International Journal of Material Forming最新文献

In this study, we present a Finite Difference Method (FDM)-based stress integration algorithm for Crystal Plasticity Finite Element Method (CPFEM). It addresses the complexity of computing the first derivative of resolved shear stress in the Euler backward stress integration algorithm with Newton-Raphson method. The proposed FDM-based model was verified by evaluating its accuracy, convergence and computational efficiency through single-element simulations. The developed FDM-based model can be easily applied to various constitutive models for CPFEM, overcoming the problem of deriving complex derivative regardless of constitutive models. Additionally, the proposed FDM-based model was validated with the reduced texture approach using AA 2090-T3. Specific parameters including crystallographic orientations were calibrated and the plastic anisotropy was successfully described. In addition, the earing profiles were compared using various stress integration methods. As a result, the proposed FDM-based model can be used as an alternative to the Euler backward method using analytic derivatives with the compatible accuracy, convergence, computational efficiency along with easy implementation within the CPFEM framework.

This article presents the development of a plane strain tensile test aiming at an easy classification of aluminium automotive alloys according to their formability in prototyping steps. A parametric study with finite element method is performed on three different designs inspired by literature. It is found that, due to plastic anisotropy, specimens designed for steel are not suited for aluminium alloys. One optimized specimen geometry, ensuring near plane strain state on a large zone all along the deformation range up to failure, is selected. On this geometry, tensile tests instrumented by Digital Image Correlation are performed for five different aluminium alloys (5xxx and 6xxx) in three different directions of the metal sheet (rolling, diagonal and transverse). From Digital Image Correlation analysis, necking limits are evaluated and their relevance for the ranking of alloys according to their formability is discussed in comparison with a standard formability test, namely the Limiting Dome Height test.

Graphical Abstract

Due to the growing trend towards miniaturization, small-scale manufacturing processes have become widely used in various engineering fields to manufacture miniaturized products. These processes generally exhibit complex size effects, making the behavior of materials highly dependent on their geometric dimensions. As a result, accurate understanding and modeling of such effects are crucial for optimizing manufacturing outcomes and achieving high-performance final products. To this end, advanced gradient-enhanced plasticity theories have emerged as powerful tools for capturing these complex phenomena, offering a level of accuracy significantly greater than that provided by classical plasticity approaches. However, these advanced theories often require the identification of a large number of material parameters, which poses a significant challenge due to limited experimental data at small scales and high computation costs. The present paper aims at evaluating and comparing the effectiveness of various optimization techniques, including evolutionary algorithm, response surface methodology and Bayesian optimization, in identifying the material parameter of a recent flexible gradient-enhanced plasticity model developed by the authors. The paper findings represent an attempt to bridge the gap between advanced material behavior theories and their practical industrial applications, by offering insights into efficient and reliable material parameter identification procedures.

Closed-loop control of product properties is becoming increasingly important in forming technology research and enables users to counteract unavoidable uncertainties in semi-finished product properties and process environments. Therefore, closed-loop controlled forming processes are considered to have the potential to reduce tolerances on desired product properties, resulting in consistent qualities. The achievement of associated increases in robustness and reliability is linked to enormous requirements, which in particular include the inline recording of the product properties to be controlled and the subsequent adaptation of the process control through the targeted derivation of manipulated variables. The present paper uses the example of an air bending process to show how the bending angle can be controlled camera-based and how springback can be compensated within a stroke by recording force signals and subsequently predicting the loaded bending angle using machine learning algorithms. The results show that the combined application of camera-based control and machine learning assisted springback compensation leads to highly accurate bending angles, whereby the results strongly depend on the machine learning algorithms and associated data transformation processes used.

In the realm of forging processes, the challenge of real-time process control amid inherent variabilities is prominent. To tackle this challenge, this article introduces a Proper Orthogonal Decomposition (POD)-based surrogate model for a one-blow cold upsetting process in copper billets. This model effectively addresses the issue by accurately forecasting energy setpoints, billet geometry changes, and deformation fields following a single forging operation. It utilizes Bézier curves to parametrically capture billet geometries and employs POD for concise deformation field representation. With a substantial database of 36,000 entries from 60 predictive numerical simulations using FORGE® software, the surrogate model is trained using a multilayer perceptron artificial neural network (MLP ANN) featuring 300 neurons across 3 hidden layers using the Keras API within the TensorFlow framework in Python. Model validation against experimental and numerical data underscores its precision in predicting energy setpoints, geometry changes, and deformation fields. This advancement holds the potential for enhancing real-time process control and optimization, facilitating the development of a digital twin for the process.

