Currently, there is a growing tendency to incorporate natural fibers in composites due to their affordability, lightweight nature, and eco-friendliness. Researchers are continuously exploring new materials that offer improved mechanical properties for a broader range of applications. In this work, an experimental investigation on tensile and fatigue behavior of jute-wool felt-reinforced epoxy hybrid laminate is carried, in addition to an E-glass fiber-reinforced epoxy laminate that helps in comparison. Constant amplitude tensile fatigue test is conducted for 80%, 70%, and 60% of the ultimate load of respective composites at a stress ratio of 0.1 and frequency of 7 Hz for both laminates. The jute-wool felt composite showed good fatigue resistance. Though glass fiber composite showed higher tensile strength, jute-wool felt composite exhibits higher fatigue performance than glass fiber composites at higher stress levels. However, at lower stress levels, glass fiber composite shows better fatigue resistance than jute-wool felt composite. A prediction model that uses a few set of experimental results of fatigue test was able to validate the fatigue behavior of composites. The optical microscope images of failed samples were analyzed to detect the damage in composites.
{"title":"Comparative Study on the Fatigue Behavior of Jute-Wool Felt/Epoxy\u0000 Hybrid and Glass Fiber/Epoxy Composite","authors":"Sanjay Thilakan, N. Mathivanan","doi":"10.4271/05-16-04-0024","DOIUrl":"https://doi.org/10.4271/05-16-04-0024","url":null,"abstract":"Currently, there is a growing tendency to incorporate natural fibers in\u0000 composites due to their affordability, lightweight nature, and eco-friendliness.\u0000 Researchers are continuously exploring new materials that offer improved\u0000 mechanical properties for a broader range of applications. In this work, an\u0000 experimental investigation on tensile and fatigue behavior of jute-wool\u0000 felt-reinforced epoxy hybrid laminate is carried, in addition to an E-glass\u0000 fiber-reinforced epoxy laminate that helps in comparison. Constant amplitude\u0000 tensile fatigue test is conducted for 80%, 70%, and 60% of the ultimate load of\u0000 respective composites at a stress ratio of 0.1 and frequency of 7 Hz for both\u0000 laminates. The jute-wool felt composite showed good fatigue resistance. Though\u0000 glass fiber composite showed higher tensile strength, jute-wool felt composite\u0000 exhibits higher fatigue performance than glass fiber composites at higher stress\u0000 levels. However, at lower stress levels, glass fiber composite shows better\u0000 fatigue resistance than jute-wool felt composite. A prediction model that uses a\u0000 few set of experimental results of fatigue test was able to validate the fatigue\u0000 behavior of composites. The optical microscope images of failed samples were\u0000 analyzed to detect the damage in composites.","PeriodicalId":45859,"journal":{"name":"SAE International Journal of Materials and Manufacturing","volume":"14 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81799916","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}
Vijay Pendhota, K. Brahma Raju, K. Ramji, S. Kamaluddin
Aluminum hybrid composites are driving a new trend in metal matrix composites for high strength-to-weight ratio applications such as the automotive industry (piston–cylinder, brakes, shafts), aircraft (engines, airframe), aerospace (space panels), and marine (body frame). Al 6061 is chosen as the matrix for its compatibility and excellent castability in the current work. The reinforcements were silicon carbide (SiC) of size 65μ and tungsten carbide (WC) of 3–5μ due to their enhancing mechanical and corrosion behavior with low density. Composites were prepared through stir casting using different quantities of SiC wt.% 10 and 15, while WC is 0–6% by weight in 2% increments. The results show that mechanical properties such as tensile strength and hardness enhanced due to the gradual strengthening of grains leads to high wear resistance. SEM images of tensile failure show that pits, voids, cracks, burrs, and grain fractures characterize composite failure. Corrosion tests show that the 15% SiC/6% WC composite has higher corrosion resistance than the 10% SiC composite. The corroded surface morphology indicates that the pit size of Al 6061/SiC 15%/WC 0–6% composites decreases with increasing WC weight %.
