Pub Date : 2024-08-08DOI: 10.3389/fmech.2024.1427388
Idayatou Oroun’Gobi, Chen Guang Guo
This research is based on the modeling, internal structure analysis, and automation of a cassava grinding machine. For the design, the single-cylinder grinder was chosen due to its advantages, notably simplicity and versatility. The grinding method used in this type of grinder is compression. The mechanical design and simulation software first allowed for the design of the grinder and then for performing static analyses under three loads (P1 = 10000N, P2 = 15000N, and P3 = 20000N). The results of these tests led to the selection of P3 = 20000N as the straightening load, with a maximum stress value in the static analysis of 88,18 MPa and a maximum deformation of 0,000358 under the force of load P3. Additionally, the frequency analysis distinguished five resonance modes. The results for each mode concluded that no resonance would affect the machine, thus ensuring stable operation. Furthermore, fatigue, frequency, and safety factor studies showed that the machine could withstand a load of m3 = 2000 kg without damage, with a service life of 1e+09 cycles. Considering the total number of life cycles, which is 1e+09 cycles, this means that the machine will have a service life of 347000 years, with a total grinding output of 2e+12 kg of cassava and 5840000 kg per year. The factor of safety is FoS = 1,78, indicating a sufficient margin for safe operating conditions. The automation of the grinder was carried out using a GRAFCET model and a sophisticated human-machine interface (HMI), providing an additional safety point for the machine and allowing the operator to monitor the operation via a simple graphical interface. This automation enables continuous operation with minimal human intervention, thereby improving the efficiency and safety of the cassava grinding process.
{"title":"Finite element analysis and automation of a medium scale grinder applied to the manufacture of cassava starch","authors":"Idayatou Oroun’Gobi, Chen Guang Guo","doi":"10.3389/fmech.2024.1427388","DOIUrl":"https://doi.org/10.3389/fmech.2024.1427388","url":null,"abstract":"This research is based on the modeling, internal structure analysis, and automation of a cassava grinding machine. For the design, the single-cylinder grinder was chosen due to its advantages, notably simplicity and versatility. The grinding method used in this type of grinder is compression. The mechanical design and simulation software first allowed for the design of the grinder and then for performing static analyses under three loads (P1 = 10000N, P2 = 15000N, and P3 = 20000N). The results of these tests led to the selection of P3 = 20000N as the straightening load, with a maximum stress value in the static analysis of 88,18 MPa and a maximum deformation of 0,000358 under the force of load P3. Additionally, the frequency analysis distinguished five resonance modes. The results for each mode concluded that no resonance would affect the machine, thus ensuring stable operation. Furthermore, fatigue, frequency, and safety factor studies showed that the machine could withstand a load of m3 = 2000 kg without damage, with a service life of 1e+09 cycles. Considering the total number of life cycles, which is 1e+09 cycles, this means that the machine will have a service life of 347000 years, with a total grinding output of 2e+12 kg of cassava and 5840000 kg per year. The factor of safety is FoS = 1,78, indicating a sufficient margin for safe operating conditions. The automation of the grinder was carried out using a GRAFCET model and a sophisticated human-machine interface (HMI), providing an additional safety point for the machine and allowing the operator to monitor the operation via a simple graphical interface. This automation enables continuous operation with minimal human intervention, thereby improving the efficiency and safety of the cassava grinding process.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141927576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.3389/fmech.2024.1459814
Shuvodeep De, Wei Zhao, Zhangxian Yuan
{"title":"Editorial: Lightweight mechanical and aerospace structures and materials","authors":"Shuvodeep De, Wei Zhao, Zhangxian Yuan","doi":"10.3389/fmech.2024.1459814","DOIUrl":"https://doi.org/10.3389/fmech.2024.1459814","url":null,"abstract":"","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-25DOI: 10.3389/fmech.2024.1419210
Divyanshu S. Morghode, D. G. Thakur, Sachin Salunkhe, Lenka Cepova, Emad S. Abouel Nasr
