International Journal of Material Forming最新文献

For addressing the challenge of integrating the nonlinear Mises specific plasticity power, this manuscript derives the formulation of the specific plastic power based on the Double Mean approximation criterion (DM criterion). This derivation establishes the necessary conditions for integrating the internal deformation power of a thick plate. Meanwhile, a sinusoidal velocity field that satisfies the kinematically admissible conditions is formulated, and the finite element method is employed to simulate the flow behavior of the deformed metal, thereby validating the reliability of the velocity field. Based on this, the internal deformation power is determined through energy analysis of the constructed velocity field using the DM criterion, Tresca criterion, and TSS criterion. The root vector decomposition method is utilized to derive the friction power and shear power, while various criteria are employed in obtaining the analytical solutions for the rolling force using the energy method. Comparison with the existing Sims model and experimental data demonstrates that the rolling force models in accordance with the DM criterion and Tresca criterion both have errors less than 15%, and their predictive accuracy surpasses that of the Sims model. However, the TSS criterion has a prediction error greater than 25% and performs poorly. Among them, the average relative error of the rolling force and rolling torque on the basis of the DM criterion is 7.15%, and the Tresca criterion can offset the high bias brought by the upper bound method, with an average relative error of only 3.64% for rolling force and rolling torque.

Deep-groove rings are typical profiled rings which are widely used in connect flanges, casing, etc. In traditional ring rolling, the metal is easy to flow circumferentially to expand ring diameter, but it is difficult to flow axially and radially to form the irregular section contour, making it difficult to achieve near-net forming of the deep-groove ring. In this work, a novel constrained ring rolling of the deep groove ring is proposed, which can make the ring into a multi-point constrained deformation state by changing the control mode of guide roll and conical roll, limiting the circumferential metal flow ability and promoting the axial and radial metal flow ability, thus realizing the coordinated forming of the ring diameter and section profile. The evolution law of the ring geometry, metal flow deformation behavior, and the mechanical states between the roll and ring under the traditional ring rolling and constrained ring rolling were compared and analyzed by FE simulation. The influence of guide roll and conical roll motion control parameters was further studied and found that guide roll motion and conical roll speed have great influence on ring forming. Finally, a typical deep groove ring rolling experiment is carried out and the near-net rolling of deep groove ring can be realized by using the constrained ring rolling.

During the solidification of heavy ingots during casting, internal metallurgical defects are commonly observed. Despite the application of upsetting to remove internal voids in ingots, defects are often not fully eliminated by the end of the process. To address this challenge and produce upset ingots with minimal internal defects, this study introduces a novel approach. The first step involves simulating the formation of shrinkage porosity during ingot solidification and identifying the critical zone prone to internal defects. Subsequently, the study analyzes the effective strain distribution and mean stress in different sections of the critical zone using various upsetting anvil geometries. An optimized approach is then proposed, involving the shifting of the critical area to where the most significant plastic deformation is likely to occur. This is achieved through a new pin-making strategy and the selection of the best geometry for the pair of upsetting dies. To validate the model, 100CrMo7-3 heavy ingots are produced and subjected to upsetting and cogging operations using a 63MN hydraulic press. The results from ultrasonic and microscopic examinations indicate that the proposed method leads to fewer internal imperfections. Additionally, a comparison between numerical and experimental results demonstrates good agreement, resulting in a reduced risk of remaining internal shrinkage porosities after upsetting large-scale ingots.

