International Journal of Material Forming最新文献

The purpose of this work is to study the effect of anisotropic plasticity on the micro-deep drawing of the 304 stainless steel foils through a combination of experimental testing and numerical modeling. A phenomenological anisotropic model, with the Yld2004-18p yield function, is used to model the anisotropic plasticity deformation of the material. Based on the miniature tensile experimental data and Voce's hardening law, the coefficients in the Yld2004-18p function were calibrated. The FE modelling was implemented using ABAQUS to simulate the micro-deep drawing experiments. The wall thickness and height of the cylindrical cup obtained by the simulation have shown to be reasonably close to the experimental values, and the distribution of ears is the same as the experimental results. It has shown that the Yld2004-18p anisotropic yield function can accurately describe the anisotropic behavior of 304 stainless steel foils during the micro-deep drawing process.

Conventional engineering analyses for tube drawing processes have assumed an ideal material with uniform initial tube thickness; however, these assumptions limit the ability to address quality issues in the manufacturing industry. In this study, we present a finite element analysis model to analyze the tube drawing process with non-uniformity of the initial tube thickness and misalignment of the drawing die, using the implicit elastoplastic finite element method with a multibody treatment scheme (MBTS). We specifically focus on tube eccentricity. The plug in the MBTS is regarded as a deformable body with any fixed boundary condition in the lateral direction. Our analysis results show that an adequately tilted drawing die substantially reduces the eccentricity and thickness non-uniformity. The predictions are validated by comparison with experimental results in the literature.

Direct joining of titanium and stainless steel 316 L with a strong interface is very challenging due to the formation of the brittle intermetallic compounds FeTi and Fe₂Ti in the intermixing zones and to the high residual stress induced by the mismatch of the thermal expansion coefficients. In this bimetallic directed energy deposition study, firstly, deposition of Ti on stainless steel was carried out using conventional process parameter regime to understand the interfacial cracking susceptibility and then a novel high powder flowrate approach is proposed for controlling the dilution and constraining the intermetallic phases forming at the interface. The influence of high temperature substrate preheating (520 °C) on the cracking susceptibility and interface strength was also investigated. The deposited Ti samples and their interfaces with the 316 L substrate were characterized with optical microscopy, scanning electron microscopy and energy dispersive X-ray spectroscopy to investigate the geometry, microstructures and chemical compositions in relation to the cracks. The high powder flowrate deposition of Ti on stainless steel 316 L results in an extremely thin dilution region (~ 10 μm melt pool depth in the substrate) restricting the formation of the intermetallic phases and cracks. The ultimate shear strength of the interfaces of the crack free sample was measured from cuboid deposits and the highest measured strength is 381 ± 24 MPa, exceeding the weaker base material pure Ti. The high interfacial strength for high powder flowrate deposition is due to the substantial attenuation and shadowing of the laser beam by the in-flight powder stream as demonstrated by the high-speed imaging resulting in an extremely small dilution region.

Hollow embossing rolling is a promising forming technology for metallic bipolar plates because of the high achievable production rates. However, the simulation-based process optimization is impeded by the incremental forming character and modeling of fine channel structures, which leads to large model sizes and long computation times. This paper presents a shell-based finite element approach validated by experimental forming tests using a miniaturized test geometry with typical discontinuities and varying channel orientations. The rolling experiments demonstrated that implementing restraining tension effectively decreases wrinkling, allowing successful forming of the selected test geometry by hollow embossing rolling. It was found that representing the manufacturing-related decreased rolling gap combined with the rolling gap changes due to roll system elasticity in the numerical model is essential for model accuracy. An optimized model approach with spring-controlled rollers was developed, which considers the effect of load-dependent rolling gap changes. With this approach the applied model achieves sufficient model accuracy for technological process simulation and optimization.

