International Journal of Material Forming最新文献

For wire arc additive manufacturing (WAAM) process the interlayer temperature highly influences the quality of manufactured parts. This paper proposes an optimisation of deposition parameters for a better control of interlayer temperature while reducing the printing time employing a Finite Element (FE) model and a metamodel based on Non Uniform Rational Basis Splines (NURBS) entities for a thin-walled part in aluminium alloy. Firstly, the thermal FE model is created to extract the interlayer temperature as a function of different deposition parameters that will be optimised. These parameters are the wire feed speed and the cooling time between deposition of two consecutive layers. Then, a NURBS-based metamodel is generated to approximate the (unknown) transfer function between input variables and output responses of the problem at hand. One of the advantages of this metamodeling strategy is the possibility of obtaining the gradient of the output responses without the requirement of further computational resources, as the resulting metamodel is available in analytical form with the requisite continuity and differentiability. The NURBS-based metamodel is generated as a solution of a three-step optimisation strategy aiming at determining all the parameters defining the shape of the NURBS entity. Finally, the NURBS-based metamodel is included in the optimisation process related to the considered application. The optimisation problem is defined as a weighted sum of different criteria, i.e., total printing time and the average interlayer temperature difference for each layer. The solution obtained is subsequently validated a posteriori using the high-fidelity FE model, demonstrating an excellent agreement between the prediction of the NURBS-based metamodel and those of the FE model.

Processing simulation of prepreg fabrics requires considering multiple interactive deformation mechanisms to reliably predict the response of a formed part. However, these mechanisms, especially the evolving fabric properties and their interactions, are often overlooked. In this study, through integration of a series of user-defined subroutines, a unified (enhanced) numerical model (called UNIMAT) is developed to simulate the forming of a plain-weave fiberglass/polypropylene prepreg. The model specifically involves simultaneous incorporation of the fabric nonlinear in-plane and out-of-plane behaviours (including local bending/reverse bending effect with hysteresis), the ply viscous behavior at room temperature, and inter-ply anisotropic friction as a function of the ply orientation, pressure, and slippage. UNIMAT is first validated with a benchmark hemisphere forming test, and is then used for process optimization to minimize wrinkle formation over a complex shape tool under a vacuum bagging process. The model accurately predicted the forming outcomes including the part topology, punch force, shear angles, and wrinkles’ overall severity. The optimization search, through a Convolutional Matrix Adaptation Evolution Strategy (CMA-ES) algorithm, demonstrated that the wrinkles state can be diminished by up to 30% if local constraints on the fabric boundaries are optimally applied using pressure risers (modifiers), prior to the start of the vacuum.

Numerical simulations are crucial for predicting outcomes in forging processes but often neglect dynamic interactions within forming tools and presses. This study proposes an approach for achieving accurate real-time prediction of forging outcomes. Initially, a simulation-based surrogate model is developed to replicate key process characteristics related to the billet, enabling prediction of geometry, deformation field, and forging load after an upsetting operation. Subsequently, this model is integrated with a mass-spring-damper model representing the behavior of forging machine and tools. This integration enables the prediction of blow efficiency and energy distribution after each blow, including plastic, elastic, damping, and frictional energy of the upsetting operation. The approach is validated by comparing predictions with experimental results. The coupled model outperformed Finite Element Method (FEM) predictions, exhibiting mean absolute errors (MAE) below 0.1 mm and mean absolute percentage errors (MAPE) below 1% in geometry predictions. Deformation field predictions showed errors below 0.05 mm/mm, and load-displacement curves closely matched experimental data. Blow efficiency predictions aligned well with experimental results, demonstrating a mean absolute error below 1.1%. The observed energy distribution correlated with literature findings, underscoring the model’s fidelity. The proposed methodology presents a promising approach for accurate real-time prediction of forging outcomes.

