth owing to the inhibitive films formed on the metal surface. The results demonstrated that the agricultural waste extract is an excellent green and eco-friendly corrosion inhibitor.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131211400","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}
The unsteady shock dynamics occurring in a numerically simulated unstarting scramjet isolator are examined using a novel model order reduction technique. The key challenges associated with the non-stationary nature of the phenomenon are overcome by leveraging a combination of Empirical Mode Decomposition (EMD) followed by time dependent snapshot shifting. The EMD method serves two purposes: to identify the oscillation modes of the unstarting shock train and to subsequently use the calculated non-stationary residual function to invoke a translating frame of reference that is co-moving with the unstarting shock system. Each snapshot is then shifted into the determined reference frame and subsequently windowed in space, creating a smaller, subset of snapshots from the original database. The windowing is informed by the physics of pseudo-shocks, and has the benefits of ensuring that each new snapshot contains the entire unstarting shock train, while simultaneously preventing the effects of circular shifting that have plagued other model order reduction techniques based on shift operators. When applied to the unstart problem, the shifting and windowing technique presents a more statistically stationary view of the unstarting shock dynamics in the frame of reference of the moving shock train. Dynamically relevant modes associated with upstream and downstream propagating pressure waves at the peak shock oscillation frequency in the boundary layers and separation regions are further extracted from the shifted and windowed snapshots using the sparsity promoting Dynamic Mode Decomposition algorithm.
{"title":"Model Order Reduction of Scramjet Isolator Shock Dynamics During Unstart","authors":"Jack Sullivan, D. Gaitonde","doi":"10.1115/imece2022-94316","DOIUrl":"https://doi.org/10.1115/imece2022-94316","url":null,"abstract":"\u0000 The unsteady shock dynamics occurring in a numerically simulated unstarting scramjet isolator are examined using a novel model order reduction technique. The key challenges associated with the non-stationary nature of the phenomenon are overcome by leveraging a combination of Empirical Mode Decomposition (EMD) followed by time dependent snapshot shifting. The EMD method serves two purposes: to identify the oscillation modes of the unstarting shock train and to subsequently use the calculated non-stationary residual function to invoke a translating frame of reference that is co-moving with the unstarting shock system. Each snapshot is then shifted into the determined reference frame and subsequently windowed in space, creating a smaller, subset of snapshots from the original database. The windowing is informed by the physics of pseudo-shocks, and has the benefits of ensuring that each new snapshot contains the entire unstarting shock train, while simultaneously preventing the effects of circular shifting that have plagued other model order reduction techniques based on shift operators. When applied to the unstart problem, the shifting and windowing technique presents a more statistically stationary view of the unstarting shock dynamics in the frame of reference of the moving shock train. Dynamically relevant modes associated with upstream and downstream propagating pressure waves at the peak shock oscillation frequency in the boundary layers and separation regions are further extracted from the shifted and windowed snapshots using the sparsity promoting Dynamic Mode Decomposition algorithm.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"41 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132389628","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}
Traditional multiscale methods homogenize a beam-like structure into a material point in 1-D continuum with effective properties computed over a structure gene in terms of a cross-section or a 3D segment with spanwise periodicity. Such methods lose accuracy when dealing with real world beam-like structures usually not uniform or periodic along the spanwise direction. Thus, traditional multiscale methods cannot be rigorously applied to these cases. In our previous work, a new multiscale method was proposed based on a novel application of the recently developed Mechanics of Structure Genome (MSG) to analyze beam-like structures. Beam-like structures were homogenized into a series of 3-node Heterogeneous Beam Elements (HBE) with 18 × 18 effective beam element stiffness matrices, which were used as input for one-dimensional beam analyses. However, due to the shape function limitations, HBE could not handle transverse shear loads. In this work, the shape functions and the MSG theory are further modified to enable capabilities of HBE for transverse shear loads. Using the macroscopic behavior of the beam elements as input, dehomogenization can be performed to predict the local stresses and strains in the original structure. Two examples are used (a periodic composite beam and a tapered beam) to demonstrate the capability of this improved HBE.