The layered configuration of different material plates is one of the ways of achieving protection against different kinds of kinetic energy ammunitions. The thickness of each plate is one of the most important influencing parameters to prevent the penetration of the projectile. In the present study, a layered configuration of the Al2O3 and Al 7075-T651 is analysed, to prevent the perforation of 7.62 mm Lead core projectile, under normal impact conditions, by using LS-DYNA numerical simulations. Experiments were conducted on Al 7075-T651 plate and Numerical model was validated with experiment results. To achieve the objective, the validated numerical model was used to investigate influence on various Al2O3 and Al 7075-T651 combinations. Three factors led to the selection of Al 7075-T561 and Al2O3 as the target materials. First, the literature review revealed that these materials have already been employed in the construction of armour. Second, Al2O3 is a brittle material whereas Al 7075-T651 is ductile. Consequently, when combined in a layered arrangement, these materials offer the ideal destroyer-absorber arrangement. Thirdly, these materials have lower densities than steel. As a result, these materials offer a lightweight alternative for lead core 7.62 mm bullet defense. From the analysis, it is observed that two layered configurations were found to be effective in the prevention of bullet perforation: a front plate of Al2O3 that was 10 mm thick and had a rear plate of Al 7075-T651 that was 06 mm thick, and a front plate of Al2O3 that was 04 mm thick and had a 12 mm thick layer of Al 7075-T651.
不同材料板材的分层配置是抵御各种动能弹药的方法之一。每块板的厚度是防止弹丸穿透的最重要影响参数之一。在本研究中，通过使用 LS-DYNA 数值模拟，分析了 Al2O3 和 Al 7075-T651 的分层配置，以防止 7.62 毫米铅芯弹丸在正常冲击条件下穿孔。在 Al 7075-T651 板上进行了实验，并根据实验结果对数值模型进行了验证。为了实现目标，我们使用验证过的数值模型来研究各种 Al2O3 和 Al 7075-T651 组合的影响。选择 Al 7075-T561 和 Al2O3 作为目标材料有三个因素。首先，文献综述显示，这些材料已被用于制造装甲。其次，Al2O3 是一种脆性材料，而 Al 7075-T651 则具有延展性。因此，当这些材料以分层排列的方式结合在一起时，可提供理想的破坏者-吸收者排列方式。第三，这些材料的密度比钢低。因此，这些材料为 7.62 毫米铅芯子弹的防御提供了轻质替代品。从分析中可以看出，有两种分层结构能有效防止子弹穿孔：一种是前板为 10 毫米厚的 Al2O3，后板为 06 毫米厚的 Al 7075-T651；另一种是前板为 04 毫米厚的 Al2O3，后板为 12 毫米厚的 Al 7075-T651。
{"title":"Analysis of the thickness of layered armor to provide protection against 7.62 mm ball projectiles using experimental and numerical methods","authors":"Divyanshu S. Morghode, D. G. Thakur, Sachin Salunkhe, Lenka Cepova, Emad S. Abouel Nasr","doi":"10.3389/fmech.2024.1419210","DOIUrl":"https://doi.org/10.3389/fmech.2024.1419210","url":null,"abstract":"The layered configuration of different material plates is one of the ways of achieving protection against different kinds of kinetic energy ammunitions. The thickness of each plate is one of the most important influencing parameters to prevent the penetration of the projectile. In the present study, a layered configuration of the Al2O3 and Al 7075-T651 is analysed, to prevent the perforation of 7.62 mm Lead core projectile, under normal impact conditions, by using LS-DYNA numerical simulations. Experiments were conducted on Al 7075-T651 plate and Numerical model was validated with experiment results. To achieve the objective, the validated numerical model was used to investigate influence on various Al2O3 and Al 7075-T651 combinations. Three factors led to the selection of Al 7075-T561 and Al2O3 as the target materials. First, the literature review revealed that these materials have already been employed in the construction of armour. Second, Al2O3 is a brittle material whereas Al 7075-T651 is ductile. Consequently, when combined in a layered arrangement, these materials offer the ideal destroyer-absorber arrangement. Thirdly, these materials have lower densities than steel. As a result, these materials offer a lightweight alternative for lead core 7.62 mm bullet defense. From the analysis, it is observed that two layered configurations were found to be effective in the prevention of bullet perforation: a front plate of Al2O3 that was 10 mm thick and had a rear plate of Al 7075-T651 that was 06 mm thick, and a front plate of Al2O3 that was 04 mm thick and had a 12 mm thick layer of Al 7075-T651.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141803937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.3389/fmech.2024.1392616
A. Ciszkiewicz, Raphael Dumas