{"title":"Effect of Silicon Carbide/Tungsten Carbide on Mechanical and\u0000 Corrosion Properties of Aluminum 6061 Hybrid Metal Matrix\u0000 Composites","authors":"Vijay Pendhota, K. Brahma Raju, K. Ramji, S. Kamaluddin","doi":"10.4271/05-16-04-0023","DOIUrl":"https://doi.org/10.4271/05-16-04-0023","url":null,"abstract":"Aluminum hybrid composites are driving a new trend in metal matrix composites for\u0000 high strength-to-weight ratio applications such as the automotive industry\u0000 (piston–cylinder, brakes, shafts), aircraft (engines, airframe), aerospace\u0000 (space panels), and marine (body frame). Al 6061 is chosen as the matrix for its\u0000 compatibility and excellent castability in the current work. The reinforcements\u0000 were silicon carbide (SiC) of size 65μ and tungsten carbide (WC) of 3–5μ due to\u0000 their enhancing mechanical and corrosion behavior with low density. Composites\u0000 were prepared through stir casting using different quantities of SiC wt.% 10 and\u0000 15, while WC is 0–6% by weight in 2% increments. The results show that\u0000 mechanical properties such as tensile strength and hardness enhanced due to the\u0000 gradual strengthening of grains leads to high wear resistance. SEM images of\u0000 tensile failure show that pits, voids, cracks, burrs, and grain fractures\u0000 characterize composite failure. Corrosion tests show that the 15% SiC/6% WC\u0000 composite has higher corrosion resistance than the 10% SiC composite. The\u0000 corroded surface morphology indicates that the pit size of Al 6061/SiC 15%/WC\u0000 0–6% composites decreases with increasing WC weight %.","PeriodicalId":45859,"journal":{"name":"SAE International Journal of Materials and Manufacturing","volume":"1 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81665932","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}
Prediction of the surface finish of hardened bearing steels was estimated in machining with ceramic uncoated cutting tools under various process parameters using two statistical approaches. A second-order (quadratic) regression model (MQR, multiple quantile regression) for the surface finish was developed and then compared with the artificial neural network (ANN) method based on the coefficient determination (R 2), root mean square error (RMSE), and percentage error (PE). The experimental results exhibited that cutting speed was the dominant parameter, but feed rate and depth of cut were insignificant in terms of the Pareto chart and analysis of variance (ANOVA). The optimum surface finish in machining bearing steel was achieved at 100 m/min speed, 0.1 mm/revolution (rev) feed rate, and 0.6 mm depth of cut. In addition, the ANN model revealed a better performance than that of MQR for predicting the surface finish when machining the hardened bearing steels because R 2 was about 0.787 and 0.903 for MQR and ANN, respectively. Besides, these were associated with RMSE of 0.302 and 0.1071 for MQR and ANN. Further, PE estimated from randomly selected data were about 25.56% and 10.86% for MQR and ANN, respectively. However, MQR presented the lowest error of 2.86%, but the highest error of 40.3%, while ANN indicated the lowest error of 0.11%, but the highest error of 37.0%, respectively.
{"title":"Prediction of Surface Finish on Hardened Bearing Steel Machined by\u0000 Ceramic Cutting Tool","authors":"Y. Şahin","doi":"10.4271/05-16-03-0021","DOIUrl":"https://doi.org/10.4271/05-16-03-0021","url":null,"abstract":"Prediction of the surface finish of hardened bearing steels was estimated in\u0000 machining with ceramic uncoated cutting tools under various process parameters\u0000 using two statistical approaches. A second-order (quadratic) regression model\u0000 (MQR, multiple quantile regression) for the surface finish was developed and\u0000 then compared with the artificial neural network (ANN) method based on the\u0000 coefficient determination (R\u0000 2), root mean square error (RMSE), and percentage error (PE). The\u0000 experimental results exhibited that cutting speed was the dominant parameter,\u0000 but feed rate and depth of cut were insignificant in terms of the Pareto chart\u0000 and analysis of variance (ANOVA). The optimum surface finish in machining\u0000 bearing steel was achieved at 100 m/min speed, 0.1 mm/revolution (rev) feed\u0000 rate, and 0.6 mm depth of cut. In addition, the ANN model revealed a better\u0000 performance than that of MQR for predicting the surface finish when machining\u0000 the hardened bearing steels because R\u0000 2 was about 0.787 and 0.903 for MQR and ANN, respectively. Besides,\u0000 these were associated with RMSE of 0.302 and 0.1071 for MQR and ANN. Further, PE\u0000 estimated from randomly selected data were about 25.56% and 10.86% for MQR and\u0000 ANN, respectively. However, MQR presented the lowest error of 2.86%, but the\u0000 highest error of 40.3%, while ANN indicated the lowest error of 0.11%, but the\u0000 highest error of 37.0%, respectively.","PeriodicalId":45859,"journal":{"name":"SAE International Journal of Materials and Manufacturing","volume":"44 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90528860","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}