{"title":"Heterogeneous Beam Element Based on Timoshenko Beam Model","authors":"R. Chiu, Wenbin Yu","doi":"10.1115/imece2022-94187","DOIUrl":"https://doi.org/10.1115/imece2022-94187","url":null,"abstract":"\u0000 Traditional multiscale methods homogenize a beam-like structure into a material point in 1-D continuum with effective properties computed over a structure gene in terms of a cross-section or a 3D segment with spanwise periodicity. Such methods lose accuracy when dealing with real world beam-like structures usually not uniform or periodic along the spanwise direction. Thus, traditional multiscale methods cannot be rigorously applied to these cases. In our previous work, a new multiscale method was proposed based on a novel application of the recently developed Mechanics of Structure Genome (MSG) to analyze beam-like structures. Beam-like structures were homogenized into a series of 3-node Heterogeneous Beam Elements (HBE) with 18 × 18 effective beam element stiffness matrices, which were used as input for one-dimensional beam analyses. However, due to the shape function limitations, HBE could not handle transverse shear loads. In this work, the shape functions and the MSG theory are further modified to enable capabilities of HBE for transverse shear loads. Using the macroscopic behavior of the beam elements as input, dehomogenization can be performed to predict the local stresses and strains in the original structure. Two examples are used (a periodic composite beam and a tapered beam) to demonstrate the capability of this improved HBE.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132462195","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}
A. Sierra, H. Scott, Darwin Pray, Z. Polus, P. Iglesias
Friction and wear are inherent problems in mechanical systems, leading to about 23% world’s total energy usage. However, energy losses could be reduced by up to 40% using high-performance lubricants. In order to meet these objectives, Ionic liquids have been studied for more than two decades. Ionic liquids are a class of synthetic salts with melting points below 100 °C due to their asymmetric chemical structure. This feature confers them remarkably interesting physicochemical properties. Moreover, the delocalized charge in their functional groups enables them to react with metal surfaces through the formation of protective layers that prevent them against contact. Ionic liquids are generally categorized based on the nature of their cation into aprotic ionic liquids and protic ionic liquids. Even though aprotic ionic liquids have been proved as neat lubricants and additives with great performance, their applicability is limited as a consequence of the complexity of their synthesis. On the contrary, protic ionic liquids can be easily obtained through proton transfer from a Brønsted acid to a Brønsted base. In this study, two borate-based PILs, N-methylethanolamine 1,2-dodecanediolborate and N’N-dimethylethanolamine 1,2-dodecanediolborate, were synthesized, with same anion and different ammonium cation. Their lubricating abilities were investigated as neat lubricants on steel-steel contact at room temperature, using a custom-designed ball-on-flat reciprocating tribometer. Each protic ionic liquid was tested using ground and polished steel disks and two levels of normal force and frequency. Results showed that the surface finish have an important influence on the lubricating performance of these ordered fluids. In addition, frequency was found to have an influence on the wear mechanisms on steel surfaces.