Verification, validation, and uncertainty quantification is generally recognized as a standard for assessing the credibility of mechanical models. This is especially evident in biomechanics, with intricate models, such as knee joint models, and highly subjective acquisition of parameters. Propagation of uncertainty is numerically expensive but required to evaluate the model reliability. An alternative to this is to analyze the worst-case models obtained within the specific bounds set on the parameters. The main idea of the paper is to search for two models with the greatest different response in terms of displacement-load curve. Real-Coded Genetic Algorithm is employed to effectively explore the high-dimensional space of uncertain parameters of a 2D dynamic knee model, while Radial Basis Function surrogates reduce the computation by orders of magnitude to near real-time, with negligible impact on the quality. It is expected that the studied knee joint model is very sensitive to uncertainty in the geometrical parameters. The obtained worst-case knee models showcase unrealistic behavior with one of them unable to fully extend, and the other largely overextending. Their relative difference in extension is up to 35% under ±1 mm bound set on the geometry. This unrealistic behavior of knee joint model is confirmed by the large standard deviation obtained from a classical sampling-based sensitivity analysis. The results confirm the viability of the method in assessing the reliability of biomechanical models. The proposed approach is general and could be applied to other mechanical systems as well.
{"title":"Surrogate-based worst-case analysis of a knee joint model using Genetic Algorithm","authors":"A. Ciszkiewicz, Raphael Dumas","doi":"10.3389/fmech.2024.1392616","DOIUrl":"https://doi.org/10.3389/fmech.2024.1392616","url":null,"abstract":"Verification, validation, and uncertainty quantification is generally recognized as a standard for assessing the credibility of mechanical models. This is especially evident in biomechanics, with intricate models, such as knee joint models, and highly subjective acquisition of parameters. Propagation of uncertainty is numerically expensive but required to evaluate the model reliability. An alternative to this is to analyze the worst-case models obtained within the specific bounds set on the parameters. The main idea of the paper is to search for two models with the greatest different response in terms of displacement-load curve. Real-Coded Genetic Algorithm is employed to effectively explore the high-dimensional space of uncertain parameters of a 2D dynamic knee model, while Radial Basis Function surrogates reduce the computation by orders of magnitude to near real-time, with negligible impact on the quality. It is expected that the studied knee joint model is very sensitive to uncertainty in the geometrical parameters. The obtained worst-case knee models showcase unrealistic behavior with one of them unable to fully extend, and the other largely overextending. Their relative difference in extension is up to 35% under ±1 mm bound set on the geometry. This unrealistic behavior of knee joint model is confirmed by the large standard deviation obtained from a classical sampling-based sensitivity analysis. The results confirm the viability of the method in assessing the reliability of biomechanical models. The proposed approach is general and could be applied to other mechanical systems as well.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.3389/fmech.2024.1391593
Jingjing Feng
Introduction: Nowadays, five-phase permanent magnet synchronous motors have been widely used in the industrial and transportation fields, and the existing sliding mode control methods for speed control systems can no longer meet the requirements such as fast response and good stability.Methods: In light of the aforementioned considerations, the study initially employs mathematical modeling to elucidate the five-phase permanent magnet synchronous motor. Secondly, on the basis of proportional-integral-derivative sliding mode control, radial basis function and Takagi-Sugeno-Kang fuzzy model are introduced for parameter identification and optimization and regulation. Finally, a new neural network regulation algorithm and speed control strategy are proposed.Results and Discussion: The experimental results demonstrated that the expected parameter optimization rate of the regulation algorithm can reach 90%, and the overshooting amount under small inertia working condition is only 3%, and the adjustment time is 0.02 s. The new control algorithm can be used to control the motor speed with the lowest speed fluctuation and the fastest recovery time. In addition, when affected by the load torque, the motor speed controlled by the new strategy fluctuated the least, with a speed drop of only 1% and the fastest recovery time of 0.02 s. It exhibited the lowest control error of 3.7% and the lowest overshooting amount of 5.9%.Conclusion: In summary, the suggested approach has the potential to significantly enhance the speed control system’s control performance while maintaining strong resilience and anti-interference capabilities. The method has certain guiding significance for the practical application of five-phase permanent magnet synchronous motor speed control system.