Knowing the thermo-mechanical history of a part during its processing is essential to master the final properties of the product. During forming processes, several parameters can affect it. The development of a surrogate model makes it possible to access history in real time without having to resort to a numerical simulation. We restrict ourselves in this study to the cooling phase of the casting process. The thermal problem has been formulated taking into account the metal as well as the mould. Physical constants such as latent heat, conductivities and heat transfer coefficients has been kept constant. The problem has been parametrized by the coolant temperatures in five different cooling channels. To establish the offline model, multiple simulations are performed based on well-chosen combinations of parameters. The space-time solution of the thermal problem has been solved parametrically. In this work we propose a strategy based on the solution decomposition in space, time, and parameter modes. By applying a machine learning strategy, one should be able to produce modes of the parametric space for new sets of parameters. The machine learning strategy uses either random forest or polynomial fitting regressors. The reconstruction of the thermal solution can then be done using those modes obtained from the parametric space, with the same spatial and temporal basis previously established. This rationale is further extended to establish a model for the ignored part of the physics, in order to describe experimental measures. We present a strategy that makes it possible to calculate this ignorance using the same spatio-temporal basis obtained during the implementation of the numerical model, enabling the efficient construction of processing hybrid twins.

Large Format Additive Manufacturing (LFAM) has gained prominence in the aerospace and automotive industries, where topology optimization has become crucial. LFAM facilitates the layer-by-layer production of sizeable industrial components in carbon fiber (CF) reinforced polymers, however 3D printing at large scales results in warpage generation. Printed components are deformed as residual stresses generated due to thermal gradients between adjacent layers. This paper tackles the problem at two different scales: the micro and macroscale. Initially, the microstructure characterization of the thermoplastic ABS matrix composite material enriched with 20% short CF is used in the development of numerical models to understand the mechanical behavior of the studied material. Numerical modeling is performed simultaneously by means of Mean-Field (MF) homogenization methods and Finite Element Analysis (FEA). Outcomes validated with corrected experimental mechanical testing results show a discrepancy in the elastic modulus of 7.8% with respect to FE multi-layer analysis. Micro-level results are coupled with the a macroscopic approach to reproduce the LFAM process, demonstrating the feasibility of the tool in the development of a Digital Twin (DT).

Self-piercing riveting (SPR) is one of the advanced mechanical joining techniques, and it has been widely used in automobile industry. In this paper, the effect of die misalignment on the cross-section parameters and mechanical properties of SPR joints were respectively studied through numerical simulation and experiment, and the mechanical properties degradation mechanism of the misaligned riveted joint were analyzed. A three-dimensional explicit finite element model (FEM) of SPR joint was developed by ABAQUS, and the section observation was performed to evaluate the accuracy of FEM. The riveting process and the strain of SPR joints with different misalignment distance was analyzed, and the quasi-static shear test was carried out. The results revealed that the rivet leg near the die edge was thickened due to limitations in deformation space, and a cavity was formed at the outer edge of the rivet leg near the die center, during the riveting process. It resulted in different cross-section parameters and mechanical properties of SPR joints. Specifically, the interlock distance decreased as the misalignment distance increased. The bottom thickness of the side near the die edge increased with increasing misalignment distance, while that near the die center decreased slightly as the misalignment distance increased. In addition, the maximum shear load decreased nonlinearly with increasing misalignment distance, and the movement of die along the loading end had a significantly greater impact on the maximum shear load than the movement along the fixed end. This was mainly because the interlock distance of SPR joints was asymmetrically and nonlinearly reduced due to the die misalignment.

This article aims to define the problem of the development of a “Continuous Twin” in any stamping process installed in an industry. A “Continuous Twin” is a modeling concept using the information available in both worlds, the virtual twin (simulation) and the digital twin (real-time data) of the process. There is currently a trend in the industry related to IIoT (Industrial Internet of Things) and linked to Industry 4.0. IIoT is the collection of sensors, instruments and autonomous devices connected through the internet to industrial applications. However, filling with sensors the entire industry and channelling all that information through industrial networks is a utopia. In our previous works, a new concept for generating industrializable IIoT applications has been presented, Industrializable Industrial Internet of Things (I3oT). The purpose of the I3oT is using the installations available in factories to develop IIoT applications from them. This article aims to analyse all available and accessible information from the parameters accessible from the stamping process PLC, material properties, FLD, to the measurement of the operators corrections after detecting part failures. This is information that could be included in the model in order to develop an industrializable “Continuous Twin”.