{"title":"Effects of Surface Finish and Molecular Structure on the Lubricating Ability of Borate-Based Protic Ionic Liquids","authors":"A. Sierra, H. Scott, Darwin Pray, Z. Polus, P. Iglesias","doi":"10.1115/imece2022-95163","DOIUrl":"https://doi.org/10.1115/imece2022-95163","url":null,"abstract":"\u0000 Friction and wear are inherent problems in mechanical systems, leading to about 23% world’s total energy usage. However, energy losses could be reduced by up to 40% using high-performance lubricants.\u0000 In order to meet these objectives, Ionic liquids have been studied for more than two decades. Ionic liquids are a class of synthetic salts with melting points below 100 °C due to their asymmetric chemical structure. This feature confers them remarkably interesting physicochemical properties. Moreover, the delocalized charge in their functional groups enables them to react with metal surfaces through the formation of protective layers that prevent them against contact. Ionic liquids are generally categorized based on the nature of their cation into aprotic ionic liquids and protic ionic liquids. Even though aprotic ionic liquids have been proved as neat lubricants and additives with great performance, their applicability is limited as a consequence of the complexity of their synthesis. On the contrary, protic ionic liquids can be easily obtained through proton transfer from a Brønsted acid to a Brønsted base.\u0000 In this study, two borate-based PILs, N-methylethanolamine 1,2-dodecanediolborate and N’N-dimethylethanolamine 1,2-dodecanediolborate, were synthesized, with same anion and different ammonium cation. Their lubricating abilities were investigated as neat lubricants on steel-steel contact at room temperature, using a custom-designed ball-on-flat reciprocating tribometer. Each protic ionic liquid was tested using ground and polished steel disks and two levels of normal force and frequency.\u0000 Results showed that the surface finish have an important influence on the lubricating performance of these ordered fluids. In addition, frequency was found to have an influence on the wear mechanisms on steel surfaces.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125614209","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}
Metamaterials are a group of materials with artificial engineered structures that exhibits customized properties which are not naturally available in other materials. To accelerate the computational analysis of components made from metamaterials that helps novel engineering product design process, it is crucial to develop an accurate and robust model for these materials in macroscale. The classical approach to drive a material model in continuum level is based on development of a phenomenological model to represent the physical behaviour of the material. However, this approach has specific limitations in including the effect of tailoring design parameters in the model which is a key element for metamaterials. In this study, we have proposed an artificial neural network (ANN) constitutive model to represent the macroscale mechanical behaviour of metamaterials in three-dimensional domain. Because of its extraordinary capabilities to stimulate computational performance in identifying and constructing prospective microstructure model for mechanical metamaterials, the proposed ANN constitutive model provides intriguing advantages over conventional models. The ANN constitutive model has been trained based on strain-stress data which is obtained from microscale simulation of 3D cubic lattice structure under various loading conditions. The trained material model is then validated by measuring the accuracy of material behaviour prediction.
{"title":"Development of an Artificial Neural Network (ANN) Constitutive Model for Mechanical Metamaterials","authors":"Arif Hussain, A. Sakhaei, M. Shafiee","doi":"10.1115/imece2022-94049","DOIUrl":"https://doi.org/10.1115/imece2022-94049","url":null,"abstract":"\u0000 Metamaterials are a group of materials with artificial engineered structures that exhibits customized properties which are not naturally available in other materials. To accelerate the computational analysis of components made from metamaterials that helps novel engineering product design process, it is crucial to develop an accurate and robust model for these materials in macroscale. The classical approach to drive a material model in continuum level is based on development of a phenomenological model to represent the physical behaviour of the material. However, this approach has specific limitations in including the effect of tailoring design parameters in the model which is a key element for metamaterials. In this study, we have proposed an artificial neural network (ANN) constitutive model to represent the macroscale mechanical behaviour of metamaterials in three-dimensional domain. Because of its extraordinary capabilities to stimulate computational performance in identifying and constructing prospective microstructure model for mechanical metamaterials, the proposed ANN constitutive model provides intriguing advantages over conventional models. The ANN constitutive model has been trained based on strain-stress data which is obtained from microscale simulation of 3D cubic lattice structure under various loading conditions. The trained material model is then validated by measuring the accuracy of material behaviour prediction.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124038360","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}
Senthil Kumar Velukkudi Santhanam, Harinivas Selvaraju, Mystica Augustine Michael Duke
Aluminum Alloy2014 is one of the strongest aluminum alloys and is a copper-based alloy that has a high strength-to-weight ratio. Poor corrosion resistance, porosity, cracking, and element loss makes the alloy difficult to weld in gas and arc welding techniques. To overcome these difficulties, the most suitable method for joining aluminum alloy2014 is Friction Stir Welding. Due to its high strength, aluminum alloy2014 is joined using Friction Stir Welding in aerospace industries in fuel tanks of spaceships and other automotive industries in making complex shapes. In the current study, aluminum alloy2014 alloy is friction stir welded under submerged conditions employing graphene nanofluid. The welding was carried out under the optimized process parameter of tool rotational speed 1200 rpm and a transverse speed of 72 mm/min. A hardened square pin tool of length 5.5 mm and diameter of 4 mm is used for joining the aluminum alloy2014. The graphene nanofluid is developed using the two-step method constituting water as the base fluid. Water is suspended with 0.5 wt% of graphene nanoparticles. In this investigation, Radiography analysis, surface roughness, microhardness, tensile behavior and Facture analysis under two different conditions, normal welding and submerged welding was determined.
