The cold forming process becomes necessary in ship hull panel production when certain physical properties cannot be altered. To achieve precise cold forming results for doubly curved hull plates ...using reconfigurable dies, this paper introduces springback ratio (SR) matrices and SR feature values as descriptors and compensatory measures for springback. The feasibility and validity of the SR matrix and SR feature value are confirmed through an examination of springback outcomes from nine single-curvature plates, as documented in existing literature. Theoretical deductions highlighted a substantial contrast between sail-type and saddle-type plates. Subsequently, 14 metal doubly curved plate forming experiments are introduced employing reconfigurable dies. Upon comparing the springback results of sail-type and saddle-type plates described by SR feature values, it becomes evident that saddle-type plates exhibit significantly less springback than sail-type plates. In response, a novel springback compensation algorithm is proposed based on SR matrices. This algorithm is compared with an existing method, and the results demonstrate its superior performance in springback compensation.
Stretch bending is widely used for manufacturing profile-type parts. However, one of the challenges faced by the bending-type forming processes is springback, which significantly reduces the ...dimensional accuracy of formed part, process flexibility and overall equipment effectiveness. In this study, we focus on the springback behavior in a newly developed flexible rotary stretch bending process for profiles. Using the Al-Mg-Si alloy rectangular hollow extrusions, the effect of stretching on springback, as well as process capability, is evaluated by a series of carefully designed experiments conducted for a wide range of stretching strains. Increasing the stretching strain from about 2% to 4%, the springback chord height can be reduced by about 32% and the process capability can be improved significantly, showing the strong ability of the novel flexible stretch bending strategy for controlling springback and dimensional accuracy.
Accurately predicting the amount of springback has always been a prior focus in metal forming industry, particularly for creep age forming (CAF), for its significant effect on tool cost and forming ...accuracy. In this study, a closed-form solution for CAF springback prediction covering deformation from elastic to plastic loadings was developed by combining the beam theory and Winkler’s theory, based on which an efficient springback compensation method for CAF was proposed. This developed solution extends the application area beyond the traditional beam theory-based springback prediction methods, maintaining its validity with large loading deflection in plastic range. Finite element (FE) simulation and four-point bending CAF tests adopting a 3rd generation Al-Li alloy were conducted in both elastic and plastic forming regions and the results showed close agreement with the closed-form springback predictions. For the proposed compensation method, an adjustment factor was introduced for complex flexible tool CAF to consider its deviation from the uniform stress loading and can be obtained using the closed-form solution. The flexible tool CAF tests using the Al-Li alloy demonstrated the applicability of the proposed compensation method to obtain the target shape within reasonable iterations, which can be further reduced by combining FE simulation.
Due to the discrete die of multi-point stretch bending, there are contact zone and non-contact zone on the profile, which makes the springback phenomenon more complicated. In this paper, considering ...that the neutral layer will shift due to the application of pre-stretching and post-stretching, an analytical model of the relationship between springback error and stress is established. Under the different bending radius, the maximum springback error obtained by theoretical calculation is 6.9%, while the average springback error of the traditional springback model is 10.5%, which means that the springback prediction model proposed in this paper is more reliable. Multi-point stretch bending has been unanimously recognized by everyone because of its adjustable die surface. In this paper, the secant method is used to calculate the springback compensation factor, so that the springback error of the profile is within the allowable error range of the production under the limited numbers of springback compensation.
Springback has always been a stubborn defect that affects the axial accuracy of metal bending. The finite element simulation of springback enables effective control and precise compensation to ...improve the forming quality. Affected by the material, size, and forming process, the generation pattern of the springback defect remains further exploration. Graph-based deep learning techniques support differentiable high-dimensional physics simulations with significantly lower computational resources and comparable accuracy. In this paper, a framework based on geometry/process-integrated Graph Neural Networks (GNN) is presented for simulating axial springback of mesh-based metal bending, with a specific focus on the tube bending. The framework adopts an encode-process-decode structure, equipped with parallel graph network blocks and data augmentation strategy, to capture the axial springback information with high fidelity in a form of mesh. Comparative experiments reveal that our framework achieves an accuracy comparable to that of finite elements method, yielding an average nodal error below 1 mm and outperforming three representative GNN baselines. The framework remarkably enhances the simulation efficiency, exhibiting a four-order-of-magnitude improvement on CPU and a six-order-of-magnitude improvement on GPU compared to finite elements method. Furthermore, we successfully apply the proposed framework to simulate the springback of plate V-bending, showcasing its robust generalization ability. These results illustrate the capability of our GNN framework to achieve the accurate and real-time springback simulation, with significant implications for digital twin development and bent tube quality optimization.
With the advantages of continuous bending, small bending diameter, and variable curvature, the spatial variable curvature (SVC) bent metallic tube (MT) is widely used in the aeronautics industry. Due ...to the complex characteristics of its central axis, SVC MT bending is prohibitive in terms of modeling and analysis, which results in a rather high calculation complexity. The springback is the primary detection that directly affects the axial forming accuracy. To achieve higher forming accuracy, this paper provides a numerical approximation springback prediction and compensation method considering cross-section distortion for SVC MT. The curvature and torsion mapping function of MT central axis before and after springback is constructed. According to the characteristics of different SVC MT, the differential equations in the SVC springback prediction model are solved by using three numerical approximation methods. The springback compensation method is subsequently obtained by inverse operation of the mapping relationship. To verify the feasibility of the proposed method, a 00Cr17Ni14Mo2 tube is bent with a multi-roll bender into the spiral shape. The results of the three springback numerical approximation methods and the numerical simulation result are compared. It illustrates that the Runge–Kutta method owns the highest prediction accuracy, so that we choose the Runge–Kutta method for bending compensation. The result indicates that the position deviation of each node is less than 1.4% along with the average position deviation of 0.80% after springback compensation.
