Springback Phenomenon Research Articles

Elastic Recovery In-Die During Cyclic Loading of Solid Anaerobic Digestate.

Anaerobic digestate represents a valuable organic by-product, with one of the main challenges being its enhanced utilization. Pelletization offers potential benefits by improving the digestate's storability, facilitating transport, and significantly expanding its application as a fertilizer or biofuel. Understanding the mechanisms of densification and their impact on the final product quality is essential and served as the inspiration for this research. Its primary focus was stress relaxation and the subsequent elongation of pellets within the compaction chamber (in-die). It investigated the hypothesis that elastic recovery, resulting from internal stress relaxation once the compressive force is removed, has direct implications for pellet quality. The investigations were conducted using a Zwick universal machine. Samples of digestate with varied moisture levels, i.e., 10, 13, 16, 19, and 22%, were loaded with amplitudes of 8, 11, 14, 17, and 20 kN. Ten loading and unloading cycles were employed. Elastic recovery (in-die) (ERin-die) in the investigated digestate increased with rising MC and compaction pressure but decreased with increasing cycle number. There was little correlation between ERin-die and pellet strength. Permanent strain energy exerted the greatest influence on pellet quality. Permanent strain energy had the greatest influence on pellet quality. Examining hysteresis loop behavior emerged as a promising area for further research to better understand springback phenomena.

Ultra-large springback bending strain and its atomistic mechanism in Ni nanowires

Springback is one of the most interesting mechanical phenomena for bent metals after stress/strain release. Most previous studies investigate the springback behaviors of metals only with low bending angles; rarely do studies investigate these metals under large bending angles. Here, we investigated the springback behaviors of twin-structured Ni nanowires (NWs) at various bending angles through in-situ experiments and molecular dynamics (MD) simulations. We discovered that the springback angle and deformation mode of twin-structured Ni NWs can be divided into three stages, which have rarely been reported. The results revealed that, as the maximum bending angle increases, the plasticity of the NWs transfers from partial dislocations parallel to the twin boundaries (TBs) to extended and full dislocations on multiple slip systems, and then to grain boundary (GB) generation. Unlike previous studies which suggested that deformation-induced dislocations and GBs are irreversible, our results show that these defects are reversible upon unloading. The different recoverable abilities of these deformation-induced defects lead to a bending-angle-dependent springback phenomenon.

Time-Dependent Deep Learning Manufacturing Process Model for Battery Electrode Microstructure Prediction