Abdallah Sadki, R. Younes, M. A. Bradai, N. Mesrati
The present investigation has been conducted to study the tribological and adhesion properties of X10CrNi18-8 austenitic stainless steel (ASTM 301) coatings deposited on aluminum alloys such as AU4G by using the arc-spraying process. These coatings were made with and without a bond-coat layer, which is constituted by NiAl. The structure of the phases that are present in coatings was characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The measurements of microhardness and tribological behavior at different loads were also performed on the surface of the coatings. Adherence test was also carried out using four-point bending tests. The SEM showed that the dense microstructures of coatings have a homogeneous lamellar morphology with the presence of porosities and unmelted particles. The main phase of coating corresponds to a solid solution as a face-centered cubic (fcc). The microhardness of coatings is nearly four times that of the two substrates of aluminum alloys. The four-point bending test results showed that the NiAl bond layer increases the critical interfacial fracture energy G IC, the force to share the multilayer is more important.
{"title":"Effect of NiAl Bond Layer on the Wear Resistance of an Austenitic\u0000 Stainless Steel Coating Obtained by Arc Spray Process","authors":"Abdallah Sadki, R. Younes, M. A. Bradai, N. Mesrati","doi":"10.4271/05-16-04-0022","DOIUrl":"https://doi.org/10.4271/05-16-04-0022","url":null,"abstract":"The present investigation has been conducted to study the tribological and\u0000 adhesion properties of X10CrNi18-8 austenitic stainless steel (ASTM 301)\u0000 coatings deposited on aluminum alloys such as AU4G by using the arc-spraying\u0000 process. These coatings were made with and without a bond-coat layer, which is\u0000 constituted by NiAl. The structure of the phases that are present in coatings\u0000 was characterized by X-ray diffraction (XRD) and scanning electron microscopy\u0000 (SEM). The measurements of microhardness and tribological behavior at different\u0000 loads were also performed on the surface of the coatings. Adherence test was\u0000 also carried out using four-point bending tests. The SEM showed that the dense\u0000 microstructures of coatings have a homogeneous lamellar morphology with the\u0000 presence of porosities and unmelted particles. The main phase of coating\u0000 corresponds to a solid solution as a face-centered cubic (fcc). The\u0000 microhardness of coatings is nearly four times that of the two substrates of\u0000 aluminum alloys. The four-point bending test results showed that the NiAl bond\u0000 layer increases the critical interfacial fracture energy G\u0000 IC, the force to share the multilayer is more important.","PeriodicalId":45859,"journal":{"name":"SAE International Journal of Materials and Manufacturing","volume":"16 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90688925","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}
Fiber-reinforced composites are widely used in injection molding processes because of their high strength and high elastic modulus. However, the addition of reinforcing agents such as glass fibers has a significant impact on their injection molding quality. The difference in shrinkage and hardness between the plastic and the reinforcement will bring about warpage and deformation in the injection molding of the product. At the same time, the glass fibers will be oriented in the flow direction during the injection molding process. This will enhance the mechanical properties in the flow direction and increase the shrinkage in the vertical direction, reducing the molding quality of the product. In this study, a test program was developed based on the Box-Behnken test design in the Design-Expert software, using a plastic part as an example. Moldflow software was used for simulation, and data analysis of the experimental data was carried out to investigate the significance of the influence of each injection molding process parameter on the molding quality. In addition to this, a mathematical model between the injection molding process parameters and the quality objectives was established by optimizing the model parameters of the back-propagation (BP) neural network through the ant colony optimization (ACO) algorithm. The established mathematical model is then globally optimized using a multi-objective function optimization based on the non-dominated rank-based sorting genetic algorithm (NSGA-II) to obtain the optimal combination of process parameters. The research in this article provides a theoretical basis for further combining intelligent algorithms to improve injection molding quality.