{"title":"Parameter fuzzy rectification for sliding mode control of five-phase permanent magnet synchronous motor speed control system","authors":"Jingjing Feng","doi":"10.3389/fmech.2024.1391593","DOIUrl":"https://doi.org/10.3389/fmech.2024.1391593","url":null,"abstract":"Introduction: Nowadays, five-phase permanent magnet synchronous motors have been widely used in the industrial and transportation fields, and the existing sliding mode control methods for speed control systems can no longer meet the requirements such as fast response and good stability.Methods: In light of the aforementioned considerations, the study initially employs mathematical modeling to elucidate the five-phase permanent magnet synchronous motor. Secondly, on the basis of proportional-integral-derivative sliding mode control, radial basis function and Takagi-Sugeno-Kang fuzzy model are introduced for parameter identification and optimization and regulation. Finally, a new neural network regulation algorithm and speed control strategy are proposed.Results and Discussion: The experimental results demonstrated that the expected parameter optimization rate of the regulation algorithm can reach 90%, and the overshooting amount under small inertia working condition is only 3%, and the adjustment time is 0.02 s. The new control algorithm can be used to control the motor speed with the lowest speed fluctuation and the fastest recovery time. In addition, when affected by the load torque, the motor speed controlled by the new strategy fluctuated the least, with a speed drop of only 1% and the fastest recovery time of 0.02 s. It exhibited the lowest control error of 3.7% and the lowest overshooting amount of 5.9%.Conclusion: In summary, the suggested approach has the potential to significantly enhance the speed control system’s control performance while maintaining strong resilience and anti-interference capabilities. The method has certain guiding significance for the practical application of five-phase permanent magnet synchronous motor speed control system.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141807673","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}
Grease is used as a lubricant in a wide range of fields, including bearings, because it reduces friction, prevents harmful wear of components, protects against rust and corrosion, and acts as a seal to prevent the invasion of dirt and water. Although most of the research on grease has focused on the environment inside the bearing, there has been little research on the fundamental lubrication mechanism of grease. It is known that thickeners, which keep a complex three-dimensional structure in the grease, have a significant effect on the shear characteristics of grease, and it is assumed that this is due to the orientation of the thickener structure in the shear direction. In this study, the apparent viscosity of grease in a micro-order gap was measured using our original viscometer and compared with the apparent viscosity measured with a submillimeter-order gap rheometer because grease may show different rheological properties compared to conventional measurements. In addition, the dynamic response of viscous resistance that appeared when each grease was subjected to a change in the shear force was quantitatively evaluated using relaxation time. As a result, the apparent viscosity remarkably decreased in a micro-order gap compared to a submillimeter gap, and two types of shear thinning mechanisms were proposed based on the orientation of the thickener: one caused by the narrow gap and the other by the shear force. In addition, the behavior of viscous resistance due to changes in the shear force depended on the type of thickener. It was also confirmed that the relaxation time of each grease correlates with its oil film-forming ability and the entanglement level of the thickener’s structure. Furthermore, the mechanism of the dynamic response was proposed based on the reorientation of thickeners.