Manufacturing process of Lithium-ion battery electrode has a direct impact on the resulting practical properties of the cell such as durability, safety and overall performance. In this scenario, together with experimental efforts to understand the correlation between manufacturing process parameters and final overall electrode performance, computational tools have shown the potential to produce insights on the manufacturing properties interdependencies. The ARTISTIC initiative [1] pioneered the development of a series of computational 3D-resolved physics-based models describing each step of the manufacturing process following a sequential pattern, going from the slurry phase, through the drying phase, to produce a calendered electrode. Such physics-based models have the capability to predict how manufacturing parameters impact the electrode microstructure. At the end of each phase the output microstructure is carefully validated with experimental data, assuring that the model is in good agreement with real properties. For the calendering phase, the Discrete Element Method (DEM) is used for the model simulation.One of the main limitations of the DEM simulations is their high computational cost, preventing their direct application in electrode optimization loops. In this matter, and given the great amount of already validated data that was produced in our previous works by using the ARTISTIC model, we take one step forward in the development of a new generation model employing machine learning (ML) techniques to accelerate the physics-based simulations but keeping their accuracy. In this presentation we report a novel time-dependent deep learning (DL) model of the battery electrodes manufacturing process. The DL model is demonstrated for calendering of nickel manganese cobalt (NMC111) electrodes, and trained with time-series data arising from physics-based DEM simulations coming from the ARTISTIC physics-based modeling pipeline [2]. The innovative DL model presented in this work can predict an electrode microstructure evolution over time at a given compression degree during calendering and provide the associated final relaxed electrode microstructure. Here we used the formulation of 96% AM and 4% CBD as a proof of concept.The DL model predictions are validated by comparing data evaluation metrics (e.g., mean square error (MSE) and R2 score) and electrode functional metrics (contact surface area, porosity, diffusivity, and tortuosity factor), showing very good accuracy with respect to the DEM simulations (all the properties are above 90% accurate when compared to target data). Regarding transport properties and given the high accuracy of the DL model to predict tortuosity factor and porosity values we can conclude that the model correctly predicts the effect of the calendering on the transport properties since tortuosity factor and porosity has a high impact on the effective transport properties of Li-ions in the electrolyte. The DL model can remarkably capture the elastic recovery of the electrode upon compression (spring-back phenomenon) and the main 3D electrode microstructure features without using the functional descriptors during its training. In terms of computational cost, the DL model performs a timestep in 15 seconds (wall time) while the DEM model performs an equivalent time step in ∼47 minutes (wall time). Given the DL model significant lower computational cost than the DEM simulations, it paves the way toward quasi-real-time optimization loops of the 3D electrode architecture predicting the calendering conditions to adopt in order to obtain the desired electrode performance. Moreover, we consider that our model has tremendous potential to grow in several aspects such as accuracy and predictability. Therefore, our incoming efforts will be focused on continuing the development of the model and testing it for other formulations and in other manufacturing stages.[1] ARTISTIC Project website. https://www.erc-artistic.eu.[2] D. E. Galvez-Aranda, T. L. Dinh, U. Vijay, F. M. Zanotto, A. A. Franco, Time-Dependent Deep Learning Manufacturing Process Model for Battery Electrode Microstructure Prediction. Adv. Energy Mater. 2024, 2400376. https://doi.org/10.1002/aenm.202400376 Figure 1

Multi-scale finite element analysis of laser-assisted forming of CF/PEEK composite corner structures

Laser-assisted forming can significantly increase the forming efficiency of thermoplastic composites. However, when forming CF/PEEK curved corner structures using laser-assisted forming, bending spring-back generated by the prepreg tape constrains the shape accuracy of the component. The bending deformation of unidirectional resin matrix composite materials is highly nonlinear. In this study, a multi-scale finite element method is used to obtain the bending properties of CF/PEEK composites for bending spring-back phenomenon of thermoplastic composite samples and predict the spring-back angle of CF/PEEK corner structures fabricated via laser-assisted forming. The average material properties were first calculated using RVE. Following this, a mesoscale model was developed to analyze kink deformation of the composite. Finally, the macroscopic prepreg bending spring-back was calculated. It was determined that the main mechanism of corner forming corresponds to the occurrence of a fiber kinking phenomenon on the interior of the corner. Furthermore, spring-back deformation is caused by residual stresses resulting from insufficient fiber kinking. The accuracy of the simulation results is verified via corner forming experiments. This study contributes to a deeper understanding of the spring-back mechanisms of laser-assisted forming of corner structures and provides a theoretical guidance for precision forming of multilayer thermoplastic composite bent structures.

The effect of forming conditions and treatment process applied to the material on springback

Abstract Heat treatment is often used to optimize the balance between the strength and formability of a material. However, aging during treatment affects the ability to return to its original shape after deformation. In this study, the effects of surface treatments during the painting of mild steel and aging time in the W-temper heat treatment on springback were investigated. Consequently, because of artificial aging during surface treatment, the material precipitates certain phases and enhances the mechanical properties of the material, which leads to the pre-painted mild steel being more sensitive to springback. On the other hand, it is also noted that springback is highly dependent on the transfer time between the W-temper heat treatment of high strength aluminum alloy and forming operations, and the change in shape increases with time. In summary, the springback phenomenon is a result of the interaction between the material properties, treatment procedures, and forming circumstances.

Springback characteristics and influencing laws of four-axis flexible roll bending forming for aluminum alloy.