{"title":"Predicting and Controlling the Quality of Injection Molding\u0000 Properties for Fiber-Reinforced Composites","authors":"Dezhao Wang, Xiying Fan, Y. Guo, Xiangning Lu, Changjing Wang, Wenjie Ding","doi":"10.4271/05-16-03-0020","DOIUrl":"https://doi.org/10.4271/05-16-03-0020","url":null,"abstract":"Fiber-reinforced composites are widely used in injection molding processes\u0000 because of their high strength and high elastic modulus. However, the addition\u0000 of reinforcing agents such as glass fibers has a significant impact on their\u0000 injection molding quality. The difference in shrinkage and hardness between the\u0000 plastic and the reinforcement will bring about warpage and deformation in the\u0000 injection molding of the product. At the same time, the glass fibers will be\u0000 oriented in the flow direction during the injection molding process. This will\u0000 enhance the mechanical properties in the flow direction and increase the\u0000 shrinkage in the vertical direction, reducing the molding quality of the\u0000 product. In this study, a test program was developed based on the Box-Behnken\u0000 test design in the Design-Expert software, using a plastic part as an example.\u0000 Moldflow software was used for simulation, and data analysis of the experimental\u0000 data was carried out to investigate the significance of the influence of each\u0000 injection molding process parameter on the molding quality. In addition to this,\u0000 a mathematical model between the injection molding process parameters and the\u0000 quality objectives was established by optimizing the model parameters of the\u0000 back-propagation (BP) neural network through the ant colony optimization (ACO)\u0000 algorithm. The established mathematical model is then globally optimized using a\u0000 multi-objective function optimization based on the non-dominated rank-based\u0000 sorting genetic algorithm (NSGA-II) to obtain the optimal combination of process\u0000 parameters. The research in this article provides a theoretical basis for\u0000 further combining intelligent algorithms to improve injection molding\u0000 quality.","PeriodicalId":45859,"journal":{"name":"SAE International Journal of Materials and Manufacturing","volume":"1 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89834127","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}
With the introduction of advanced lightweight materials with complex microstructures and behaviors, more focus is put on the accurate determination of their forming limits, and that can only be possible through experiments as the conventional theoretical models for the forming limit curve (FLC) prediction fail to perform. Despite that, CAE engineers, designers, and toolmakers still rely heavily on theoretical models due to the steep costs associated with formability testing, including mechanical setup, a large number of tests, and the cost of a stereo digital image correlation (DIC) system. The international standard ISO 12004-2:2021 recommends using a stereo DIC system for formability testing since two-dimensional (2D) DIC systems are considered incapable of producing reliable strains due to errors associated with out-of-plane motion and deformation. This work challenges that notion and proposes a simple strain compensation method for the determination of FLCs using a low-cost single-camera (2D) DIC system. In this study, formability tests are performed on an automotive-grade 6xxx series aluminum alloy using the Marciniak in-plane FLC testing method. The tests are performed on a custom setup that enables simultaneous optical strain measurements using a stereo DIC as well as a 2D DIC system. The results show how 2D DIC FLC points match those obtained by stereo DIC using two popular FLC approaches: ISO 12004-2 section-based spatial method and a time-dependent linear best fit (LBF) method.
