The nonlinear aeroelastic behavior of a folding fin in supersonic flow is investigated in this paper.The finite element model of the fin is established and the deployable hinges are represented by three torsion spring...The nonlinear aeroelastic behavior of a folding fin in supersonic flow is investigated in this paper.The finite element model of the fin is established and the deployable hinges are represented by three torsion springs with the freeplay nonlinearity.The aerodynamic grid point is assumed to be at the center of each aerodynamic box for simplicity.The aerodynamic governing equation is given by using the infinite plate spline method and the modified linear piston theory.An improved fixed-interface modal synthesis method,which can reduce the rigid connections at the interface,is developed to save the problem size and computation time.The uniform temperature field is applied to create the thermal environment.For the linear flutter analyses,the flutter speed increases first and then decreases with the rise of the hinge stiffness due to the change of the flutter coupling mechanism.For the nonlinear analyses,a larger freeplay angle results in a higher vibration divergent speed.Two different types of limit cycle oscillations and a multiperiodic motion are observed in the wide range of airspeed under the linear flutter boundary.The linear flutter speed shows a slight descend in the thermal environment,but the effect of the temperature on the vibration divergent speed is different under different hinge stiffnesses when there exists freeplay.展开更多
To address the charging infrastructure challenges associated with slow electric vehicle(EV)industry growth,this study investigates the collaboration between private charging-pile-sharing platforms struggling with prof...To address the charging infrastructure challenges associated with slow electric vehicle(EV)industry growth,this study investigates the collaboration between private charging-pile-sharing platforms struggling with profitability and automotive companies.This collaboration is crucial,as it demands a balanced price and service quality management due to consumer expectations.This paper introduces a Stackelberg game model to explore the relationship between a charging platform and an automotive company.Through numerical analysis,we assess how this cooperation might improve the platform’s efficiency and benefit society,potentially overcoming existing industry hurdles.Our findings indicate that such partnerships could benefit all parties involved,despite possible negative environmental impacts.However,after collaborat-ing,platforms may increase consumer prices and payments to suppliers,potentially lowering service quality for brand-associated consumers due to a compromise between shorter waiting times and service quality.This research offers valu-able insights for stakeholders on the effects of cooperation,enabling better strategic decisions in the EV charging sector.展开更多
Adhesives have attracted a great deal of attention as an advanced modality in biomedical engineering because of their unique wound management behavior.However,it is a grand challenge for current adhesive systems to ac...Adhesives have attracted a great deal of attention as an advanced modality in biomedical engineering because of their unique wound management behavior.However,it is a grand challenge for current adhesive systems to achieve robust adhesion due to their tenuous interfacial bonding strength.Moreover,the absence of dynamic adaptability in conventional chemical adhesives restricts neoblasts around the wound from migrating to the site,resulting in an inferior tissue-regeneration effect.Herein,an extracellular matrix-derived biocomposite adhesive with robust adhesion and a real-time skin healing effect is well-engineered.Liquid–liquid phase separation is well-harnessed to drive the assembly of the biocomposite adhesive,with the active involvement of supramolecular interactions between chimeric protein and natural DNA,leading to a robustly reinforced adhesion performance.The bioadhesive exhibits outstanding adhesion and sealing behaviors,with a sheared adhesion strength of approximately 18 MPa,outperforming its reported counterparts.Moreover,the engineered bioderived components endow this adhesive material with biocompatibility and exceptional biological functions including the promotion of cell proliferation and migration,such that the use of this material eventually yields real-time in situ skin regeneration.This work opens up novel avenues for functionalized bioadhesive engineering and biomedical translations.展开更多
Artificial intelligence has achieved remarkable success in materials science,accelerating novel material design.However,real-world material systems exhibit multiscale complexity—spanning composition,processing,struct...Artificial intelligence has achieved remarkable success in materials science,accelerating novel material design.However,real-world material systems exhibit multiscale complexity—spanning composition,processing,structure,and properties—posing significant challenges for modeling.While some approaches fuse multiscale features to improve prediction,important modalities such as microstructure are often missing due to high acquisition costs.Existing methods struggle with incomplete data and lack a framework to bridge multiscale material knowledge.To address this,we propose MatMCL,a structure-guided multimodal learning framework that jointly analyzes multiscale material information and enables robust property prediction with incomplete modalities.Using a selfconstructed multimodal dataset of electrospun nanofibers,we demonstrate that MatMCL improves mechanical property prediction without structural information,generates microstructures from processing parameters,and enables cross-modal retrieval.We further extend it via multi-stage learning and apply it to nanofiber-reinforced composite design.MatMCL uncovers processingstructure-property relationships,suggesting its promise as a generalizable approach for AI-driven material design.展开更多
文摘The nonlinear aeroelastic behavior of a folding fin in supersonic flow is investigated in this paper.The finite element model of the fin is established and the deployable hinges are represented by three torsion springs with the freeplay nonlinearity.The aerodynamic grid point is assumed to be at the center of each aerodynamic box for simplicity.The aerodynamic governing equation is given by using the infinite plate spline method and the modified linear piston theory.An improved fixed-interface modal synthesis method,which can reduce the rigid connections at the interface,is developed to save the problem size and computation time.The uniform temperature field is applied to create the thermal environment.For the linear flutter analyses,the flutter speed increases first and then decreases with the rise of the hinge stiffness due to the change of the flutter coupling mechanism.For the nonlinear analyses,a larger freeplay angle results in a higher vibration divergent speed.Two different types of limit cycle oscillations and a multiperiodic motion are observed in the wide range of airspeed under the linear flutter boundary.The linear flutter speed shows a slight descend in the thermal environment,but the effect of the temperature on the vibration divergent speed is different under different hinge stiffnesses when there exists freeplay.