This study aims to solve the problem of springback control of aluminum alloy components in the rolling process, and the method of combining experiment and simulation is adopted. Firstly, a series of aluminum alloy samples are designed, and the four-axis flexible bending machine is used for precision roll bending. Secondly, the three-dimensional (3D) shape change data of the workpiece before and after roll bending is monitored and recorded in real-time by a high-precision 3D scanner. Meanwhile, aiming at different rolling process parameters of each group (including roll bend speed, feed rate, pre-deformation amount, mold curvature radius, and other factors), advanced finite element software is used to carry out detailed simulation and calculations. In addition, the coincidence is compared and analyzed between the actual experiment results and the simulation prediction. The stress-strain distribution and springback evolution of aluminum alloy during roll bending are described accurately. The experimental and simulation results show that the springback rate of aluminum alloy fluctuates in the range of 5% to 15% after four-axis flexible roll bending, and the specific springback value is influenced by various process parameters. For example, under the premise of keeping other conditions unchanged, when the roll bending speed is increased from 30mm/s to 60mm/s, the springback rate shows an upward trend of about 3%. By increasing the feed rate by 20%, an average decrease of about 7% in springback quantity is observed. It can be seen that the increase in roll bending speed can aggravate the springback phenomenon, and the appropriate increase in feed rate can play a certain role in restraining the springback. Further analysis shows that the choice of the mold curvature radius and pre-deformation amount also has a decisive influence on the springback characteristics. There is a nonlinear relationship between the two parameters and the amount of springback. Changing these two parameters in a specific range can effectively regulate the springback effect.

Effect of weld-line position on springback behavior in advanced high-strength steel tailor-welded blanks on hat-shaped bending application

In this study, both experiments and finite-element analysis are performed to elucidate the effect of weld-line position on the springback behavior of advanced high-strength steel tailor-welded blanks (AHSS-TWBs). AHSS-TWBs are fabricated from grade 590Y high-strength steel and 980Y advanced high-strength steel, each with a thickness of 1.2 mm. Gas tungsten arc welding is performed to obtain autogenous butt-weld joints. Three distinct weld-line position patterns are systematically analyzed to investigate the springback phenomenon via hat-shaped draw bending. Experiments on the AHSS-TWBs show that the weld-line position affects springback. The stress distribution changes with the weld-line position, thereby initiating variations in both the components of the bending moment and the corresponding springback angle. Depending on the weld-line position, different springback behaviors and bending moments are resulted on the components.

Study on L-Bending Springback of 45 Steel Leather Cutting Tool Coupled with Local Induction Heating

Springback error is a major obstacle in L-bending sheets via cold working. Although thermal processing can effectively reduce the springback phenomenon, it is challenging to heat the sheet globally due to the influence of working conditions. Therefore, this study applied local induction heating to reduce the springback of 45 steel sheets and investigated the effects of bending parameters on springback behavior. Initially, a thermodynamic coupling model and a static model were created utilizing the VOCE hardening model and the von Mises yield criterion in the ANSYS workbench 2022 R2 software. The springback behavior and stress distribution of the sheets were then investigated under different temperatures (room temperature and 800 °C) and bending angles (15°, 30°, 45°, 60°, 75°, and 90°). Simultaneously, the experiments were performed to investigate springback behavior and guarantee the accuracy of the model. The results indicate that the springback reached a minimum value at the 45° bending angle at room temperature while increasing with the increasing bending angle under 800 °C local heating. The springback under local heating can be decreased by 75.2% and the error of the bending angle can improve by 2–7° compared with samples processed in room temperature.

A global springback compensation method for manufacturing metallic seal ring with complex cross-section and submillimeter precision

The fabrication of complex thin-walled components with irregular cross-sectional geometries often necessitates multi-pass forming processes. The springback phenomena at the microscale level contribute significantly difficulty to the precise control of geometrical accuracy for such components. To achieve submillimeter precision control of micro features in metal seal rings, this research proposed a global springback compensation method to facilitate the attainment of the optimized surfaces of dies. Through the analysis of changes in cross-sectional shape, stress distribution and bending moment in the multiple stages, several partition points were set up to divide the cross-section into four zones. For a partitional control of the manufactured surface, the compensation magnitudes for each segment are determined by iteratively refining the compensation factors using the secant method. The iteration of compensation factors is based on the deviation of dimensions measured by finite element simulation, which greatly saves experimental costs. The experimental results indicate that the predictive dimensional alterations by the global compensation agree with the experimental ones exhibiting a maximum error of less than 3 %. Furthermore, the springback behavior during the unloading and trimming stages coupling caused a dimensional error of 14.9 % for the wave width and 8.3 % for the peak width. Following the application of coupled compensation through two iterations, a distinct decrease in the relative average errors of springback values for both part width and peak width, achieving reductions to 2.4 % and 0.6 %, respectively. Compared to the traditional single springback compensation technique, the global compensation strategy effectively mitigates the out-of-tolerance issues induced by the trimming process.

