Isaiah Yasko, Lloyd Furuta, C. Fais, Muhammad Ali, B. Wisner
This work investigates the use of carbon fiber filled polyamide filament as feedstock material for fused filament fabrication of hydrodynamic tapered-land thrust bearings. Experimental analysis was conducted on fused filament fabricated carbon fiber filled polyamide samples to obtain elastic properties and thermal expansion coefficients along the longitudinal and transverse directions with respect to the print orientation. Single bearing pads were modeled using the obtained mechanical properties and were then analyzed under in-service bearing operating pressures and temperatures. Thermo-mechanical analysis conducted in ABAQUS/CAE shows that taper geometry forms on both [0,90] and [0,0,90] print orientations with depths of 174 μm and 260 μm as a result of thermal expansion occurring from the heat load produced during hydrodynamic bearing operation.
{"title":"Thermo-Mechanical Analysis of a Composite Tapered-Land Hydrodynamic Thrust Bearing Sector Manufactured Using Fused Filament Fabrication","authors":"Isaiah Yasko, Lloyd Furuta, C. Fais, Muhammad Ali, B. Wisner","doi":"10.1115/imece2022-94853","DOIUrl":"https://doi.org/10.1115/imece2022-94853","url":null,"abstract":"This work investigates the use of carbon fiber filled polyamide filament as feedstock material for fused filament fabrication of hydrodynamic tapered-land thrust bearings. Experimental analysis was conducted on fused filament fabricated carbon fiber filled polyamide samples to obtain elastic properties and thermal expansion coefficients along the longitudinal and transverse directions with respect to the print orientation. Single bearing pads were modeled using the obtained mechanical properties and were then analyzed under in-service bearing operating pressures and temperatures. Thermo-mechanical analysis conducted in ABAQUS/CAE shows that taper geometry forms on both [0,90] and [0,0,90] print orientations with depths of 174 μm and 260 μm as a result of thermal expansion occurring from the heat load produced during hydrodynamic bearing operation.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"51 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":"121982722","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 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}
Ahmed H. Hegazy, Mahmoud E. Abd El-Latief, Omar Khalaf, M. Shazly
Composite materials, nowadays, are being used heavily in many industrial applications such as renewable energy, aerospace, and automotive. With the increased production rates, companies relying on the GFRP do not recycle it due to monetary issues using chemical or thermal methods which make it more expensive. Glass fiber recycling methods are mainly divided into mechanical, chemical, and thermal methods. Mechanical recycling involves the reduction in the size of the composite waste into different sizes and different forms such as large particles, small particles, and powder. In the present study, glass/epoxy composite wastes were mechanically recycled by shredding the bulk material. Small particles (< 1mm) and powder recyclates were used as a filler to improve the interlaminar fracture toughness of glass/epoxy composite while large particles (> 1mm) were used as a sandwich-like composite along with chopped strand fiberglass mats. For 25% concentration, samples with 4.75mm particles have improved flexural strength compared to samples with 1.25mm particles. For finer recyclates, it was found that for filler size 600μm and 5% concentration, GIIC was 85% higher than original coupons with higher flexural strength. For filler size 100μm, the performance was enhanced compared to original coupons by increasing the concentrations from 5% to 10%.
