In this work,the nickel-based powder metallurgy superalloy FGH95 was selected as experimental material,and the experimental parameters in multiple overlap laser shock processing(LSP)treatment were selected based on or...In this work,the nickel-based powder metallurgy superalloy FGH95 was selected as experimental material,and the experimental parameters in multiple overlap laser shock processing(LSP)treatment were selected based on orthogonal experimental design.The experimental data of residual stress and microhardness were measured in the same depth.The residual stress and microhardness laws were investigated and analyzed.Artificial neural network(ANN)with four layers(4-N-(N-1)-2)was applied to predict the residual stress and microhardness of FGH95 subjected to multiple overlap LSP.The experimental data were divided as training-testing sets in pairs.Laser energy,overlap rate,shocked times and depth were set as inputs,while residual stress and microhardness were set as outputs.The prediction performances with different network configuration of developed ANN models were compared and analyzed.The developed ANN model with network configuration of 4-7-6-2 showed the best predict performance.The predicted values showed a good agreement with the experimental values.In addition,the correlation coefficients among all the parameters and the effect of LSP parameters on materials response were studied.It can be concluded that ANN is a useful method to predict residual stress and microhardness of material subjected to LSP when with limited experimental data.展开更多
Surface microstructure and mechanical properties of pearlitic Fe–0.8%C(mass fraction) steel after laser shock processing(LSP) with different laser pulse energies were investigated by scanning electron microscopy(SEM)...Surface microstructure and mechanical properties of pearlitic Fe–0.8%C(mass fraction) steel after laser shock processing(LSP) with different laser pulse energies were investigated by scanning electron microscopy(SEM),transmission electron microscopy(TEM),X-ray diffraction(XRD) and microhardness measurements.After LSP,the cementite lamellae were bent,kinked and broken into particles.Fragmentation and dissolution of the cementite lamellae were enhanced by increasing the laser pulse energy.Due to the dissolution of carbon atoms in the ferritic matrix,the lattice parameter of α-Fe increased.The grain size of the surface ferrite was refined,and the microstructure changed from lamellae to ultrafine micro-duplex structure(ferrite(α)+cementite(θ)) with higher laser pulse energy,accompanied by the residual stress and microhardness increase.展开更多
基金Projects(51875558,51471176)supported by the National Natural Science Foundation of ChinaProject(2017YFB1302802)supported by the National Key R&D Program of China。
文摘In this work,the nickel-based powder metallurgy superalloy FGH95 was selected as experimental material,and the experimental parameters in multiple overlap laser shock processing(LSP)treatment were selected based on orthogonal experimental design.The experimental data of residual stress and microhardness were measured in the same depth.The residual stress and microhardness laws were investigated and analyzed.Artificial neural network(ANN)with four layers(4-N-(N-1)-2)was applied to predict the residual stress and microhardness of FGH95 subjected to multiple overlap LSP.The experimental data were divided as training-testing sets in pairs.Laser energy,overlap rate,shocked times and depth were set as inputs,while residual stress and microhardness were set as outputs.The prediction performances with different network configuration of developed ANN models were compared and analyzed.The developed ANN model with network configuration of 4-7-6-2 showed the best predict performance.The predicted values showed a good agreement with the experimental values.In addition,the correlation coefficients among all the parameters and the effect of LSP parameters on materials response were studied.It can be concluded that ANN is a useful method to predict residual stress and microhardness of material subjected to LSP when with limited experimental data.
基金Projects(50801021,51201061)supported by the National Natural Science Foundation of ChinaProject(144200510009)supported by the Henan Province Program for Science and Technology Innovation Excellent Talents,China+1 种基金Project(152102210077)supported by the Science and Technology Project of Henan Province,ChinaProject(2015XTD006)supported by the Science and Technology Innovation Team of Henan University of Science and Technology,China
文摘Surface microstructure and mechanical properties of pearlitic Fe–0.8%C(mass fraction) steel after laser shock processing(LSP) with different laser pulse energies were investigated by scanning electron microscopy(SEM),transmission electron microscopy(TEM),X-ray diffraction(XRD) and microhardness measurements.After LSP,the cementite lamellae were bent,kinked and broken into particles.Fragmentation and dissolution of the cementite lamellae were enhanced by increasing the laser pulse energy.Due to the dissolution of carbon atoms in the ferritic matrix,the lattice parameter of α-Fe increased.The grain size of the surface ferrite was refined,and the microstructure changed from lamellae to ultrafine micro-duplex structure(ferrite(α)+cementite(θ)) with higher laser pulse energy,accompanied by the residual stress and microhardness increase.
