In this work,the types of shock wave structure for hydro-elastoplastic model under compression are researched.The emphasis focuses on the theory of shock transition in the presence of elastic-plastic-fluid phase trans...In this work,the types of shock wave structure for hydro-elastoplastic model under compression are researched.The emphasis focuses on the theory of shock transition in the presence of elastic-plastic-fluid phase transition.As a result,in addition to the classical three-wave structure,two new shock wave patterns are found with the increase of loading strength.Several numerical tests are presented to verify the existence of the three types of wave structure.展开更多
To overcome the defects of traditional rarefied numerical methods such as the Direct Simulation Monte Carlo(DSMC)method and unified Boltzmann equation schemes and extend the covering range of macroscopic equations in ...To overcome the defects of traditional rarefied numerical methods such as the Direct Simulation Monte Carlo(DSMC)method and unified Boltzmann equation schemes and extend the covering range of macroscopic equations in high Knudsen number flows,data-driven nonlinear constitutive relations(DNCR)are proposed first through the machine learning method.Based on the training data from both Navier-Stokes(NS)solver and unified gas kinetic scheme(UGKS)solver,the map between responses of stress tensors and heat flux and feature vectors is established after the training phase.Through the obtained off-line training model,new test cases excluded from training data set could be predicated rapidly and accurately by solving conventional equations with modified stress tensor and heat flux.Finally,conventional one-dimensional shock wave cases and two-dimensional hypersonic flows around a blunt circular cylinder are presented to assess the capability of the developed method through various comparisons between DNCR,NS,UGKS,DSMC and experimental results.The improvement of the predictive capability of the coarsegraining model could make the DNCR method to be an effective tool in the rarefied gas community,especially for hypersonic engineering applications.展开更多
基金supported by the China Postdoctoral Science Foundation(No.2022M722185)the Guangdong Basic and Applied Basic Research Foundation(No.2022A1515110521)+1 种基金the National Natural Science Foundation of China(Nos.12302377 and 11972330)the Foundation of Laboratory of Computation Physics(No.6142A05RW202211).
文摘In this work,the types of shock wave structure for hydro-elastoplastic model under compression are researched.The emphasis focuses on the theory of shock transition in the presence of elastic-plastic-fluid phase transition.As a result,in addition to the classical three-wave structure,two new shock wave patterns are found with the increase of loading strength.Several numerical tests are presented to verify the existence of the three types of wave structure.
基金funded by the National Numerical Wind-Tunnel Project(NO.NNW2019ZT3-A08)support of the National Natural Science Foundation of China(Grant No.12002306 and 6162790014).
文摘To overcome the defects of traditional rarefied numerical methods such as the Direct Simulation Monte Carlo(DSMC)method and unified Boltzmann equation schemes and extend the covering range of macroscopic equations in high Knudsen number flows,data-driven nonlinear constitutive relations(DNCR)are proposed first through the machine learning method.Based on the training data from both Navier-Stokes(NS)solver and unified gas kinetic scheme(UGKS)solver,the map between responses of stress tensors and heat flux and feature vectors is established after the training phase.Through the obtained off-line training model,new test cases excluded from training data set could be predicated rapidly and accurately by solving conventional equations with modified stress tensor and heat flux.Finally,conventional one-dimensional shock wave cases and two-dimensional hypersonic flows around a blunt circular cylinder are presented to assess the capability of the developed method through various comparisons between DNCR,NS,UGKS,DSMC and experimental results.The improvement of the predictive capability of the coarsegraining model could make the DNCR method to be an effective tool in the rarefied gas community,especially for hypersonic engineering applications.