The effect of pre-painting and W-temper forming on springback

AbstractThe present investigation examined the impact of thermal cycling applied during the painting of sheet steels and the transfer period in the forming of W-temper heat treatment of high-strength aluminum alloy on springback. The U-draw bending test was conducted numerically and experimentally to examine the springback parameters. Pre-painted steel might be aged due to surface cycling during painting and it changes the mechanical characteristics. As a result, pre-painted steel becomes more susceptible to springback. It is also observed that springback is mostly reliant on the amount of transfer time between the W-temper forming of aluminum alloy. To sum up, the interplay among material characteristics, processing techniques, and forming conditions leads to the springback phenomena.

Experimental Investigations of a Springback in Hydromechanical Deep Drawing of Low Carbon Steel 1008 AISI

Hydro mechanical deep drawing (HMDD) is an emerging technology that reduces the number of sheet-forming stages and increases the production of advanced lightweight materials with intricate shapes. This study aims to verify the springback in HMDD and the effect of holding time and fluid pressure on this phenomenon (springback). The springback was measured using a new method by matching the projector p-300 axes with the cylindrical cup wall. The difference between the wall and the axis represents the springback value. Using a blank of low carbon steel (1008-AISI) with 80 mm of diameter and a thickness of 0.7 mm. The effect of holding time (1, 2, and 3 minutes) and the fluid pressure (0.6, 0.8, and 1 N/mm2) was studied. The used hydraulic oil was (code number 3803). The springback value of a cylindrical cup was calculated using the profile projector P-300. The result showed that the springback phenomenon was presented in the hydromechanical deep-drawing process but at a lower rate than the traditional deep-drawing process. The holding time and fluid pressure significantly affected the springback value. The springback decreased with increasing the fluid pressure and holding time.

Analysis of the springback phenomenon using finite element method

The springback phenomenon is a significant concern in manufacturing processes, particularly in metal component forming, as it directly affects dimensional control and the shape of formed parts. Accurate prediction and analysis of springback are crucial for achieving precise dimensional control and ensuring the desired final shape. Therefore, this study focuses on analyzing the springback phenomenon using finite element method. The primary objective is to develop a Matlab program for analyzing three-dimensional springback problems. Throughout the research process, the understanding of the phenomenon has been enhanced. The developed program has been successfully implemented to model and simulate the forming process, considering various aspects of the problem. The results of the solutions have been compared and evaluated, leading to important conclusions. The research also outlines future developments in this field. It is hoped that the results and understanding of this research will contribute to the field of computational mechanics and inspire further research.

Toward understanding the damage behavior during orthogonal cutting of 2.5D C/SiC composite based on multi-scale modeling and high-speed photography

2.5D C/SiC composite has been a critical high temperature material for aerospace filed due to its excellent wear, high temperature and oxidation resistance. Understanding the cutting damage behavior is crucial for achieving the high reliability application. This paper presents an in-depth study on damage behavior and material removal mechanism during orthogonal cutting of 2.5D C/SiC composite based on multi-scale modeling and high-speed photography. A three-dimensional numerical micro-macro multi-scale model is established considering the characteristics of the brittle SiC matrix, the isotropic carbon fiber reinforcement, and the pyrolytic carbon (PyC) layer. The orthogonal cutting experiments of 2.5D C/SiC composite with high-speed photography technology is carried out. The results show that the proposed model can accurately predict the microscopic deformation and fracture of the fiber. Meanwhile, surface fiber spring-back phenomenon is found based on high-speed photography, and its mechanism is first explanation based on the stress evolution analysis of the multi-scale model. In addition, it indicates that the increase of the depth of cut has a significant impact on the chip shape evolution, transitioning from powdery, needle-like, to block-like or strip-like shape. The paper covers some new sights for low-damage cutting of 2.5D C/SiC composite materials.