{"title":"Evaluation of Graded Recycled Glass/Epoxy Composite","authors":"Ahmed H. Hegazy, Mahmoud E. Abd El-Latief, Omar Khalaf, M. Shazly","doi":"10.1115/imece2022-95733","DOIUrl":"https://doi.org/10.1115/imece2022-95733","url":null,"abstract":"\u0000 Composite materials, nowadays, are being used heavily in many industrial applications such as renewable energy, aerospace, and automotive. With the increased production rates, companies relying on the GFRP do not recycle it due to monetary issues using chemical or thermal methods which make it more expensive. Glass fiber recycling methods are mainly divided into mechanical, chemical, and thermal methods. Mechanical recycling involves the reduction in the size of the composite waste into different sizes and different forms such as large particles, small particles, and powder. In the present study, glass/epoxy composite wastes were mechanically recycled by shredding the bulk material. Small particles (< 1mm) and powder recyclates were used as a filler to improve the interlaminar fracture toughness of glass/epoxy composite while large particles (> 1mm) were used as a sandwich-like composite along with chopped strand fiberglass mats. For 25% concentration, samples with 4.75mm particles have improved flexural strength compared to samples with 1.25mm particles. For finer recyclates, it was found that for filler size 600μm and 5% concentration, GIIC was 85% higher than original coupons with higher flexural strength. For filler size 100μm, the performance was enhanced compared to original coupons by increasing the concentrations from 5% to 10%.","PeriodicalId":146276,"journal":{"name":"Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology","volume":"167 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":"115768181","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}
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}
Reinforced polymer composite materials are widely used in several areas of aerospace, other civilian structures, in view of tailor-suiting to the design requirements. During service, barely visible damages are induced due to accidental tool drops, hail storms and bird strikes, and they can propagate due to fatigue cycles applied during a mission. The damage progression can result in loss of load carrying capacity and ultimate failure. Damage progression due to fatigue in composites has been an important aspect of study as it can result in loss of load carrying capacity and ultimate failure. In this study, the stiffness degradation in a quasi-isotropic carbon fiber polymer composite specimen subjected to FALSTAFF (Fighter Aircraft Loading Standard for Fatigue) spectrum was assessed, after it has been subjected to a drop-impact. Fatigue test was carried out post-impact till specimen failure, which meant testing over several days. The unloading stiffness of the specimen was estimated from the load versus displacement data that was recorded after every block of FALSTAFF loading. It is observed that the stiffness of the specimen degrades with the progression of damage. An Infrared thermal imaging camera (TIM 160 from MicroEpsilon, Germany) was used in passive mode to monitor the temperature changes in the specimen during fatigue cycling. In view of the long duration of fatigue test spanning several days and IR camera cooling requirements, the test was periodically interrupted after certain blocks of FALSTAFF loading. Temperature data during fatigue cycling was compared with stiffness degradation to understand the fatigue damage progression in specimens. The first derivative of temperature response data was found to have a reasonable correlation with the first derivative of stiffness.
{"title":"Studies on Fatigue Damage Progression in Post-Impacted CFRP Composite Through Passive Thermography and Stiffness Measurement","authors":"R. Prakash","doi":"10.1115/imece2022-95102","DOIUrl":"https://doi.org/10.1115/imece2022-95102","url":null,"abstract":"\u0000 Reinforced polymer composite materials are widely used in several areas of aerospace, other civilian structures, in view of tailor-suiting to the design requirements. During service, barely visible damages are induced due to accidental tool drops, hail storms and bird strikes, and they can propagate due to fatigue cycles applied during a mission. The damage progression can result in loss of load carrying capacity and ultimate failure. Damage progression due to fatigue in composites has been an important aspect of study as it can result in loss of load carrying capacity and ultimate failure.\u0000 In this study, the stiffness degradation in a quasi-isotropic carbon fiber polymer composite specimen subjected to FALSTAFF (Fighter Aircraft Loading Standard for Fatigue) spectrum was assessed, after it has been subjected to a drop-impact. Fatigue test was carried out post-impact till specimen failure, which meant testing over several days. The unloading stiffness of the specimen was estimated from the load versus displacement data that was recorded after every block of FALSTAFF loading. It is observed that the stiffness of the specimen degrades with the progression of damage.\u0000 An Infrared thermal imaging camera (TIM 160 from MicroEpsilon, Germany) was used in passive mode to monitor the temperature changes in the specimen during fatigue cycling. In view of the long duration of fatigue test spanning several days and IR camera cooling requirements, the test was periodically interrupted after certain blocks of FALSTAFF loading. Temperature data during fatigue cycling was compared with stiffness degradation to understand the fatigue damage progression in specimens. The first derivative of temperature response data was found to have a reasonable correlation with the first derivative of stiffness.","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":"126304611","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}
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