基金supported by the National Natural Science Foundation of China(72474034,72104034)Humanities and Social Science Fund of the Ministry of Education of China(21YJC630037,22XJC910001)China Postdoctoral Science Foundation(2022T150072)。
文摘To address the charging infrastructure challenges associated with slow electric vehicle(EV)industry growth,this study investigates the collaboration between private charging-pile-sharing platforms struggling with profitability and automotive companies.This collaboration is crucial,as it demands a balanced price and service quality management due to consumer expectations.This paper introduces a Stackelberg game model to explore the relationship between a charging platform and an automotive company.Through numerical analysis,we assess how this cooperation might improve the platform’s efficiency and benefit society,potentially overcoming existing industry hurdles.Our findings indicate that such partnerships could benefit all parties involved,despite possible negative environmental impacts.However,after collaborat-ing,platforms may increase consumer prices and payments to suppliers,potentially lowering service quality for brand-associated consumers due to a compromise between shorter waiting times and service quality.This research offers valu-able insights for stakeholders on the effects of cooperation,enabling better strategic decisions in the EV charging sector.
基金supported by National Natural Science Foundation of China(71801206,71971203,72171219)USTC Research Funds of the Double First-Class Initiative(YD2040002004)+1 种基金the Fundamental Research Funds for the Central Universities(WK2040000027)Special Research Assistant Support Program of Chinese Academy of Sciences。
基金supported by the National Key Research and Development Program of China(2022YFA0913200 and 2021YFB3502300)the National Natural Science Foundation of China(22020102003,22125701,22277064,82272161,52222214,and 22107097)+3 种基金Beijing Municipal Science and Technology Commission(221100007422088)Beijing Nova Program(Z211100002121132)Beijing Natural Science Foundation(2222010)Xiangfu Lab Research Project(XF012022C0200)。
文摘Adhesives have attracted a great deal of attention as an advanced modality in biomedical engineering because of their unique wound management behavior.However,it is a grand challenge for current adhesive systems to achieve robust adhesion due to their tenuous interfacial bonding strength.Moreover,the absence of dynamic adaptability in conventional chemical adhesives restricts neoblasts around the wound from migrating to the site,resulting in an inferior tissue-regeneration effect.Herein,an extracellular matrix-derived biocomposite adhesive with robust adhesion and a real-time skin healing effect is well-engineered.Liquid–liquid phase separation is well-harnessed to drive the assembly of the biocomposite adhesive,with the active involvement of supramolecular interactions between chimeric protein and natural DNA,leading to a robustly reinforced adhesion performance.The bioadhesive exhibits outstanding adhesion and sealing behaviors,with a sheared adhesion strength of approximately 18 MPa,outperforming its reported counterparts.Moreover,the engineered bioderived components endow this adhesive material with biocompatibility and exceptional biological functions including the promotion of cell proliferation and migration,such that the use of this material eventually yields real-time in situ skin regeneration.This work opens up novel avenues for functionalized bioadhesive engineering and biomedical translations.
基金supported by the National Key Research and Development Program of China(2022YFB3807300)Zhejiang Provincial Natural Science Foundation of China(LR25E030001)+2 种基金the Key Research and Development Project of Zhejiang Province(2024C03073)the financial support from the State Key Laboratory of Transvascular Implantation Devices(012024019)Transvascular Implantation Devices Research Institute China(TIDRIC)(KY012024007,KY012024009).
文摘Artificial intelligence has achieved remarkable success in materials science,accelerating novel material design.However,real-world material systems exhibit multiscale complexity—spanning composition,processing,structure,and properties—posing significant challenges for modeling.While some approaches fuse multiscale features to improve prediction,important modalities such as microstructure are often missing due to high acquisition costs.Existing methods struggle with incomplete data and lack a framework to bridge multiscale material knowledge.To address this,we propose MatMCL,a structure-guided multimodal learning framework that jointly analyzes multiscale material information and enables robust property prediction with incomplete modalities.Using a selfconstructed multimodal dataset of electrospun nanofibers,we demonstrate that MatMCL improves mechanical property prediction without structural information,generates microstructures from processing parameters,and enables cross-modal retrieval.We further extend it via multi-stage learning and apply it to nanofiber-reinforced composite design.MatMCL uncovers processingstructure-property relationships,suggesting its promise as a generalizable approach for AI-driven material design.
