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您的检索式：作者名="Shahed Rezaei"
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| 1 | Lossless multi-scale constitutive elastic relations with artificial intelligence显示文摘A seamless and lossless transition of the constitutive description of the elastic response of materials between atomic and continuum scales has been so far elusive.Here we show how this problem can be overcome by using artificial intelligence(AI).A convolutional neural network(CNN)model is trained,by taking the structure image of a nanoporous material as input and the corresponding elasticity tensor,calculated from molecular statics(MS),as output.Trained with the atomistic data,the CNN model captures the size-and pore-dependency of the material’s elastic properties which,on the physics side,derive from its intrinsic stiffness as well as from surface relaxation and non-local effects.To demonstrate the accuracy and the efficiency of the trained CNN model,a finite element method(FEM)-based result of an elastically deformed nanoporous beam equipped with the CNN as constitutive law is compared with that obtained by a full atomistic simulation.The trained CNN model predicts the elasticity tensor in the test dataset with a root-mean-square error of 2.4 GPa(3.0%of the bulk modulus)when compared to atomistic calculations.On the other hand,the CNN model is about 230 times faster than the MS calculation and does not require changing simulation methods between different scales.The efficiency of the CNN evaluation together with the preservation of important atomistic effects makes the trained model an effective atomistically informed constitutive model for macroscopic simulations of nanoporous materials,optimization of nanostructures,and the solution of inverse problems. | Jaber Rezaei Mianroodi Shahed Rezaei Nima H.Siboni Bai-Xiang Xu Dierk Raabe | 2022 | npj Computational Materials2022，，1： | 1 |
| 2 | Recent advances and trends in roll bonding process and bonding model:A review显示文摘This review presents a thorough survey of the roll bonding process with a focus on the bimetallic bars/tubes as well as the bonding models and criteria.The review aims to provide insight into cold,hot and cryogenic bonding mechanisms at the micro and atomic scale and act as a guide for researchers working on roll bonding,other joining processes and bonding simulation.Mean-while,the shortcomings of roll bonding processes are presented from the aspect of formable shapes,while bonding models are shown from the aspect of calculation time,convergence,interface behav-ior of dissimilar materials as well as hot bonding status prediction.Two well-accepted numerical methodologies of bonding models,namely the contact algorithm and cohesive zone model(CZM)of bonding models and in simulations of the bonding process are highlighted.Particularly,recent advances and trends in the application of the combination of mechanical interlocking and metallurgical bonding,special energy fields,gradient structure,novel materials,green technology and soft computing method in the roll bonding process are also discussed.The challenges for advancing and prospects of the roll bonding process and bonding model are presented in an attempt to shed some light on the future research direction. | Zixuan LI Shahed REZAEI Tao WANG Jianchao HAN Xuedao SHU Zbigniew PATER Qingxue HUANG | 2023 | Chinese Journal of Aeronautics2023，36，4： | 0 |
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