As primary load-bearing components extensively utilized in engineering applications,beam structures necessitate the design of their microstructural configurations to achieve lightweight objectives while satisfying div...As primary load-bearing components extensively utilized in engineering applications,beam structures necessitate the design of their microstructural configurations to achieve lightweight objectives while satisfying diverse mechanical performance requirements.Combining topology optimization with fully coupled homogenization beam theory,we provide a highly efficient design tool to access desirable periodic microstructures for beams.The present optimization framework comprehensively takes into account for key deformation modes,including tension,bending,torsion,and shear deformation,all within a unified formulation.Several numerical results prove that our method can be used to handle kinds of microstructure design for beam-like structures,e.g.,extreme tension(compression)-torsion stiffness,maximization of minimum critical buckling load,and minimization of structural compliance.When optimizing microstructures for macroscopic performance,we emphasize investigating the influence of shear stiffness on the optimized results.The novel chiral beam-like structures are fabricated and tested.The experimental results indicate that the optimized tension(compression)-torsion structure has excellent buffer characteristics,as compared with the traditional square tube.This proposed optimization framework can be further extended to other physical problems of Timoshenko beams.展开更多
特殊螺纹接头是高温高压井油套管柱连接的重要部件,管内流体压力、流速的变化诱发管柱振动,引起特殊螺纹接头密封面发生微滑,表现为力与位移的刚度软化与滞回等非线性特征,进而导致接头密封性能下降。为查明密封面的微滑机制,基于离散I...特殊螺纹接头是高温高压井油套管柱连接的重要部件,管内流体压力、流速的变化诱发管柱振动,引起特殊螺纹接头密封面发生微滑,表现为力与位移的刚度软化与滞回等非线性特征,进而导致接头密封性能下降。为查明密封面的微滑机制,基于离散Iwan模型本构关系,建立某锥面-锥面Φ88.9 mm×6.45 mm P110特殊螺纹接头有限元分析模型,得到不同循环位移载荷下密封面处的力-位移滞回曲线,通过滞回曲线离散化分析,识别出离散Iwan模型的4组参数;构建该特殊螺纹接头等效Iwan模型,分析密封面间的微滑状态;对比分析两种模型滞回曲线的相似度,验证等效Iwan模型的准确性。结果表明:构建的特殊螺纹接头等效Iwan模型与有限元分析模型的综合相似度较高,滞回曲线面积重合度大于92%,位置误差小于2%;利用特殊螺纹接头等效Iwan模型得到的滞回曲线,能够准确描述密封面间黏着、滑移、宏观滑移之间的转化过程,从而为特殊螺纹接头滞回曲线分析提供一种新方法。展开更多
Recently,numerous studies have demonstrated that the physics-informed neural network(PINN)can effectively and accurately resolve hyperelastic finite deformation problems.In this paper,a PINN framework for tackling hyp...Recently,numerous studies have demonstrated that the physics-informed neural network(PINN)can effectively and accurately resolve hyperelastic finite deformation problems.In this paper,a PINN framework for tackling hyperelastic-magnetic coupling problems is proposed.Since the solution space consists of two-phase domains,two separate networks are constructed to independently predict the solution for each phase region.In addition,a conscious point allocation strategy is incorporated to enhance the prediction precision of the PINN in regions characterized by sharp gradients.With the developed framework,the magnetic fields and deformation fields of magnetorheological elastomers(MREs)are solved under the control of hyperelastic-magnetic coupling equations.Illustrative examples are provided and contrasted with the reference results to validate the predictive accuracy of the proposed framework.Moreover,the advantages of the proposed framework in solving hyperelastic-magnetic coupling problems are validated,particularly in handling small data sets,as well as its ability in swiftly and precisely forecasting magnetostrictive motion.展开更多
基金supported by the National Natural Science Foundation of China(grant number 11902015)the Open Fund of Deceleration and Landing Laboratory of the Fifth Academy of Aerospace Science and Technology Group(grant number EDL19092138)the Ministry of Education Chunhui Plan(HZKY20220014).
文摘As primary load-bearing components extensively utilized in engineering applications,beam structures necessitate the design of their microstructural configurations to achieve lightweight objectives while satisfying diverse mechanical performance requirements.Combining topology optimization with fully coupled homogenization beam theory,we provide a highly efficient design tool to access desirable periodic microstructures for beams.The present optimization framework comprehensively takes into account for key deformation modes,including tension,bending,torsion,and shear deformation,all within a unified formulation.Several numerical results prove that our method can be used to handle kinds of microstructure design for beam-like structures,e.g.,extreme tension(compression)-torsion stiffness,maximization of minimum critical buckling load,and minimization of structural compliance.When optimizing microstructures for macroscopic performance,we emphasize investigating the influence of shear stiffness on the optimized results.The novel chiral beam-like structures are fabricated and tested.The experimental results indicate that the optimized tension(compression)-torsion structure has excellent buffer characteristics,as compared with the traditional square tube.This proposed optimization framework can be further extended to other physical problems of Timoshenko beams.
文摘特殊螺纹接头是高温高压井油套管柱连接的重要部件,管内流体压力、流速的变化诱发管柱振动,引起特殊螺纹接头密封面发生微滑,表现为力与位移的刚度软化与滞回等非线性特征,进而导致接头密封性能下降。为查明密封面的微滑机制,基于离散Iwan模型本构关系,建立某锥面-锥面Φ88.9 mm×6.45 mm P110特殊螺纹接头有限元分析模型,得到不同循环位移载荷下密封面处的力-位移滞回曲线,通过滞回曲线离散化分析,识别出离散Iwan模型的4组参数;构建该特殊螺纹接头等效Iwan模型,分析密封面间的微滑状态;对比分析两种模型滞回曲线的相似度,验证等效Iwan模型的准确性。结果表明:构建的特殊螺纹接头等效Iwan模型与有限元分析模型的综合相似度较高,滞回曲线面积重合度大于92%,位置误差小于2%;利用特殊螺纹接头等效Iwan模型得到的滞回曲线,能够准确描述密封面间黏着、滑移、宏观滑移之间的转化过程,从而为特殊螺纹接头滞回曲线分析提供一种新方法。
基金supported by the National Natural Science Foundation of China(Nos.12072105 and 11932006)。
文摘Recently,numerous studies have demonstrated that the physics-informed neural network(PINN)can effectively and accurately resolve hyperelastic finite deformation problems.In this paper,a PINN framework for tackling hyperelastic-magnetic coupling problems is proposed.Since the solution space consists of two-phase domains,two separate networks are constructed to independently predict the solution for each phase region.In addition,a conscious point allocation strategy is incorporated to enhance the prediction precision of the PINN in regions characterized by sharp gradients.With the developed framework,the magnetic fields and deformation fields of magnetorheological elastomers(MREs)are solved under the control of hyperelastic-magnetic coupling equations.Illustrative examples are provided and contrasted with the reference results to validate the predictive accuracy of the proposed framework.Moreover,the advantages of the proposed framework in solving hyperelastic-magnetic coupling problems are validated,particularly in handling small data sets,as well as its ability in swiftly and precisely forecasting magnetostrictive motion.
