The one-step finite element method （FEM）, based on plastic deformation theory, has been widely used to simulate sheet metal forming processes, but its application in bulk metal forming simulation has been seldom inv...The one-step finite element method （FEM）, based on plastic deformation theory, has been widely used to simulate sheet metal forming processes, but its application in bulk metal forming simulation has been seldom investigated, because of the complexity involved. Thus, a bulk metal forming process was analyzed using a rapid FEM based on deformation theory. The material was assumed to be rigid-plastic and strain-hardened. The constitutive relationship between stress and total strain was adopted, whereas the incompressible condition was enforced by penalty function. The geometrical non-linearity in large plastic deformation was taken into consideration. Furthermore, the force boundary condition was treated by a simplified equivalent approach, considering the contact history. Based on constraint variational principle, the deformation FEM was proposed. The one-step forward simulation of axisymmettic upsetting process was performed using this method. The results were compared with those obtained by the traditional incremental FEM to verify the feasibility of the proposed method.展开更多
The infrared radiation characteristics of aircraft are a key focus in attack-defense confrontation and early warning detection.A rapid simulation method for calculating the infrared characteristics of targets is propo...The infrared radiation characteristics of aircraft are a key focus in attack-defense confrontation and early warning detection.A rapid simulation method for calculating the infrared characteristics of targets is proposed by combining the discrete transfer method.By constructing the aerodynamic shape of a Su-27-like aircraft,the flow field parameters and skin temperature under cruise conditions were calculated.The proposed method was used to generate infrared images and calculate infrared radiation intensity at various detection angles,and perform speed tests.The results indicate that this method has high accuracy;the generated infrared image is clear,accurate,and can be used to identify the characteristic attributes of the target.In the pitch detection plane,the total infrared radiation intensity of the aircraft exhibits a“8”distribution,with the fuselage contributing the most(approximately 50%).In the yaw plane,the vertical stabilizer’s infrared radiation intensity shows a lobed distribution,with peaks at 60°and 120°.The method can achieve a calculation speed of four times per second for a single detection angle,meeting real-time processing requirements and providing valuable data for infrared target recognition algorithms.展开更多
Pretrained universal machine-learning interatomic potentials(MLIPs)have revolutionized computational materials science by enabling rapid atomistic simulations as efficient alternatives to ab initio methods.Fine-tuning...Pretrained universal machine-learning interatomic potentials(MLIPs)have revolutionized computational materials science by enabling rapid atomistic simulations as efficient alternatives to ab initio methods.Fine-tuning pretrained MLIPs offers a practical approach to improving accuracy for materials and properties where predictive performance is insufficient.However,this approach often induces catastrophic forgetting,undermining the generalizability that is a key advantage of pretrained MLIPs.Herein,we propose reEWC,an advanced fine-tuning strategy that integrates Experience Replay and Elastic Weight Consolidation(EWC)to effectively balance forgetting prevention with fine-tuning efficiency.Using Li_(6)PS_(5)Cl(LPSC),a sulfide-based Li solid-state electrolyte,as a fine-tuning target,we show that reEWC significantly improves the accuracy of a pretrained MLIP,resolving well-known issues of potential energy surface softening and overestimated Li diffusivities.Moreover,reEWC preserves the generalizability of the pretrained MLIP and enables knowledge transfer to chemically distinct systems,including other sulfide,oxide,nitride,and halide electrolytes.Compared to Experience Replay and EWC used individually,reEWC delivers clear synergistic benefits,mitigating their respective limitations while maintaining computational efficiency.These results establish reEWC as a robust and effective solution for continual learning in MLIPs,enabling universal models that can advance materials research through large-scale,high-throughput simulations across diverse chemistries.展开更多
基金Sponsored by National Natural Science Foundation of China(50575143)Specialized Research Fund for Doctoral Program of Higher Education of China(20040248005)
文摘The one-step finite element method （FEM）, based on plastic deformation theory, has been widely used to simulate sheet metal forming processes, but its application in bulk metal forming simulation has been seldom investigated, because of the complexity involved. Thus, a bulk metal forming process was analyzed using a rapid FEM based on deformation theory. The material was assumed to be rigid-plastic and strain-hardened. The constitutive relationship between stress and total strain was adopted, whereas the incompressible condition was enforced by penalty function. The geometrical non-linearity in large plastic deformation was taken into consideration. Furthermore, the force boundary condition was treated by a simplified equivalent approach, considering the contact history. Based on constraint variational principle, the deformation FEM was proposed. The one-step forward simulation of axisymmettic upsetting process was performed using this method. The results were compared with those obtained by the traditional incremental FEM to verify the feasibility of the proposed method.
基金This work was supported by the National Natural Science Foundation of China(12102356).
文摘The infrared radiation characteristics of aircraft are a key focus in attack-defense confrontation and early warning detection.A rapid simulation method for calculating the infrared characteristics of targets is proposed by combining the discrete transfer method.By constructing the aerodynamic shape of a Su-27-like aircraft,the flow field parameters and skin temperature under cruise conditions were calculated.The proposed method was used to generate infrared images and calculate infrared radiation intensity at various detection angles,and perform speed tests.The results indicate that this method has high accuracy;the generated infrared image is clear,accurate,and can be used to identify the characteristic attributes of the target.In the pitch detection plane,the total infrared radiation intensity of the aircraft exhibits a“8”distribution,with the fuselage contributing the most(approximately 50%).In the yaw plane,the vertical stabilizer’s infrared radiation intensity shows a lobed distribution,with peaks at 60°and 120°.The method can achieve a calculation speed of four times per second for a single detection angle,meeting real-time processing requirements and providing valuable data for infrared target recognition algorithms.
基金supported by the Nano & Material Technology Development Programs through the National Research Foundation of Korea (NRF) funded by Ministry of Science and ICT (No. RS-2024-00407995 and No. RS-2024-00450102). The computations were carried out at Korea Institute of Science and Technology Information (KISTI) National Supercomputing Center (KSC-2025-CRE-0110) and at the Center for Advanced Computations (CAC) at Korea Institute for Advanced Study (KIAS).
文摘Pretrained universal machine-learning interatomic potentials(MLIPs)have revolutionized computational materials science by enabling rapid atomistic simulations as efficient alternatives to ab initio methods.Fine-tuning pretrained MLIPs offers a practical approach to improving accuracy for materials and properties where predictive performance is insufficient.However,this approach often induces catastrophic forgetting,undermining the generalizability that is a key advantage of pretrained MLIPs.Herein,we propose reEWC,an advanced fine-tuning strategy that integrates Experience Replay and Elastic Weight Consolidation(EWC)to effectively balance forgetting prevention with fine-tuning efficiency.Using Li_(6)PS_(5)Cl(LPSC),a sulfide-based Li solid-state electrolyte,as a fine-tuning target,we show that reEWC significantly improves the accuracy of a pretrained MLIP,resolving well-known issues of potential energy surface softening and overestimated Li diffusivities.Moreover,reEWC preserves the generalizability of the pretrained MLIP and enables knowledge transfer to chemically distinct systems,including other sulfide,oxide,nitride,and halide electrolytes.Compared to Experience Replay and EWC used individually,reEWC delivers clear synergistic benefits,mitigating their respective limitations while maintaining computational efficiency.These results establish reEWC as a robust and effective solution for continual learning in MLIPs,enabling universal models that can advance materials research through large-scale,high-throughput simulations across diverse chemistries.