{"title":"A Method for Measuring In-Plane Forming Limit Curves Using 2D Digital\u0000 Image Correlation","authors":"Akshat Agha, F. Abu-Farha","doi":"10.4271/05-16-03-0019","DOIUrl":"https://doi.org/10.4271/05-16-03-0019","url":null,"abstract":"With the introduction of advanced lightweight materials with complex\u0000 microstructures and behaviors, more focus is put on the accurate determination\u0000 of their forming limits, and that can only be possible through experiments as\u0000 the conventional theoretical models for the forming limit curve (FLC) prediction\u0000 fail to perform. Despite that, CAE engineers, designers, and toolmakers still\u0000 rely heavily on theoretical models due to the steep costs associated with\u0000 formability testing, including mechanical setup, a large number of tests, and\u0000 the cost of a stereo digital image correlation (DIC) system. The international\u0000 standard ISO 12004-2:2021 recommends using a stereo DIC system for formability\u0000 testing since two-dimensional (2D) DIC systems are considered incapable of\u0000 producing reliable strains due to errors associated with out-of-plane motion and\u0000 deformation. This work challenges that notion and proposes a simple strain\u0000 compensation method for the determination of FLCs using a low-cost single-camera\u0000 (2D) DIC system. In this study, formability tests are performed on an\u0000 automotive-grade 6xxx series aluminum alloy using the Marciniak in-plane FLC\u0000 testing method. The tests are performed on a custom setup that enables\u0000 simultaneous optical strain measurements using a stereo DIC as well as a 2D DIC\u0000 system. The results show how 2D DIC FLC points match those obtained by stereo\u0000 DIC using two popular FLC approaches: ISO 12004-2 section-based spatial method\u0000 and a time-dependent linear best fit (LBF) method.","PeriodicalId":45859,"journal":{"name":"SAE International Journal of Materials and Manufacturing","volume":"18 2 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86319909","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 comprehensive literature review of the optimization techniques used for the process parameter optimization of Abrasive Jet Machining (AJM), Ultrasonic Machining (USM), Laser Beam Machining (LBM), Electrochemical Machining (ECM), and Plasma Arc Machining (PAM) are presented in this review article. This review article is an extension of the review work carried out by previous researchers for the process parameter optimization of non-traditional machining processes using various advanced optimization algorithms. The review period considered for the same is from 2012 to 2022. The prime motive of this review article is to find out the sanguine effects of various optimization techniques used for the optimization of various considered objectives of selected non-traditional machining processes in addition to deemed materials and foremost process parameters. It is found that most of the researchers have more inclination towards the minimization of Surface Roughness (SR) compared to the maximization of the Material Removal Rate (MRR) as their objective function for AJM and PAM. Similarly, for USM and ECM, researchers are more inclined towards the maximization of MRR compared to the minimization of SR. Minimization of the Heat-Affected Zone (HAZ) and SR are the two most considered response parameters for the LBM and its allied processes. This study provides ready-to-use details on the use of various advanced optimization techniques for AJM, USM, LBM, ECM, and PAM, with the considered workpiece material, process parameters, and imposed limitations. This review work is carried out on such a large scale that it will help future researchers and industrialists to decide their research direction.
{"title":"Process Parameter Optimization of Abrasive Jet, Ultrasonic, Laser\u0000 Beam, Electrochemical, and Plasma Arc Machining Processes Using Optimization\u0000 Techniques: A Review","authors":"A. Pandey, Ankit Saroj, Anshuman Srivastava","doi":"10.4271/05-16-03-0018","DOIUrl":"https://doi.org/10.4271/05-16-03-0018","url":null,"abstract":"A comprehensive literature review of the optimization techniques used for the\u0000 process parameter optimization of Abrasive Jet Machining (AJM), Ultrasonic\u0000 Machining (USM), Laser Beam Machining (LBM), Electrochemical Machining (ECM),\u0000 and Plasma Arc Machining (PAM) are presented in this review article. This review\u0000 article is an extension of the review work carried out by previous researchers\u0000 for the process parameter optimization of non-traditional machining processes\u0000 using various advanced optimization algorithms. The review period considered for\u0000 the same is from 2012 to 2022. The prime motive of this review article is to\u0000 find out the sanguine effects of various optimization techniques used for the\u0000 optimization of various considered objectives of selected non-traditional\u0000 machining processes in addition to deemed materials and foremost process\u0000 parameters. It is found that most of the researchers have more inclination\u0000 towards the minimization of Surface Roughness (SR) compared to the maximization\u0000 of the Material Removal Rate (MRR) as their objective function for AJM and PAM.