{"title":"Shear properties and dynamic responses of greases in a micrometer-order gap","authors":"Hanul Chun, Tomoko Hirayama, Naoki Yamashita, Naoya Hatano, Kazuya Tatsumi, R. Kuriyama","doi":"10.3389/fmech.2024.1420852","DOIUrl":"https://doi.org/10.3389/fmech.2024.1420852","url":null,"abstract":"Grease is used as a lubricant in a wide range of fields, including bearings, because it reduces friction, prevents harmful wear of components, protects against rust and corrosion, and acts as a seal to prevent the invasion of dirt and water. Although most of the research on grease has focused on the environment inside the bearing, there has been little research on the fundamental lubrication mechanism of grease. It is known that thickeners, which keep a complex three-dimensional structure in the grease, have a significant effect on the shear characteristics of grease, and it is assumed that this is due to the orientation of the thickener structure in the shear direction. In this study, the apparent viscosity of grease in a micro-order gap was measured using our original viscometer and compared with the apparent viscosity measured with a submillimeter-order gap rheometer because grease may show different rheological properties compared to conventional measurements. In addition, the dynamic response of viscous resistance that appeared when each grease was subjected to a change in the shear force was quantitatively evaluated using relaxation time. As a result, the apparent viscosity remarkably decreased in a micro-order gap compared to a submillimeter gap, and two types of shear thinning mechanisms were proposed based on the orientation of the thickener: one caused by the narrow gap and the other by the shear force. In addition, the behavior of viscous resistance due to changes in the shear force depended on the type of thickener. It was also confirmed that the relaxation time of each grease correlates with its oil film-forming ability and the entanglement level of the thickener’s structure. Furthermore, the mechanism of the dynamic response was proposed based on the reorientation of thickeners.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141645781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-12DOI: 10.3389/fmech.2024.1397131
Yue Sun, Chao Chen, Yuesheng Xu, Sihong Xie, Rick S. Blum, Parv Venkitasubramaniam
Graph neural networks (GNNs) have gained significant attention in diverse domains, ranging from urban planning to pandemic management. Ensuring both accuracy and robustness in GNNs remains a challenge due to insufficient quality data that contains sufficient features. With sufficient training data where all spatiotemporal patterns are well-represented, existing GNN models can make reasonably accurate predictions. However, existing methods fail when the training data are drawn from different circumstances (e.g., traffic patterns on regular days) than test data (e.g., traffic patterns after a natural disaster). Such challenges are usually classified under domain generalization. In this work, we show that one way to address this challenge in the context of spatiotemporal prediction is by incorporating domain differential equations into graph convolutional networks (GCNs). We theoretically derive conditions where GCNs incorporating such domain differential equations are robust to mismatched training and testing data compared to baseline domain agnostic models. To support our theory, we propose two domain-differential-equation-informed networks: Reaction-Diffusion Graph Convolutional Network (RDGCN), which incorporates differential equations for traffic speed evolution, and the Susceptible-Infectious-Recovered Graph Convolutional Network (SIRGCN), which incorporates a disease propagation model. Both RDGCN and SIRGCN are based on reliable and interpretable domain differential equations that allow the models to generalize to unseen patterns. We experimentally show that RDGCN and SIRGCN are more robust with mismatched testing data than state-of-the-art deep learning methods.