This study aims to identify the Coulomb friction coefficient and shear friction factor in aluminum forming processes at high temperatures by using the warm and hot upsetting sliding test (WHUST). The presence of pile-up material in front of the contactor when performing the WHUST on aluminum alloys at elevated temperatures modified the contact geometry. Thus, in this study, the pile-up material was derived as a parameter in the analytical equations. It was found that the analytical equation allows to identify the Coulomb friction coefficient directly from the experimental data, while the analytical equation for the shear friction factor requires the yield stress at the contact surface in addition to the experimental data. For the experiment, the WHUST was performed on AA6082-T6 aluminum alloy against AISI H13 hot work tool steel under dry contact conditions at 400 °C. To precisely control the testing temperature, the WHUST apparatus was installed into the heating chamber of the Bruker UMT TriboLab. Finite Element Analysis (FEA) was used to determine the yield stress at the contact surface. In this study, three commercial FEA software, ABAQUS, DEFORM, and FORGE NxT, with two different sets of material data based on Hansel-Spittel material behavior law were carried out to demonstrate the variations in the computational results of the yield stress and its impact on the identification result of the shear friction factor. Finally, the Coulomb friction coefficient was 0.57, and the shear friction factor ranged between 0.76 and 0.90, depending on the yield stress obtained from the FEA software.

In order to investigate the temperature rise mechanism of laser cladding assisted by ultrasonic energy field, the multi-field heat flow behavior of laser cladding with or without ultrasonic field assistance is studied.Based on the theoretical analysis of laser-powder interaction and thermal effect of ultrasonic energy field, the coupling equation of laser effective heat input and ultrasonic effective heat conversion is obtained.A numerical model of three-dimensional phase-change heat transfer in laser cladding assisted by ultrasonic energy field is established. The solid–liquid phase change and dynamic evolution of the cladding layer are treated by the apparent heat capacity method and the deformation geometry method respectively. The variations of transient heat and velocity with distance based on laser spot center with or without ultrasonic energy field are studied. The effect of ultrasonic energy field on multi-field coupling of heat flow in laser cladding layer is discussed.Then ultrasonic field-assisted laser cladding IN718 experiment is conducted. The surface temperature of the melt pool is tracked in real time. The evolution law of the microstructure of the cladding layer and the distribution of alloying elements are analyzed.The reliability of the model is verified by analyzing the experimental results.The results show that when the laser cladding time is 2 s, the peak temperature and velocity of the molten pool reach the maximum value, which are 2483 K and 0.316 m/s respectively.Under the action of ultrasonic field, when the cladding time is 1 s, 2 s, 3 s and 3.5 s, the peak temperature of the molten pool increases by 26 K, 38 K, 105 K and 121 K respectively. The velocity of the molten pool reaches the maximum when the ultrasonic field acts for 2 s, which reaches 0.319 m/s.With the continuous application of ultrasonic field, the temperature gradient(G) of the cladding layer decreases gradually, and the solidification rate(R) and cooling rate increase. The ratio of temperature gradient to solidification rate (G/R) decreased.In the test range, the temperature variation of the molten pool surface is basically consistent with the simulation results.Ultrasonic field can promote the transformation of microstructure of IN718 cladding layer from columnar dendrites to equiaxial dendrites. The average minimum grain size of the top, middle and bottom of the cladding layer is reduced by 53.70%, 21.8% and 40.82% respectively. The element distribution of the cladding layer is also more uniform.

Using a segmented holding system can effectively reduce cracking and wrinkling in the stamping process and improve the forming limit of stamped parts. Different segmentation schemes can be achieved flexibly using a blank holding system driven by electromagnetics. However, how to segment the blank holder to fulfill the demand for flow control of complex parts is still an obstacle to overcome. This paper proposes a flow rate-based design of distributed blank holders on demand for complex parts. A theoretical model is first established to analyze the differences in flow rate in the flange. Then, the flow rates are identified circumferentially and radially to find the locations where the changes in rates are large, and these locations are lined and deemed as the boundaries for segmenting holders. Moreover, a design implementation, including location identification and the electromagnetic system configuration for complex parts, is developed to explore the optimal segmentation schemes. To validate the effectiveness, the downscaling part of a car door with the material DP600 is selected to find the segmented scheme, and the corresponding prototypes of integral and segmented electromagnetic dies are then configured. Experimental results show that the thickening ratio is decreased by 15.4%, and the thinning ratio is increased by 22.5% compared with that of the integral blank holder, and the design achieves better quality and fewer segmented pieces compared with the conventional approach. This research assists in designing segmented blank holding systems enabled by electromagnetics and provides a universal segmentation approach to form better-quality complex parts.