\u0000 Similarly, for USM and ECM, researchers are more inclined towards the\u0000 maximization of MRR compared to the minimization of SR. Minimization of the\u0000 Heat-Affected Zone (HAZ) and SR are the two most considered response parameters\u0000 for the LBM and its allied processes. This study provides ready-to-use details\u0000 on the use of various advanced optimization techniques for AJM, USM, LBM, ECM,\u0000 and PAM, with the considered workpiece material, process parameters, and imposed\u0000 limitations. This review work is carried out on such a large scale that it will\u0000 help future researchers and industrialists to decide their research\u0000 direction.","PeriodicalId":45859,"journal":{"name":"SAE International Journal of Materials and Manufacturing","volume":"59 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74217431","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 article describes the research work taken to compare the effect of air blast and surface-buried mine blast loading on an armored fighting vehicle (AFV) escape hatch, using the coupled Eulerian-Lagrangian (CEL) technique. Two types of escape hatch were considered for the study, namely, the flat plate version and double-side curved-plate version. To evaluate the research methodology used in this investigation, initially, a published experimental work on a circular plate subjected to air blast was chosen and a benchmark simulation was carried out using the CEL technique to establish the simulation procedure. Then the established procedure was utilized for further analysis. It was observed that the variation in the deformation between the published literature and the simulation work was well within the acceptable engineering limits. After that, numerical studies were conducted on the flat and double-side curved hatch by subjecting it to both air blast and surface-buried mine blast loading using the previously established CEL technique. The results of the peak central deflection of the hatch and the transmitted impulse to the base structure were compared for each type of loading case. It was systematically established that the double-side curved hatch gives better protection to the crew against both air blast loading and surface-buried mine blast loading situations.
{"title":"Numerical Analysis of Armored Fighting Vehicle Escape Hatch Subjected\u0000 to Mine Blast Loading Using Coupled Eulerian-Lagrangian\u0000 Technique","authors":"Sundaresan Parthasarathy, J. R. Kumar","doi":"10.4271/05-16-03-0017","DOIUrl":"https://doi.org/10.4271/05-16-03-0017","url":null,"abstract":"This article describes the research work taken to compare the effect of air blast\u0000 and surface-buried mine blast loading on an armored fighting vehicle (AFV)\u0000 escape hatch, using the coupled Eulerian-Lagrangian (CEL) technique. Two types\u0000 of escape hatch were considered for the study, namely, the flat plate version\u0000 and double-side curved-plate version. To evaluate the research methodology used\u0000 in this investigation, initially, a published experimental work on a circular\u0000 plate subjected to air blast was chosen and a benchmark simulation was carried\u0000 out using the CEL technique to establish the simulation procedure. Then the\u0000 established procedure was utilized for further analysis. It was observed that\u0000 the variation in the deformation between the published literature and the\u0000 simulation work was well within the acceptable engineering limits. After that,\u0000 numerical studies were conducted on the flat and double-side curved hatch by\u0000 subjecting it to both air blast and surface-buried mine blast loading using the\u0000 previously established CEL technique. The results of the peak central deflection\u0000 of the hatch and the transmitted impulse to the base structure were compared for\u0000 each type of loading case. It was systematically established that the\u0000 double-side curved hatch gives better protection to the crew against both air\u0000 blast loading and surface-buried mine blast loading situations.","PeriodicalId":45859,"journal":{"name":"SAE International Journal of Materials and Manufacturing","volume":"51 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80395291","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. Javidinejad, Hunter J. Orensztein, M. Ramírez, Jack I. Berman
{"title":"Applications of the Finite Element Analysis for Determination of\u0000 Failure Safety Margins of the Design of the Honda CTX700 Motorcycle Front\u0000 Braking System","authors":"A. Javidinejad, Hunter J. Orensztein, M. Ramírez, Jack I. Berman","doi":"10.4271/05-16-03-0016","DOIUrl":"https://doi.org/10.4271/05-16-03-0016","url":null,"abstract":"","PeriodicalId":45859,"journal":{"name":"SAE International Journal of Materials and Manufacturing","volume":"16 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80121994","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}
{"title":"Optimization of Crane Telescopic Boom Structure Based on Finite\u0000 Element Software","authors":"Chao Wang, B. Xing","doi":"10.4271/05-16-02-0015","DOIUrl":"https://doi.org/10.4271/05-16-02-0015","url":null,"abstract":"","PeriodicalId":45859,"journal":{"name":"SAE International Journal of Materials and Manufacturing","volume":"5 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89785934","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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