International Journal of Material Forming最新文献

Incremental Sheet Forming (ISF) is a flexible, dieless manufacturing process that enables rapid prototyping and small-batch production of complex geometries without the need for dedicated tooling. A key aspect of ISF process optimization is the accurate measurement of formability, traditionally achieved through electrochemical etching (EE) of circle grids. However, EE is time-consuming, requires specialized dies, and can yield inconsistent results. This study explores laser marking as an alternative technique for formability evaluation in ISF, comparing its performance with conventional EE. Aluminum alloy (AA1200-H14) sheets were marked using both CO₂ and Nd: YAG nanosecond-pulsed lasers under various process parameters, and the resulting surfaces were analyzed in terms of groove depth, contrast, and marking reproducibility. Incremental forming tests were conducted using a robotic arm to assess the influence of marking methods on material behavior and formability. Statistical analyses revealed that the Nd: YAG laser with parameter set 1 achieved optimal results, producing high-contrast, geometrically precise, and reproducible grids without adversely affecting the mechanical integrity of the material. Conversely, excessive energy input parameter set 2 significantly reduced formability due to surface damage and stress concentration. The findings demonstrate that properly optimized laser marking provides a reliable, non-contact, and efficient method for strain measurement in ISF, overcoming the limitations of electrochemical etching and supporting improved process monitoring and prediction.

The application breadth and strategic value of magnesium alloy bending parts, which offer significant lightweight advantages within the manufacturing field, continue to increase. However, forming defects such as cracking and springback that are generated during the bending process, along with the problem of accurate statistics of dynamic response data of overall macro and micro characteristics, seriously restrict the improvement of bending performance and hinder its application toward lightweight and depth. The three key strategies based on microstructure dominance, process path dominance, and numerical simulation dominance have become the core means to improve the bending performance due to the significant effectiveness of their control effects. This paper systematically reviews the latest progress in the regulation of bending properties of magnesium alloys, with a focus on the diversified design of microstructure, multifaceted innovation of process path, and numerical simulation of bending properties. Furthermore, challenges and future development directions of the research are prospected, in order to provide a reference for the theoretical innovation and industrial implementation of the bending performance control strategy of magnesium alloys.

Rupture disk devices are non-reclosing pressure relief mechanisms employed to safeguard vessels, pipelines, and other pressure-containing components from high pressure and/or vacuum conditions. The rupture disk is also a load rate- sensitive device. Burst pressures can vary significantly with the applied pressure rate on the rupture disk device. In this study, two types of disks were manufactured using hydroforming (HF) and deep drawing (DD) processes, and the effect of load rates was investigated on burst pressure and bulge height of hydroformed and deep drawn rupture disks. First, the HF and DD processes were applied to form the rupture disks. Second, the burst of the disks was done using a waterjet machine and then simulated by ABAQUS software. The Gurson-Tvergaard-Needlemann (GTN) criterion was used to determine the parameters defining the damage in software. After validation of simulation results, the effect of load rates was investigated on the bulge height and burst pressure of HF and DD rupture disks.

This study comprehensively examined the tensile properties and damage evolution behavior of AA2024/AA7075 dissimilar alloy Friction Stir Welding (FSW) joints using the Gurson-Tvergaard-Needleman (GTN) damage model. Through integrating tensile testing, microscopic characterization, and statistical analysis, the GTN model parameters for various welding zones were accurately calibrated. A multi-region coupled refined finite element model was established. The stress-strain curves obtained from FE simulation exhibited excellent consistency with the experimental results, thereby validating the accuracy of the proposed model. It was found that the microstructural inhomogeneity of the welded joint significantly influenced the damage evolution. Specifically, the Advancing Side of Heat Affected Zone (AS-HAZ), characterized by grain coarsening and stress concentration, emerged as the primary crack initiation region. The fracture mode of the joint exhibited a mixed ductile-brittle nature, wherein second-phase particles played a critical role by promoting void nucleation and accelerating crack propagation. Damage variables rapidly accumulated within the HAZ and propagated from the center to the edge of the cross-section along the direction of maximum shear stress, eventually leading to fracture. This study clarified the damage evolution mechanism of FSW joints, providing a quantitative theoretical basis for process optimization and performance improvement of the joints.

Cold-forming broaching with a shaped tool represents a contemporary method for forming the geometry of internal surfaces with a periodic profile via plastic deformation. A key limitation of this process is the progressive depletion of the material’s plasticity during groove formation, which leads to the degradation of mechanical strength properties. This study presents an experimental investigation into the mechanics of deformation, specifically examining the influence of tool geometry on the parameters governing deformation-induced strengthening of the material, as well as assessing the residual plasticity during the formation of internal grooves. Fracture work calculations for grooved specimens produced via сold forming broaching revealed that the specific fracture energy decreases with reductions in both the tool tooth sharpening angle and the base width of the trapezoidal profile. In order to accurately define сold forming broaching process parameters for different materials, deformation paths were constructed for the most critical points within the workpiece. The stress–strain state was evaluated using the LS-DYNA finite element software. The study establishes the impact of both the inclination angle of the tool tooth and the base dimension of its trapezoidal section on the residual plasticity resource of the workpiece.