{"title":"Evaluation of Weld Quality Through Non-Destructive Testing and Weld Property Analysis of Friction Stir Welded AA2014 Under Submerged Condition","authors":"Senthil Kumar Velukkudi Santhanam, Harinivas Selvaraju, Mystica Augustine Michael Duke","doi":"10.1115/imece2022-94518","DOIUrl":"https://doi.org/10.1115/imece2022-94518","url":null,"abstract":"\u0000 Aluminum Alloy2014 is one of the strongest aluminum alloys and is a copper-based alloy that has a high strength-to-weight ratio. Poor corrosion resistance, porosity, cracking, and element loss makes the alloy difficult to weld in gas and arc welding techniques. To overcome these difficulties, the most suitable method for joining aluminum alloy2014 is Friction Stir Welding. Due to its high strength, aluminum alloy2014 is joined using Friction Stir Welding in aerospace industries in fuel tanks of spaceships and other automotive industries in making complex shapes. In the current study, aluminum alloy2014 alloy is friction stir welded under submerged conditions employing graphene nanofluid. The welding was carried out under the optimized process parameter of tool rotational speed 1200 rpm and a transverse speed of 72 mm/min. A hardened square pin tool of length 5.5 mm and diameter of 4 mm is used for joining the aluminum alloy2014. The graphene nanofluid is developed using the two-step method constituting water as the base fluid. Water is suspended with 0.5 wt% of graphene nanoparticles. In this investigation, Radiography analysis, surface roughness, microhardness, tensile behavior and Facture analysis under two different conditions, normal welding and submerged welding was determined.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124582545","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}
An HVAC water cooling tower utilizes water in the heat transfer process. Occupational Safety and Health Administration (OSHA) mandates that HVAC systems must be cleaned twice a year to prevent pneumatic diseases, which is a costly process. In this work, hydrophobic coatings of Yb2O3, and coatings of TiO2 and TiO2+Cu are tested as potential coatings for water cooling towers. The samples were placed in water splash zones to ensure exposure to sufficient water effects. The samples were placed for 6 months in. One sample of each set was placed in the shade, while another sample was placed in sunlight to examine the different effects. For the TiO2, all samples were placed in sun-exposed areas. During the test, the sample with the prime coating of YSZ and top coating of 50 μm Yb2O3 exhibited the best behavior compared with the rest of the samples coated with bond coating of Cr2O3. As expected, sunlight adversely affected all samples, with an increase in the number of locations with dark stains due to algae formation. In addition, the top coating of Yb2O3 improved the result. For the TiO2 coating, the addition of copper rendered better results, whereas low concentrations of several elements, such as slats, are observed in the samples with the added copper. The results are in a preliminary stage, and a complete antimicrobial analysis is needed.