Modelling and evaluation of the post-hardness and forming limit diagram in the single point incremental hole flanging (SPIHF) process using ANN, FEM and experimental

In the single point incremental hole flanging (SPIHF) process, a sheet material with pre-cut holes is deformed using the SPIF technique to generate a flange, making it an effective approach for low volume manufacturing and quick prototyping. In the case of the SPIHF technique, the post-forming hardness property, the forming limit diagram (FLD), and spring-back phenomena are not completely evaluated. To this end, this paper employs experimental investigation and numerical validation to analyse the impact of SPIHF process parameters like tool diameter, feed rate, spindle speed, and initial hole diameter on these aspects for the truncated incrementally formed components made from AA1060 aluminium alloy and DC01 carbon steel. The plasticity behaviour of both sheet metals was simulated using the Workbench LS-DYNA model and ANSYS software version 18. Additionally, Cowper Symonds power-law hardening was added to the model to account for material properties. The average post-hardness of AA1060 and DC01 was evaluated using an SPIHF prediction model based on the performance of an artificial neural network (ANN). This ANN model was developed using a feed-forward back-propagation network trained using the Levenberg-Marquardt approach. The ANNs 4-n-1 were created by varying the transfer functions and the number of hidden neurons. Greater spindle speed and bigger pre-cut holes were shown to significantly increase the post-formed hardness of the truncated components, whereas the converse was seen when using a higher feed rate and a larger tool diameter. In addition, the FLD and spring-back improved dramatically with larger hole diameters. Employing correlation coefficient (R) and mean square error (MSE) as validation measures, it was shown that the established ANN models accurately predicted the SPIHF process response. Both the DC01 and AA1060 neural network models with a 4-8-1 network architecture performed very well, with MSE and R values of 0.0000105 and 1 for DC01 and 0.02613 and 0.99982 for AA1061.

Al-Cu Composite’s Springback in Micro Deep Drawing

With the recent technological trend of miniaturization in manufacturing industries, the rise of micro forming operations such as micro deep drawing (MDD) is inevitable. On the other hand, the need of more advanced materials is essential to accommodate various applications. However, a major problem are size effects that make micro scale operations challenging. One of the most important behaviors affected by size effects is the springback phenomenon, which is the tendency of a deformed material to go back to its original shape. Springback can affect dimensional accuracy, which is very important in micro products. Thus, this paper investigated the springback behavior of Al-Cu composite in MDD operations. Micro cups were fabricated from blank sheet specimens using an MDD apparatus with variation of annealing holding time. The springback values were measured and compared to each other. The results showed that different grain sizes lead to variation in the amount of springback. However, unlike in single-element materials, the amount of springback in Al-Cu composite is not only related to the thickness to grain size (t/d) ratio. Another factor, i.e., the existence of an interfacial region between layers, alters the mechanical behavior of the composite.

Experimental and Numerical Investigation of Folding Process—Prediction of Folding Force and Springback

The folding process is characterized by the springback phenomenon. Several experimental folding tests are elaborated and illustrated in this paper. The precision and the quality of the folded sheet workpiece are related to the reduction in the springback phenomena. For that, two tools are designed and used for the folding process. An accurate design of the folding tool plays a significant role in contributing to the folding process and reducing potential defects related to springback. An experimental solution is presented to avoid the forming of defaults and compensate the workpiece springback after its removal from the die. Moreover, an accurate numerical modeling enables an efficient prediction of the springback. This allows us to obtain precise parts through the folding process. For that, a modified Johnson–Cook model is implemented on ABAQUS software in order to predict the folding force and the springback in a U-die folding process. In addition to the isotropic hardening law, a nonlinear kinematic hardening rule is used. To ensure the model’s accuracy and reliability, we conducted validation experiments. The model’s predictions are compared with experimental tests to show its capability to simulate the folding process effectively. The developed mechanical model can adequately predict and analyze springback effects and folding force evolution, helping designers compensate for them and achieve the desired final shape.