Based on the numerical thermal-fluid coupling simulation and experiments of laser melting deposition(LMD), microstructure growth and evolution characteristics of the molten pool at different scanning speeds were investigated. Integrating experimental metallographic observations with quantitative analysis on shape control factor(G/R), cooling rate(G×R) and volume fraction of the equiaxed grains(φ) derived from the numerical temperature gradient(G) and solidification rate(R), the molten pool is divided into bottom, middle and top regions, and the grain type, grain size as well as grain transformation in each region are investigated separately and integrally. When increasing the scanning speed, the length of dendrites in the direction of temperature gradient decreases and it splits into smaller grain structures, and the grains are refined to be thinner and smaller, and therefore the microhardness of the deposition layer is improved. Scanning speed is an effectively controllable process parameter in LMD that affects G and R, which are the critical factors to be regulated for the targeted microstructures and mechanical properties. By qualitative and quantitative discussion on solidification parameters, microstructure and microhardness, this integrated numerical and experimental analysis effectively relates process parameter, microstructure and mechanical property with intrinsic mechanisms.

Modeling a material in its manufacturing process saves resources by optimizing the process conditions without using the material in trial-and-error tests. A finite element material model is in development to predict the deformation of highly-aligned discontinuous fiber prepregs in thermoforming. Unlike other high-performance composite prepregs, this material can stretch even in the fiber direction, due to the short fibers flowing and repositioning in the sheet. During stretching, this material exhibits highly-anisotropic, viscous behavior with a dominant viscosity in the fiber direction, as well as a unique stress-strain response called strain softening in which the material viscosity reduces with increasing strain. Both of these behaviors are inherently unstable: the material can stretch with little resistance in the transverse direction, and the more it stretches longitudinally, the easier it can stretch further due to strain softening. An equation was developed that describes this material’s extension behavior and implemented into the finite element solver AniForm. The parameters that describe the stretching behavior were derived from axial extension tests performed on TuFF made of IM7 carbon fibers and 977-3 thermoset resin under one set of process conditions (temperature, strain rate). The model was verified by matching the experimental data in longitudinal extension. The model was then validated by accurately predicting the extension-dominated deformation of a 4-ply laminate in gas-pressure bladder molding through a die similar to realistic part forming. The strain state on the surface ply was tracked in-situ using a DIC setup during forming and the results were compared with the AniForm simulation in which the constitutive equation that described the highly-aligned discontinuous fiber prepreg behavior was implemented.

Aiming at the nonlinear characteristics of the driver head formation process in interference-fit riveting, the difficulty in establishing correlations between driver head dimension and riveting force, and the inability of existing methods to properly guide riveting force determination for joints with different process parameters, this paper proposes a theoretical model based on metal plastic forming mechanics theory to predict the required riveting force for achieving standard driver head dimensions. Finite element simulation technology and riveting experiments were employed to obtain driver head dimensions of Φ4 × 9 mm and Φ5 × 10 mm 2A10 semi-spherical rivets under different riveting forces. The results show that the theoretical riveting forces calculated from simulation-measured driver head dimensions have average errors of 1.41% and 1.89% compared to set values. The theoretical riveting forces calculated from experimentally measured driver head height and maximum diameter initially exhibit larger errors. After introducing an interference correction coefficient, the average errors decrease to 3.01% and 0.81% respectively, demonstrating good agreement.

Superplastic forming technology exhibits broad application prospects in the manufacturing of aluminum alloy components, with advantages including high dimensional accuracy, low residual stresses, and minimal rebound, it enables substantial weight reduction without compromising strength while even enhancing stiffness. However, formed components still face challenges such as uneven wall thickness and cracking. This paper analyses the rheological behavior of 5083 aluminum alloy plates at temperatures of 470 °C, 490 °C, and 510 °C and strain rates of 0.01 s⁻¹, 0.004 s⁻¹, 0.0075 s⁻¹, and 0.0006 s⁻¹. Using ABAQUS software, numerical simulations of superplastic forming for 5083 aluminum alloy cup shell were conducted. To maximize the thinning rate of cup shell parts, response surface methodology was employed to perform numerical simulations of their preforming process, revealing the relationship between superplastic forming process parameters and the minimum thickness of cup shell, yielding the optimal combination of superplastic forming process parameters for 5083 aluminum alloy; furthermore, the forming height under varying rated pressures was analyzed, and forming tests were conducted using the optimal parameters to verify the accuracy of the experimental and simulation results. Finally, mechanical property evaluations at different locations of formed components were performed via tensile and hardness testing, while microstructural characterization was carried out via electron backscatter diffraction (EBSD). Results indicated that the superplastic forming cup shell parts demonstrating uniformly refined microstructures and high forming quality. These findings offer critical insights for manufacturing more complex aluminum alloy superplastic forming prats in aerospace and transportation industries.

Graphical abstract

To increase the ratio of manufactured recycled poly(ethylene terephthalate) (rPET) bottle, the control of ISBM (Injection Stretch Blow Moulding) process must account for varying mechanical and thermal properties of mechanically recycled PET. Calibration and optimization of the process have been successfully realized in past works, but they use costly PDE-based models. Therefore, they are difficult to use online for applications where the process parameters need to be regularly adjusted, i.e. whenever a new batch of preforms made of recycled PET is considered. To address this, a meta-algorithm is proposed to replace the PDE-based digital twin. A gaussian process regression is trained offline using the PDE-based digital twin results in the process’s variabilities range. Using the internal pressure history of a test ISBM operation, our strategy allows us to obtain calibrated results without solving PDEs online. To show the capability of the methodology, a simplified process and its associated parametric uncertainties are enunciated. Finite element simulations of the ISBM process where the properties follow a multivariate Gaussian distribution are used to realize the Gaussian process regression. The quality of the digital twin’s predictions is assessed. Then, an illustrative example is presented, demonstrating the use of the digital twin predictions to optimize the thickness distribution of a bottle following the blowing process.