Lightweight automotive extrusions are increasingly complex, thin-walled, multi-hollow profiles made from quench-sensitive alloys like AA6082. These profiles require rapid (water) quenching as they leave the press in preparation for age-hardening. Conventional rapid quenching, which only directly cools the profile’s extremity, can distort the part. Lower quenching rates reduce distortion but may compromise the mechanical properties. We test three hypotheses: (1) That the different cooling rates across the section during quenching induce varying mechanical properties as well as distortion; (2) That this temperature differential can be minimized by combining novel internal profile quenching with conventional quenching; and (3) That internal quenching can be achieved using insulated channels in the extrusion die to convey the quenchant to the profile’s interior. The first hypothesis is tested experimentally by taking tensile specimens from a AA6082 multi-hollow profile. The second is examined experimentally using a lab-built quench box and theoretically using thermo-mechanical finite element simulations. The third hypothesis is tested by conducting a hollow profile extrusion trial using a specially designed porthole die. The testing shows that conventional quenching results in reduced mechanical properties in the profile’s internal walls but that combined external/internal quenching alleviates this problem and reduces distortion. The extrusion trial on internal quenching demonstrates die survivability, an acceptable die temperature drop during quenchant flow, and effective quenchant disposal via evaporation and capture of liquid at the end of the profile. This study suggests that internal quenching is a promising technology option for reducing scrap and improving mechanical properties of hard-to-quench aluminum profiles.

The general ({I}_{1}{J}_{2}{J}_{3}) yield function (Lou et al. in Int J Plast 158:103414, 33) is extended to an analytically anisotropic form by using a newly proposed five-parameter linear transformation tensor based on the work of Barlat et al. Int J Plast 7:693–712, 7). The anisotropic parameters are analytically calculated so that the proposed yield function can model both differential hardening at various stress states and anisotropic hardening along different loading directions. The extended anisotropic form is applied to characterize the strain hardening behavior of metals of three different polycrystal structures, including AA7075 T6 aluminium, QP1180 steel, and AZ31 magnesium. The results show that the extended anisotropic form is capable of precisely modelling both the differential and anisotropic hardening for the studied metals under various stress states. The proposed function is also applied to a high strength steel QP980 (Hou et al. J Mater Process Technol 290:116979, 17) to validate the capability of the proposed model for the modeling of strength differential (SD) effect between uniaxial tension and compression and its evolution with respect to plastic strain. The results show that the proposed function is capable of predicting the SD effect between uniaxial tension and compression with very high accuracy along RD, DD and TD. Convexity analysis is conducted during yield surface evolution by a newly proposed geometry-inspired numerical convex analysis method to ensure the yield surface convexity during significant change of yield surfaces.

Aluminum alloy forged wheel hubs are lightweight materials for electric vehicles. However, forming high-ribbed spokes is challenging due to potential shrinkage during high rib extrusion with plane strain characteristics. This study utilizes the finite element method to analyze the high-rib extrusion process with plane-strain characteristics. It is found that a region of tensile stress exists near the bottom fillet of the rib persisting until the high rib contour is fully filled. The position and size of this region remain largely unchanged during extrusion. Defining the occurrence of shrinkage defects as a critical state, the thickness is defined as the critical residual thickness. By constructing a stress state slip line field for plane-strain extrusion, a prediction formula for the critical residual thickness of high-rib extrusion is proposed. The proposed critical residual thickness is evaluated through finite element calculations and high-rib extrusion experiments. The results show that the critical residual thickness is linearly positively correlated with the half-width of the rib root and negatively correlated with the fillet radius of the rib root, taper angle, and shear friction coefficient. The initial blank thickness does not affect the critical residual thickness. The depth of the shrinkage increases linearly with the decrease in residual thickness. The experimental critical residual thickness can be determined by combining finite element calculations and extrusion experiments. The proposed theoretical formula for the critical residual thickness has an error of + 8.14% compared to the experimental critical residual thickness. This theoretical prediction is relatively conservative and can guide the design of high-rib extrusion forming billets to ensure defect-free high-rib forming.

In the light of recent developments in the design of structural materials, micro-architected heterogenous-structure metals are considered among most structurally efficient. In this work, a new technique for Local High Pressure Torsion (L-HPT) enabling the creation of heterogeneous structures through localised deformation processing in sheet metals by impeding a rotating punch is proposed. Using AA5083 aluminium alloy as an example, we show experimentally that the rotation of the punch sets adjacent material layers in motion. This results in more than two-fold increase in material hardness over initial level in the workpiece bulk with rather sharp gradients in hardness level transition. The maximum hardness is observed at the peripheral edge of a punch tip. Finite-element modelling of the L-HPT process confirmed that the rotational flow of workpiece material leads to the accumulation of shear strain. The level of accumulated strain increases with an increase in friction at the contact surface. Further analysis based on dimensionality theory revealed that for such an L-HPT configuration the level of equivalent strain is directly proportional to the ratio of rotation-to-translation speeds at the punch.