The metal additive manufacturing (MAM) process has most employed methods to build complex geometry and lightweight 3-dimensional (3-D) parts directly from a computerized solid model. Distortion of the printed part is a highly significant concern within the MAM process. This issue is because of the heating and cooling effect of printing process that could accumulate residual stress (RS) during part building up. The aim of the literature work is to present various methodologies for measuring RS in MAM components and to furnish a brief summary of recent developments in the domain. These details aid scholars in the discernment of suitable techniques, namely destructive, semi-destructive, or non-destructive, contingent on their particular applications and the accessibility of these methods. Moreover, it facilitates the explication of their formation mechanisms, effectiveness of process parameters, prediction, and control techniques. The effect of RS on the mechanical characteristics of printed parts is analyzed and presented. Additionally, common defects incorporated into RS are discussed. Moreover, this review article discusses about the future challenges and opportunities in the RS analysis of MAM parts.

Material testing and modeling is one of the cornerstones of virtual analysis of sheet metal forming processes. However, it is also becoming more and more relevant for incoming goods inspection, especially in view of the increasing amount of recycled material or frequent changes of suppliers, e.g. to provide workers, processes and/or process models with relevant information about a new batch of material. Efficient material testing and straight-forward test evaluation is essential for this. The flow curve and yield locus are central to describe the forming behavior of sheet metal materials. However, the parameters of the associated models are currently determined in various tests on different systems and with special sample geometries. The present work presents a methodology that allows the determination of a set of flow curve and yield locus parameters from three three-point bending tests only. The evaluation routine does not require finite element simulation and processes only the force-displacement information of the bending tests, which also places low demands on the measurement technology. The results were compared with a conventionally determined parameter set using a validation test, and the results are of reasonable quality, especially considering the minimal effort involved.

Additive manufacturing (AM) has emerged as a commonly utilized technique in the manufacturing process of a wide range of materials. Recent advances in AM technology provide precise control over processing parameters, enabling the creation of complex geometries and enhancing the quality of the final product. Moreover, Machine Learning (ML) has become widely used to make systems work better by using materials and processes more intelligently and controlling their resulting properties. In industrial settings, implementing ML not only reduces the lead time of manufacturing processes but also enhances the quality and properties of produced parts through optimization of process parameters. Also, ML techniques have facilitated the advancement of cyber manufacturing in AM systems, thereby revolutionizing Industry 4.0. The current review explores the application of ML techniques across different aspects of AM including material and technology selection, optimization and control of process parameters, defect detection, and evaluation of properties results in the printed objects, as well as integration with Industry 4.0 paradigms. The progressive phases of utilizing ML in the context of AM, including data gathering, data preparation, feature engineering, model selection, training, and validation, have been discussed. Finally, certain challenges associated with the use of ML in the AM and some of the best-practice solutions have been presented.

Knowledge of the deformation behaviour of Ti-6Al-4V using single-point micro incremental forming (SPMIF) is very important to understand the physics behind the microstructural changes, and forming limit. In SPIF, shape changes in sheet metals up to ultra-thin sizes can be performed without using a die and punch (does not require any specific tooling as in the conventional forming process) and hence, this process is recommended for the fabrication of parts in the aerospace, automobile, and bio-medical industries. Furthermore, in SPIF, the components are manufactured using a hemispherical end tool moving along a predefined path with an enhanced forming limit. The present research work has focused on studying the formability, microstructure, mechanical properties and fracture mechanics of Ti–6Al–4V alloy foils during SPMIF. The importance of spindle speed on the forming limits of the Ti–6Al–4V alloy foil was studied and it was found that the maximum forming limits were achieved at higher spindle speeds (200 rpm) due to strengthening of basal texture and weakening of prismatic texture components. A forming limit strain (FLS) was drawn at different spindle speeds (100, 150, and 200 rpm). XRD, EBSD and TEM analyses were performed for the phase analysis, orientation and dislocation density respectively. The fracture behaviour was investigated and the void coalescence parameters were compared with respect to spindle speed.