•The theoretical model for investigating springback of spatial tubes is extended to different loading modes and hardening materials.•Radii and angles after springback will both increase accordingly ...with the increasing of loading index k (defined in this paper).•Evaluating the loading index k reasonably is beneficial for improving the precision of springback prediction.
The objective of this paper is to investigate the springback of spatial tubes. The model for analyzing the springback of spatial tubes in 1 is extended to different loading modes and hardening materials. Comparisons among theoretical model, FEM model and experiments are performed to validate the effectiveness of the predictions. Results show that the new model is more effective to describe the springback behavior of spatial tubes, and the principles obtained by the new model are coincident with previous researches. Based on the theoretical model, the influence of loading modes on spatial tube springback is newly investigated. It is found that radii after springback and angles after springback will both increase accordingly with the increasing of loading index k. And evaluating the loading index k reasonably is beneficial for improving the precision of prediction results.
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In this study, electromagnetic-assisted stamping (EMAS) with magnetic-force reverse loading was introduced to control springback. Compared to conventional EMAS, this new method does not change the ...mold structure used in traditional stamping technology. Thus, this approach can greatly extend the operating lifetime of the mold and readily be adopted for commercial production. Results indicate that the equivalent plastic strain and the plastic dissipation energy increase, while the tangential stress and the elastic strain energy decrease considerably, with increasing in discharge-voltage. The simulation results accurately predict the sheet deformation for quasi-static stamping and dynamic magnetic pulse forming. Both simulations and experiments show that the angle after springback decreases with increasing in discharge-voltage.
Quenching and partitioning (QP) steels exhibit apparent tension-compression asymmetry and evolving Bauschinger effect as plastic deformation proceeds, which brings challenges to accurately predict ...springback of QP steel parts. Loading-reverse loading tests are conducted to characterize the Bauschinger effect of a QP steel with a strength grade of 1500 MPa (QP1500), where the maximum achievable strains are limited. A machine-learning method is developed to extend the capability limit of physical tension-compression (TC) or compression-tension (CT) tests and virtually generate stress vs. strain curves at larger strains (up to 0.18), which cover the strain history of an actual forming part (e.g. M-shaped part). Then a data-driven method is proposed to calibrate parameters of a kinematic hardening model (Yoshida-Uemori model), which adopts all TC and CT stress vs. strain curves from physical tests and machine learning. This new set of Yoshida-Uemori model parameters is used in finite element simulations to predict springback of an M-shaped QP1500 steel part, and an obviously improved agreement is reached between simulation and experimental measurements of the M-shaped part. The mean error of predicted local springback distance was reduced to 0.23 mm. It is demonstrated that machine learning method is capable to capture the asymmetric and evolving Bauschinger effect within a much broader strain range and improve springback prediction of QP1500 steel.
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•QP1500 steel exhibits evolving Bauschinger effect as a function of strain.•QP1500 steel shows obvious tension-compression asymmetry between TC & CT loading.•Machine learning (ML) is employed to acquire TC/CT curves at larger strains.•A data-driven calibration method for YU parameters uses data from experiment & ML.•Data-driven calibration enhances springback prediction of QP1500 steel part.
lA mathematical model of springback under severe plastic compressive deformation (SPCD) is established based on physical and mechanics mechanisms.lEffects of macro variables on saturated springback ...of SPCD are discussed.lAnisotropy springback model of FCC metal material under SPCD in a Gaussian form is firstly proposed.lThe non-quasi-static anisotropy springback model containing size effect factor and comprehensive effect factor have high accuracy in predicting saturated springback of bulk forming.
Accurate prediction of springback under severe plastic deformation is necessary for the geometric error in precision forming process, in order to establish accurate model of saturated springback under bulk forming. In this paper, the springback behavior and prediction model of anisotropic face-centered cubic (FCC) crystal copper alloy under severe plastic compressive deformation (SPCD) were studied from micro-perspective and macro-perspective. From the micro-perspective, a mathematical model of springback was established based on physical and mechanics mechanisms for predicting the saturated springback of the SPCD. Subsequently, from the macro-perspective, the effects of the macro variables including stress, strain, applied load, deformed surface area, external work, etc., on the saturated springback of quasi-static SPCD were discussed, and a anisotropic springback model of FCC material for the quasi-static SPCD process in a Gaussian form was set up based on above discussion and the expression of the proposed mathematical model of springback. Furthermore, the non-quasi-static anisotropic springback model containing comprehensive effect factor and size effect factor was proposed to predict the saturated springback of copper alloy after rolling process. The results indicated that the proposed springback models based on physical mechanism and macro variables can accurately predict the saturated springback of the anisotropic copper alloy under the SPCD. By introducing comprehensive effect and size effect factors, the anisotropic springback model for the non-quasi-static SPCD process has higher accuracy in predicting the saturated springback of bulk forming process. The present study revealed the springback behavior of anisotropic FCC copper alloy, and proposed accurate prediction models of saturated springback, which are of great significance to adjust the forming process and compensate the springback error of the FCC metal material during the bulk forming process.
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