{"title":"Material Behavior of Hydrophobic Yb2O3 and Photocatalytic TiO2 Coatings in HVAC Water Cooling Towers: A Case Study","authors":"K. Al-Athel, Turky M. Aldossary, S. S. Akhtar","doi":"10.1115/imece2022-95726","DOIUrl":"https://doi.org/10.1115/imece2022-95726","url":null,"abstract":"\u0000 An HVAC water cooling tower utilizes water in the heat transfer process. Occupational Safety and Health Administration (OSHA) mandates that HVAC systems must be cleaned twice a year to prevent pneumatic diseases, which is a costly process. In this work, hydrophobic coatings of Yb2O3, and coatings of TiO2 and TiO2+Cu are tested as potential coatings for water cooling towers. The samples were placed in water splash zones to ensure exposure to sufficient water effects. The samples were placed for 6 months in. One sample of each set was placed in the shade, while another sample was placed in sunlight to examine the different effects. For the TiO2, all samples were placed in sun-exposed areas.\u0000 During the test, the sample with the prime coating of YSZ and top coating of 50 μm Yb2O3 exhibited the best behavior compared with the rest of the samples coated with bond coating of Cr2O3. As expected, sunlight adversely affected all samples, with an increase in the number of locations with dark stains due to algae formation. In addition, the top coating of Yb2O3 improved the result. For the TiO2 coating, the addition of copper rendered better results, whereas low concentrations of several elements, such as slats, are observed in the samples with the added copper. The results are in a preliminary stage, and a complete antimicrobial analysis is needed.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127892871","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}
Visual Simultaneous Localization and Mapping (V-SLAM) is a trending robotics research concept as well as the basis for autonomous and smart navigation. It is an integral part of vision-based applications which include virtual reality, unmanned aerial vehicles, augmented reality, and unmanned ground vehicles. V-SLAM carries out localization and mapping by learning relevant feature points from images and estimating their pose based on the correlation between the camera and the feature points. It also represents the ability of a robot to effectively navigate itself, employing visual sensors and prior information of the given location, in an uncharted environment while updating and constructing a coordinated map of the scene. However, due to the challenges of data association triggered by illumination, different viewpoints and environment dynamics, there has been rapid adoption of deep learning in the area of feature extraction/description, pose/depth estimation, mapping, loop closure detection and global optimization as it concerns visual SLAM. This paper sets out to elucidate diverse applications of supervised and unsupervised deep learning methods in all aspects of visual SLAM. It also briefly explains a case study regarding the application of both deep learning and SLAM for underground mining applications. It highlights recent research developments in addition to limitations hindering their effective application and investigates how a combination of deep learning with other methods offers a promising direction for visual SLAM research.
{"title":"Supervised and Unsupervised Deep Learning Applications for Visual SLAM: A Review","authors":"U. Ukaegbu, L. Tartibu, Chee Wah Lim","doi":"10.1115/imece2022-95685","DOIUrl":"https://doi.org/10.1115/imece2022-95685","url":null,"abstract":"\u0000 Visual Simultaneous Localization and Mapping (V-SLAM) is a trending robotics research concept as well as the basis for autonomous and smart navigation. It is an integral part of vision-based applications which include virtual reality, unmanned aerial vehicles, augmented reality, and unmanned ground vehicles. V-SLAM carries out localization and mapping by learning relevant feature points from images and estimating their pose based on the correlation between the camera and the feature points. It also represents the ability of a robot to effectively navigate itself, employing visual sensors and prior information of the given location, in an uncharted environment while updating and constructing a coordinated map of the scene. However, due to the challenges of data association triggered by illumination, different viewpoints and environment dynamics, there has been rapid adoption of deep learning in the area of feature extraction/description, pose/depth estimation, mapping, loop closure detection and global optimization as it concerns visual SLAM. This paper sets out to elucidate diverse applications of supervised and unsupervised deep learning methods in all aspects of visual SLAM. It also briefly explains a case study regarding the application of both deep learning and SLAM for underground mining applications. It highlights recent research developments in addition to limitations hindering their effective application and investigates how a combination of deep learning with other methods offers a promising direction for visual SLAM research.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128010406","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：