The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to ...The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to achieving controllable stress-strain rate loading.In this study,we have,for the first time,combined one-dimensional fluid computational software with machine learning methods.We first elucidated the mechanisms by which GDI structures control stress and strain rates.Subsequently,we constructed a machine learning model to create a structure-property response surface.The results show that altering the loading velocity and interlayer thickness has a pronounced regulatory effect on stress and strain rates.In contrast,the impedance distribution index and target thickness have less significant effects on stress regulation,although there is a matching relationship between target thickness and interlayer thickness.Compared with traditional design methods,the machine learning approach offers a10^(4)—10^(5)times increase in efficiency and the potential to achieve a global optimum,holding promise for guiding the design of GDI.展开更多
Five kinds of mortars with density grades of 500,600,700,800,and 900 kg/m^(3)were prepared.Their thermal conductivity and compressive strength were measured,and the morphological changes before and after simulated tun...Five kinds of mortars with density grades of 500,600,700,800,and 900 kg/m^(3)were prepared.Their thermal conductivity and compressive strength were measured,and the morphological changes before and after simulated tunnel fire were observed.To investigate the fire resistance,the interfacial temperature of a 30 mm thick aerogel-cement mortar and self-compacting concrete(SCC)in a simulated tunnel fire with the maximum temperature of 1100℃for 2.5 h was tested and recorded.The results showed that as the density decreased,both compressive strength and thermal conductivity of the aerogel-cement mortar exhibited an exponential decrease.The effective fire resistance time of the mortar with 500,600,700,800,and 900 kg/m^(3)for protecting SCC from tunnel fire were 97 min,114 min,144 min,>150 min,136 min,respectively.700-800 kg/m^(3)was the optimum density for engineering application of tunnel concrete fireproof coating.展开更多
Two types of Mg-Cu composition system graded density impactors used for complex loading （shock loading and quasi-isentropic compression） are designed by the elastic-plastic hydrodynamic method in this paper. Mixture...Two types of Mg-Cu composition system graded density impactors used for complex loading （shock loading and quasi-isentropic compression） are designed by the elastic-plastic hydrodynamic method in this paper. Mixtures of metal powders in the Mg-Cu system are cast into a series of 17 and 25 uniform compositions ranging from 100% Mg to 100% Cu. The graded den- sity impactors are launched to the stationary 10 Ixm aluminum film and 12 mm LiF window targets by a two-stage light-gas gun in the National Key Laboratory for Shock Wave and Detonation Physics Research, Institute of Fluid Physics, CAEP, and the resulting wave profiles are measured with the DISAR system. Hydrodynamic simulation results are perfectly consistent with the experiments. Our work in this paper will set up a foundation for further research of controllable loading/releasing routes and rate experiments in the future.展开更多
基金supported by the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2021B0301030001)the National Key Research and Development Program of China(Grant No.2021YFB3802300)the Foundation of National Key Laboratory of Shock Wave and Detonation Physics(Grant No.JCKYS2022212004)。
文摘The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to achieving controllable stress-strain rate loading.In this study,we have,for the first time,combined one-dimensional fluid computational software with machine learning methods.We first elucidated the mechanisms by which GDI structures control stress and strain rates.Subsequently,we constructed a machine learning model to create a structure-property response surface.The results show that altering the loading velocity and interlayer thickness has a pronounced regulatory effect on stress and strain rates.In contrast,the impedance distribution index and target thickness have less significant effects on stress regulation,although there is a matching relationship between target thickness and interlayer thickness.Compared with traditional design methods,the machine learning approach offers a10^(4)—10^(5)times increase in efficiency and the potential to achieve a global optimum,holding promise for guiding the design of GDI.
基金Funded by National Natural Science Foundation of China(No.51678081)the Natural Science Research of the Jiangsu Higher Education Institution of China(No.18KJB560001)。
文摘Five kinds of mortars with density grades of 500,600,700,800,and 900 kg/m^(3)were prepared.Their thermal conductivity and compressive strength were measured,and the morphological changes before and after simulated tunnel fire were observed.To investigate the fire resistance,the interfacial temperature of a 30 mm thick aerogel-cement mortar and self-compacting concrete(SCC)in a simulated tunnel fire with the maximum temperature of 1100℃for 2.5 h was tested and recorded.The results showed that as the density decreased,both compressive strength and thermal conductivity of the aerogel-cement mortar exhibited an exponential decrease.The effective fire resistance time of the mortar with 500,600,700,800,and 900 kg/m^(3)for protecting SCC from tunnel fire were 97 min,114 min,144 min,>150 min,136 min,respectively.700-800 kg/m^(3)was the optimum density for engineering application of tunnel concrete fireproof coating.
基金supported by the National Natural Science Foundation of China (Grant No. 11072228, 11002129)the Science Foundation of China Academy of Engineering Physics (Grant No. 2011B0202005)+1 种基金the Open Foundation of State Key Laboratory of Explosion Science and Technology(Grant No. KFJJ09-06)the Open Foundation of State Key Laboratory of Advanced Technology for Materials Synthesis and Process-ing, Wuhan University of Technology
文摘Two types of Mg-Cu composition system graded density impactors used for complex loading （shock loading and quasi-isentropic compression） are designed by the elastic-plastic hydrodynamic method in this paper. Mixtures of metal powders in the Mg-Cu system are cast into a series of 17 and 25 uniform compositions ranging from 100% Mg to 100% Cu. The graded den- sity impactors are launched to the stationary 10 Ixm aluminum film and 12 mm LiF window targets by a two-stage light-gas gun in the National Key Laboratory for Shock Wave and Detonation Physics Research, Institute of Fluid Physics, CAEP, and the resulting wave profiles are measured with the DISAR system. Hydrodynamic simulation results are perfectly consistent with the experiments. Our work in this paper will set up a foundation for further research of controllable loading/releasing routes and rate experiments in the future.