The Sheet Molding Compound (SMC) process is essential in high-volume manufacturing of composite structures due to its scalability and efficiency. A primary challenge, however, lies in determining the initial charge shape that ensures complete mold filling without excessive overflow, typically resolved through labor-intensive trial and error. While simulations can anticipate the mold filling outcome, they often lack the capability to fine-tune the initial preform configuration, leading to inefficiencies in both time and material. This study presents an innovative, simulation-driven approach for accurately predicting initial charge shapes for two-dimensional (2D) mold designs. By employing Darcy’s Law and a fixed mesh grid framework, the methodology simulates a reverse material flow to trace the optimal preform shape. A complementary machine learning (ML) model was then developed to predict the preform shapes based on mold geometry, final thickness, and initial charge thickness. Serving as a digital twin of the SMC process, this ML model delivers results with comparable accuracy to simulations, significantly enhancing computational efficiency and avoiding common convergence issues in traditional simulations. This ML-driven digital twin approach also provides a robust proof of concept for addressing initial charge shapes in complex three-dimensional (3D) molds, where the computational demands of reverse flow simulations may present challenges. This combined simulation and ML framework equips manufacturers with a more precise and efficient tool for optimizing SMC processes, minimizing material waste, and reducing production time.

Explosive welding (EXW) is a high-speed process used to join dissimilar materials and produce large surface sheet products. While traditionally reliant on experimental observations of welded interfaces, this approach offers limited insight into the dynamic phenomena during flyer and base plate collisions, hindering the development of closed-loop control systems. Therefore, numerical modeling has emerged as a critical tool to optimize welding parameters and predict product properties more effectively. This research presents a novel physics-based numerical model for EXW, developed using a refined Smooth Particle Hydrodynamics (SPH) framework. Unlike existing models that simplify or exclude the explosive material’s dynamics, this approach explicitly simulates explosive detonation, flyer plate response, and the resulting welding process. The model integrates comprehensive equations of state and constitutive laws to capture both macroscale and microscale phenomena observed in experiments. The key novelty lies in bridging microscale interface behavior with macroscale process outcomes, offering a detailed representation of vortex formation and weld quality. Validation against analytical solutions and experimental data demonstrates the model’s accuracy and ability to resolve critical features of the EXW process, providing a foundation for future optimization and control strategies.

Sheet metal forming is essential in automotive and aerospace industries, where accurate simulations are crucial for optimizing material deformation and tool design. Finite Element Analysis (FEA) is a key tool for predicting stresses, strains, and material flow in these processes. Recent advancements in artificial intelligence (AI) and machine learning have further enhanced these simulations, improving toolpath planning and overall process efficiency Appl Mech 1:97-110, 2020, ASME J Manuf Sci Eng 144(2):021012, 2021. A critical aspect of sheet metal forming is the development of forming tools, which must withstand high forces and ensure precision. Traditionally, tool design has relied on a trial-and-error approach, heavily dependent on manufacturer expertise. This paper introduces an innovative methodology that integrates sheet metal forming simulations with the structural analysis of forming tools, facilitated by a specialized connector. The connector enables integrated analysis of the forming process and tool structural behaviour, providing feedback on tool performance under operational loads. The output of the forming simulation (contact pressures between workpiece and tools) feeds the structural model. Additionally, the methodology incorporates AI-driven what-if analysis to streamline decision-making in the early design stages. This modular solution is designed to integrate with a Digital Twin framework, offering continuous optimization. The proposed methodology enhances manufacturing efficiency by reducing simulation time and improving tool structural behaviour predictions, enabling faster, more accurate tool development and ultimately minimizing trial-and-error in tool design.