{"title":"On the generalization discrepancy of spatiotemporal dynamics-informed graph convolutional networks","authors":"Yue Sun, Chao Chen, Yuesheng Xu, Sihong Xie, Rick S. Blum, Parv Venkitasubramaniam","doi":"10.3389/fmech.2024.1397131","DOIUrl":"https://doi.org/10.3389/fmech.2024.1397131","url":null,"abstract":"Graph neural networks (GNNs) have gained significant attention in diverse domains, ranging from urban planning to pandemic management. Ensuring both accuracy and robustness in GNNs remains a challenge due to insufficient quality data that contains sufficient features. With sufficient training data where all spatiotemporal patterns are well-represented, existing GNN models can make reasonably accurate predictions. However, existing methods fail when the training data are drawn from different circumstances (e.g., traffic patterns on regular days) than test data (e.g., traffic patterns after a natural disaster). Such challenges are usually classified under domain generalization. In this work, we show that one way to address this challenge in the context of spatiotemporal prediction is by incorporating domain differential equations into graph convolutional networks (GCNs). We theoretically derive conditions where GCNs incorporating such domain differential equations are robust to mismatched training and testing data compared to baseline domain agnostic models. To support our theory, we propose two domain-differential-equation-informed networks: Reaction-Diffusion Graph Convolutional Network (RDGCN), which incorporates differential equations for traffic speed evolution, and the Susceptible-Infectious-Recovered Graph Convolutional Network (SIRGCN), which incorporates a disease propagation model. Both RDGCN and SIRGCN are based on reliable and interpretable domain differential equations that allow the models to generalize to unseen patterns. We experimentally show that RDGCN and SIRGCN are more robust with mismatched testing data than state-of-the-art deep learning methods.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141654955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-12DOI: 10.3389/fmech.2024.1284758
An Zhang, Peng Liu, He Zhang
The penetration fuze, as the initiation control component of the penetration weapon, usually experiences an overload of tens of thousands or even hundreds of thousands of g during the penetration process. In order to prevent the fuze from being overloaded and causing the weapon to explode or misfire early, this article introduces the use of internal sealing reinforcement and external energy absorbing buffer materials to protect the internal circuit modules of the fuze. Several kinds of energy absorbing and buffering materials, including foam metal materials and composite sandwich structure materials, as well as metamaterials that have recently attracted the attention of industry and academia, are reviewed. The high overload impact energy absorption characteristics of materials and the mechanical properties of different material structures are emphatically introduced. In addition, this article also evaluates the applicability and limitations of existing buffer materials and methods, and proposes some potential improvement plans, such as the impact of parameters such as viscoelasticity, porosity, surface coating, printing process, heat treatment process on the energy absorption effect of materials, further improving the engineering practicality of buffer protection materials. A summary of the key technologies in the research of penetration fuze protective materials was made, and some mechanical testing methods were proposed, which can better characterize the impact resistance and resilience of materials. Finally, the future development direction of buffer materials for penetration fuzes was explored, which will help promote the research on the concept of buffer materials used on penetration missiles.
{"title":"Advancements in research on high-overload impact-buffering protective materials","authors":"An Zhang, Peng Liu, He Zhang","doi":"10.3389/fmech.2024.1284758","DOIUrl":"https://doi.org/10.3389/fmech.2024.1284758","url":null,"abstract":"The penetration fuze, as the initiation control component of the penetration weapon, usually experiences an overload of tens of thousands or even hundreds of thousands of g during the penetration process. In order to prevent the fuze from being overloaded and causing the weapon to explode or misfire early, this article introduces the use of internal sealing reinforcement and external energy absorbing buffer materials to protect the internal circuit modules of the fuze. Several kinds of energy absorbing and buffering materials, including foam metal materials and composite sandwich structure materials, as well as metamaterials that have recently attracted the attention of industry and academia, are reviewed. The high overload impact energy absorption characteristics of materials and the mechanical properties of different material structures are emphatically introduced. In addition, this article also evaluates the applicability and limitations of existing buffer materials and methods, and proposes some potential improvement plans, such as the impact of parameters such as viscoelasticity, porosity, surface coating, printing process, heat treatment process on the energy absorption effect of materials, further improving the engineering practicality of buffer protection materials. A summary of the key technologies in the research of penetration fuze protective materials was made, and some mechanical testing methods were proposed, which can better characterize the impact resistance and resilience of materials. Finally, the future development direction of buffer materials for penetration fuzes was explored, which will help promote the research on the concept of buffer materials used on penetration missiles.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141653341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.3389/fmech.2024.1422412
Hikaru Okubo, Tomori Ishikawa, H. Hashiba, Toru Inamochi, Ken Nakano
This paper reports the thermally activated ultralow friction of 100% cellulose nanofiber (CNF) molding. The mechanism of friction reduction was investigated using a laboratory-built in-situ Raman tribometer. Our experimental results showed that a CNF molding exhibited an ultralow friction coefficient of below 0.04 in a CNF ring and steel disk tribopair under high-temperature conditions (T > 100°C). The results of the temperature-rise friction test showed that the friction coefficient of the CNF molding strongly depended on the temperature and decreased linearly with increasing temperature. The in situ tribo-Raman monitoring results, during friction, indicated a change in the structure of the CNF molding. Therefore, the crystallinity indices and lengths of the CNF fibers gradually changed as the temperature increased. Moreover, transfer tribofilms were observed on the counter-steel surface against the CNF rings. When the CNF molding exhibited thermally activated ultralow friction, the tribofilm was mainly composed of cellulose and graphitic carbon. Our results suggest that the thermal and friction-activated structural transformations of CNF molding and CNF-derived transfer film formation are pivotal factors contributing to the ultralow friction phenomenon observed in CNF molding at high temperatures.