Effect of metal powder properties of reinforced friction stir welded blanks on springback phenomenon

The influence of properties of metal powder reinforcement in the weld zone of friction stir welded blanks on springback is investigated. The weld zone properties of friction stir welded aluminum alloys namely AA5052 and AA8011 were modified by reinforcing metal powders like Al and Cu at different volume fractions. Tensile behavior of unreinforced and metal powder reinforced friction stir welded blanks was monitored by tensile test, and springback was evaluated through the V-bending process. The results show that the tensile strength and ductility increase with an increase in volume fraction of both types of powder reinforcement up to a certain level after which decrease. There is about a 7% reduction in springback with a maximum level of 1.2 vol% of both types of reinforcements as compared with unreinforced welded blanks. This study helps us select suitable properties of reinforcing material to improve the mechanical properties and to reduce springback of tailor welded blanks.

Springback Prediction of Free Bending Based on Experimental Method

The springback phenomenon has an impact on tube-processing quality during the free-bending process. For different pipe benders, the forming process is affected by different factors, such as gaps between the tube and the bending die and friction between the tube and the guiding mechanism and the bending die; thus, the theoretical U-R relationship cannot complete the precise processing required. In order to overcome the influence of springback during the free-bending forming process, a U-R experiment was performed first, and the actual U-R relationship was established. The U-R experiment demonstrated that when the bending die offset U increased, the tube-bending radius R decreased. Then, based on the results of the springback experiments, a springback prediction method was presented. The experimental method successfully predicted springback, demonstrating that the springback problem can be effectively solved through compensation of the arc section.

Characterization and Simulation of Nanoscale Catastrophic Failure of Metal/Ceramic Interfaces.

The catastrophic failure of metal/ceramic interfaces is a complex process involving the energy transfer between accumulated elastic strain energy and many types of energy dissipation. To quantify the contribution of bulk and interface cohesive energy to the interface cleavage fracture without global plastic deformation, we characterized the quasi-static fracture process of both coherent and semi-coherent fcc-metal/MgO(001) interface systems using a spring series model and molecular static simulations. Our results show that the theoretical catastrophe point and spring-back length by the spring series model are basically consistent with the simulation results of the coherent interface systems. For defect interfaces with misfit dislocations, atomistic simulations revealed an obvious interface weakening effect in terms of reduced tensile strength and work of adhesion. As the model thickness increases, the tensile failure behaviors show significant scale effects-thick models tend to catastrophic failure with abrupt stress drop and obvious spring-back phenomenon. This work provides insight into the origin of catastrophic failure at metal/ceramic interfaces, which highlights a pathway by combining the material and structure design to improve the reliability of layered metal-ceramic composites.

On the Springback and Load in Three-Point Air Bending of the AW-2024 Aluminium Alloy Sheet with AW-1050A Aluminium Cladding.

This article presents the results of an analysis of the bending load characteristics and the springback phenomenon occurring during three-point bending of 1.0 and 2.0 mm thick AW-2024 aluminium alloy sheets with rolled AW-1050A cladding. A new proprietary equation was proposed for determining the bending angle as a function of deflection, which takes into account the influence of the tool radius and the sheet thickness. The experimentally determined springback and bending load characteristics were compared with the results of numerical modelling using different models: Model I, a 2D model for a plane deformation state, disregarding the material properties of the clad layers; Model II, a 2D model for a plane deformation state, taking into account the material properties of the cladding layers; Model III, a 3D shell model with the Huber-von Mises isotropic plasticity condition; Model IV, a 3D shell model with the Hill anisotropic plasticity condition; and Model V, a 3D shell model with the Barlat anisotropic plasticity condition. The effectiveness of these five tested FEM models in predicting the bending load and springback characteristics was demonstrated. Model II was the most effective in predicting bending load, while Model III was the most effective in predicting the amount of springback after bending.