This paper is concerned with experiments and finite element (FE) simulations using the coupled Eulerian‒Lagrangian (CEL) method for multi-material joining by the flow drill screw (FDS) process. The FDS joining experiments involved various combinations of aluminum alloys (Al6061-T6 2.0t and Al6063-T6 2.0t), and steel (SPRC45E 1.6t) sheets. During the FDS joining, thermocouples and a thermal imaging camera, FLIR, were used to measure the elevated temperature near the joint. Cross-sections of the multi-material joint specimens were prepared to check the joining quality and the deformed shape of the materials. To consider the complexity of the joining process and convergence issue of numerical simulation, the FE modeling approach for the FDS joining was constructed based on the CEL method using the ABAQUS/Explicit, considering the strain rate and thermal softening dependent strain hardening of each material. From the comparison of experimental and FE simulation results, the reliability of the FE modeling was validated, revealing the predictability of the deformed shape was 90% or more, especially in terms of the bushing length. Furthermore, it was confirmed that the proposed modeling approach can accurately describe the temperature history and peak values during rapid joining.

The article presents a novel technique for performing high reduction radial shear rolling (HRRSR) of aluminum alloy bars. For this purpose, rolls with a special calibration were developed, including a high reduction section and a roll feed angle of 20°. The proposed process was investigated using FEM simulation, first. The temperature, stress-strain state, and force parameters analysis showed that the proposed method can produce defect-free bars with a natural gradient microstructure. Afterward, the experimental alloy Al-3Ca-2La-1Mn (wt%), was processed by a single-pass HRRSR process, resulting in a bar with an elongation ratio of 5. High compression and shear strains provide severe deformation of the initial cast microstructure and form a uniform distribution of small eutectic inclusions of the Al4(Ca, La) phase in the aluminum matrix. The obtained results, indicate the possibility of severe deformation of aluminum alloys using the radial shear rolling method. The proposed method of deformation can be the basis for an effective technology for obtaining bulk, long-length bars from various aluminum alloys, with a high reduction in a single pass.

Designing extrusion dies remains a tricky issue when considering polymers. In fact, polymers exhibit strong non-Newtonian rheology that manifest in noticeable viscoelastic behaviors as well as significant normal stress differences. As a consequence, when they are pushed through a die, an important die-swelling is observed, and consequently the final geometry of the extruded profile differs significantly from the one of the die. This behavior turns the die’s design into a difficult task, and its geometry must be defined in such a way that the extruded profile results in the targeted one. Numerical simulation was identified as a natural way for building and solving the inverse problem of defining the die, leading to the targeted extruded geometry. However, state-of-the-art rheological models reveal inaccuracies for the desired level of precision. In this paper, we propose a data-driven approach that, based on the accumulated experience on the extruded profiles for different dies, learns the relation enabling efficient die design.

In this paper, a new forging system was developed and a new complex methodology was tested for the analysis of the closure of voids. The effective geometric shapes of anvils and optimal the forging parameters has been determined. A new cogging process provided a complete closure of voids, which was confirmed by experimental tests. The effect of the reduction ratio, original anvil shape, forging ratio and the location and size of introduced voids on the efficiency of void closure during the multi-transition cogging process was assessed. Moreover, the following were used for the evaluation of void closure: the hydrostatic stress around voids, stress triaxiality, effective strain around voids, and the critical reduction ratio. Numerical examinations were performed using the finite element method (FEM) for the three-dimensional forging process at elevated temperature. Computer simulations of the cogging process under investigation were carried out using a program DEFORM-3D, and selected simulation results were compared with experimental test results. Void reduction predictions obtained from the FEM analysis were in good agreement with the experimental findings. The test results are supplemented with the prediction of crack formation in the zone of existing voids and within the forging volume during the multi-transition cogging process.

Due to the current changes in mobility, lightweight design concepts continue to be of particular interest to the automotive industry. One form is the multi-material design, in which the advantageous properties of different materials are combined in one component. In this work, a component made of a steel sheet with stiffening structures of cast aluminum is considered. The joint is created by channel structures with undercuts on the surface of the steel sheet, into which the molten aluminum can flow. After solidification, an interlocking connection is created. The aim of this work is to investigate the influence of a bending operation on the surface structure before the die casting process. Numerical simulations and experimental validations were performed with different bending angles and radii as well as orientations between the channel structure and the punch. The results show that the undercuts on the outer radius are reduced by up to 75% by the bending operation, thus weakening the resulting joint. On the inner radius, the channel opening width narrows by up to 73% and can thus impede the filling with the melt.