{"title":"In-situ vibrational spectroscopic observation for thermally activated structural changes of 100% cellulose nanofiber molding with ultralow friction","authors":"Hikaru Okubo, Tomori Ishikawa, H. Hashiba, Toru Inamochi, Ken Nakano","doi":"10.3389/fmech.2024.1422412","DOIUrl":"https://doi.org/10.3389/fmech.2024.1422412","url":null,"abstract":"This paper reports the thermally activated ultralow friction of 100% cellulose nanofiber (CNF) molding. The mechanism of friction reduction was investigated using a laboratory-built in-situ Raman tribometer. Our experimental results showed that a CNF molding exhibited an ultralow friction coefficient of below 0.04 in a CNF ring and steel disk tribopair under high-temperature conditions (T > 100°C). The results of the temperature-rise friction test showed that the friction coefficient of the CNF molding strongly depended on the temperature and decreased linearly with increasing temperature. The in situ tribo-Raman monitoring results, during friction, indicated a change in the structure of the CNF molding. Therefore, the crystallinity indices and lengths of the CNF fibers gradually changed as the temperature increased. Moreover, transfer tribofilms were observed on the counter-steel surface against the CNF rings. When the CNF molding exhibited thermally activated ultralow friction, the tribofilm was mainly composed of cellulose and graphitic carbon. Our results suggest that the thermal and friction-activated structural transformations of CNF molding and CNF-derived transfer film formation are pivotal factors contributing to the ultralow friction phenomenon observed in CNF molding at high temperatures.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141666280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-09DOI: 10.3389/fmech.2024.1412137
F. Becker-Dombrowsky, E. Kirchner
Condition monitoring of machine elements becomes more important over the last years. Different approaches to detect failures in mechanical components have been developed. All these methods are located at a distance from the point of interest, the observed machine element. This leads to uncertainties in the data, which influences the data quality negatively. Using the electrical impedance for condition monitoring enables in situ measurement with reduced uncertainties and higher data quality. In the last years, research considering this topic was done, but a systematic overview is missing. In this article, a systematic literature research according to the PRISMA approach is fulfilled. The main questions are, what application fields for electrical impedance-based condition monitoring approaches exists and which research gaps are not addressed yet. At the end, 21 articles are categorized in their application fields. Analyzing their content, research questions are identified which have to be addressed in further investigations.
{"title":"Electrical impedance based condition monitoring of machine elements–a systematic review","authors":"F. Becker-Dombrowsky, E. Kirchner","doi":"10.3389/fmech.2024.1412137","DOIUrl":"https://doi.org/10.3389/fmech.2024.1412137","url":null,"abstract":"Condition monitoring of machine elements becomes more important over the last years. Different approaches to detect failures in mechanical components have been developed. All these methods are located at a distance from the point of interest, the observed machine element. This leads to uncertainties in the data, which influences the data quality negatively. Using the electrical impedance for condition monitoring enables in situ measurement with reduced uncertainties and higher data quality. In the last years, research considering this topic was done, but a systematic overview is missing. In this article, a systematic literature research according to the PRISMA approach is fulfilled. The main questions are, what application fields for electrical impedance-based condition monitoring approaches exists and which research gaps are not addressed yet. At the end, 21 articles are categorized in their application fields. Analyzing their content, research questions are identified which have to be addressed in further investigations.","PeriodicalId":53220,"journal":{"name":"Frontiers in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141665732","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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